Basin water resource effectiveness and controllability collaborative evaluation method and device and medium

Abstract

The present application relates to the technical field of water resources evaluation, and discloses a method and device for the collaborative evaluation of basin water resource effectiveness and controllability, and a medium, wherein a multi-level spatial evaluation scale is constructed, and water resource effectiveness evaluation indexes and water resource controllability evaluation indexes are established; the values of the evaluation indexes are obtained; the weights of the evaluation indexes are determined; based on a multi-objective decision method, the water resource effectiveness relative closeness and the water resource controllability relative closeness of each evaluation object are calculated according to the values and weights of the evaluation indexes; and the evaluation grades and collaborative change characteristics of the water resource effectiveness and the water resource controllability of each evaluation object are determined according to the water resource effectiveness relative closeness and the water resource controllability relative closeness. The present application solves the technical problems in the prior art, such as the lack of collaborative analysis of water resource effectiveness and controllability, the lack of objectivity of the evaluation results caused by subjective weighting and static analysis, and the disconnection between the distributed hydrological model and the multi-index comprehensive evaluation model.

Description

Technical Field

[0001] This invention relates to the field of water resources assessment technology, specifically to a method, apparatus, and medium for the collaborative evaluation of the effectiveness and controllability of water resources in a watershed. Background Technology

[0002] With increasing global climate change and human activities intensifying in watersheds, the underlying surface patterns, water cycle processes, and spatial and temporal distribution of water resources have undergone significant changes, leading to increasingly complex patterns in slope runoff generation and concentration, vegetation and soil water consumption, and river runoff evolution. Existing water resource assessments often focus solely on the single dimension of slope water resource effectiveness or river runoff controllability, severing the intrinsic linkages between the slope-river hydrological system and lacking a holistic analysis of effectiveness and controllability from a watershed perspective.

[0003] Traditional evaluation methods often employ subjective weighting and single statistical models, making it difficult to take into account the spatial heterogeneity and process mechanism characteristics of hydrological elements. The determination of indicator weights is highly subjective, and the evaluation results lack objectivity. At the same time, conventional evaluation methods tend to focus on static status analysis, failing to accurately depict the feedback mechanism between slope ecological water consumption, runoff generation processes, and river runoff regulation and variation characteristics. Consequently, it is difficult to accurately quantify the effective utilization level and controllability of watershed water resources.

[0004] In addition, although distributed hydrological models can simulate complete hydrological processes on watershed slopes and river channels, they lack a supporting multi-index comprehensive quantitative evaluation system; while conventional multi-index evaluation models lack the support of hydrological physical processes, making it difficult to achieve an organic combination of hydrological process simulation and multi-dimensional collaborative evaluation. Summary of the Invention

[0005] This invention provides a method, apparatus, and medium for the collaborative evaluation of watershed water resource effectiveness and controllability. It addresses the technical problems in existing technologies, such as the lack of collaborative analysis of water resource effectiveness and controllability due to the fragmentation of the intrinsic linkage between the slope-channel hydrological system; insufficient objectivity in evaluation results due to subjective weighting and static analysis, which fails to characterize feedback mechanisms; and the disconnect between distributed hydrological models and multi-index comprehensive evaluation models, making it difficult to organically integrate hydrological process simulation and multi-dimensional collaborative evaluation. This invention integrates a collaborative evaluation method combining distributed hydrological process simulation and an objective comprehensive evaluation model, providing a theoretical basis and technical support for the rational allocation of watershed water resources, ecological protection, and runoff regulation.

[0006] In a first aspect, the present invention provides a method for the coordinated evaluation of the effectiveness and controllability of water resources in a watershed, comprising: using the catchment units of the target watershed as the primary evaluation units, nesting and dividing them into slope units and river control sections as secondary evaluation units to form a multi-level spatial evaluation scale, and using each evaluation unit in the multi-level spatial evaluation scale as the evaluation object; establishing water resource effectiveness evaluation indicators and water resource controllability evaluation indicators; obtaining the values ​​of the water resource effectiveness evaluation indicators and water resource controllability evaluation indicators; determining the weight of each evaluation indicator; and, based on a multi-objective decision-making method, calculating the relative proximity of water resource effectiveness and water resource controllability of each evaluation object according to the values ​​and weights of each evaluation indicator; and determining the evaluation level and coordinated change characteristics of water resource effectiveness and water resource controllability on each evaluation object based on the relative proximity of water resource effectiveness and water resource controllability.

[0007] This invention constructs a multi-level spatial evaluation scale by using catchment units as the main evaluation units and nesting them with slope units and river control sections. It integrates slopes and rivers into a unified evaluation framework, using each evaluation unit as the evaluation object for both effectiveness and controllability evaluation. This overcomes the shortcomings of existing technologies that fragment the intrinsic linkage between the slope-river hydrological system and lack collaborative analysis. Furthermore, by simultaneously establishing two sets of indicator systems—water resource effectiveness evaluation indicators and water resource controllability evaluation indicators—and based on a multi-objective decision-making method, calculates the relative proximity of water resource effectiveness and water resource controllability for each evaluation object according to the values ​​and weights of each evaluation indicator. This invention achieves a synergistic quantitative evaluation of the effectiveness of slope water resources and the controllability of river water resources, overcoming the shortcomings of conventional evaluation methods that suffer from insufficient objectivity due to subjective weighting and static analysis, and are unable to characterize the slope-river feedback mechanism. Furthermore, based on the aforementioned two relative proximity degrees, this invention determines the evaluation level and synergistic change characteristics of water resource effectiveness and controllability on each evaluation object. By determining synchronous and asynchronous changes, it can accurately identify the synergistic evolution law of effectiveness and controllability within the watershed, filling the technical gap of organically integrating distributed hydrological process simulation and multi-dimensional synergistic evaluation, and providing a scientific basis for the rational allocation of watershed water resources, ecological protection, and runoff regulation.

[0008] In one optional implementation, the multi-level spatial evaluation scale includes: using a grid as the smallest computational unit, slope units and river control sections as secondary evaluation units, catchment units as primary evaluation units, and the target watershed as the overall evaluation scale, forming a multi-level nested structure of grid-slope-catchment-watershed; wherein, the catchment unit is a sub-watershed or small watershed. This implementation, by constructing a multi-level nested structure of grid-slope-catchment-watershed, forms a complete spatial evaluation chain from the smallest computational unit to the overall watershed evaluation scale. The grid, as the basic computational unit of the distributed hydrological model, ensures the spatial accuracy of water and heat flux calculation; slope units and river control sections achieve spatial correspondence and precise connection between slope water production and river runoff; the catchment unit (sub-watershed or small watershed), as the primary evaluation unit, ensures the integrity of the hydrological boundary and the closure of the slope-river coupling relationship; and the target watershed, as the overall evaluation scale, realizes regional macro-evaluation and spatial distribution analysis. The aforementioned multi-level nested structure incorporates slopes and waterways into a unified spatial evaluation framework, enabling collaborative evaluation and spatial comparison of water resource effectiveness and controllability at different spatial scales, significantly improving the spatial accuracy and scale adaptability of the evaluation results.

[0009] In one optional implementation, slope units are divided according to slope position and slope gradient, with the same slope position, slope gradient, and land use type within the same slope unit. River control sections are set at the confluence of various gullies, natural bottlenecks in the watershed, or existing hydrological monitoring sections. This implementation ensures the homogeneity of topography and underlying surface conditions within the same slope unit by uniformly dividing slope units according to slope position, slope gradient, and land use type. This allows for accurate characterization of the runoff and water consumption characteristics of each slope unit, avoiding evaluation bias caused by spatial heterogeneity within the slope. Simultaneously, by setting river control sections at the confluence of various gullies, natural bottlenecks in the watershed, or existing hydrological monitoring sections, the upstream catchment area of ​​each control section can uniquely correspond to the water production area of ​​several slope units, achieving spatial topological matching and precise connection between slope water production and river confluence. Through the above-mentioned design of slope unit division and river cross-section layout, the distributed hydrological model can directly drive the confluence calculation of the river cross-section based on the water production output of the slope unit. This provides a spatial basis for the accurate quantification of the slope-river coupling relationship under multi-level nested spatial evaluation scales, and effectively ensures the consistency of water resource effectiveness evaluation and controllability evaluation within the same spatial framework.

[0010] In one optional implementation, the water resource effectiveness evaluation indicators include vegetation transpiration, canopy intercepted evapotranspiration, vegetation water consumption, and water yield coefficient; the water resource controllability evaluation indicators include the available water resources in the river channel, peak flow, dry season flow ratio, and rainfall-runoff coefficient of variation ratio. This implementation achieves a classified and quantitative evaluation of the slope eco-hydrological processes and river runoff evolution characteristics by establishing two sets of indicator systems: water resource effectiveness evaluation indicators and water resource controllability evaluation indicators. Among them, vegetation transpiration, canopy intercepted evapotranspiration, and vegetation water consumption characterize the intensity of direct water consumption by slope vegetation from different perspectives, while the water yield coefficient reflects the proportion of slope water output as surface runoff and flowing into the river channel. These four indicators complement each other and comprehensively cover the entire process of water transport in the slope system; the available water resources in the river channel, peak flow, dry season flow ratio, and rainfall-runoff coefficient of variation ratio comprehensively characterize the controllable utilization level of river runoff from four dimensions: water quantity, process, time distribution, and degree of variation. By applying the two sets of indicators in synergy, the simulation output of the distributed hydrological model can simultaneously serve the evaluation of the effectiveness of slope water resources and the controllability of river water resources. This provides an indicator basis for the synergistic quantitative evaluation of water resource effectiveness and controllability, and solves the problem that the existing single-dimensional evaluation cannot reflect the inherent linkage relationship of the slope-river system.

[0011] In one optional implementation, obtaining the numerical values ​​of water resource effectiveness evaluation indicators and water resource controllability evaluation indicators includes: constructing a distributed hydrological model of the target watershed, and simulating and outputting the numerical values ​​of each evaluation indicator through the distributed hydrological model. This implementation achieves the synchronous, efficient, and accurate acquisition of water resource effectiveness evaluation indicators and water resource controllability evaluation indicators by constructing a distributed hydrological model of the target watershed and simulating and outputting the numerical values ​​of each evaluation indicator. The distributed hydrological model, by coupling multi-source data such as meteorology, topography, soil, vegetation, and land use, can characterize the water exchange mechanism between slopes and rivers; at the same time, the model has spatial discretization computing capabilities, and can output vegetation transpiration, canopy intercepted evapotranspiration, vegetation water consumption, and water yield coefficient for slope units, as well as the available water resources, peak flow, dry season flow ratio, and rainfall-runoff variation coefficient ratio for river control sections, thereby simultaneously producing all the indicator data required for effectiveness evaluation and controllability evaluation within the same model framework.

[0012] In one optional implementation, the distributed hydrological model uses nested sub-basin grids as computational units. A mosaic method is employed to classify land use types within the grid units, calculating the water and heat fluxes for each land use type separately, and then weighting and merging these fluxes according to their area proportions to form the total grid flux. This implementation, using nested sub-basin grids as computational units, can consider both the overall hydrological process of the watershed and the spatial heterogeneity within the slope. Simultaneously, the mosaic method classifies land use types within the grid units, calculates the water and heat fluxes for each land use type separately, and then weights and merges them according to their area proportions to form the total grid flux. This avoids computational biases caused by homogenizing multiple land use types within the grid, enabling the model to distinguish the differences in runoff and water consumption among different underlying surfaces such as forest, shrubs, grassland, and bare land, and accurately quantify the contribution of each land use type to slope water production and consumption.

[0013] In one optional implementation, determining the weights of each evaluation indicator includes: using the entropy weight method to determine the weights of each evaluation indicator; and using a multi-objective decision-making method to calculate the relative proximity of water resource effectiveness and water resource controllability of each evaluation object based on the values ​​and weights of each evaluation indicator, including: calculating the distance between each evaluation object and the ideal solution using the TOPSIS method to obtain the relative proximity. This implementation uses the entropy weight method to determine the weights of each evaluation indicator, making the weight allocation entirely dependent on the dispersion or information content of the original data of each indicator, effectively avoiding the bias and uncertainty caused by subjective weighting methods such as expert scoring. Based on this, the TOPSIS method is used to calculate the relative proximity of water resource effectiveness and water resource controllability of each evaluation object, achieving a comprehensive quantitative evaluation of slope water resource effectiveness and river water resource controllability. The TOPSIS method determines the positive and negative ideal solutions of each indicator, calculates the Euclidean distance between each evaluation object and the positive and negative ideal solutions, and then obtains the relative proximity, resulting in evaluation results with clear physical meaning and a unified quantitative scale. By organically combining the entropy weight method and the TOPSIS method, the evaluation results of water resource effectiveness and controllability are made more objective, scientific and interpretable, providing a reliable quantitative basis for the subsequent determination of coordinated change characteristics.

[0014] In one optional implementation, the synergistic change characteristics include synchronous and asynchronous changes; synchronous change means that the evaluation level of water resource effectiveness is the same as the evaluation level of water resource controllability; asynchronous change means that the evaluation level of water resource effectiveness is different from the evaluation level of water resource controllability. This implementation quantifies the synergistic change characteristics of water resource effectiveness and controllability into two determineable types: synchronous and asynchronous changes. It defines synchronous change as the evaluation level of water resource effectiveness being the same as the evaluation level of water resource controllability, and asynchronous change as the evaluation levels being different, establishing explicit determination rules for the synergistic relationship between effectiveness and controllability. This allows for the quantitative identification and classification of the synergistic state of the slope-channel system. Based on these determination rules, spatial statistics and distribution analysis of the synergistic change characteristics of each evaluation unit within the watershed can be further conducted to accurately identify which areas within the watershed have a coordinated development state of water resource effectiveness and controllability, and which areas have an imbalance between the two, providing clear spatial guidance for differentiated watershed management decisions. This judgment rule solves the technical problems in existing technologies, such as the difficulty in quantifying the synergistic relationship between effectiveness and controllability, the inability to classify synergistic states, and the inability to locate synergistic problems. It enables water resource managers to maintain the status quo in areas with synchronous development and to implement precise policies in areas with asynchronous development.

[0015] Secondly, this invention provides a device for the collaborative evaluation of watershed water resource effectiveness and controllability, comprising: an evaluation unit division module, used to divide the target watershed's catchment units as primary evaluation units, nesting slope units and river control sections as secondary evaluation units to form a multi-level spatial evaluation scale, with each evaluation unit in the multi-level spatial evaluation scale as the evaluation object; an indicator system establishment module, used to establish water resource effectiveness evaluation indicators and water resource controllability evaluation indicators; an indicator value acquisition module, used to acquire the values ​​of the water resource effectiveness evaluation indicators and the water resource controllability evaluation indicators; a proximity calculation module, used to determine the weight of each evaluation indicator, and based on a multi-objective decision-making method, calculate the relative proximity of water resource effectiveness and relative proximity of water resource controllability for each evaluation object according to the values ​​and weights of each evaluation indicator; and a collaborative evaluation module, used to determine the evaluation level and collaborative change characteristics of water resource effectiveness and water resource controllability for each evaluation object based on the relative proximity of water resource effectiveness and relative proximity of water resource controllability.

[0016] Thirdly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the watershed water resources effectiveness and controllability collaborative evaluation method described in the first aspect or any corresponding embodiment. Attached Figure Description

[0017] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the first process of the collaborative evaluation method for the effectiveness and controllability of water resources in a basin, according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the second process of the collaborative evaluation method for the effectiveness and controllability of water resources in a basin, according to an embodiment of the present invention. Figure 3 This refers to the proximity of the effectiveness and controllability of water resources in the upstream basin of the target river from the 1970s to the 2010s in a specific embodiment of the present invention. Figure 4 This is a spatial distribution map of water resource availability levels in the upstream basin of the target river from the 1970s to the 2010s, as shown in a specific embodiment of the present invention. Figure 5 This is a spatial distribution map of the controllability level of water resources in the upstream basin of the target river from the 1970s to the 2010s, as shown in a specific embodiment of the present invention. Figure 6 This is a schematic diagram illustrating the spatial distribution characteristics of the simultaneous development of water resource effectiveness and controllability in the upstream basin of the target river in a specific embodiment of the present invention; Figure 7 This is a schematic diagram illustrating the spatial distribution characteristics of the asynchronous development of water resource effectiveness and controllability in the upstream basin of the target river in a specific embodiment of the present invention; Figure 8 This is a structural block diagram of a watershed water resources effectiveness and controllability collaborative evaluation device according to an embodiment of the present invention; Figure 9 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0021] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0022] Existing water resource assessments often focus solely on the effectiveness of slope water resources or the controllability of river runoff, severing the intrinsic linkage between the slope and river hydrological systems and lacking a holistic watershed perspective for collaborative analysis of effectiveness and controllability. Furthermore, traditional assessment methods often employ subjective weighting and single statistical models, resulting in highly subjective determination of indicator weights, insufficient objectivity in evaluation results, and a focus on static status quo analysis, failing to accurately depict the feedback mechanism between slope ecological water consumption and river runoff regulation. In addition, while distributed hydrological models can simulate complete hydrological processes on watershed slopes and in rivers, they lack a comprehensive multi-indicator quantitative evaluation system, while conventional multi-indicator evaluation models lack support from hydrological physical processes, making it difficult to organically combine hydrological process simulation with multi-dimensional collaborative evaluation. Based on this, the present invention provides a method, device and medium for the collaborative evaluation of the effectiveness and controllability of water resources in a watershed, in order to solve the technical problems in the prior art that are due to the lack of collaborative analysis of the effectiveness and controllability of water resources caused by the separation of the inherent linkage between the slope-channel hydrological system, the lack of objectivity of the evaluation results caused by subjective weighting and static analysis and the inability to characterize the feedback mechanism, and the disconnect between the distributed hydrological model and the multi-index comprehensive evaluation model, making it difficult to achieve the organic integration of hydrological process simulation and multi-dimensional collaborative evaluation.

[0023] According to an embodiment of the present invention, a method for synergistic evaluation of the effectiveness and controllability of water resources in a watershed is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0024] This embodiment provides a method for the coordinated evaluation of the effectiveness and controllability of water resources in a watershed. Figure 1 This is a flowchart of a watershed water resources effectiveness and controllability collaborative evaluation method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps: Step S101: The catchment unit of the target watershed is used as the main evaluation unit, and the slope unit and the river control section are nested as secondary evaluation units to form a multi-level spatial evaluation scale. Each evaluation unit in the multi-level spatial evaluation scale is used as the evaluation object.

[0025] Among them, a catchment unit refers to a closed hydrological spatial unit with an independent hydrological boundary, capable of completing the entire process of slope water production and river confluence. Its hydrological boundary is complete, enabling a closed-loop balance of water volume between slope water production and consumption and river confluence throughout the entire process. A slope unit refers to a slope spatial sub-unit with consistent water production and consumption patterns, defined according to topographic and underlying surface characteristics. It is used to quantify hydrological processes such as slope vegetation transpiration, soil evaporation, and slope runoff. A river control section refers to the hydrological monitoring and confluence control sections deployed at river confluence nodes. It is used to invert the total upstream runoff into the slope, achieving a precise correspondence between slope inflow and river confluence.

[0026] In this step, the multi-level spatial evaluation scale refers to a nested spatial evaluation system from grids, slopes, catchment units to the target watershed. This step uses the catchment unit as the primary evaluation unit, ensuring the integrity of the hydrological boundary and guaranteeing the closure of water transfer between slope inflow and river confluence. Nested division of slope units and river control sections as secondary evaluation units allows for a correspondence between slope water production and river confluence processes within the same spatial framework. By forming a multi-level spatial evaluation scale and using each evaluation unit as the evaluation object for subsequent steps, a spatial foundation is laid for the spatial discretization calculation of the distributed hydrological model and the collaborative analysis of water resource effectiveness and controllability evaluation at different spatial scales in subsequent steps.

[0027] Step S102: Establish water resource effectiveness evaluation indicators and water resource controllability evaluation indicators.

[0028] Among them, water resource effectiveness evaluation indicators refer to a set of indicators used to quantitatively characterize the actual water use efficiency and effective supply capacity of slope ecosystems. Water resource controllability evaluation indicators refer to a set of indicators used to quantitatively characterize the possibility and degree of controllability of river runoff resources being regulated, utilized, and managed.

[0029] Water resource effectiveness refers to non-runoff water resources that are effective for the ecological environment within a broad sense of water resources. This includes effective precipitation that exists in the slope system and can be directly absorbed and utilized by vegetation and soil, supporting the physiological growth of vegetation and the normal functioning of ecological systems. The main entities that can directly utilize slope water resources are slope vegetation and soil; the greater the utilization of slope water by vegetation and soil, the better the effectiveness of slope water resources. Water resource controllability needs to be defined based on the runoff generation and distribution feedback mechanism of the slope and river system: the greater the effective precipitation utilized by slope vegetation and soil, the less effective precipitation enters the river channel. Therefore, water resource controllability refers to the effective water that is effective for the ecological environment and can be developed and utilized by changing the underlying surface development pattern or through engineering scheduling, and can be reflected through changes in river runoff.

[0030] This step establishes two sets of indicator systems: one for evaluating water resource effectiveness and the other for evaluating water resource controllability. These systems provide a quantitative evaluation basis for the same evaluation object from two different dimensions: slope ecological utilization and river runoff regulation. This enables the subsequent distributed hydrological model to specifically simulate and output the two types of indicator data, providing indicator support for calculating the relative proximity of water resource effectiveness and the relative proximity of water resource controllability. Ultimately, this lays the indicator foundation for determining the synergistic change characteristics of effectiveness and controllability.

[0031] Step S103: Obtain the values ​​of water resource effectiveness evaluation indicators and water resource controllability evaluation indicators.

[0032] In this step, the values ​​of the water resource effectiveness evaluation indicators refer to the specific quantitative values ​​used to quantify the water use efficiency of the slope ecosystem, including vegetation transpiration, canopy intercepted evapotranspiration, vegetation water consumption, and water production coefficient, etc.; the values ​​of the water resource controllability evaluation indicators refer to the specific quantitative values ​​used to quantify the level of regulation and utilization of river runoff resources, including the amount of water resources available in the river, peak flow, dry season flow ratio, and rainfall-runoff variation coefficient ratio, etc.

[0033] This step, by constructing a distributed hydrological model of the target watershed, simulates and outputs the numerical values ​​of the aforementioned evaluation indicators, achieving the synchronous acquisition of water resource effectiveness and controllability evaluation indicators within a unified model framework. The distributed hydrological model couples multi-source data from meteorology, topography, soil, vegetation, and land use, calculating the water and heat flux of each unit using a raster as the basic computational unit. Through step-by-step calculations of slope runoff and river runoff, it can simultaneously output water consumption and yield indicators for slope units (vegetation transpiration, canopy intercepted evapotranspiration, vegetation water consumption, and yield coefficient) and runoff indicators for river control sections (available water resources within the river channel, peak flow, dry season flow ratio, and rainfall-runoff variation coefficient ratio) within the same model framework. This ensures the consistency of the two indicator systems in terms of time and spatial scale, avoiding the scale mismatch problem caused by the fragmented data acquisition methods in traditional methods, where effectiveness indicators rely on field observations and controllability indicators rely on hydrological statistics. This provides a unified and reliable data foundation for subsequent collaborative quantitative evaluation of water resource effectiveness and controllability.

[0034] Step S104: Determine the weight of each evaluation indicator. Based on the multi-objective decision-making method, calculate the relative proximity of water resource effectiveness and relative proximity of water resource controllability for each evaluation object according to the values ​​and weights of each evaluation indicator.

[0035] Among them, the weight of the evaluation index refers to the importance of each evaluation index in the comprehensive evaluation, reflecting the magnitude of the impact of different evaluation indicators on the evaluation results. Relative closeness refers to the degree of proximity between the evaluated object and the ideal solution, which can be calculated using the TOPSIS method. Its value ranges from 0 to 1; the larger the value, the closer the evaluated object is to the positive ideal solution, i.e., the higher the water resource effectiveness or controllability. Multi-objective decision-making methods refer to decision analysis methods used to comprehensively compare and rank the merits of multiple conflicting or different-dimensional evaluation indicators.

[0036] This step begins by determining the weight of each evaluation indicator. A higher weight indicates that the indicator is more important in the evaluation system and has a stronger ability to discriminate the evaluation results.

[0037] In one optional implementation, the weights of each indicator are automatically calculated based on the dispersion of the original data using the entropy weight method. The weight allocation relies entirely on the statistical characteristics of the data itself, rather than human experience, avoiding biases caused by subjective weighting. Then, based on a multi-objective decision-making method (preferably the TOPSIS method), the relative proximity of water resource effectiveness and water resource controllability for each evaluation object is calculated. The TOPSIS method determines the positive ideal optimal solution and the negative ideal worst solution for each indicator, calculates the Euclidean distance from each evaluation object to the positive ideal optimal solution and the negative ideal worst solution, and obtains the relative proximity based on the ratio of the two. In the TOPSIS method, the positive ideal optimal solution refers to the virtual solution where each evaluation indicator reaches its optimal value among all evaluation objects, and the negative ideal worst solution refers to the virtual solution where each evaluation indicator reaches its worst value among all evaluation objects. For positive indicators, the positive ideal optimal solution takes the maximum value, and the negative ideal worst solution takes the minimum value; the opposite is true for negative indicators. The final relative proximity score integrates and condenses the information from multiple evaluation indicators into a quantitative index between 0 and 1, realizing a comprehensive quantitative evaluation and ranking of the effectiveness and controllability of water resources for each evaluation object.

[0038] This step independently calculates the relative closeness of each evaluation object for both the water resources effectiveness evaluation index and the water resources controllability evaluation index, resulting in two relative closeness scores. These scores respectively characterize the comprehensive performance level of each evaluation object in the water resources effectiveness dimension and the water resources controllability dimension, providing a comparable quantitative basis for determining the synergistic change characteristics of effectiveness and controllability in subsequent steps.

[0039] Step S105: Based on the relative proximity of water resource effectiveness and the relative proximity of water resource controllability, determine the evaluation level and synergistic change characteristics of water resource effectiveness and water resource controllability for each evaluation object.

[0040] The evaluation level refers to a standardized classification of the degree of water resource effectiveness or controllability based on a range of values ​​indicating relative closeness. Coordinated change characteristics refer to the relationship between the two evaluation dimensions—water resource effectiveness and water resource controllability—at the level level on the same evaluation object, including both synchronous and asynchronous changes. Synchronous change means that the evaluation level of water resource effectiveness is the same as that of water resource controllability, indicating that the ecological water use efficiency of the slope and the level of river runoff regulation on the evaluation object are in a state of coordinated development. Asynchronous change means that the evaluation level of water resource effectiveness is different from that of water resource controllability, indicating an imbalance between the ecological water use efficiency of the slope and the level of river runoff regulation on the evaluation object.

[0041] Since the relative proximity scores of water resource effectiveness and water resource controllability calculated in step S104 are both continuous values ​​between 0 and 1, although the numerical values ​​can reflect the overall quality of each evaluation object, they lack intuitive qualitative meaning and are difficult to use directly for management decisions. Therefore, this step first maps the relative proximity scores of water resource effectiveness to their corresponding evaluation levels, and simultaneously maps the relative proximity scores of water resource controllability to their corresponding evaluation levels, thereby transforming the two abstract numerical results into qualitative conclusions with clear semantic meanings. Based on this, this step further compares and judges the two evaluation levels: if the two levels are the same, they are judged to be synchronous changes; if the two levels are different, they are judged to be asynchronous changes. Through the above judgment, the synergistic state of the slope-river system is quantified into an identifiable type, solving the technical problems in the prior art of making it difficult to quantify the synergistic relationship between effectiveness and controllability, classify synergistic states, and locate synergistic problems.

[0042] The watershed water resources effectiveness and controllability collaborative evaluation method provided in this embodiment constructs a multi-level spatial evaluation scale by using the catchment unit as the main evaluation unit and nesting it with slope units and river control sections. This integrates the slope and river into a unified evaluation framework, using each evaluation unit as the evaluation object to conduct effectiveness and controllability evaluations separately. This overcomes the shortcomings of existing technologies that lack collaborative analysis due to the separation of the intrinsic linkage between the slope and river hydrological systems. Furthermore, by simultaneously establishing two sets of indicator systems—water resources effectiveness evaluation indicators and water resources controllability evaluation indicators—and based on a multi-objective decision-making method, calculates the evaluation objects for each evaluation object according to the values ​​and weights of each evaluation indicator. The invention utilizes the relative proximity of water resource effectiveness and water resource controllability to achieve a synergistic quantitative evaluation of slope water resource effectiveness and river water resource controllability. This overcomes the shortcomings of conventional evaluation methods, which suffer from insufficient objectivity due to subjective weighting and static analysis, and are unable to characterize the slope-river feedback mechanism. Furthermore, based on the aforementioned two relative proximity values, the invention determines the evaluation level and synergistic change characteristics of water resource effectiveness and water resource controllability for each evaluation object. By determining synchronous and asynchronous changes, it can accurately identify the synergistic evolution law of effectiveness and controllability within the watershed, providing a scientific basis for the rational allocation of water resources, ecological protection, and runoff regulation in the watershed.

[0043] This embodiment also provides another method for the coordinated evaluation of watershed water resource effectiveness and controllability. Figure 2 This is a flowchart of a watershed water resources effectiveness and controllability collaborative evaluation method according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps: Step S201: The catchment unit of the target watershed is used as the main evaluation unit, and the slope unit and the river control section are nested as secondary evaluation units to form a multi-level spatial evaluation scale. Each evaluation unit in the multi-level spatial evaluation scale is used as the evaluation object.

[0044] In this embodiment, the primary evaluation unit is selected as the catchment unit (such as a sub-basin or small watershed), which ensures the integrity of the hydrological boundary and gives the evaluation unit a closed water cycle spatial boundary, fully reflecting the coupling relationship between slope inflow and river confluence. In the secondary evaluation units, slope units are divided according to slope position, slope zone, and land use type, ensuring consistency between the topography and underlying surface conditions within the same slope unit, and ensuring accurate characterization of slope runoff and water consumption characteristics. River control sections are selected from key hydrological monitoring sections within the watershed or set at river confluence nodes, so that the upstream catchment area of ​​each section corresponds to the water production area of ​​several slope units, achieving a precise correspondence between the slope and the river. The grid scale is the smallest calculation unit, providing a spatial basis for grid-by-grid hydrothermal flux calculation and sub-basin division of the distributed hydrological model, ensuring the spatial accuracy of the evaluation.

[0045] Among these, the integrity of the hydrological boundary refers to the spatial constraint imposed by the topographic watershed and the hydrogeological boundary, which makes the evaluation unit a closed water cycle spatial unit. The confluence paths of surface runoff and groundwater runoff are closed and unique, and the evaluation unit has only one natural hydrological outlet. There is no lateral inflow or outflow of surface water across the boundary, and no cross-boundary groundwater recharge or discharge. Through the above constraints of the integrity of the hydrological boundary, the evaluation unit can achieve a closed-loop balance of water volume in the entire process of slope water production and consumption and river confluence, and fully characterize the watershed spatial boundary conditions of the coupling process between slope water inflow and river confluence.

[0046] For example, consider selecting a small, closed watershed surrounded by mountains as the evaluation unit: First, the water volume is locked in by closing the boundary: the watershed line of the outer mountain ridge is used as the surface boundary, and the groundwater is sealed by the bottom shale aquitard, so that no surface water crosses the mountain to enter or leave, and no groundwater seeps across the area, and all precipitation water production is kept in the watershed.

[0047] Secondly, internal unit nesting is carried out: multiple independent slope units are divided according to slope position, slope gradient and vegetation type, and the bottom edge of each slope unit is close to the tributary ditch; river control sections are set up at the outlet of the tributary ditch and the outlet of the main ditch, so that the water produced by each slope unit flows into only one corresponding ditch and one corresponding downstream monitoring section.

[0048] Based on this, synchronous monitoring and comparison were carried out: the measured vegetation water consumption and slope runoff on the slope were compared with the measured runoff at the river cross-section; when the vegetation water consumption of a certain slope unit increased, the slope runoff decreased, and the river runoff at the corresponding downstream cross-section decreased synchronously, which intuitively reflects the linkage between the slope and the river.

[0049] Finally, water balance verification showed that the total rainfall in the entire basin equaled the sum of the total water consumption of vegetation, the total water yield of the slope, and the change in water storage in the basin. Furthermore, the total water yield of the slope, after deducting river evaporation, basically matched the measured runoff at the basin outlet, proving that all slope water was completely converted into river runoff, and the coupling relationship was intact. Conversely, if water from one slope flows over the mountain and out of the basin, the slope water yield cannot all flow into the local river channels, the coupling relationship is broken, and the coupling relationship between slope water and river runoff cannot be fully reflected.

[0050] In one optional implementation, the multi-level spatial evaluation scale includes: using a grid as the smallest calculation unit, slope units and river control sections as secondary evaluation units, water catchment units as the primary evaluation unit, and the target watershed as the overall evaluation scale, forming a multi-level nested structure of grid-slope-water catchment unit-watershed; wherein, the water catchment unit is a sub-watershed or small watershed.

[0051] In one optional implementation, the division of slope units must simultaneously meet four criteria: topographic criteria, underlying surface criteria, runoff boundary criteria, and hydrological function criteria. The topographic criteria require that the slope position within the same slope unit be uniform (uphill, middle, or downhill) and that the slope gradient be singular (gentle slope 0°~5°, mild slope 5°~15°, steep slope 15°~25°, or extremely steep slope greater than 25°). Slopes crossing different slope positions or gradient gradients must be divided into different units. The underlying surface criteria require that vegetation and land use types be homogeneous, using the boundaries of woodland, shrubland, grassland, and bare land as dividing lines. Areas with similar leaf area index, root depth, and canopy interception capacity should be classified as the same unit, while areas with abrupt changes in vegetation type should be separated into new slope units. The runoff boundary criteria require that the natural watershed and gully edge lines serve as enclosing boundaries. The upper boundary of the unit is the minor watershed, and the lower boundary is adjacent to the shoreline of the nearest tributary, ensuring that all water produced by a single slope unit flows into only one gully, without cross-gully confluence. The hydrological function standard requires that the mechanisms of rainfall infiltration, vegetation transpiration, and slope runoff within a unit be similar. When selecting slope units, it is necessary to avoid boundaries disturbed by human activities (artificial canals, water inlets, etc.). Slopes with field irrigation or small drainage ditches should be divided by artificial structures to prevent artificial water diversion from altering the natural water production process and interfering with the accuracy of water production coefficients and water consumption indicators.

[0052] Specifically, slope position is classified based on topographic elevation, relative elevation difference, and confluence location: the entire slope is divided into three categories from top to bottom: upslope, middle slope, and downslope, using the ridge, middle section of the slope, and valley edge as boundaries. Among them, the upslope is the ridge slope near the watershed, with the highest elevation and the starting point of slope confluence. This area has a small catchment area and thin soil layer, and rainfall is mainly infiltrated and intercepted by vegetation for evaporation. The middle slope is the middle area of ​​the slope, which is the main area of ​​the slope. The soil layer is of moderate thickness, and the vegetation is best developed. The vegetation transpiration and vegetation water consumption are the highest in the entire watershed. The downslope is the slope near the edge of the gully or river channel, which receives the upslope runoff. The amount of interflow and surface runoff is large, and the slope water flows directly into the gully nearby.

[0053] Slope zones are extracted from raster slopes based on digital elevation models (DEMs) and classified according to hydrological runoff characteristics. In one optional implementation, slope zones are divided into the following four categories: gentle slope zones (0°~5°), characterized by strong infiltration, high vegetation water consumption, weak surface runoff, and low water yield coefficient; gentle slope zones (5°~15°), characterized by balanced infiltration and runoff, moderate canopy interception and evaporation, representing the most common slope type in the watershed; steep slope zones (15°~25°), characterized by fast runoff velocity, low infiltration, high surface runoff, and high water yield coefficient; and extremely steep slope zones (greater than 25°), characterized by well-developed interflow, strong soil erosion, poor vegetation rooting conditions, and low vegetation water consumption.

[0054] Based on the above division, slope units satisfy the requirements of having the same slope position, the same slope gradient, and consistent land use or vegetation type; different combinations are split into independently evaluated slopes, and each unit is an independent water-producing unit. For example, in the spatial division operation, the slope position partitioning layer and the slope gradient partitioning layer are overlaid to generate a slope position-slope composite partition; land use (such as woodland, shrubland, grassland, bare land) boundaries are overlaid, and units are segmented at abrupt changes in vegetation type; natural watersheds and gully edges are used as the natural boundaries of slope units, with the bottom edge of the unit closely adhering to the shoreline of a tributary or main gully; the divided slope units are numbered and managed, with the numbering rule adopting the format of "slope position-slope gradient-vegetation type", such as "uphill-gentle slope-woodland", "medium slope-steep slope-shrubland", "downhill-gentle slope-grassland", etc.

[0055] In one optional implementation, the selection of river control sections must correspond to slope units to invert the total runoff of all upstream inflows into the slope, match the runoff calculation of slope units, and serve model calibration and verification. Locations meeting two or more of the following conditions can be designated as key sections: confluences of various levels of channels (e.g., a primary tributary flowing into a secondary tributary, or a tributary flowing into the main channel), where the catchment area above the section is enclosed by several slope units, serving as a confluence node control section; locations where the river channel is narrow or at topographical passes, with clear confluence boundaries and no lateral inflow from tributaries, serving as a natural bottleneck section of the watershed; sections of existing hydrological monitoring stations with year-round rainfall and runoff observations, providing daily measured river flow for hydrological model parameter calibration and slope runoff coupling verification; and downstream river sections at the boundaries of vegetation control or soil and water conservation measures zones, used for water resource controllability assessment.

[0056] Based on the identification of key cross-sections, precise correspondence between slopes and river channels is achieved through spatial analysis: Digital elevation models (DEMs) are used to calculate runoff accumulation and flow direction data, tracking the runoff discharge destination of each slope unit and marking the outflow ditch sections. Slopes whose runoff all flows into the same river section and upstream of the same control cross-section are grouped together, establishing a correspondence between slope groups and corresponding monitoring cross-sections. For example, if a slope unit of a medium-slope gentle forest and a slope unit of a steep downhill shrubland both have their runoff flowing into a first-order tributary, and a monitoring cross-section is set up at the outlet of this tributary, then the two slope units form a precise correspondence with this monitoring cross-section.

[0057] Step S202: Establish water resource effectiveness evaluation indicators and water resource controllability evaluation indicators.

[0058] In this embodiment, the water resource effectiveness evaluation index system is constructed based on the effective precipitation that can be directly utilized by the slope ecosystem. The core carriers of water consumption in the slope ecosystem are vegetation and soil: vegetation mainly consumes slope water directly through vegetation transpiration, canopy interception of evapotranspiration, and ecophysiological water consumption; soil consumes slope water through soil evaporation and water adsorption. The slope water consumption process can improve water resource effectiveness, while the slope water production process has an inhibitory effect. That is, the greater the slope water production, the more water flows into rivers as surface runoff, and the less water resources are available for direct use by slope vegetation and soil; conversely, the smaller the slope water production, the less surface runoff is lost, and the more abundant the water resources that the slope ecosystem can directly utilize. Based on the above mechanism, this embodiment uses vegetation transpiration, canopy interception of evapotranspiration, and vegetation water consumption as positive evaluation indicators characterizing the slope water consumption process, and the water production coefficient as a negative evaluation indicator characterizing the slope water production process, together constituting the water resource effectiveness evaluation index system.

[0059] The construction of a water resources controllability evaluation index system needs to be combined with changes in river runoff, establishing it from two aspects: runoff volume and runoff process. First, to ensure the normal functioning of the river's basic ecological functions, priority should be given to reserving water for the river's ecological water demand. The remaining water volume after deducting the ecological water demand is the available water resources within the river, serving as the basic indicator for river water resources regulation and optimal allocation. Second, the core objective of river runoff regulation is to mitigate peak flows and replenish runoff during dry seasons. By regulating flood peaks and replenishing runoff during dry seasons, runoff fluctuations can be smoothed, and the river's inflow pattern can be stabilized, thereby improving the river's water resources regulation capacity and controllability. Furthermore, the degree of variability in the river's runoff process is a key indicator for measuring the ease of runoff process control, and the degree of variability in precipitation processes is the decisive factor causing changes in the river's runoff process. Based on the above mechanism, this embodiment uses the available water resources in the river channel and the proportion of flow during the dry season as positive evaluation indicators to characterize the runoff, and the ratio of peak flow to the coefficient of variation of rainfall-runoff as negative evaluation indicators to characterize the difficulty of runoff process regulation, together forming a water resources controllability evaluation index system.

[0060] Therefore, in a preferred embodiment, the water resource effectiveness evaluation indicators include vegetation transpiration, canopy intercepted evapotranspiration, vegetation water consumption, and water production coefficient; the water resource controllability evaluation indicators include the amount of water available in the river channel, peak flow, dry season flow ratio, and rainfall-runoff variation coefficient ratio.

[0061] It is worth noting that in the assessment of water resource effectiveness, slope water consumption processes promote the improvement of water resource effectiveness; therefore, vegetation transpiration, canopy intercepted evapotranspiration, and vegetation water consumption are positive indicators for water resource effectiveness assessment. Conversely, slope water production processes inhibit the improvement of water resource effectiveness; therefore, the water production coefficient is a negative indicator for water resource effectiveness assessment. In the assessment of water resource controllability, the amount of usable water resources in the river channel and the proportion of flow during the dry season promote the improvement of water resource controllability; therefore, the amount of usable water resources in the river channel and the proportion of flow during the dry season are positive indicators for water resource controllability assessment. The variability of peak runoff and rainfall-runoff processes inhibits the improvement of water resource controllability; therefore, the ratio of peak flow to rainfall-runoff coefficient of variation is a negative indicator for water resource controllability assessment. The above classification of positive and negative indicators provides a basis for determining the positive ideal optimal solution and the negative ideal worst solution using the TOPSIS method in subsequent step S204.

[0062] Step S203: Obtain the values ​​of water resource effectiveness evaluation indicators and water resource controllability evaluation indicators.

[0063] Before constructing a distributed hydrological model, basic data for the target watershed must be collected. This basic data includes physical geographic data, meteorological and hydrological data, land use data, soil and vegetation data, and socioeconomic data. The data includes: physical geographic data (geographic location, topography, geomorphology, and elevation data) for extracting watershed boundaries, slope, slope length, and slope unit division; meteorological data (daily or hourly data on precipitation, temperature, humidity, wind speed, and radiation) for driving model calculations of potential evapotranspiration and vegetation transpiration; hydrological data (natural and measured runoff data at river control sections) for model calibration and validation; land use data (distribution data of cultivated land, forest land, grassland, and construction land) for determining the underlying surface type of each slope unit; soil data (soil type, soil thickness, and saturated hydraulic conductivity) for determining soil moisture movement parameters; vegetation data (vegetation type, vegetation cover, and leaf area index) for determining core parameters of canopy interception and vegetation transpiration; and socioeconomic data (water conservancy project information and water use data for the three biological processes) for determining the impact of human activities on hydrological processes.

[0064] In one optional implementation, a distributed hydrological model of the target watershed is constructed, and the numerical values ​​of each evaluation index are output through simulation by the distributed hydrological model. The distributed hydrological model uses nested grids of sub-watersheds as the calculation unit, and uses the mosaic method to classify the land use types on the grid units, calculates the water and heat fluxes of each land use type separately, and combines them into the total grid flux by weighting according to the area proportion of each type.

[0065] In this embodiment, the distributed hydrological model is a type of hydrological numerical model with physical mechanisms and spatial discretization. This model combines satellite remote sensing data, geographic information data, and watershed topographic and geomorphological parameters, comprehensively considering the influence of underlying vegetation and soil characteristics on slope and river runoff generation within the catchment area. It calculates hydrological processes such as precipitation interception, vegetation transpiration, soil evaporation, infiltration, runoff generation, interflow, and groundwater runoff in each discrete unit. Then, through inter-unit water exchange and river network runoff calculations, it obtains the overall spatiotemporal hydrological variation process of the watershed, capable of describing the spatiotemporal heterogeneity of watershed hydrological processes, and offering high computational accuracy and speed. For example, the distributed hydrological model can be implemented using the WEP (Water and Energy Transfer Process) model.

[0066] The spatiotemporal variation process of hydrology refers to the entire process of continuous changes in hydrological elements such as rainfall, interception, evaporation, surface runoff, interflow, groundwater recharge, river runoff, and soil water storage over time and space. In the temporal dimension, the same slope unit experiences abundant rainfall and high runoff during the flood season, with evaporation varying according to seasonal vegetation growth, while during the dry season, it relies on groundwater baseflow to replenish the river channel. In the spatial dimension, forest slopes exhibit high interception and transpiration with low runoff, while bare slopes have weak infiltration and high surface runoff. Upstream tributaries have low flow, while the flow gradually increases after converging with the main stream, thus constituting a complete spatiotemporal evolution characteristic.

[0067] For example, taking the same small watershed: in the temporal dimension, when the rainfall in July during the flood season is 12mm, the surface runoff on the forest slope is 4.16mm; while in December, during the vegetation withering period, almost all of the 3mm of rainfall is consumed by soil evaporation, with no surface runoff; in the spatial dimension, on the same day, the surface runoff of an adjacent bare slope under the same rainfall conditions can reach 7.8mm, showing a significant difference from the forest slope. Runoff flows from the upstream slope into the downstream main channel step by step, with the flow gradually increasing along the river, thus constituting a complete spatiotemporal evolution process.

[0068] Based on the aforementioned collected basic data, a distributed hydrological model for the target watershed is constructed. The model data input includes three parts: meteorological data input, spatial data input, and correction parameter input.

[0069] Specifically, spatial data refers to geographic information describing the topography, water system, and underlying surface attributes of a watershed. It is used to construct model computational units and characterize spatial heterogeneity. This includes: topographic data, namely digital elevation models (DEMs), used to extract flow direction, river network, sub-watershed division, contour zone division, and slope and aspect; water system data, namely river network vectors, river segment topology, and the location and parameters of reservoirs and dams; and underlying surface data, namely land use and cover (such as cultivated land, forest land, grassland, urban areas, and water bodies), soil types and profiles (including texture, thickness, porosity, and saturated hydraulic conductivity), and vegetation parameters (including vegetation cover, leaf area index, and root depth).

[0070] Correction parameters refer to adjustable parameters in the model that need to be calibrated. They are used to empirically correct physical process parameters to reduce the deviation between simulated and measured values. Correction parameters include: soil parameters such as soil thickness, saturated hydraulic conductivity, field capacity, and wilting coefficient; vegetation parameters such as interception coefficient, evapotranspiration coefficient, and root water uptake parameters; hydrogeological parameters such as riverbed permeability coefficient, groundwater recharge coefficient, and specific yield; and runoff and engineering parameters such as channel roughness, reservoir scheduling coefficient, and water intake coefficient. Initial values ​​of correction parameters can be obtained by referring to literature, soil survey data, hydrogeological exploration reports, or remote sensing inversion, and then calibrated using measured cross-sectional runoff data to obtain correction parameters suitable for the target watershed.

[0071] In one alternative implementation, the distributed hydrological model is constructed as follows: (a) Spatial partitioning.

[0072] Spatial discretization was performed using a nested partitioning approach of "sub-basins + contour slope zones". Specifically, based on the digital elevation model (DEM) and measured river systems, the D8 flow direction algorithm was used to extract watersheds, dividing closed sub-basins as primary evaluation units to form natural hydrological boundaries. Within each sub-basin, contour slope zones were divided according to elevation and slope, serving as slope units (secondary calculation units). The mosaic method was used to classify various underlying surfaces within a single slope zone, including forest land, farmland, urban areas, bare land, and water bodies, and the water and heat fluxes of each type of underlying surface were calculated separately. The river channel was segmented along the confluence path, and key control sections were set up at the confluence of tributaries and the exit of the main stream, ensuring that each section uniquely received the total water runoff from several upstream slope units.

[0073] (ii) Vertical stratification.

[0074] The model adopts a 9-layer vertical structure, from top to bottom: vegetation canopy interception layer, surface depression filling layer, multi-layer vadose zone soil, transition layer, shallow groundwater, impermeable layer and deep confined water. Infiltration, evaporation, interflow and lateral discharge of groundwater are calculated layer by layer to completely depict the vertical water cycle path.

[0075] (III) Database and module setup.

[0076] The basic input data for the model includes digital elevation model (DEM) topographic data, land use data, soil data, daily meteorological data (rainfall, temperature, radiation, etc.), water system data, water conservancy project data, and regional water intake records. The model comprises five major computational modules: hydrothermal evaporation, slope runoff generation, soil water movement, groundwater movement, and river confluence and artificial water use regulation. These modules are modularly coupled and assembled. The model parameters are calibrated using measured cross-sectional runoff data, and the simulation results are validated.

[0077] Based on this, the model calculates water volume on slopes and in rivers through the following working mechanism. The core mechanism of the model is water-heat balance-driven runoff, that is, calculating the actual evaporation of vegetation and soil using the surface energy balance equation: Rainfall is first intercepted by the canopy, filled in depressions on the surface, and consumed by soil evaporation. The remaining water is distributed according to the following paths: when the rainfall intensity is greater than the infiltration capacity, surface runoff (excessive infiltration runoff) is formed on the slope; when the soil layer is saturated, full-saturation runoff is formed; some of the infiltrated water forms lateral flow in the soil and some recharges groundwater. The groundwater slowly flows out to form baseflow in the river channel, thus simultaneously simulating three types of runoff modes: excessive infiltration runoff, full-saturation runoff, and baseflow overflow.

[0078] For example, the model calculates hydrological processes such as precipitation interception, vegetation transpiration, soil evaporation, infiltration, runoff generation, interflow, and groundwater runoff on each discrete unit. Water surface evaporation is calculated using the Penman formula, vegetation transpiration is calculated using the Penman-Monteith formula, soil evaporation is calculated using the modified Penman formula (considering the soil moisture function), and slope runoff and river runoff are calculated using the kinematic wave equation.

[0079] Based on the completed runoff calculation, the model further couples the slope inflow and river runoff through stepwise confluence calculation from the slope to the river channel: the slope unit uses the kinematic wave formula to calculate the total runoff (the sum of surface runoff and interflow) along the slope direction, with all runoff flowing laterally into the adjacent river segment at fixed points, without flowing out of the sub-basin; the river channel unit performs confluence calculation segment by segment from top to bottom according to the Saint-Venant kinematic wave equation, and each control section summarizes the total runoff of the entire upstream slope. Through the above mechanism, the changes in evaporation and runoff caused by changes in the underlying surface of the slope will change the lateral inflow into the river, thereby causing the runoff at the downstream control section to change synchronously, realizing the complete quantification of the slope-river channel coupling relationship. The sub-basin includes multiple discrete slope units such as forest slopes, bare slopes, and shrublands, and the river channel is classified into first-level tributaries and main channels, with each slope bottom edge connecting to the corresponding ditch nearby. Inter-unit water exchange includes water distribution within slope units, water exchange between slopes and adjacent rivers, and water exchange between groundwater units. Specifically, water distribution within a slope unit refers to the sequential breakdown of a single rainfall event into canopy interception, vegetation transpiration, soil evaporation, infiltration, surface runoff, interflow, and groundwater recharge. Water exchange between slopes and adjacent rivers refers to the complete lateral inflow of surface runoff and interflow generated by the slope unit into the adjacent river section, while the unit's groundwater slowly discharges and continuously recharges the river's baseflow. Water exchange between groundwater units refers to the lateral flow of groundwater between adjacent groundwater calculation units based on hydraulic gradient, with groundwater from higher-level units migrating to lower-level units and partially emerging elsewhere to recharge downstream river sections.

[0080] In the step-by-step calculation of river network confluence, the river channel is segmented and discrete, and a one-dimensional kinematic wave equation is used to calculate the flow from top to bottom segment by segment: each tributary receives lateral inflow from its corresponding slope unit, and the daily flow at the outlet section of each tributary is calculated; after each tributary flows into the main channel, the main channel receives lateral inflow from other slope units, and the calculation continues, finally obtaining the total runoff at the total outlet section of the basin. Through the above process, the individual hydrological quantities dispersed on each discrete slope are collected by lateral inflow into the river network, and then evolve segment by segment through the river channel, realizing the complete transformation from the hydrological quantity of a single unit to the overall runoff process at the outlet of the entire basin.

[0081] In addition, the model incorporates an artificial side-branch regulation module on the basis of the natural water cycle, including the impact of human activities such as reservoir impoundment, farmland irrigation water diversion, urban and rural water intake and drainage, groundwater extraction and soil and water conservation projects. Artificial water intake directly consumes slope soil water or river water, changing the production, runoff and distribution process, in order to adapt to the water resource controllability assessment.

[0082] The model is validated through closed-loop water balance across the entire basin: the total precipitation in the entire basin is equal to the sum of total evaporation water consumption, total slope runoff, and soil and groundwater storage variables (external leakage in the closed sub-basin is approximately zero); the total slope runoff, after deducting the evaporation from the river surface, is matched with the measured runoff at the cross section to ensure the integrity of the hydrological boundary and the authenticity of the slope-river coupling relationship.

[0083] In this embodiment, the distributed hydrological model achieves fine characterization and efficient computation of the spatiotemporal heterogeneity of watershed hydrological processes through the following mechanism.

[0084] (a) Depicting spatiotemporal heterogeneity.

[0085] In the spatial dimension, the model relies on remote sensing data and geographic information data to obtain vegetation leaf area index, land use type, soil spatial distribution and topographic parameters, and divides the watershed into independent discrete units according to characteristics such as vegetation, soil and slope; each unit is assigned localized parameters (such as interception coefficient, hydraulic conductivity, crop coefficient, etc.), forest units adopt high interception and high transpiration parameters, and bare slope units adopt low infiltration and high runoff parameters. Hydrological components are calculated independently for different spatial units, naturally reflecting the spatial differences in runoff generation and confluence.

[0086] In terms of time dimension, the model is driven by daily meteorological time series data. The crop coefficient and leaf area index during the vegetation growth period are adjusted upward (increased transpiration), and the parameters are adjusted downward after the leaves fall in autumn and winter. Evaporation and interception change dynamically with the seasons, accurately reproducing the seasonal temporal changes of hydrological elements.

[0087] By combining spatially differentiated parameters with time-segmented dynamic boundaries, the spatiotemporal differentiation patterns of hydrology are reconstructed from the bottom layer of the model.

[0088] (ii) Ensuring computational accuracy.

[0089] The model adopts a physical mechanism-driven sub-item calculation method. Processes such as interception, evaporation, infiltration, interflow and groundwater are all calculated using physical hydrological formulas. It relies on local parameters such as the underlying surface, soil and topography measured by remote sensing, avoiding the rough estimation caused by the use of uniform parameters for the entire watershed in traditional lumped models.

[0090] Meanwhile, the model performs closed-loop verification by coupling the units with the river network at each level. The water volume of each unit meets the unit water volume balance. The slope inflow and the river confluence are matched step by step. Sensitive parameters are corrected by using measured river cross-section flow. After calibration and verification, the errors in runoff generation and confluence calculation are significantly reduced.

[0091] In addition, the model updates vegetation cover and land use change data year by year through satellite remote sensing, dynamically corrects unit parameters, and adapts to the changes in hydrological patterns brought about by the annual evolution of the underlying surface.

[0092] (iii) Improved computational efficiency.

[0093] In terms of computational efficiency, the model employs discretized, modular, and decoupled computation: the entire watershed is divided into numerous independent small units, and the hydrological processes of each slope unit are calculated in parallel (interception, evaporation, and infiltration are not nested and iterated), with the river network only being connected through lateral inflow at the confluence stage. Compared to solving high-order partial differential equations simultaneously across the entire watershed, the unit equations after decomposition are simpler and the solution is more efficient.

[0094] Meanwhile, the model adopts a hierarchical and segmented calculation method for the river network, with the river network calculated progressively from tributaries to main streams. Small catchment areas are first aggregated and then aggregated upwards level by level, avoiding a large-scale numerical iteration across the entire area at once, thus balancing distributed precision with computational efficiency. Geographic information and satellite data are pre-interpolated in batches and assigned values ​​in zones, completing the automatic assignment of parameters for all watershed units before modeling, saving the time-consuming manual surveying and parameter determination of each unit.

[0095] The model performs calculations based on energy and water cycles. In this embodiment, the energy cycle refers to the process of energy absorption, transfer, consumption, and conversion among the atmosphere, vegetation canopy, land surface, soil, and water bodies, with solar radiation as the primary energy source. Hydrological processes such as evaporation and transpiration are controlled by energy balance. The water cycle refers to the entire process of continuous migration, transformation, and balance of water within a watershed among the atmosphere, vegetation, soil, groundwater, and river channels. The main components include atmospheric precipitation, vegetation canopy interception, surface filling and infiltration, surface runoff, interflow, groundwater recharge, river confluence, and water evaporation and transpiration returning to the atmosphere, forming a closed loop.

[0096] During the calculation process, the model adopts a hierarchical and progressive calculation method. In terms of time scale, the model uses a daily scale as the basic calculation step, inputting daily meteorological data such as rainfall, temperature, and radiation, and calculating various hydrological components daily. For short-duration rainstorm and flood simulations, an hourly scale is used; for the total water resources and multi-year average statistical evaluation, a monthly or annual scale is used. In terms of spatial scale, the model calculates and summarizes water volume step by step, from small to large and from local to overall, following the progression from "basic slope unit → tributary catchment area → sub-basin → entire target watershed." In terms of workflow, it follows the progressive sequence of internal slope hydrological processes → inter-unit water exchange → river network confluence.

[0097] Through hierarchical progressive calculation, the spatial heterogeneity of hydrology can be accurately reflected. That is, the smallest slope unit is calculated independently using local vegetation, soil, and topographic parameters, preserving the differences in runoff generation under different underlying surfaces, and then summarizing at each level, which reflects both local characteristics and overall patterns. It can ensure the rigor of calculation logic and the closure of water balance, that is, water income and expenditure are checked at each level, and errors are checked at each level to improve the overall calculation accuracy. It can adapt to the needs of multi-scale evaluation, and can extract single slope data to carry out slope-scale water resource effectiveness evaluation, as well as extract sub-basin and whole-basin river runoff to carry out regional water resource controllability evaluation, so as to achieve multi-scale results from a single model. At the same time, it can improve calculation efficiency and reduce solution difficulty. That is, after splitting, small units are calculated independently, avoiding the need for complex simultaneous equations across the whole basin. The runoff is gradually aggregated at each level, the calculation logic is simple, the iteration is small, and high accuracy and high calculation speed are balanced.

[0098] At the element scale, the radiation module is first invoked to calculate the energy cycle process grid by grid. In this embodiment, the element scale refers to the spatial resolution or statistical unit used in the hydrological model for different hydrological, meteorological, and underlying surface elements. It is a quantitative standard for distinguishing the spatial refinement of different elements. The distributed model uses grids as the basic spatial unit, and different elements can use consistent or differentiated scales. The scale size directly determines the simulation refinement. The radiation module is the input module for the energy cycle and also the core front-end module for hydrothermal coupling. It is used to calculate the total solar radiation and net radiation of each grid based on meteorological observation data and topographic and vegetation corrections. Net radiation is the energy source for water phase change processes such as vegetation transpiration and soil evaporation, directly driving the entire energy cycle and water cycle. The core calculation content of the radiation module includes: calculating theoretical astronomical radiation (solar radiation at the upper atmospheric boundary); calculating the total solar radiation reaching the surface by combining sunshine hours, cloud cover, and atmospheric transparency; calculating the surface net radiation (i.e., the effective radiation actually absorbed by the surface or vegetation) by combining grid vegetation cover and surface albedo; and outputting the daily net radiation grid by grid, which is then passed to the evapotranspiration calculation module as a driving term for the energy cycle.

[0099] For example, using a single forest grid as the computational unit and a daily timescale, the following explanation is provided: After the radiation module outputs net radiation, the net radiation Rn reaching the grid is distributed according to the surface energy balance equation. The energy destination is divided into four parts: sensible heat flux H, latent heat flux LE, soil heat flux G, and grid cell energy storage change ΔQ, i.e., Rn = H + LE + G + ΔQ. Here, Rn is the net surface radiation of the grid (total input energy), H is the sensible heat flux for heating the air, LE is the latent heat flux for energy consumption through water evaporation and transpiration (a coupling term between the water cycle and energy cycle), G is the soil heat flux for heating the lower soil layer, and ΔQ is the grid cell energy storage change (a value that is extremely small at the daily scale and can be ignored in conventional calculations). The latent heat flux LE directly corresponds to vegetation transpiration and soil evaporation and is the key to energy-driven water movement.

[0100] In the step-by-step grid-by-grid calculation, the energy fluxes are first calculated separately based on parameters such as grid temperature, wind speed, vegetation height, and soil moisture. The latent heat flux is obtained by back-calculation from the energy balance, i.e., LE=Rn. H G. Then, the latent heat flux is decomposed into vegetation transpiration latent heat and soil evaporation latent heat according to the grid vegetation cover; the energy is converted into evaporation and transpiration water volume (unit: mm) using the latent heat of vaporization constant, completing the conversion of energy cycle to water cycle (at room temperature, water vaporization latent heat L≈2.45MJ / kg, 1mm water depth corresponds to 1kg / m² water volume). Finally, an energy closure check is performed on a single grid to verify whether Rn=H+LE+G holds true.

[0101] In the grid-by-grid batch calculation across the entire watershed, all grids within the watershed are traversed, with each grid independently executing the above process. Different underlying surface grids are assigned differentiated parameter values ​​(e.g., bare land grids have high albedo, low vegetation transpiration latent heat, and high soil evaporation latent heat; dense forest grids have low albedo and a large proportion of vegetation transpiration latent heat). After the energy calculations for all grids are completed, the water results of each grid are linked to carry out inter-unit water exchange and river network confluence calculations. Through the above grid-by-grid energy cycle calculation, with each grid as an independent unit, the net radiation is first obtained from the radiation module, and then the sensible heat, latent heat, and soil heat flux are decomposed according to the surface energy balance equation. The latent heat flux is further converted into hydrological components such as vegetation transpiration and soil evaporation, realizing energy cycle driving water cycle. The independent calculation of the entire watershed grid naturally reflects the spatial heterogeneity of the underlying surface, balancing simulation accuracy and computational efficiency.

[0102] The system then calls upon the surface runoff generation module, slope runoff module, and river runoff module to calculate the key elements of the water cycle. In this embodiment, the key elements of the water cycle refer to the various runoff components and runoff results formed after precipitation is intercepted by the canopy, evaporated, transpirated, and distributed through infiltration. These are core quantitative indicators that connect the hydrological processes of slopes, gullies, and watersheds. Specifically, they include surface runoff, slope runoff, soil runoff, groundwater runoff (baseflow), segmented river flow, and total flow at the watershed outlet section. The preceding elements include canopy interception, vegetation transpiration, soil evaporation, and soil infiltration.

[0103] The surface runoff module uses single-grid or slope units as computational units. It combines rainfall, infiltration capacity, soil moisture content, and underlying surface conditions to determine the runoff mechanism (over-infiltration runoff or saturation runoff), calculating the surface runoff within the unit. Simultaneously, it outputs infiltration, interflow, and groundwater recharge, serving as the initial stage of the entire runoff process. The slope runoff module receives the calculation results from the surface runoff module, simulating the collection and movement of water flow downhill within a single slope. It aggregates the runoff from discrete grids into the total inflow for the entire slope, distinguishing between surface runoff and interflow runoff. This completes the aggregation from grid runoff to the overall slope inflow, preparing for river flow. It outputs the total surface runoff and total interflow for the slope. The river confluence module is used to receive lateral inflows from all surrounding slopes, calculate water flow movement from top to bottom along the hierarchical river network (from tributaries to main stream), summarize upstream water inflows level by level, calculate real-time flow at each control section and watershed outlet, and finally obtain the overall watershed runoff process. It is the final aggregation link of the runoff process, outputting the flow of each river section, the flow of each hydrological control section, and the total flow of the watershed outlet.

[0104] In the overall calculation, the order of calling each module is as follows: first, the radiation module and energy balance module are called to output vegetation transpiration and soil evaporation; then, the surface runoff generation module is called to perform runoff generation calculation at the grid scale; next, the slope runoff confluence module is called to perform runoff aggregation at the slope scale; and finally, the river runoff confluence module is called to perform runoff calculation at each level of the river network. The data is passed and calculated step by step to form a complete calculation link of "radiation + energy balance → surface runoff generation → slope runoff confluence → river runoff confluence".

[0105] The specific calculation process for each indicator is as follows: Vegetation transpiration and soil evaporation are calculated by the radiation module and the surface energy balance module: The radiation module takes into account data such as sunshine duration, temperature, and latitude to calculate astronomical radiation, total solar radiation, and net surface radiation; the energy balance module constructs the surface energy balance equation based on net radiation, decomposes sensible heat flux and soil heat flux, and calculates the total latent heat flux; the latent heat flux is decomposed into vegetation transpiration latent heat and soil evaporation latent heat according to the grid vegetation cover; the energy flux is converted into water volume using the latent heat of water vaporization to obtain vegetation transpiration and soil evaporation. Evaporation and evaporation, as water consumption, are directly input into the surface runoff generation module to participate in rainfall redistribution calculations.

[0106] The slope runoff is calculated by the surface runoff generation module and the slope runoff collection module: In the surface runoff generation module, the daily rainfall, canopy interception, vegetation transpiration, soil evaporation, soil infiltration capacity, and soil moisture content are used as inputs. Effective rainfall is subtracted from infiltration and evapotranspiration in sequence, and the remaining water volume forms grid surface runoff and interflow. Infiltrated water replenishes groundwater and subsequently forms groundwater runoff. The output is the surface runoff, interflow, and groundwater recharge of a single grid. In the slope runoff collection module, the surface runoff and interflow of all grids in the slope are summarized. The kinematic wave equation is used to simulate the water flow along the slope direction. The groundwater recharge is output as slope groundwater runoff (baseflow) after groundwater regulation. The total slope runoff is obtained by summing the surface runoff, interflow, and groundwater runoff.

[0107] The river runoff and discharge are calculated by the river confluence module: the slope runoff (lateral inflow) of multiple adjacent slopes, the river network topology, the length of the river segment, the roughness of the river channel, and the cross-sectional morphology are used as inputs. The tributaries are calculated first and then flow into the main stream, following the one-dimensional kinematic wave equation to push the flow segment by segment. A single river segment receives the upstream inflow and the lateral runoff from the slopes on both sides to obtain the river runoff of this river segment. The water flow evolves along the river channel to the hydrological control section or the watershed outlet, and finally outputs the cross-sectional river runoff.

[0108] The model output data includes evaporation, transpiration, river runoff, slope runoff, and river runoff.

[0109] During the processing of model output data, scale transformation is necessary because the time or spatial scale of the model calculations may differ from the time and spatial scales required for water resource effectiveness and controllability assessment. Spatially, when the grid scale simulated by the model differs from the required spatial scale for assessment, spatial analysis tools are used to unify the grid data (e.g., converting coarse grid data from the model output to the fine grid scale required for assessment). Temporally, when the time scale simulated by the model (e.g., daily scale) differs from the required time scale for assessment (e.g., monthly or yearly scale), daily-scale data is converted to monthly or yearly-scale data. After scale transformation, water resource effectiveness assessment indicators and water resource controllability assessment indicators are calculated separately.

[0110] Through the above steps, the values ​​of each evaluation index output by the model can be used to determine the weights using the entropy weight method and calculate the relative closeness using the TOPSIS method in step S204, thereby supporting the determination of the synergistic change characteristics of water resource effectiveness and controllability in step S205.

[0111] Step S204: Determine the weight of each evaluation indicator, and based on the multi-objective decision-making method, calculate the relative proximity of water resource effectiveness and relative proximity of water resource controllability for each evaluation object according to the values ​​and weights of each evaluation indicator.

[0112] Specifically, step S204 above includes: Step S2041: The entropy weight method is used to determine the weight of each evaluation indicator. The entropy weight method automatically calculates the weight based on the dispersion or information entropy value of the original data of each evaluation indicator. The greater the fluctuation of the indicator data and the more information it contains, the higher its weight is assigned. It relies entirely on the statistical characteristics of the data itself rather than human experience judgment.

[0113] In this embodiment, original data matrices are constructed for the water resource effectiveness evaluation index and the water resource controllability evaluation index, respectively. Assume there are n evaluation objects (i.e., each evaluation unit determined in step S201) and m evaluation indicators (m is the total number of indicators in the current evaluation system; water resource effectiveness and water resource controllability each contain 4 indicators, calculated independently), forming the original data indicator matrix B: ; Where x ij Let represent the raw data of the j-th indicator for the i-th evaluation object, where ; , This represents the total number of evaluation objects; This indicates the total number of selected evaluation indicators (e.g., m=4 when evaluating water resource effectiveness, and m=4 when evaluating water resource controllability).

[0114] The range standardization method is used to standardize the indicator data to eliminate differences in units and orders of magnitude among the indicators. For positive indicators: ; For negative indicators: ; in, This represents the standardized value of the j-th indicator for the i-th evaluation object. and Let $\mathbf{j}$ be the maximum and minimum values ​​of the $j$-th indicator among all evaluation objects, respectively. After standardization, the standardized evaluation matrix $R$ is obtained. ; Then, calculate the weight of the indicator value of the i-th evaluation object under the j-th indicator: ; Calculate the entropy value of the j-th index: ; Calculate the weight of the j-th indicator: ; In the above formula, n represents the number of evaluation objects, such as n evaluation years; Indicates the number of evaluation indicators; This represents the weight of the i-th evaluation object under the j-th indicator; , .

[0115] The objective weights of each evaluation indicator can be obtained through the entropy weight method described above. A higher weight value indicates greater importance of the indicator in the evaluation system and a stronger ability to discriminate the effectiveness of slope ecological water resources. The entropy weight method was performed independently for both water resource effectiveness and water resource controllability evaluation indicators, yielding the weights of each effectiveness indicator and each controllability indicator, respectively.

[0116] Step S2042: The TOPSIS method is used to calculate the relative proximity of water resource effectiveness and water resource controllability for each evaluation object. First, the positive ideal optimal solution and negative ideal worst solution for each evaluation index are determined based on the TOPSIS method. Second, the first Euclidean distance from each evaluation object to the positive ideal optimal solution and the second Euclidean distance from each evaluation object to the negative ideal worst solution are calculated. Finally, the second Euclidean distance is divided by the sum of the first and second Euclidean distances to obtain the relative proximity.

[0117] For water resource effectiveness assessment, an evaluation matrix is ​​constructed using four indicators: vegetation transpiration, canopy evapotranspiration interception, vegetation water consumption, and water yield coefficient. Vegetation transpiration, canopy evapotranspiration interception, and vegetation water consumption are positive indicators, while the water yield coefficient is a negative indicator. Combining the effectiveness indicator weights determined in step S2041, the relative closeness of water resource effectiveness for each evaluation object is calculated according to the following steps. For water resource controllability assessment, an evaluation matrix is ​​constructed using four indicators: available water resources in the river channel, peak flow, proportion of dry season flow, and the ratio of rainfall-runoff coefficient of variation. Available water resources in the river channel and proportion of dry season flow are positive indicators, while peak flow and the ratio of rainfall-runoff coefficient of variation are negative indicators. Combining the controllability indicator weights determined in step S2041, the relative closeness of water resource controllability for each evaluation object is calculated according to the same steps.

[0118] The specific process is as follows: The first step is to combine the weights of each indicator obtained in step S2041 with the standardized original data to construct a weighted decision matrix: ; in Let j be the weighted standardized value of the j-th indicator for the i-th evaluation object. Let be the weight of the j-th indicator.

[0119] The second step is to determine the positive ideal optimal solution and the negative ideal worst solution for each evaluation index.

[0120] The optimal combination of each indicator across all evaluation objects constitutes the positive ideal optimal solution: ; The worst-case combination of each indicator constitutes the negative ideal worst-case solution: .

[0121] The third step, for the i-th evaluation object, is to calculate the Euclidean distance between the evaluation object and the positive ideal optimal solution and the negative ideal worst solution, which is to square the difference between the value of the evaluation object on each index and the value of that index in the positive / negative ideal solution, sum them, and then take the square root: ; ; in, Let be the Euclidean distance from the i-th evaluation object to the positive ideal optimal solution. Let be the Euclidean distance from the i-th evaluation object to the worst-case negative ideal solution; Let j be the positive ideal optimal solution for the j-th index. The worst-case scenario for the j-th index is the negative ideal solution. is the weighted standardized value of the j-th indicator for the i-th evaluation object; m is the total number of evaluation indicators.

[0122] Step 4: Calculate the relative closeness: ; Where Si represents the relative proximity of the i-th evaluation object, with a value range of [0,1]. The larger the Si value, the closer the evaluation object is to the positive ideal optimal solution, that is, the higher the effectiveness of slope ecological water resources.

[0123] Through the above steps, the relative proximity of water resource effectiveness and relative proximity of water resource controllability of each evaluation object are obtained respectively. The value range of both proximity is [0,1]. The larger the value, the higher the water resource effectiveness or controllability of the evaluation object.

[0124] Step S205: Based on the relative proximity of water resource effectiveness and the relative proximity of water resource controllability, determine the evaluation level and synergistic change characteristics of water resource effectiveness and water resource controllability for each evaluation object.

[0125] The aforementioned relative proximity of water resource effectiveness and relative proximity of water resource controllability both range from [0,1]. To better characterize the spatiotemporal variation of water resource effectiveness and controllability in the basin, this embodiment divides the effectiveness proximity and controllability proximity into five levels, and names the levels from low to high using numbers 1 to 5, where [0, 0.2) is the very poor level, [0.2, 0.4) is the poor level, [0.4, 0.6) is the average level, [0.6, 0.8) is the good level, and [0.8, 1] is the very good level.

[0126] In a preferred embodiment, the cooperative change features include synchronous change and asynchronous change; The evaluation level for water resource effectiveness is changed synchronously to be the same as the evaluation level for water resource controllability; The evaluation level of water resource effectiveness differs from the evaluation level of water resource controllability due to asynchronous changes.

[0127] In one optional implementation, based on the judgment results of the coordinated change characteristics of water resource effectiveness and water resource controllability in each evaluation unit, a spatial analysis tool (such as ArcGIS software) is used to statistically analyze the coordinated change of water resource effectiveness and water resource controllability at the watershed scale, generating a spatial distribution map of the evaluation level and coordinated change characteristics of water resource effectiveness and water resource controllability at the watershed scale, so as to intuitively display the coordinated status of water resource effectiveness and controllability in each region within the watershed.

[0128] The solution of the present invention will be explained and illustrated below with specific implementation examples.

[0129] This embodiment uses the upper reaches of the Pihe River as the target river, with a drainage area of ​​1816.8 km². The entire area is predominantly mountainous, with terrain mainly consisting of low and medium mountains and canyons. The terrain slopes from south to north, with steep slopes and rapid currents, and mountainous areas account for over 70% of the area. This invention uses the upper reaches of the target river as a case study area to clearly and completely describe the specific processes and technical solutions of this invention. Specifically, it includes the following steps: (1) Basic data collection.

[0130] The evaluation basin was defined as the upper reaches of the target river, and the necessary basic data were collected. Topographic data, using a 90m resolution digital elevation model (DEM), was used for basin discretization and topographic feature extraction. Meteorological data, including multi-year average precipitation, temperature, wind speed, humidity, radiation, and evaporation, were obtained from meteorological station monitoring data within the basin. Soil data, including soil type, soil texture, and field capacity, was collected. Vegetation data, including vegetation cover, vegetation type, and leaf area index, was obtained through remote sensing image inversion. Hydrological monitoring data, including soil moisture content and river runoff, were obtained from hydrological stations and reservoir monitoring data within the basin. Hydraulic engineering data, including the storage capacity and regulation capacity of several large reservoirs within the basin, was collected. Land use data, using remote sensing interpretation data, was used to clarify the distribution of land use types within the basin.

[0131] (2) Construction of distributed hydrological model and calculation of indicators.

[0132] Based on the aforementioned collected basic data, a distributed hydrological model of the upstream basin of the target river was constructed, spatially discretizing the study area into 150m×150m grids. To eliminate the complexity of land use types within the grid cells, the model used a mosaic method to classify land use types within the grid cells, including water bodies, bare land-vegetated areas, and impermeable water bodies, calculating the water and heat fluxes for different land use scenarios within each grid cell. Sensitive parameters such as soil moisture content, vegetation cover, and runoff coefficient were further identified and calibrated using a surrogate optimization calibration method. Natural runoff data from two hydrological stations within the upstream basin of the target river from 1972 to 2020 were selected to validate the simulation results of the distributed hydrological model. The validation results are shown in Table 1, serving as verification of the simulation results of the distributed hydrological model of the upstream basin of the target river. The verification results show that, whether in the calibration period or the verification period, the Nash efficiency coefficients of the two hydrological stations are all above 0.7, the correlation coefficients are all above 0.85, and the absolute values ​​of the relative errors are all less than 10%. The model simulation results are good and meet the simulation requirements, which can provide data support for subsequent indicator calculations.

[0133] Through model simulation, we can accurately obtain water resource effectiveness evaluation indicators (vegetation transpiration, canopy intercepted evapotranspiration, vegetation water consumption and water production coefficient) and water resource controllability evaluation indicators (water resources available in the river channel, peak flow, dry season flow ratio and rainfall-runoff coefficient of variation ratio).

[0134] Table 1

[0135] (3) Evaluation of water resource effectiveness and controllability.

[0136] The watershed water resources effectiveness and controllability evaluation model was used to evaluate the simulated water resources effectiveness and controllability evaluation indicators of the upstream watershed of the target river. The water resources effectiveness and controllability proximity scores for the upstream watershed of the target river from the 1970s to the 2010s were obtained, such as... Figure 3 As shown, the spatial distribution of proximity of water resource availability and water resource controllability in the upstream basins of the target rivers in different years are respectively as follows: Figure 4 and Figure 5 As shown. In this embodiment, 1970s~2010s refers to five decade periods: 1970~1979, 1980~1989, 1990~1999, 2000~2009, and 2010~2020.

[0137] The evaluation results show that: from the 1970s to the 2010s, the water resource availability accuracy of the target river's upstream basin was between 0.4 and 0.6, which was at a moderate level; by the 2010s, the accuracy had decreased to a poor level. The water resource controllability accuracy was at a moderate level in the 1970s; from the 1980s to the 1990s, it was between 0.2 and 0.4, both at a poor level; and from the 2000s to the 2010s, the controllability accuracy was greater than 0.6, which was at a relatively good level.

[0138] In terms of spatial distribution, the number of areas with poor or lower water resource availability in the upstream basin of the target river increased significantly from the 1970s to the 2010s, indicating that the overall water resource availability of the entire basin deteriorated; while the number of areas with good or higher water resource controllability increased significantly, indicating that the overall water resource controllability of the entire basin improved.

[0139] (4) Determination of collaborative change characteristics.

[0140] Based on the aforementioned spatiotemporal hierarchical characteristics of water resource availability and controllability in the upstream basins of the target rivers from the 1970s to the 2010s, a statistical analysis was conducted on the co-evolutionary characteristics of water resource availability and controllability in the upstream basins of the target rivers from the 1970s to the 2010s. Table 2 shows the co-evolutionary characteristics of water resource availability and controllability in the upstream basins of the target rivers from the 1970s to the 2010s, as well as the spatial distribution characteristics of the synchronous or asynchronous development of water resource availability and controllability in the basin (as shown in Table 2). Figure 6 and Figure 7 (As shown).

[0141] The results show that in the 1970s, the water resources effectiveness and controllability of the basin were both at a general level, exhibiting synchronous development characteristics. From the 1980s to the 2010s, both characteristics were at different levels, exhibiting asynchronous development characteristics. Spatially, from the 1970s to the 2010s, the areas with synchronous development of water resources effectiveness and controllability in the upstream basin of the target river were less than those with asynchronous development. The synchronous development area showed a decreasing trend, while the asynchronous development area showed an increasing trend, with the area of ​​asynchronous development ranging from 69.2% to 96.7%.

[0142] Table 2

[0143] This embodiment also provides a device for the coordinated evaluation of watershed water resource effectiveness and controllability. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0144] This embodiment provides a device for the coordinated evaluation of the effectiveness and controllability of water resources in a watershed, such as... Figure 8 As shown, it includes: The evaluation unit division module 801 is used to take the catchment unit of the target watershed as the main evaluation unit, and nest the division of slope unit and river control section as secondary evaluation units to form a multi-level spatial evaluation scale, and take each evaluation unit in the multi-level spatial evaluation scale as the evaluation object. The indicator system establishment module 802 is used to establish water resource effectiveness evaluation indicators and water resource controllability evaluation indicators; The indicator value acquisition module 803 is used to acquire the values ​​of water resource effectiveness evaluation indicators and water resource controllability evaluation indicators; The proximity calculation module 804 is used to determine the weight of each evaluation indicator. Based on the multi-objective decision-making method, it calculates the relative proximity of water resource effectiveness and relative proximity of water resource controllability of each evaluation object according to the value and weight of each evaluation indicator. The collaborative evaluation module 805 is used to determine the evaluation level and collaborative change characteristics of water resource effectiveness and water resource controllability for each evaluation object based on the relative proximity of water resource effectiveness and water resource controllability.

[0145] The watershed water resources effectiveness and controllability co-evaluation device provided in this embodiment of the invention can execute the watershed water resources effectiveness and controllability co-evaluation method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0146] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0147] The following is a detailed reference. Figure 9 This diagram illustrates a suitable structural schematic for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 901, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 902 or a program loaded from memory 908 into random access memory (RAM) 903. The RAM 903 also stores various programs and data required for the operation of the electronic device. The processor 901, ROM 902, and RAM 903 are interconnected via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0148] Typically, the following devices can be connected to I / O interface 905: input devices 906 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 907 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 908 including, for example, magnetic tapes, hard disks, etc.; and communication devices 909. Communication device 909 allows electronic devices to exchange data via wireless or wired communication with other devices. Although Figure 9 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0149] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 909, or installed from a memory 908, or installed from a ROM 902. When the computer program is executed by the processor 901, it performs the functions defined in the watershed water resources effectiveness and controllability collaborative evaluation method of the embodiments of the present invention.

[0150] Figure 9 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0151] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the watershed water resources effectiveness and controllability co-evaluation method shown in the above embodiments is implemented.

[0152] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0153] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for synergistic evaluation of the effectiveness and controllability of water resources in a watershed, characterized in that, The method includes: The target watershed catchment unit is used as the main evaluation unit, and the slope unit and river control section are nested as secondary evaluation units to form a multi-level spatial evaluation scale. Each evaluation unit in the multi-level spatial evaluation scale is used as the evaluation object. Establish water resource effectiveness evaluation indicators and water resource controllability evaluation indicators; Obtain the values ​​of the water resource effectiveness evaluation index and the water resource controllability evaluation index; The weights of each evaluation indicator are determined, and based on the multi-objective decision-making method, the relative proximity of water resource effectiveness and relative proximity of water resource controllability of each evaluation object are calculated according to the values ​​of each evaluation indicator and the weights. Based on the relative proximity of water resource effectiveness and the relative proximity of water resource controllability, the evaluation level and synergistic change characteristics of water resource effectiveness and water resource controllability for each evaluation object are determined.

2. The method according to claim 1, characterized in that, The multi-level spatial evaluation scale includes: using a grid as the smallest calculation unit, slope units and river control sections as secondary evaluation units, the catchment unit as the primary evaluation unit, and the target watershed as the overall evaluation scale, forming a multi-level nested structure of grid-slope-catchment unit-watershed; wherein the catchment unit is a sub-watershed or small watershed.

3. The method according to claim 1, characterized in that, The slope units are divided according to slope position and slope zone. Within the same slope unit, the slope position, slope zone and land use type are the same. The river control sections are set at the confluence of ditches at all levels, natural bottlenecks in the watershed or existing hydrological monitoring sections.

4. The method according to claim 1, characterized in that, The water resource effectiveness evaluation indicators include vegetation transpiration, canopy intercepted evapotranspiration, vegetation water consumption, and water yield coefficient; the water resource controllability evaluation indicators include the amount of water available in the river channel, peak flow, dry season flow ratio, and the ratio of rainfall to runoff variation coefficient.

5. The method according to claim 1, characterized in that, The process of obtaining the values ​​of the water resources effectiveness evaluation index and the water resources controllability evaluation index includes: constructing a distributed hydrological model of the target watershed, and simulating and outputting the values ​​of each evaluation index through the distributed hydrological model.

6. The method according to claim 5, characterized in that, The distributed hydrological model uses nested sub-basin grids as computational units. The mosaic method is used to classify the land use types on the grid units, calculate the water and heat fluxes of each land use type separately, and then weight and merge them into the total grid flux according to the area proportion of each type.

7. The method according to claim 1, characterized in that, Determining the weight of each of the evaluation indicators includes: using the entropy weight method to determine the weight of each of the evaluation indicators; The multi-objective decision-making method calculates the relative proximity of water resource effectiveness and water resource controllability of each evaluation object based on the values ​​of each evaluation index and the weights, including: calculating the distance between each evaluation object and the ideal solution based on the TOPSIS method to obtain the relative proximity.

8. The method according to claim 1, characterized in that, The characteristics of coordinated change include synchronous change and asynchronous change; The synchronous change is that the evaluation level of water resource effectiveness is the same as the evaluation level of water resource controllability; The asynchronous change refers to the fact that the evaluation level of water resource effectiveness is different from the evaluation level of water resource controllability.

9. A device for synergistic evaluation of the effectiveness and controllability of water resources in a watershed, characterized in that, The device includes: The evaluation unit division module is used to take the catchment unit of the target watershed as the main evaluation unit, and nest the division of slope unit and river control section as secondary evaluation units to form a multi-level spatial evaluation scale, with each evaluation unit in the multi-level spatial evaluation scale as the evaluation object. The indicator system establishment module is used to establish water resource effectiveness evaluation indicators and water resource controllability evaluation indicators; The indicator value acquisition module is used to acquire the values ​​of the water resource effectiveness evaluation indicator and the water resource controllability evaluation indicator; The proximity calculation module is used to determine the weight of each evaluation indicator, and based on the multi-objective decision-making method, calculates the relative proximity of water resource effectiveness and relative proximity of water resource controllability of each evaluation object according to the value of each evaluation indicator and the weight. The collaborative evaluation module is used to determine the evaluation level and collaborative change characteristics of water resource effectiveness and water resource controllability for each evaluation object based on the relative proximity of water resource effectiveness and the relative proximity of water resource controllability.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the watershed water resources effectiveness and controllability collaborative evaluation method as described in any one of claims 1 to 8.

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