Quantitative Diagnosis Method and System for Water Conservation Function Integrating Hydrological and Ecological Elements

Abstract

A quantitative diagnosis method and system for water conservation function integrating hydrological and ecological elements, comprising the following steps: obtaining spatial data and non-spatial data of the target basin; obtaining key elements of the hydrological process of the target basin and ecological elements representing vegetation growth adaptable to the basin based on hydrological models and statistical analysis methods; processing and calculating the obtained key elements of the hydrological process and ecological elements representing vegetation growth adaptable to the basin; constructing a comprehensive evaluation index matrix for water conservation function based on key hydrological elements and ecological elements, calculating the water conservation function index, and diagnosing the water conservation function of the basin. Developing a comprehensive and objective quantitative diagnosis and evaluation method for the water conservation capacity of the basin ecosystem provides an important way and method for quantifying the changes in the water conservation function of the basin ecosystem and the improvement of ecosystem service functions, and provides theoretical support for the reasonable implementation of basin comprehensive management.

Description

Technical Field

[0001] The present invention relates to the field of eco - hydrology, and particularly to a method and system for quantitatively diagnosing the water conservation function by integrating hydrological and ecological elements. Background Art

[0002] The terrestrial water cycle and the health status of water resources are important prerequisites for ensuring regional sustainable development and ecosystem security. As an important part of ecosystem services, the water conservation function plays a crucial role in the stability and sustainability of regional ecosystems. The weakening of its function will directly lead to a decrease in biodiversity in the basin ecosystem, an intensification of land desertification, and even phenomena such as deterioration of local weather conditions, causing the originally dynamically balanced basin ecosystem to become unbalanced, and further affecting the landscape structure and ecological functions in the basin ecosystem.

[0003] In recent decades, scholars at home and abroad have conducted a large number of studies on the ecosystem services of river basins, especially the water conservation function. The research methods and perspectives are diverse. Currently, the methods for calculating the water conservation function mostly focus on exploring the variation laws and influencing factors of single or a few hydrological elements (such as surface runoff, soil water, water yield), or only focus on the changes in vegetation growth conditions and their impacts. There are also studies that conduct local analysis and discussion through field sampling at the station scale. Considering only from the perspective of water conservation volume or hydrological elements, due to the single data volume or short time scale, the evaluation conclusions obtained have great uncertainties. Most of the work often ignores the integrity of the basin ecosystem and lacks theoretical research on the combined effects of hydrological processes and multiple ecosystem elements on the water conservation function. Most of the existing calculation methods for the water conservation function of river basins consider fewer factors, have a smaller scale, and are also discontinuous in the time series. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for quantitatively diagnosing the water conservation function by integrating hydrological and ecological elements, so as to solve the problem that existing methods only discuss the water conservation volume of the river basin but are difficult to reflect the function of water - conserving vegetation.

[0005] To achieve the above - mentioned purpose, the present invention adopts the following technical solutions:

[0006] A method for quantitatively diagnosing the water conservation function by integrating hydrological and ecological elements, comprising the following steps:

[0007] Obtain the spatial data and non - spatial data of the target river basin;

[0008] Based on the methods of hydrological models and statistical analysis, obtain the key elements of the hydrological process of the target river basin and the ecological elements representing the vegetation growth of the adapted river basin;

[0009] Process and calculate the key elements of the hydrological process and the ecological elements representing the growth of the vegetation adapted to the basin.

[0010] Based on the key hydrological elements and ecological elements, construct a comprehensive evaluation index matrix for water conservation function, calculate the water conservation function index, and diagnose the water conservation function of the basin.

[0011] Furthermore, the spatial data includes digital elevation model, land use data, soil property data, meteorological data, evapotranspiration data, and gross primary productivity data; the non-spatial data includes hydrological data and literature data.

[0012] Furthermore, the key elements of the basin hydrological process include: soil water SW, evaporation ET, surface rapid flow Q s and water yield WY. The ecological element indicating the growth of the vegetation in the water conservation area selects the gross primary productivity GPP element. GPP is the total amount of organic matter produced by the plant community in the ecosystem per unit time and unit area.

[0013] Furthermore, calculate the water conservation amount WR of the basin according to the water balance theory, and select the coefficient of variation of water yield to characterize this property Cv WY , Cv WY It is calculated by the change of water yield on the time scale at the scale of the basin hydrological response unit, specifically including:

[0014] After the SWAT hydrological model is verified and calibrated, use geographic information system software and R software to perform statistical calculations and analyses on the output file (output.hru) of the SWAT model. Use the R program to extract the soil water SW, evaporation ET, surface rapid flow Q s , water yield WY and the input precipitation P data on the scale of the basin hydrological response unit HRU, and calculate WR and Cv WY for each HRU according to the extracted hydrological elements;

[0015] The calculation formula for the water conservation amount WR:

[0016] WR i =P i -ET i -Q si (1)

[0017] In the formula: i represents the hydrological response unit number; WR is the water conservation amount, mm; P refers to the precipitation, mm; ET refers to the evapotranspiration, mm; Q S refers to the surface rapid flow, mm;

[0018] The coefficient of variation of water yield Cv WYStatistical calculation: The amplitude of the change of WY over time is expressed by Cv, and the mean value Mean of the monthly runoff of each hydrological response unit in the study area is statistically analyzed. WY , standard deviation SD WY , and then calculate the coefficient of variation Cv of the runoff of each hydrological response unit WY . Different underlying surface condition factors have different runoff generation capabilities, and the coefficients of variation are different; the larger the coefficient of variation, the greater the short-term water production fluctuation under this underlying surface factor, and the poorer the long-term water conservation ability; the smaller the coefficient of variation, the smaller the short-term water production fluctuation under this underlying surface factor, indicating that the water conservation ability of the underlying surface is relatively strong.

[0019] Cv WY_i = SD WY_i / Mean WY_i (2)

[0020] In the formula: i is the number of the hydrological response unit HRU; Cv WY_i is the coefficient of variation of the runoff of the hydrological response unit with the i-th number; SD WYi is the standard deviation of WY of the hydrological response unit with the i-th number; Mean i is the mean value of WY of the hydrological response unit with the i-th number.

[0021] Furthermore, the processing of GPP data:

[0022] First, use the "Buffer" function in the spatial analysis of geographic information system according to the contour area of the basin; second, extract the basin GPP according to the basin range and buffer area, and reclassify the basin GPP data into block accuracy data by using the "Reclassify" function; then use the "Zonal" function to conduct regional statistical analysis according to HRU to obtain the spatial distribution pattern of the basin GPP at the HRU scale; automate the calculation of the above process through Python programming to obtain the annual GPP data of the basin at the HRU scale.

[0023] Furthermore, calculate the water conservation function index:

[0024] First, construct a comprehensive evaluation index matrix of water conservation function based on key hydrological elements and ecological elements;

[0025] Second, conduct the co-directionalization and dimensionless processing of the contribution of the matrix for the water conservation function evaluation index matrix;

[0026] Calculate the weights of the index elements of the water conservation function index based on the entropy method;

[0027] Quantitatively calculate the water conservation function index of the basin, and classify and calculate the differences in the water conservation function index under different land use types.

[0028] Furthermore, establish an evaluation matrix for the comprehensive evaluation index of water conservation function:

[0029] A ij =[A i1 , A i2 , A i3 , A i4 ,] T (3)

[0030] Where: i represents the HRU number, and j represents the index elements for evaluating water conservation function; A i1 represents the SW of the hydrological response unit with the i-th number, A i2 represents the WR of the hydrological response unit with the i-th number, A i3 represents the Cv WY of the hydrological response unit with the i-th number, and A i4 represents the GPP of the hydrological response unit with the i-th number.

[0031] Furthermore, perform contribution co-directionalization and dimensionless processing on the evaluation index matrix of water conservation function index:

[0032] According to the contribution of each index to water conservation function, perform co-directionalization processing. SW, WR, and GPP are positive indicators, and Cv WY is a negative indicator, obtaining the evaluation matrix A';

[0033] Adopt the Min-Max normalization method for normalization processing. This method is a linear transformation of the original data, and different algorithms are used for positive and negative indicators for normalization processing, so that the normalized result value falls within the interval [0,1];

[0034] The processing method for positive indicators is shown in formula (4):

[0035]

[0036] The processing method for negative indicators is shown in formula (5):

[0037]

[0038] In formulas (4) and (5): A is the index function value of each hydrological response unit, A max is the maximum value of the index data in the A min sequence, and A

[0039] Furthermore, calculate the weights of each index element of water conservation function index based on the entropy value method:

[0040] Calculate the proportion of the i-th sample value under the j-th index in this index

[0041]

[0042] Calculate the entropy value of the j-th index

[0043]

[0044] Calculate the information entropy redundancy

[0045] k j = 1 - q j (8)

[0046] Calculate the weights of each index

[0047]

[0048] Calculation of the water conservation function index:

[0049]

[0050] With the help of geographic information system, statistically analyze the WRFI of different land use types in different regions, and use Python to achieve automatic processing to generate the annual sequence of WRFI

[0051] Furthermore, a quantitative diagnosis system for water conservation function that integrates hydrological and ecological elements includes:

[0052] A data acquisition module for acquiring spatial data and non-spatial data of the target basin;

[0053] An element acquisition module for acquiring key elements of the hydrological process and ecological elements representing vegetation growth in the target basin based on hydrological models and statistical analysis methods;

[0054] An element processing module for processing and calculating the key elements of the hydrological process and ecological elements representing vegetation growth in the target basin;

[0055] A diagnosis module for constructing a comprehensive evaluation index matrix of water conservation function based on key hydrological elements and ecological elements, calculating the water conservation function index, and diagnosing the water conservation function of the basin.

[0056] Compared with the prior art, the present invention has the following technical effects:

[0057] The existing diagnostic methods for the water source function of river basins generally start from the perspective of water balance. The previous diagnostic methods only considered the variation laws and impacts of one or a few hydrological elements such as water conservation capacity, soil water, or runoff generation, without considering the function of the vegetation in the water conservation area of the river basin. Based on the interpretation of the hydrological process of the river basin, this invention selects hydrological elements (soil water) that can reflect the water conservation function of the river basin, the water conservation capacity, and Cv that can reflect the difference in water production capacity under different underlying surface conditions of the river basin WY . In addition, by combining ecological elements indicating the growth of vegetation in the river basin, the water conservation function of the river basin is comprehensively diagnosed and evaluated to solve the problem in the existing methods that only the water conservation capacity of the river basin is explored but it is difficult to reflect the function of the water conservation vegetation. Develop a comprehensive and objective quantitative diagnosis and evaluation method for the water conservation capacity of the river basin ecosystem, provide an important way and method for quantifying the change of the water conservation function of the river basin ecosystem and the improvement of the ecosystem service function, and provide theoretical support for the reasonable implementation of river basin comprehensive management Brief Description of the Drawings

[0058] Figure 1 It is the algorithm flow chart of the water conservation function index

[0059] Figure 2 It is the spatio-temporal distribution map of the water conservation function index of the river basin in the embodiment of the present invention

[0060] Figure 3 It is the difference map of the water conservation function index under different land use types with different targets in the embodiment of the present invention Detailed Embodiment

[0061] The following further explains the present invention with reference to the drawings

[0062] Please refer to Figures 1 to 3 ,

[0063] The present invention proposes a scheme for quantitatively evaluating the water conservation function of a river basin based on hydrological processes and hydrological elements, focusing on solving the problem that the evaluation and calculation of the water conservation function in the existing technical background only consider hydrological processes and ignore the important function of water conservation vegetation. The following description and icon explanations show the specific implementation schemes of the present invention, so that scientific researchers and managers in this field can practice scientifically and effectively. Only the technical scheme of the present invention is adopted in the embodiment, and the individual components and functions are optional and changeable

[0064] The present invention aims to provide a solution for estimating the water conservation function of a watershed based on ecological hydrological processes and ecological elements. On the basis of quantitatively calculating the hydrological processes of the watershed, this solution combines ecological elements indicating the growth of vegetation in the watershed to reflect the function of water conservation vegetation, and comprehensively evaluates the water conservation function of the watershed, so as to solve the problem that existing methods only discuss the water conservation volume of the watershed but are difficult to reflect the function of water conservation vegetation. To achieve the above object, the present invention is realized through the following technical solutions, specifically including:

[0065] (1) Obtain the key elements of the hydrological process of the target watershed and the ecological elements characterizing the growth of vegetation

[0066] According to the research requirements, obtain the spatial data (digital elevation model, land use data, soil property data, meteorological data, evapotranspiration data and gross primary productivity data) with a certain resolution of the target watershed and non-spatial data (hydrological data, literature data, etc.). Based on the methods of hydrological models and statistical analysis, obtain the key elements of the hydrological process of the target watershed and the ecological elements characterizing the growth of vegetation adapted to the watershed. Among them, the key elements of the watershed hydrological process include: soil water (SW), evaporation (ET), surface rapid flow (Q s ) and water yield (WY). The ecological element indicating the growth of water conservation vegetation in the water conservation area is selected as the gross primary productivity (GPP) element. Calculate the water conservation volume (WR) of the watershed according to the water balance theory; there are differences in the water production characteristics of vegetation with different land uses in terms of duration. Select the coefficient of variation of water yield to characterize this characteristic (Cv WY ), Cv WY is calculated by the change of water yield on the time scale at the scale of the watershed hydrological response unit.

[0067] (2) Quantitatively diagnose the water conservation function of the watershed by calculating the water conservation function index

[0068] First, construct a comprehensive evaluation index matrix of water conservation function based on key hydrological elements and ecological elements; second, perform matrix contribution co-directionalization and dimensionless processing on the water conservation function evaluation index matrix; third, calculate the weights of each index element of the water conservation function index based on the entropy method; fourth, quantitatively calculate the water conservation function index of the watershed, and classify and calculate the differences in the water conservation function index under different land use types.

[0069] The following is a detailed description in combination with implementation cases and operation steps in figures (tables) and texts. Specifically as follows:

[0070] The first step: Select the watershed of the study area and obtain the relevant data of the study area

[0071] The present invention takes the Weihe River Basin as the research area. The Weihe River Basin is located between 106°18′ - 110°37′ east longitude and 33°42′ - 37°20′ north latitude, with a basin area of approximately 134,800 km². For the preparation of research data, spatial data (digital elevation model, land use data, soil property data, meteorological data, evapotranspiration data, and gross primary productivity data) and non-spatial data (hydrological data, literature data, etc.) of the Weihe River Basin are collected. The relevant information of the data sources is shown in Table 1 below.

[0072] Table 1 Relevant Information of Data Sources

[0073]

[0074]

[0075] Step 2: Selection of Evaluation Index Elements in the Water Conservation Function Index (WRFI)

[0076] For hydrological elements, soil water (SW), water conservation volume (WR), and coefficient of variation of water yield (Cv WY ) are selected. Among them, SW and WR are important indicators for evaluating the water conservation function of the region. In previous methods for evaluating the water conservation function, the water conservation function status of the region is usually evaluated by calculating WR. The water yield (WY) of different land use types varies with time. The water yield of forest land is more continuous and has a smaller variation range compared to grassland and farmland. The coefficient of variation of water yield (Cv WY ) is selected to characterize the above characteristics.

[0077] For ecological elements, gross primary productivity (GPP) is selected. GPP is the total amount of organic matter produced by plant communities in an ecosystem per unit time and per unit area. In the evaluation of the water conservation function, ecological elements are important indicators reflecting the water conservation function of the region. GPP can comprehensively reflect the differences in vegetation growth status under different land use types in the water conservation area of the basin.

[0078] Step 3: Processing and Calculation of Index Elements in the Water Conservation Function Index

[0079] By collecting spatial data (digital elevation model, land use data, soil property data, and meteorological data) and non-spatial data (hydrological data, literature data, etc.) of the Weihe River Basin, and with the help of hydrological model (SWAT) simulation, in this example, the measured runoff data of Huaxian Station, Zhuangtou Station, and Linjiacun Station are selected for calibration and verification. Secondly, the MODIS remote sensing evaporation data is used to verify the ET value simulated by the model.

[0080] After the SWAT hydrological model is verified and calibrated, statistical calculations and analyses are performed on the SWAT model output file (output.hru) using geographic information system software and R software. The R program is used to extract data on SW, ET, QS, WY, and the input precipitation (P) at the hydrological response unit (HRU) scale in the Weihe River Basin. Based on the extracted hydrological elements, WR and Cv are calculated for each HRU. WY Calculation of

[0081] The calculation formula for water conservation capacity (WR):

[0082] WR i = P i - ET i - Q si (1)

[0083] In the formula: i represents the hydrological response unit number; WR is the water conservation capacity, in mm; P refers to the precipitation, in mm; ET refers to the evapotranspiration, in mm; Q S refers to the surface rapid flow, in mm.

[0084] Statistical calculation of the coefficient of variation of runoff (Cv WY ). WY is one of the important indicators characterizing the water conservation ability. The amplitude of the change of WY over time can be expressed by Cv. In the present invention, Cv WY is used as one of the indicators for evaluating the water conservation ability, and its calculation method is more complex than the above hydrological indicators. The average value (Mean WY ) and standard deviation (SD WY ) of the monthly runoff of each hydrological response unit in the study area are statistically analyzed, and then the coefficient of variation of the runoff (Cv WY ) of each hydrological response unit is calculated. Different underlying surface condition factors have different runoff generation capabilities, and the coefficients of variation are different. The larger the coefficient of variation, the greater the fluctuation of the water yield in a short time under this underlying surface factor, and the poorer the long-term water conservation ability; the smaller the coefficient of variation, the smaller the fluctuation of the water yield in a short time under this underlying surface factor, indicating that the water conservation ability of the underlying surface is relatively strong.

[0085] Cv WY_i = SD WY_i / Mean WY_i (2)

[0086] In the formula: i is the hydrological response unit (HRU) number; Cv WY_i is the coefficient of variation of the runoff of the hydrological response unit numbered i; SD WYi is the standard deviation of WY of the hydrological response unit numbered i; Mean i is the mean value of WY of the hydrological response unit numbered i.

[0087] Processing of GPP data. The GPP data obtained in this study is at the national scale (1 km × 1 km). To ensure precision adaptation, first, according to the contour area of the Weihe River Basin, using the "Buffer" function in the spatial analysis of geographic information system, a buffer zone is set with the Weihe River Basin as the boundary and extended 3 km; second, according to the scope of the Weihe River Basin and the buffer area, the GPP of the Weihe River Basin is extracted, and the GPP data of the Weihe River Basin is reclassified into data with a precision of 30 m × 30 m using the "Reclassify" function; then, using the "Zonal" function, regional statistical analysis is carried out according to HRU to obtain the GPP spatial distribution pattern of the Weihe River Basin at the HRU scale; the above process is designed through Python programming to automatically calculate and obtain the GPP data of the Weihe River Basin at the annual HRU scale.

[0088] Step 4: Calculation of the water conservation function index

[0089] The following elaborates in detail on the algorithm process of the water conservation function index:

[0090] 1. Obtain the hydrological elements output by SWAT simulation through hydrological model simulation, and process and calculate the key ecological elements representing vegetation growth.

[0091] 2. Establish an evaluation matrix for the comprehensive evaluation index of the water conservation function:

[0092] A ij =[A i1 ,A i2 ,A i3 ,A i4 ,][[ID=e26]] T (3)

[0093] Where: i represents the HRU number, and j represents the index elements for evaluating the water conservation function; A i1 represents the SW of the i-th numbered hydrological response unit, A i2 represents the WR of the i-th numbered hydrological response unit, A i3 represents the Cv WY of the i-th numbered hydrological response unit, and Ai4 represents the GPP of the i-th numbered hydrological response unit.

[0094] 3. Homogenize the contribution and dimensionless process of the evaluation index matrix of the water conservation function.

[0095] Based on the evaluation matrix established in "Step 1", the contribution of each index to the water conservation function is homogenized (SW, WR, and GPP are positive indicators, and Cv WY is a negative indicator) to obtain the evaluation matrix A'.

[0096] Since the units or magnitudes of multiple indicators are different, the evaluation indicators are dimensionless processed. The present invention uses the Min-Max normalization method for normalization processing. This method is a linear transformation of the original data, and different algorithms are used for normalization processing of positive indicators and negative indicators, so that the normalized result value falls within the range of [0, 1].

[0097] The processing method for positive indicators is shown in formula (4):

[0098]

[0099] The processing method for negative indicators is shown in formula (5):

[0100]

[0101] In formulas (4) and (5): A is the index function value of each hydrological response unit, A max is the maximum value of the index data in the sequence, A min is the minimum value of the index data in the sequence.

[0102] 4. Calculate the weight of each index element of the water conservation function index based on the entropy method.

[0103] Calculate the proportion of the i-th sample value under the j-th index in this index

[0104]

[0105] Calculate the entropy value of the j-th index

[0106]

[0107] Calculate the redundancy of information entropy

[0108] k j = 1 - q j (8)

[0109] Calculate the weight of each index

[0110]

[0111] 5. Calculation of the water conservation function index.

[0112]

[0113] The spatio-temporal distribution map of the water conservation function index in the Weihe River Basin from 2000 to 2015 is shown in Figure 2 :[[]]END]]

[0114] 6. By using the geographical information system to statistically analyze the WRFI of different land use types in different regions and using Python to automate the processing to generate the interannual sequence of WRFI, the interannual changes of the WRFI of forest land, grassland, and farmland in the Weihe River Basin are shown in Figure 3 , and the order of the WRFI size is: forest land > grassland > farmland. The present invention can more realistically reflect the status of the water conservation function of the basin for different land use types.

[0115] Previous methods for calculating the water conservation function of the basin mostly focused on exploring the variation laws and influencing factors of single or a few hydrological elements (such as surface runoff, soil water, and runoff generation), or conducting local analysis and discussion through field sampling at the station scale. Considering only from the perspective of water conservation volume or hydrological elements, the evaluation conclusions obtained will have great uncertainties, and the integrity of the basin ecosystem is ignored, lacking the content of the combined action of hydrological processes and ecosystem elements on the water conservation function. Most of the existing methods for calculating the water conservation function of the basin consider fewer factors and are at a smaller scale, and are also discontinuous in the time series.

[0116] In view of this, on the basis of explaining the basin hydrological process, the ecological elements indicating the growth of the basin vegetation are combined to reflect the vegetation conservation function, and the water conservation function of the basin is comprehensively evaluated to solve the problem that only the water conservation volume of the basin is explored in the existing methods but it is difficult to reflect the vegetation conservation function. Develop a comprehensive and objective quantitative diagnosis and evaluation method for the water conservation capacity of the basin ecosystem, provide an important way and method for quantifying the change of the water conservation function of the basin ecosystem and the improvement of the ecosystem service function, and provide theoretical support for the reasonable implementation of basin comprehensive management.

Claims

1. A quantitative diagnosis method for water conservation function integrating hydrological and ecological elements, characterized in that, It includes the following steps: Obtain the spatial data and non-spatial data of the target basin; Based on the spatial data and non-spatial data, by means of methods based on hydrological models and statistical analysis, obtain the key hydrological elements of the hydrological process in the target basin and the ecological elements representing vegetation growth suitable for the basin; The key hydrological elements of the hydrological process in the target basin include: soil water SW, evaporation ET, surface rapid flow Q s and water yield WY; Process and calculate the key hydrological elements of the obtained hydrological process and the ecological elements representing vegetation growth suitable for the basin; Based on the processed and calculated key hydrological elements and ecological elements, construct an evaluation index matrix of water conservation function, calculate the water conservation function index, and diagnose the water conservation function of the basin; Establish an evaluation index matrix of water conservation function: A ij = [A i1 , A i2 , A i3 , A i4 T (3) Among them: i represents the HRU number, and j represents the index element for evaluating the water conservation function; A i1 represents the SW of the hydrological response unit numbered i, A i2 represents the WR of the hydrological response unit numbered i, A i3 represents the Cv of the hydrological response unit numbered i WY , A i4 represents the GPP of the hydrological response unit numbered i;​ Homogenize the contributions and dimensionless process the evaluation index matrix of water conservation function: Carry out homogenization processing on the contributions of various indicators to the water conservation function. SW, WR, and GPP are positive indicators, and Cv WY is a negative indicator to obtain the evaluation index matrix A ij ; Use the Min-Max standardization method for normalization. This method is a linear transformation of the original data. Different algorithms are used for standardization of positive and negative indicators, so that the normalized result values fall within the interval [0,1]; The processing method for positive indicators is shown in formula (4): The processing method for negative indicators is shown in formula (5): In formulas (4) and (5): A is the index function value of each hydrological response unit, and A max is the maximum value of the index data, and A min is the minimum value of the index data; Calculate the weights of each index element of the water conservation function index based on the entropy method; Calculate the proportion of the i-th sample value under the j-th index in this index Calculate the entropy value of the j-th index Calculate the redundancy of information entropy k j = 1 - q j (8) Calculate the weights of each index Calculation of the water conservation function index: With the help of a geographic information system, statistically analyze the WRFI of different land use types in different regions, and use Python to achieve automated processing to generate the inter-annual sequence of WRFI.

2. The quantitative diagnosis method for water conservation function integrating hydrological and ecological elements according to claim 1, characterized in that Spatial data includes digital elevation model, land use data, soil property data, meteorological data, evapotranspiration data and gross primary productivity data; non-spatial data includes hydrological data and literature data.

3. The quantitative diagnosis method for water conservation function integrating hydrological and ecological elements according to claim 1, characterized in that The key hydrological elements of the basin hydrological process include soil water SW, evaporation ET, surface rapid flow Q s And water yield WY, indicating the ecological factors that nourish vegetation growth in water conservation areas, the gross primary productivity GPP factor is selected. GPP is the total amount of organic matter produced by plant communities in the ecosystem per unit time and per unit area.

4. The quantitative diagnosis method for water conservation function integrating hydrological and ecological elements according to claim 3, characterized in that Calculate the water conservation volume WR of the basin according to the water balance theory, and select the coefficient of variation Cv of water yield WY Characterize the water yield WY, Cv WY It is calculated by the change of water yield on the time scale at the scale of the basin hydrological response unit, specifically including: After the SWAT hydrological model is verified and calibrated, statistical calculations and analyses are performed on the SWAT model output file output.hru using geographic information system software and R software; the R program is used to extract the soil water SW, evaporation ET, surface rapid flow Q at the hydrological response unit scale HRU of the basin, and the data of the water yield WY and the input precipitation P. The WR and Cv WY of each HRU are calculated based on the extracted key hydrological elements; s 、The water yield WY and the input precipitation P data, and the WR and Cv WY of each HRU are calculated according to the extracted key hydrological elements; Calculation formula for water conservation volume WR: WR i = P i - ET i - Q si In Equation (1): i represents the hydrological response unit number; WR is the water conservation volume; P refers to the precipitation; ET refers to the evaporation; Q is the surface rapid flow s ; Coefficient of variation of water yield Cv WY Statistical calculation: The amplitude of the change in WY over time is expressed by Cv. The mean Mean WY and standard deviation SD WY of the monthly water yield of each hydrological response unit in the study area are statistically analyzed, and then the coefficient of variation Cv of the water yield of each hydrological response unit is calculated WY The water yield capacities of different underlying surface condition factors are different, and the coefficients of variation are also different. The larger the coefficient of variation, the greater the fluctuation of the water yield in a short time under this underlying surface factor, and the poorer the long-term water conservation capacity. The smaller the coefficient of variation, the smaller the fluctuation of the water yield in a short time under this underlying surface factor, indicating that the water conservation capacity of the underlying surface is relatively strong Cv WY_i = SD WY_i / Mean WY_i (2) Where: i is the hydrological response unit (HRU) number; Cv WY_i is the coefficient of variation of the water yield of the hydrological response unit numbered i; SD WYi is the standard deviation of the water year (WY) of the hydrological response unit numbered i; Mean i is the mean of the water year (WY) of the hydrological response unit numbered i.

5. The quantitative diagnosis method for water conservation function integrating hydrological and ecological elements according to claim 3, characterized in that Processing of GPP data: First, use the "Buffer" function in the spatial analysis of the geographic information system according to the basin contour area; secondly, extract the basin GPP according to the basin range and buffer area, and use the "Reclassify" function to reclassify the basin GPP data into block-precision data; then use the "Zonal" function to conduct regional statistical analysis according to HRU to obtain the spatial distribution pattern of basin GPP at the HRU scale; automate the above process through Python programming to calculate and obtain the annual GPP data of the basin at the HRU scale.

6. The quantitative diagnosis method for water conservation function integrating hydrological and ecological elements according to claim 1, characterized in that, Calculate the water conservation function index: First, construct an evaluation index matrix of water conservation function based on key hydrological elements and ecological elements; Secondly, conduct the matrix contribution homogenization and dimensionless processing for the evaluation index matrix of water conservation function; Calculate the weights of each index element of the water conservation function index based on the entropy method; Quantitatively calculate the water conservation function index of the basin, and classify and calculate the differences in the water conservation function index under different land use types.

7. A quantitative diagnosis system for water conservation function integrating hydrological and ecological elements, characterized in that, It includes: A data acquisition module for obtaining the spatial data and non-spatial data of the target basin; An element acquisition module for obtaining the key hydrological elements of the hydrological process in the target basin and the ecological elements representing vegetation growth suitable for the basin based on hydrological models and statistical analysis methods; The key hydrological elements of the hydrological process in the target basin include: soil water SW, evaporation ET, surface rapid flow Q s and water yield WY; An element processing module for processing and calculating the key hydrological elements of the hydrological process and the ecological elements representing vegetation growth in the adapted basin; A diagnosis module for constructing an evaluation index matrix of water conservation function based on the key hydrological elements and ecological elements, calculating the water conservation function index, and diagnosing the water conservation function of the basin; Establish an evaluation index matrix of water conservation function: A ij = [A i1 , A i2 , A i3 , A i4 T (3) Among them: i represents the HRU number, and j represents the index element for evaluating the water conservation function; A i1 represents the SW of the hydrological response unit with the i-th number, A i2 represents the WR of the hydrological response unit with the i-th number, A i3 represents the Cv of the hydrological response unit with the i-th number WY , A i4 represents the GPP of the hydrological response unit with the i-th number;​ Contribution co-directionalization and dimensionless processing of the evaluation index matrix of water conservation function: Homogenize the contributions of various indicators to the water conservation function. SW, WR, and GPP are positive indicators, and Cv WY is a negative indicator, obtaining the evaluation index matrix A ij ; Use the Min-Max normalization method for normalization. This method is a linear transformation of the original data. Different algorithms are used for positive and negative indicators for normalization, so that the normalized result values fall within the interval [0,1]; The processing method for positive indicators is shown in formula (4): The processing method for negative indicators is shown in formula (5): In formulas (4) and (5): A is the index function value of each hydrological response unit, and A max is the maximum value of the index data, and A min is the minimum value of the index data; Calculate the weights of the index elements of the water conservation function index based on the entropy method: Calculate the proportion of the i-th sample value under the j-th index in this index Calculate the entropy value of the j-th index Calculate the redundancy of information entropy k j = 1 - q j (8) Calculate the weights of each index Calculation of the water conservation function index: With the help of a geographic information system, statistically analyze the WRFI of different land use types by region, and use Python to implement automated processing to generate the annual sequence of WRFI.

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