Ecological flow guarantee method based on runoff prediction and supply

Abstract

The invention discloses an ecological flow guarantee method based on runoff prediction and supply. Meteorological, hydrological and other data of the Tongkeng river basin are collected, an SWAT model is constructed and verified to simulate runoff, and extended rainfall is analyzed based on an R / S method and a wavelet method. And constructing a surface water and underground water coupling model, and predicting underground water volume, water level and water quality. And ecological flow safeguard measures are formulated after water resource supply and demand balance analysis, wherein the ecological flow safeguard measures comprise optimal allocation of water resources, enhanced management, ecological water supplementation, water environment treatment, ecological restoration project development and the like. The method has the advantages that measure implementation subjects and progresses are defined, monitoring system evaluation effects are established, adjustment and optimization are performed according to results, ecological flow is guaranteed, sustainable utilization of drainage basin water resources and ecological environment protection are realized, remarkable social, economic and environmental benefits are achieved, and a scientific and effective method is provided for water resource management.

Description

Technical Field

[0001] The present invention relates to the field of ecological flow assurance methods based on runoff prediction and replenishment, and in particular to an ecological flow assurance method based on runoff prediction and replenishment. Background Art

[0002] With the impact of population growth, economic development and climate change, the contradiction between water supply and demand has become increasingly prominent, and ecological flow has been difficult to be effectively guaranteed.

[0003] In terms of water resource data collection, previous data may have suffered from insufficient time spans and illogical distribution of collection points, resulting in an incomplete and inaccurate understanding of the basin's water resources status. Traditional hydrological model construction often uses a single parameter calibration method, which makes it difficult to consider multiple runoff evaluation indicators, resulting in limited model simulation accuracy. In precipitation analysis, relying solely on simple trend analysis methods may fail to accurately grasp the complex patterns of precipitation changes, thereby affecting the reliability of runoff forecasts.

[0004] Surface water and groundwater are closely hydraulically linked, but existing research and management approaches often separate them and fail to fully consider their interactions, resulting in inaccurate simulations and predictions of river basin water resources systems. Analyses of water supply and demand balances lack comprehensive consideration of multiple development scenarios and dynamic changes in water use efficiency, making it difficult to formulate scientifically sound water resource management strategies.

[0005] Furthermore, the formulation of ecological flow assurance measures lacks systematicity and scientificity, fails to fully assess the comprehensive benefits of various measures, and has low public participation, hindering their effective implementation and continuous improvement. Therefore, a scientific and effective ecological flow assurance method that comprehensively considers multiple factors is urgently needed to achieve sustainable water resource utilization and ecological environmental protection in the Tongken River Basin. Summary of the Invention

[0006] The purpose of the present invention is to provide an ecological flow assurance method based on runoff prediction and recharge to solve the problems raised in the above background technology.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an ecological flow guarantee method based on runoff prediction and replenishment, comprising the following steps:

[0008] Step 1: Collection and analysis of water resources data in the basin

[0009] Data collection: Collect meteorological data such as precipitation, temperature, evaporation, hydrological data such as river flow, water level, groundwater level, topographic data such as digital elevation model (DEM), land use data, soil data, and water conservancy project data such as reservoir capacity and irrigation channels in Hailun City in the Tongken River Basin;

[0010] Data processing and analysis: Organize and analyze the collected data to extract characteristic information related to water resources, such as the temporal and spatial distribution of precipitation, the changing trend of river flow, and the relationship between land use types and water resource utilization;

[0011] Step 2: Build a SWAT model

[0012] Database establishment: Based on the collected data, a soil attribute database for Hailun City (soil type, soil texture, and soil moisture content) was established; DEM data was processed using ArcGIS software to obtain the basin's topographic characteristics, slope, aspect, and basin area; land use types for different regions (cultivated land, forest land, grassland, and water area) were determined based on land use data; meteorological data was collated to ensure data accuracy and completeness;

[0013] Model construction and parameter calibration: ArcSWAT software was used to divide the Tongken River basin into several sub-basins based on the above database, and hydrological response units (HRUs) were further generated. The model parameters were calibrated by adjusting the parameters closely related to runoff, including soil characteristic parameters (effective water capacity SOL_Z, biological mixing efficiency SOL_AWC, saturated hydraulic conductivity SOL_K, soil moistening albedo SOL_ALB), air temperature parameters (base snowmelt temperature SMTMP, snow temperature hysteresis TIMP, snowmelt factor SMFMX, SMFMN, snowfall temperature SFTMP), base flow characteristic parameters (base flow threshold GWQMN, delay time GW_DELAY, reevaporation coefficient GW_REVAP, alpha factor ALPHA_BF, reevaporation coefficient REVAPMN), and river channel parameters (hydraulic conductivity CH_K2, SCS curve BIOMIX, runoff curve coefficient CN2, Manning coefficient CH_N2).

[0014] Step 3: SWAT model validation and runoff simulation

[0015] Model validation: The constructed SWAT model was calibrated using measured runoff data from 2008 to 2009, and the model was validated using measured runoff data from 2010 to 2016. The model's simulation accuracy was evaluated by calculating the correlation coefficient (R²) and the Nash coefficient (ENS) evaluation indicators. If R² reached 0.895 and ENS reached 0.87, the model was considered to be able to truly reflect the actual trend of runoff changes in the study area and the model validation passed. Otherwise, the model parameters were readjusted until the model validation passed.

[0016] Runoff simulation: After the model is validated, the model is used to simulate the surface runoff process of the Tongken River Basin at different time scales of year, month, season and day. The surface runoff data, runoff volume, runoff coefficient and runoff peak value from the historical period of 2010 to 2016 are obtained, and their temporal and spatial distribution characteristics are analyzed.

[0017] Step 4: Precipitation analysis and extension based on R / S method and wavelet method

[0018] Precipitation trend analysis: The Hurst exponent of the precipitation series was calculated using the R / S method and the rescaled range method to analyze the trend characteristics of precipitation in the time series. If the Hurst exponent is less than 0.5, it indicates that the precipitation in the time series has a state of reversal, that is, there is a high probability that the future precipitation trend will be opposite to the past. The R2 value was also calculated. If the R2 is greater than 0.70, it further demonstrates the reliability of the trend analysis.

[0019] Precipitation cycle analysis: Morlet wavelet analysis was used to analyze the real part contours and wavelet variance of the precipitation series to determine the precipitation cycle. Annual precipitation may have cycles of 45 years, 1015 years, 1723 years, and 2535 years, with the 45-year oscillation being more significant throughout the observation period. Based on the precipitation cycle and multi-year average precipitation, an extended prediction of future precipitation was made for 2017-2030, generating predicted precipitation data for different time scales, seasons, and months.

[0020] Step 5: Constructing a surface water and groundwater coupling model

[0021] Conceptual model construction: Analyze the hydrogeological conditions of the study area, generalize the groundwater aquifer into pore-confined water, and determine its heterogeneous, isotropic, three-dimensional, unsteady flow characteristics. Based on the topographic and geomorphological information, generalize the boundary conditions, such as considering the northeastern boundary as a water barrier, the western and eastern boundaries as river boundaries, and the southern boundary as a water barrier or river boundary based on actual conditions.

[0022] Model establishment and parameter assignment: Visual MODFLOW Flex 6.1 software was used to establish a groundwater numerical model. Based on the actual conditions of the study area, the model parameters of permeability coefficient K, water supply μ, and water storage rate Ss were assigned to different zones. Initial values ​​were determined based on pumping tests, seepage tests, and previous research results, and were adjusted and optimized based on measured water level data.

[0023] Model coupling and data fusion: The rainfall infiltration recharge and evaporation data output by the SWAT model are used as input to the VisualMODFLOWFlex model to achieve data coupling between the two models. By establishing a correspondence between the hydrological response units (HRUs) in the SWAT model and the grid cells in the VisualMODFLOW model, the spatial correspondence problem of the minimum calculation unit is solved, ensuring accurate data transmission and fusion between the two models.

[0024] Step 6: Groundwater quantity, water level and water quality prediction

[0025] Water volume and water level forecasting: Considering the impact of population changes, economic development, and agricultural irrigation on groundwater, different forecasting scenarios were developed. The extraction rate of centralized water supply wells was adjusted based on population growth trends, and the irrigation water extraction rate was determined based on changes in paddy field area. Combined with extended precipitation and evaporation data, a coupled model was used to predict changes in groundwater volume and level in 2025 and 2030. The total inflow, storage, extraction, discharge, and evaporation of groundwater resources in the Tongken River Basin were forecasted in 2025, as well as changes in these indicators in 2030. Trends in these indicators compared to 2025 were analyzed.

[0026] Water quality prediction: Select nitrate NO3 - Nitrite NO2 - Ammonium NH4 + Chloride ion Cl - We simulated the solute transport of typical ions significantly affected by human activities. Using the measured concentrations of typical ions in groundwater in 2019 as initial concentrations, we calibrated the solute transport model using the 2019 concentration observation data to predict changes in typical ion concentrations through December 31, 2025. We analyzed the migration patterns, concentration distribution, diffusion trends, and vertical migration of typical ions in groundwater to determine the changing trends in groundwater quality and its main influencing factors, including agricultural fertilizer runoff and domestic sewage seepage.

[0027] Step 7: Water supply and demand balance analysis

[0028] Water supply analysis: Calculate the water supply capacity of Hailun City's existing surface water supply projects, water storage projects, water diversion projects, water extraction projects, and groundwater supply projects, including agricultural wells, urban water supply, and rural drinking water wells for humans and livestock. Forecast the available surface water and groundwater supply for different planning horizons, from 2020 to 2025. Analyze the changing trends in water supply capacity, and consider the impact of water resources development and utilization policy factors on water supply during water conservancy project construction.

[0029] Water demand analysis: Calculate the current water consumption in Hailun City, including water consumption for agriculture, irrigation, forestry, animal husbandry, fishery, livestock, industrial water, urban public water, residential water, ecological environment, and other sectors, and analyze the water consumption structure; use a grey model to predict the water demand of various sectors in different future planning years, such as residential water demand, agricultural irrigation water demand, industrial water demand, ecological environment water demand, and forestry, animal husbandry, fishery, and livestock water demand, taking into account the impact of population growth, economic development, industrial structure adjustment, and water-saving measures on water demand;

[0030] Supply and demand balance calculation and analysis: Compare and analyze the predicted water supply and demand, calculate the water supply and demand balance relationship for each industry in different planning levels, and assess the supply and demand gap or surplus; analyze the factors affecting the water supply and demand balance, such as climate change, population change, economic development model, and water resource management policy, to provide a basis for the rational allocation of water resources;

[0031] Step 8: Formulate ecological flow protection measures

[0032] Determine ecological flow targets: Based on the ecological and environmental characteristics and protection requirements of the Tongken River Basin, determine ecological flow targets for each river section. Consider the river's basic ecological water requirements to meet the growth needs of aquatic organisms, sediment transport requirements to maintain the balance of scour and sedimentation in the river channel, water purification requirements to improve river water quality, surface evaporation requirements to maintain the water balance of the river ecosystem, and river infiltration recharge requirements to maintain the hydraulic connection between groundwater and surface water. The minimum and optimal ecological flow values ​​are determined comprehensively.

[0033] Formulate safeguard measures based on prediction results: formulate ecological flow safeguard measures based on the runoff prediction and water resources supply and demand balance analysis results; if the predicted runoff is lower than the ecological flow target, take the following measures: first, optimize water resource allocation, adjust water quotas for various industries, and give priority to ecological water use; second, strengthen water resource management, formulate strict water resource development and utilization policies, restrict the development of high water-consuming industries, and promote water-saving technologies and measures; third, implement ecological water replenishment projects, such as using reservoir water storage and inter-basin water transfer methods to replenish rivers during dry seasons or when ecological flow is insufficient, to ensure a stable supply of ecological flow; fourth, strengthen water environment management, reduce pollutant emissions, improve river water quality, and increase the availability of water resources; fifth, carry out ecological restoration projects, such as restoring river wetland and riverbank vegetation to enhance the ecological self-purification capacity of rivers and the stability of the ecosystem;

[0034] Step 9: Implementation and Monitoring and Evaluation

[0035] Implementation of measures: Put the formulated ecological flow guarantee measures into practice, clarify the division of responsibilities and timelines for the implementation of each measure; strengthen coordination and cooperation among various departments to ensure the effective implementation of the measures; the water conservancy department will be responsible for water resource allocation and water conservancy project construction and management; the environmental protection department will be responsible for water environment monitoring and management; and the agricultural department will be responsible for promoting agricultural water-saving technologies;

[0036] Monitoring and evaluation: Establish and improve a water resources monitoring system, conduct real-time monitoring of river flow, water level, water quality, and groundwater level indicators, and monitor water use and ecological environment conditions in various industries; regularly evaluate the effectiveness of the implementation of ecological flow protection measures, and compare and analyze the changes in ecological flow before and after the implementation of measures, the balance of water resources supply and demand, and the improvement of the ecological environment based on monitoring data; adjust and optimize protection measures in a timely manner according to the evaluation results to ensure the realization of ecological flow targets and the sustainable use of water resources.

[0037] Furthermore, in step one, the collection time span of the meteorological data is no less than 10 years, and the distribution density of the data collection points should meet the requirements of the spatial variability analysis of meteorological elements in the basin to ensure that the spatiotemporal distribution characteristics of the meteorological elements of precipitation, temperature, and evaporation in the basin can be accurately reflected.

[0038] Furthermore, in step 2, during the calibration of the model parameters, a multi-objective optimization algorithm is used, and multiple evaluation indicators of runoff simulation are considered simultaneously, such as the total runoff error, peak flow error, and peak time error, to obtain the globally optimal parameter combination and improve the accuracy and reliability of the SWAT model in simulating the runoff in the Tongken River Basin.

[0039] Furthermore, in step 4, in the precipitation trend analysis, in addition to calculating the Hurst index and R2 value, the Mann-Kendall test method is also used to perform a significance test on the precipitation trend. If the test result shows that the precipitation trend is significant, its variation range and possible influencing factors are further analyzed to provide a more reliable basis for precipitation extension prediction.

[0040] Furthermore, in step five, when constructing the surface water-groundwater coupling model, in the process of assigning parameters to the groundwater aquifer, the spatial variability of geological structure and stratum lithology factors is fully considered, and the geostatistical method is used to spatially interpolate the permeability coefficient, water supply degree and water storage rate parameters to improve the accuracy of parameter assignment, thereby improving the accuracy of the coupling model's simulation of the groundwater system.

[0041] Furthermore, in step six, when predicting the groundwater quality, in addition to typical ions, total hardness, total dissolved solids, and chemical oxygen demand indicators are also included to more comprehensively evaluate the changes in groundwater quality; at the same time, in the solute transport simulation, the effects of soil adsorption and ion exchange physical and chemical processes on the migration and transformation of pollutants are considered, and the convection-diffusion equation is combined with chemical reaction terms for simulation to improve the scientificity and accuracy of water quality prediction.

[0042] Furthermore, in step seven, when analyzing the balance between water supply and demand, a scenario analysis method is adopted to set different development scenarios, analyze the changing trend of the balance between water supply and demand under each scenario, and provide a basis for formulating adaptive water resource management strategies; and, in the water demand forecast, the impact of technological progress on water use efficiency is taken into account, and a water use efficiency elasticity coefficient is introduced to dynamically adjust the water demand of each industry.

[0043] Furthermore, in step eight, when the ecological flow guarantee measures are formulated, an ecological flow guarantee benefit evaluation index system is established, including ecosystem service value enhancement indicators, socio-economic benefit indicators and environmental improvement indicators, to quantitatively evaluate the comprehensive benefits of various guarantee measures, optimize and rank the measures based on the evaluation results, and give priority to implementing guarantee measures with significant benefits.

[0044] Furthermore, in step nine, during the monitoring and evaluation process, a combination of satellite remote sensing technology, Internet of Things technology and geographic information system is used to achieve all-round, real-time dynamic monitoring of the water resources and ecological environment in the basin; big data analysis technology is used to deeply mine the monitoring data, establish a quantitative relationship model between water resources and ecological environment-related factors, and provide more accurate data support and scientific basis for evaluating the effectiveness of the implementation of guarantee measures.

[0045] Furthermore, during the entire implementation process of the method, a public participation mechanism will be established to regularly disclose water resource monitoring data, progress in the implementation of safeguard measures, and evaluation results of the effectiveness of ecological flow safeguards to the public, and widely solicit public opinions and suggestions; an expert team will be organized to scientifically analyze and demonstrate public feedback, and reasonable opinions and suggestions will be incorporated into the adjustment and optimization process of safeguard measures to improve the scientific nature, democracy, and social recognition of ecological flow safeguard work.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] By collecting meteorological, hydrological, and other data over a long period of time and from appropriately distributed collection points, we can comprehensively and accurately understand the water resources status of the basin, providing a solid foundation for subsequent analysis. Using a multi-objective optimization algorithm to calibrate SWAT model parameters, and comprehensively considering multiple runoff evaluation indicators, we can significantly improve the accuracy of runoff simulations and make water resource management decisions more scientific.

[0048] We use a variety of advanced methods such as the R / S method, Mann-Kendall test method, and wavelet method to analyze precipitation trends and cycles. Combined with the relationship between precipitation and runoff, we can achieve accurate predictions of runoff and groundwater volume, water level, and water quality, providing a reliable basis for water resources planning and allocation.

[0049] By constructing a coupled model of surface water and groundwater, fully considering the interaction between the two, and combining water supply and demand balance research with multiple scenario analyses, we can formulate a more reasonable water resource allocation plan, effectively alleviate the contradiction between supply and demand, and improve water resource utilization efficiency.

[0050] Systematically formulate ecological flow guarantee measures, establish a benefit evaluation index system, quantify the comprehensive benefits of evaluation measures, give priority to the implementation of high-efficiency measures, ensure that ecological flow is effectively guaranteed, and promote the stability and healthy development of the river basin ecosystem.

[0051] Establish a public participation mechanism, widely solicit public opinions and suggestions, and scientifically incorporate them into the process of adjusting and optimizing safeguard measures, improve the democracy and transparency of ecological flow safeguard work, enhance public understanding and support for water resources management, and enhance social recognition. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 Flowchart of the present invention. DETAILED DESCRIPTION

[0053] See also Figure 1 The present invention's ecological flow assurance method based on runoff prediction and recharge aims to solve many problems facing water resource management and ecological protection in Hailun City, Tongken River Basin. The specific implementation process is as follows:

[0054] Step 1: Collection and analysis of water resources data in the basin

[0055] (1) Data collection scope and time span

[0056] Meteorological data collection covers the entire Tonken River basin, including Hailun City, for at least 10 years to ensure that long-term climate change trends are captured. Precipitation data are collected from multiple rain gauges located across the basin's diverse topographical regions, ensuring that the data captures spatial variability in precipitation. Temperature and evaporation data are collected from evenly distributed meteorological observation stations equipped with high-precision temperature and evaporation instruments that undergo regular calibration and maintenance.

[0057] Hydrological data collection includes flow and water level data for major rivers and tributaries within the basin. Real-time monitoring is performed through hydrological monitoring stations located at key river sections. The frequency of monitoring is determined by the river's hydrological characteristics, generally multiple times daily. Groundwater level data are obtained through observation wells located in areas with different groundwater aquifer types (such as shallow phreatic aquifers and deep confined aquifers). The distribution density of observation wells must meet the requirements for analyzing the spatial variability of groundwater levels to accurately understand the dynamic changes in groundwater levels.

[0058] Topographic data uses a high-precision digital elevation model with a resolution of no less than a certain standard (e.g., 10m×10m) to clearly depict the basin's topographic undulations, slope, aspect, and other features, providing accurate basic topographic information for subsequent hydrological model construction. Land use data is obtained through interpretation of satellite remote sensing imagery and verified and revised in conjunction with field surveys to ensure the accuracy of land use classification, including the detailed distribution of various types of land, such as cultivated land, forest land, grassland, water areas, and construction land. Soil data is obtained through soil sampling and analysis. Sampling points are set up within the basin according to the distribution of different soil types, and soil samples are collected for physical and chemical property analysis, such as soil texture, soil bulk density, porosity, soil water content, soil nutrient content, and other parameters, to establish a detailed soil property database. The water conservancy project data collection covers all types of water conservancy projects built in the basin, including information such as the storage capacity, water level and storage capacity curves, and operation and scheduling rules of water storage projects; the water transmission capacity, water intake location and flow regulation capacity of water diversion projects; the water lifting scale, lift and operation efficiency of water lifting projects; as well as related information such as the construction year, operation and maintenance status of water conservancy projects. These data are obtained through engineering archives of water conservancy departments, field surveys and surveys and interviews with relevant management personnel.

[0059] (2) Data processing and analysis methods

[0060] Collected data on meteorology, hydrology, topography, land use, soil, and water conservancy projects are collated and quality-checked to remove outliers and erroneous data. Missing data are supplemented using appropriate interpolation methods to ensure data continuity and integrity.

[0061] Statistical analysis methods are used to analyze the spatiotemporal distribution characteristics of meteorological data such as precipitation, temperature, and evaporation. Indicators such as multi-year average precipitation, precipitation coefficient of variation, temperature mean and trend, and the intra-annual distribution characteristics of evaporation are calculated. Hydrological frequency analysis methods are used to analyze river flow data to determine design flows at different frequencies, providing a basis for water resource supply and demand balance analysis and ecological flow calculations. Geographic Information System technology is used to spatially analyze topography, land use, and soil data, extracting information such as the watershed's drainage network, slope classification, land use type area ratio, and soil type distribution. The relationship between land use and soil type and water resource distribution and utilization is analyzed, for example, to study the spatial matching between cultivated land distribution and irrigation water demand, and the impact of the infiltration characteristics of different soil types on runoff formation.

[0062] Step 2: Build a SWAT model

[0063] (1) Database establishment and improvement

[0064] The processed DEM data was loaded into ArcGIS software to perform watershed division operations to determine the watershed boundaries, sub-watershed ranges, and river network topology. Based on land use data and soil data, the watershed was divided into several hydrological response units (HRUs). The division of HRUs comprehensively considered factors such as land use type, soil type, and terrain slope to ensure that each HRU had relatively uniform hydrological characteristics. For the soil property database, based on the results of soil sampling and analysis, soil parameters were entered and classified according to different soil types and depth levels, and the relationship between soil parameters and soil type, terrain location, and other factors was established for accurate call in the model. Meteorological data was organized in a time series format to ensure that the temporal resolution of the data was consistent with the model simulation requirements, and was correlated and matched with the spatial location information within the watershed to provide accurate meteorological driving data for the model.

[0065] (2) Model construction and parameter calibration process

[0066] ArcSWAT software was used to construct a SWAT model based on the established watershed database. During the model construction process, various parameters of the model, such as river channel parameters, hydrological response unit parameters, meteorological parameters, etc., were reasonably set according to the actual hydrological processes and characteristics of the watershed. For parameters closely related to runoff, such as soil characteristic parameters, temperature parameters, base flow characteristic parameters and river channel parameters, a multi-objective optimization algorithm (such as the NSGAII algorithm) was used for parameter calibration. The multi-objective optimization algorithm simultaneously considers multiple evaluation indicators of runoff simulation, such as the relative error of total runoff (RE), the relative error of peak flow (PE), the peak time error (TE), the correlation coefficient (R2) and the Nash coefficient (ENS), etc., to construct a multi-objective function:

[0067]

[0068] Among them, Q sim,i is the simulated runoff, Q obs,i is the measured runoff, Q p,sim To simulate the peak flow, Q p,obs is the measured peak flow, T p,sim is the simulated peak time, T p,obs is the measured peak time, is the mean simulated runoff volume, is the mean of the measured runoff, and n is the number of data points.

[0069] Through continuous iterative calculations, we seek parameter combinations that can make multiple objective functions reach optimal or near-optimal values ​​at the same time. After multiple simulations and parameter adjustments, we finally determine the optimal parameter values ​​of the model, thereby improving the accuracy and reliability of the SWAT model in simulating the runoff of the Tongken River Basin.

[0070] Step 3: SWAT model validation and runoff simulation

[0071] (1) Model verification methods and standards

[0072] The constructed SWAT model was calibrated using measured runoff data from 2008 to 2009. During the calibration process, the simulated results were compared with the measured runoff data. Model parameters were adjusted to optimize various simulated runoff evaluation indicators or meet specific standards. The calibrated model was validated using measured runoff data from 2010 to 2016. Validation metrics also included the relative error (RE) of total runoff, the relative error (PE) of peak discharge, the error of peak time (TE), the correlation coefficient (R²), and the Nash coefficient (ENS). Generally speaking, when the R² reached 0.895 or above and the ENS reached 0.87 or above, the model was considered to accurately reflect the actual runoff trends in the study area and passed the validation. If the validation results did not meet the requirements, the model construction process, parameter settings, and data quality were reviewed, and the model was further adjusted and optimized until it passed the validation.

[0073] (2) Runoff simulation and analysis of spatiotemporal distribution characteristics

[0074] After the model was validated, it was used to simulate surface runoff processes at different time scales in the Tongken River Basin. For annual runoff simulation, the multi-year average runoff and its interannual trends were analyzed, the coefficient of variation of annual runoff was calculated, and the stability and variability of the basin's water resources over long-term time series were studied. For monthly runoff simulation, the annual distribution of runoff was analyzed, determining the proportion of runoff between the high, normal, and low water periods, and the correlation between monthly runoff and meteorological factors such as precipitation and temperature. For daily runoff simulation, the diurnal variation of runoff was analyzed, analyzing characteristics such as the morphology of flood hydrographs, peak flow, and flood duration, as well as the relationship between daily runoff and human activities within the basin, such as land use and water conservancy project operations. Using GIS technology, the runoff simulation results were spatially visualized, analyzing the spatial distribution of runoff across different sub-basins and different topographical regions within the basin. The mechanisms influencing factors such as topography, land use, and soil type on the spatial distribution of runoff were studied, providing a basis for the rational allocation of water resources and the zoning management of ecological flows.

[0075] Step 4: Precipitation analysis and extension based on R / S method and wavelet method

[0076] (1) Analysis and verification of precipitation trends

[0077] The Hurst exponent of the precipitation series was calculated using the R / S method to analyze the trend characteristics of precipitation in the time series. If the Hurst exponent is less than 0.5, it indicates that the precipitation in the time series has a state of reversal, that is, there is a high probability that the future precipitation trend will be opposite to the past.

[0078] (2) Analysis and extended forecast of precipitation cycles

[0079] The wavelet method is used to analyze the real part contours and wavelet variance of the precipitation series to determine the precipitation variation period.

[0080] Based on the precipitation cycle and multi-year average precipitation, future precipitation can be forecasted. This forecasting method can employ time series forecasting methods such as the autoregressive moving average model. Based on historical precipitation data and incorporating precipitation cycle characteristics, it can predict future precipitation data at different time scales. When constructing an ARIMA model, the precipitation time series is first tested for stationarity. If the series is nonstationary, it is converted to a stationary series using methods such as differencing. The model order is then determined based on the characteristics of the autocorrelation function (ACF) and partial autocorrelation function (PACF). Historical precipitation data is used to estimate model parameters and perform goodness-of-fit tests, and the optimal model is selected for future precipitation forecasts. By incorporating precipitation cycle characteristics into the model forecasting process, the accuracy and reliability of precipitation forecasts are improved, providing a more scientific basis for subsequent water resource management and ecological flow assurance.

[0081] Step 5: Constructing a surface water and groundwater coupling model

[0082] (1) Conceptual model construction and boundary condition determination

[0083] An in-depth analysis of the hydrogeological conditions of the study area was conducted. Through geological surveys, borehole data analysis, and pumping tests, a detailed understanding of the structure, lithologic composition, thickness variations, and hydraulic properties of the groundwater aquifer was obtained. The groundwater aquifer was generalized as porous confined water, and its heterogeneous, isotropic, three-dimensional, unsteady flow characteristics were determined. Boundary conditions were generalized based on topographical information, geomorphology, and structural information. Using high-precision topographic data and geological structural maps, and GIS-assisted analysis, the boundary conditions of the watershed boundary and groundwater flow field were determined. For example, the northeastern boundary was considered an impermeable boundary based on geological structure and groundwater flow direction. Parts of the western and eastern boundaries were considered river boundaries due to their hydraulic connection with the river. The southern boundary was determined as an impermeable or river boundary based on actual geological and hydrological surveys combined with numerical simulation tests. In determining boundary conditions, the impact of possible faults, fissures, and other geological structures within the watershed on groundwater flow was fully considered to ensure the accuracy of the boundary conditions.

[0084] (2) Model establishment, parameter assignment and coupling implementation

[0085] A groundwater numerical model was established using VisualMODFLOWFlex 6.1 software. Based on the actual conditions of the study area, parameters such as the permeability coefficient, water supply, and water storage rate were assigned to specific zones. Initial values ​​were determined based on pumping tests, seepage tests, and previous research results. After the model was initially operational, adjustments and optimizations were made based on measured water level data. During the parameter assignment process, the spatial variability of factors such as geological structure and stratum lithology was fully considered. Geostatistical methods were used to spatially interpolate parameters such as the permeability coefficient, water supply, and water storage rate to improve the accuracy of parameter assignment and, consequently, the precision of the coupled model in simulating the groundwater system. Data such as rainfall infiltration recharge and evaporation output from the SWAT model were used as inputs for the VisualMODFLOWFlex model, enabling data coupling between the two models. By establishing a correspondence between the hydrological response units (HRUs) in the SWAT model and the grids in the VisualMODFLOW model, the spatial correspondence of the smallest computational units was resolved, ensuring accurate data transfer and integration between the two models. When establishing the corresponding relationship, appropriate mapping methods (such as area weighting method) are used for data conversion and transmission based on factors such as the spatial position and area size of HRU and CELL to ensure the consistency and coordination of the two models in terms of temporal and spatial scales.

[0086] Step 6: Prediction of groundwater quantity, water level and water quality

[0087] (1) Water volume and water level forecast considerations and scheme setting

[0088] Different forecasting scenarios are developed, taking into account the impact of factors such as population change, economic development, and agricultural irrigation on groundwater. The population change factor uses a population growth forecast model to determine the population size at different future periods. Changes in residential water demand are calculated based on per capita water quotas, which in turn influence groundwater withdrawal. The economic development factor analyzes the development trends and water use intensity of different industries to predict changes in groundwater demand due to economic development. The agricultural irrigation factor determines changes in agricultural irrigation water withdrawal based on trends in irrigated farmland area, adjustments to irrigation quotas, and the water demand patterns of different crops. Based on the changing trends of these factors, various forecasting scenarios are developed, including a baseline scenario, a high-speed economic development scenario, a water conservation priority scenario, and a scenario with intensified climate change.

[0089] (2) Water quality prediction indicators and physical and chemical process considerations

[0090] Solute transport simulations were conducted using indicators such as nitrate, nitrite, ammonium, chloride, total hardness, total dissolved solids, and chemical oxygen demand. Initial concentrations of typical ions measured in groundwater in previous years were used as the initial concentrations, and the solute transport model was calibrated using these observations. The solute transport simulations considered the impact of physicochemical processes such as soil adsorption and ion exchange on pollutant migration and transformation, using a convection-diffusion equation combined with chemical reaction terms. The convection-diffusion equation describes the convection and diffusion of solutes in groundwater, while the chemical reaction term accounts for chemical reactions such as adsorption, desorption, precipitation, dissolution, and redox reactions in soil and groundwater. Parameters such as soil adsorption isotherms, ion exchange capacity, and chemical reaction rate constants were obtained through experimental measurements and literature research. These parameters were incorporated into the solute transport model to improve the scientific and accurate nature of water quality predictions. The migration patterns, concentration distribution, diffusion trends, and vertical transport of typical ions in groundwater were analyzed to determine the changing trends in groundwater quality and its primary influencing factors, including agricultural fertilizer runoff and domestic sewage seepage. By simulating the changes in groundwater quality under different scenarios, the impact of human activities on groundwater quality is evaluated, providing a scientific basis for the prevention and control of groundwater pollution.

[0091] Step 7: Water supply and demand balance analysis

[0092] (1) Water supply analysis and change trend assessment

[0093] The water supply capacity of Hailun City's existing surface water and groundwater supply projects was calculated. For water storage projects, the available water volume under different water level conditions was calculated based on the reservoir's storage capacity curve, water level fluctuations, and reservoir operation and scheduling rules. For water diversion projects, the water supply capacity was determined based on the channel's water transfer capacity, water supply conditions at the water source, and the temporal and spatial distribution of water demand. For water lifting projects, the water supply capacity was assessed by considering the pumping capacity, lift, operating efficiency, and energy supply of the pumping stations. The water supply capacity of groundwater supply projects was calculated based on the number and distribution density of pumped wells, the water yield per well, and groundwater level fluctuations. The available surface and groundwater volumes were projected for different future planning horizons, taking into account the impact of water conservancy project construction plans on water supply capacity and the impact of water resource development and utilization policies on water supply capacity. Trends in water supply capacity were analyzed, and by comparing available water volumes in different planning horizons, the extent of growth or decline in water supply capacity was assessed, providing basic data for water resource supply and demand balance analysis.

[0094] (2) Improvement of water demand analysis and prediction methods

[0095] The current water consumption in Hailun City was calculated, including that of agricultural irrigation, forestry, animal husbandry, fishery, and livestock, industrial water, urban public water, residential water, and ecological and environmental water. The water use structure was also analyzed. A gray model was used to predict water demand for each industry in different future planning years. During the gray model construction process, the raw data was preprocessed to improve data quality. The impact of factors such as population growth, economic development, industrial restructuring, and water-saving measures on water demand was considered. These factors were used as input variables in the gray model. Correlation analysis was performed to determine the closeness of the relationship between each factor and water demand, and a dynamic water demand forecasting model was established. For example, the forecast for residential water demand takes into account factors such as population growth, urbanization, improved living standards, and the prevalence of water-saving devices. The forecast for agricultural irrigation water demand incorporates factors such as changes in irrigated farmland area, adjustments in crop planting structure, advances in irrigation technology, and changing climatic conditions. The forecast for industrial water demand considers factors such as industrial output growth, optimization and upgrading of the industrial structure, and increased reuse of industrial water. The forecast for ecological and environmental water demand determines water demand standards for different ecosystem types based on watershed ecological protection goals and takes into account the impact of ecological and environmental improvement plans on water demand.

[0096] (3) Supply and demand balance calculation and analysis of influencing factors

[0097] Compare and analyze projected water supply and demand, calculate the water supply and demand balance for various industries in different planning horizons, and assess supply and demand gaps or surpluses. By establishing a water supply and demand balance calculation model, comprehensively considering the available surface and groundwater, water demand by various industries, and water allocation plans, water supply and demand balance indicators, such as the supply-demand ratio and water shortage rate, are calculated under different scenarios. Analyze factors influencing the water supply and demand balance, including climate change, demographic changes, economic development models, and water resource management policies. Scenario analysis is used to set up different development scenarios and analyze the changing trends of the water supply and demand balance under each scenario, providing a basis for formulating adaptive water resource management strategies. During the scenario analysis process, methods such as system dynamics models are used to simulate the interactions between different factors, predict the dynamic changes in the water resource system under different scenarios, and assess the stability and sustainability of the water supply and demand balance.

[0098] Step 8: Formulate ecological flow protection measures

[0099] (1) Methods and considerations for determining ecological flow targets

[0100] Ecological flow targets for each river section are determined based on the ecological and environmental characteristics and protection requirements of the Tongken River Basin. Minimum and optimal ecological flow values ​​are determined by comprehensively considering factors such as the river's basic ecological water demand, sediment transport demand, water purification demand, surface evaporation demand, and infiltration recharge demand. Field surveys and monitoring are used to understand the river's ecosystem structure and function, analyze the flow requirements of different biological groups, and determine basic ecological water demands. Sediment transport demand is calculated based on the river's sediment content, channel morphology, and hydrodynamic conditions. Water purification demand is determined by considering river water quality targets and pollutant degradation patterns. Surface evaporation demand is estimated based on the basin's climatic conditions and surface area. Infiltration recharge demand is determined by considering groundwater level dynamics and the hydraulic connection between the river and groundwater. By comprehensively analyzing these factors and employing multi-criteria decision-making methods such as the analytic hierarchy process, target ecological flow values ​​for each river section are determined, and corresponding ecological flow guarantee plans are formulated.

[0101] (2) Development and implementation of safeguard measures based on forecast results

[0102] Based on the results of runoff forecasts and water supply and demand balance analysis, measures to ensure ecological flow will be formulated. If the forecasted runoff falls below the ecological flow target, the following measures will be implemented: First, optimize water resource allocation, adjust water quotas for various industries, and prioritize ecological water use. By establishing a water resource optimization model, a reasonable water resource allocation plan will be formulated, taking into account water resource availability, water demand across various industries, and ecological protection objectives. Regarding agricultural water use, water-saving irrigation technologies will be promoted, cropping structures will be adjusted, and agricultural water use will be reduced. Regarding industrial water use, water conservation management will be strengthened, industrial water reuse rates will be increased, and the development of water-intensive industries will be restricted. Regarding urban domestic water use, publicity and education will be strengthened to raise residents' awareness of water conservation and promote water-saving appliances. Second, water resource management will be strengthened, strict water resource development and utilization policies will be formulated, the development of water-intensive industries will be restricted, and water-saving technologies and measures will be promoted. A sound water resource management system will be established, water resource assessment, water withdrawal permits, and water resource fee collection will be strengthened, and the intensity of water resource development will be strictly controlled. Enterprises and social capital will be encouraged to participate in water resource protection and water conservation projects to promote the sustainable use of water resources. Third, implement ecological water replenishment projects, such as using reservoirs and inter-basin water transfers, to replenish rivers during dry seasons or when ecological flows are insufficient, ensuring a stable supply of ecological flows. Based on the water resource status and ecological flow requirements of the basin, plan and construct ecological water replenishment projects and formulate scientific and rational water replenishment scheduling plans to ensure effective replenishment. Fourth, strengthen water environment management, reduce pollutant emissions, improve river water quality, and increase water resource availability. Strengthen industrial pollution source control, promote clean production, and strictly control industrial wastewater discharge to meet standards. Strengthen the construction and operation management of urban domestic sewage treatment facilities to increase sewage treatment rates. Strengthen the prevention and control of agricultural non-point source pollution, rationally use pesticides and fertilizers, and reduce the amount of agricultural non-point source pollutants entering rivers. Fifth, carry out ecological restoration projects, such as restoring river wetlands and riverbank vegetation, to enhance the ecological self-purification capacity of rivers and the stability of their ecosystems. Through wetland restoration projects, wetland area will be increased, improving their pollutant purification capacity and biodiversity. Planting suitable vegetation along river banks will stabilize riverbanks, reduce soil erosion, and provide habitats and food sources for aquatic life.

[0103] Step 9: Implementation and Monitoring and Evaluation

[0104] (1) Organization and coordination of implementation of measures

[0105] Implement the formulated ecological flow guarantee measures, clarifying the division of responsibilities and timelines for the implementation of each measure. Establish a dedicated leading group for water resources management and ecological protection to coordinate the implementation of all measures. The water conservancy department will be responsible for water resource allocation, water conservancy project construction and management, developing water resource scheduling plans to ensure the supply of water for ecological use. The environmental protection department will be responsible for water environment monitoring and treatment, strengthening supervision of industrial pollution sources, urban domestic sewage, and agricultural non-point source pollution, and formulating and implementing environmental protection policies. The agricultural department will be responsible for promoting agricultural water-saving technologies, adjusting planting structures, and guiding farmers in the rational use of water and fertilizers. The forestry department will be responsible for carrying out riverbank vegetation restoration and wetland protection work to increase forest coverage and ecosystem stability. Other relevant departments will actively cooperate in carrying out related work according to their respective responsibilities. Strengthen coordination and cooperation among departments, establish a regular communication and collaboration mechanism, and promptly resolve issues that arise during the implementation of measures to ensure their effective implementation.

[0106] (2) Establishment of monitoring and evaluation system and data analysis

[0107] Establish and improve a water resources monitoring system to conduct real-time monitoring of river flows, water levels, water quality, and groundwater levels, while also monitoring water use by various industries and the state of the ecological environment. Install automated monitoring equipment at key river sections and groundwater monitoring wells to enable real-time data collection and transmission. Establish a monitoring data quality management system to ensure the accuracy, reliability, and integrity of monitoring data. Regularly evaluate the effectiveness of ecological flow safeguarding measures, using monitoring data to compare and analyze changes in ecological flow before and after implementation of measures, the water supply and demand balance, and the effects of improvements on the ecological environment. Utilize statistical analysis methods and mathematical models to conduct in-depth analysis of monitoring data to assess the impact of various safeguarding measures on ecological flow, the water supply and demand balance, and the ecological environment. For example, the effectiveness of ecological water replenishment projects can be assessed by comparing changes in river flows and ecosystem conditions before and after implementation; and the effectiveness of water-saving measures can be assessed by analyzing changes in water consumption and water resource utilization efficiency by various industries before and after implementation. Based on the evaluation results, safeguarding measures can be adjusted and optimized in a timely manner to ensure the achievement of ecological flow targets and the sustainable use of water resources. If the assessment results indicate that a particular measure is ineffective or has problems, timely adjustments or improvements will be made to the measure, such as adjusting the operating parameters of the water replenishment project, optimizing water-saving technical solutions, and strengthening environmental governance measures. At the same time, based on new monitoring data and analysis results, water resource management strategies and ecological protection plans will be dynamically adjusted to adapt to changes in the basin's water resources and ecological environment.

Claims

1. An ecological flow assurance method based on runoff prediction and recharge, characterized in that: The following steps are involved: Step 1: Collection and analysis of water resources data in the basin Data collection: Collect meteorological data such as precipitation, temperature, evaporation, hydrological data such as river flow, water level, groundwater level, topographic data such as digital elevation model (DEM), land use data, soil data, and water conservancy project data such as reservoir capacity and irrigation channels in Hailun City in the Tongken River Basin; Data processing and analysis: Organize and analyze the collected data to extract characteristic information related to water resources, such as the temporal and spatial distribution of precipitation, the changing trend of river flow, and the relationship between land use types and water resource utilization; Step 2: Build a SWAT model Database establishment: Based on the collected data, a soil attribute database for Hailun City (soil type, soil texture, and soil moisture content) was established; DEM data was processed using ArcGIS software to obtain the basin's topographic characteristics, slope, aspect, and basin area; land use types for different regions (cultivated land, forest land, grassland, and water area) were determined based on land use data; meteorological data was collated to ensure data accuracy and completeness; Model construction and parameter calibration: ArcSWAT software was used to divide the Tongken River basin into several sub-basins based on the above database, and hydrological response units (HRUs) were further generated. The model parameters were calibrated by adjusting the parameters closely related to runoff, including soil characteristic parameters (effective water capacity SOL_Z, biological mixing efficiency SOL_AWC, saturated hydraulic conductivity SOL_K, soil moistening albedo SOL_ALB), air temperature parameters (base snowmelt temperature SMTMP, snow temperature hysteresis TIMP, snowmelt factor SMFMX, SMFMN, snowfall temperature SFTMP), base flow characteristic parameters (base flow threshold GWQMN, delay time GW_DELAY, reevaporation coefficient GW_REVAP, alpha factor ALPHA_BF, reevaporation coefficient REVAPMN), and river channel parameters (hydraulic conductivity CH_K2, SCS curve BIOMIX, runoff curve coefficient CN2, Manning coefficient CH_N2). Step 3: SWAT model validation and runoff simulation Model validation: The constructed SWAT model was calibrated using measured runoff data from 2008 to 2009, and the model was validated using measured runoff data from 2010 to 2016. The model's simulation accuracy was evaluated by calculating the correlation coefficient (R²) and the Nash coefficient (ENS) evaluation indicators. If R² reached 0.895 and ENS reached 0.87, the model was considered to be able to truly reflect the actual trend of runoff changes in the study area and the model validation passed. Otherwise, the model parameters were readjusted until the model validation passed. Runoff simulation: After the model is validated, the model is used to simulate the surface runoff process of the Tongken River Basin at different time scales of year, month, season and day. The surface runoff data, runoff volume, runoff coefficient and runoff peak value from the historical period of 2010 to 2016 are obtained, and their temporal and spatial distribution characteristics are analyzed. Step 4: Precipitation analysis and extension based on R / S method and wavelet method Precipitation trend analysis: The Hurst index of the precipitation series is calculated using the R / S method and the rescaled range method to analyze the trend characteristics of precipitation in the time series; If the Hurst index is less than 0.5, it indicates that precipitation has a state of opposites in the time series, that is, there is a high probability that the future precipitation trend will be opposite to the past. At the same time, the R² value is calculated. If the R² is greater than 0.70, it further demonstrates the reliability of the trend analysis. Precipitation cycle analysis: Morlet wavelet analysis was used to analyze the real part contours and wavelet variance of the precipitation series to determine the precipitation cycle. Annual precipitation may have cycles of 45 years, 1015 years, 1723 years, and 2535 years, with the 45-year oscillation being more significant throughout the observation period. Based on the precipitation cycle and multi-year average precipitation, an extended prediction of future precipitation was made for 2017-2030, generating predicted precipitation data for different time scales, seasons, and months. Step 5: Constructing a surface water and groundwater coupling model Conceptual model construction: Analyze the hydrogeological conditions of the study area, generalize the groundwater aquifer into pore-confined water, and determine its heterogeneous, isotropic, three-dimensional, unsteady flow characteristics. Based on the topographic and geomorphological information, generalize the boundary conditions, such as considering the northeastern boundary as a water barrier, the western and eastern boundaries as river boundaries, and the southern boundary as a water barrier or river boundary based on actual conditions. Model establishment and parameter assignment: Visual MODFLOW Flex 6.1 software was used to establish a groundwater numerical model. Based on the actual conditions of the study area, the model parameters of permeability coefficient K, water supply μ, and water storage rate Ss were assigned to different zones. Initial values ​​were determined based on pumping tests, seepage tests, and previous research results, and were adjusted and optimized based on measured water level data. Model coupling and data fusion: The rainfall infiltration recharge and evaporation data output by the SWAT model are used as input to the VisualMODFLOWFlex model to achieve data coupling between the two models. By establishing a correspondence between the hydrological response units (HRUs) in the SWAT model and the grid cells in the VisualMODFLOW model, the spatial correspondence problem of the minimum calculation unit is solved, ensuring accurate data transmission and fusion between the two models. Step 6: Groundwater quantity, water level and water quality prediction Water volume and water level forecasting: Considering the impact of population changes, economic development, and agricultural irrigation on groundwater, different forecasting scenarios were developed. The extraction rate of centralized water supply wells was adjusted based on population growth trends, and the irrigation water extraction rate was determined based on changes in paddy field area. Combined with extended precipitation and evaporation data, a coupled model was used to predict changes in groundwater volume and level in 2025 and 2030. The total inflow, storage, extraction, discharge, and evaporation of groundwater resources in the Tongken River Basin were forecasted in 2025, as well as changes in these indicators in 2030. Trends in these indicators compared to 2025 were analyzed. Water quality prediction: Typical ions that are significantly affected by human activities, including nitrate (NO3), nitrite (NO2), ammonium (NH4), and chloride (Cl), were selected for solute transport simulation. The measured concentrations of typical ions in groundwater in 2019 were used as initial concentrations. The solute transport model was calibrated using the 2019 concentration observation data to predict changes in typical ion concentrations through December 31, 2025. The migration patterns, concentration distribution, diffusion trends, and vertical migration of typical ions in groundwater were analyzed to determine the changing trends in groundwater quality and the main influencing factors, including agricultural fertilizer runoff and domestic sewage seepage. Step 7: Water supply and demand balance analysis Water supply analysis: Analyze the water supply capacity of Hailun City's existing surface water supply projects, water storage projects, water diversion projects, water extraction projects, and groundwater supply projects, as well as agricultural wells, urban water supply, and rural drinking water wells for humans and livestock. Forecast the available surface water and groundwater supply in different planning years, from 2020 to 2025. Analyze the changing trend of water supply capacity and consider the impact of water resources development and utilization policy factors on water supply during water conservancy project construction; Water demand analysis: Calculate the current water consumption in Hailun City, including water consumption for agriculture, irrigation, forestry, animal husbandry, fishery, livestock, industrial water, urban public water, residential water, ecological environment, and other sectors, and analyze the water consumption structure; use a grey model to predict the water demand of various sectors in different future planning years, such as residential water demand, agricultural irrigation water demand, industrial water demand, ecological environment water demand, and forestry, animal husbandry, fishery, and livestock water demand, taking into account the impact of population growth, economic development, industrial structure adjustment, and water-saving measures on water demand; Supply and demand balance calculation and analysis: Compare and analyze the predicted water supply and demand, calculate the water supply and demand balance relationship for each industry in different planning levels, and assess the supply and demand gap or surplus; analyze the factors affecting the water supply and demand balance, such as climate change, population change, economic development model, and water resource management policy, to provide a basis for the rational allocation of water resources; Step 8: Formulate ecological flow protection measures Determine ecological flow targets: Based on the ecological and environmental characteristics and protection requirements of the Tongken River Basin, determine ecological flow targets for each river section. Consider the river's basic ecological water requirements to meet the growth needs of aquatic organisms, sediment transport requirements to maintain the balance of scour and sedimentation in the river channel, water purification requirements to improve river water quality, surface evaporation requirements to maintain the water balance of the river ecosystem, and river infiltration recharge requirements to maintain the hydraulic connection between groundwater and surface water. The minimum and optimal ecological flow values ​​are determined comprehensively. Formulate safeguard measures based on prediction results: formulate ecological flow safeguard measures based on the runoff prediction and water resources supply and demand balance analysis results; if the predicted runoff is lower than the ecological flow target, take the following measures: first, optimize water resource allocation, adjust water quotas for various industries, and give priority to ecological water use; second, strengthen water resource management, formulate strict water resource development and utilization policies, restrict the development of high water-consuming industries, and promote water-saving technologies and measures; third, implement ecological water replenishment projects, such as using reservoir water storage and inter-basin water transfer methods to replenish rivers during dry seasons or when ecological flow is insufficient, to ensure a stable supply of ecological flow; fourth, strengthen water environment management, reduce pollutant emissions, improve river water quality, and increase the availability of water resources; fifth, carry out ecological restoration projects, such as restoring river wetland and riverbank vegetation to enhance the ecological self-purification capacity of rivers and the stability of the ecosystem; Step 9: Implementation and Monitoring and Evaluation Implementation of measures: Put the formulated ecological flow guarantee measures into practice, clarify the division of responsibilities and timelines for the implementation of each measure; strengthen coordination and cooperation among various departments to ensure the effective implementation of the measures; the water conservancy department will be responsible for water resource allocation and water conservancy project construction and management; the environmental protection department will be responsible for water environment monitoring and management; and the agricultural department will be responsible for promoting agricultural water-saving technologies; Monitoring and evaluation: Establish and improve a water resources monitoring system, conduct real-time monitoring of river flow, water level, water quality, and groundwater level indicators, and monitor water use and ecological environment conditions in various industries; regularly evaluate the effectiveness of the implementation of ecological flow protection measures, and compare and analyze the changes in ecological flow before and after the implementation of measures, the balance of water resources supply and demand, and the improvement of the ecological environment based on monitoring data; adjust and optimize protection measures in a timely manner according to the evaluation results to ensure the realization of ecological flow targets and the sustainable use of water resources.

2. The ecological flow guarantee method based on runoff prediction and recharge according to claim 1 is characterized in that: In step one, the collection time span of the meteorological data is no less than 10 years, and the distribution density of the data collection points should meet the requirements of the spatial variability analysis of meteorological elements in the basin to ensure that the spatiotemporal distribution characteristics of the meteorological elements of precipitation, temperature, and evaporation in the basin can be accurately reflected.

3. The ecological flow guarantee method based on runoff prediction and recharge according to claim 1 is characterized in that: In step 2, during the model parameter calibration process, a multi-objective optimization algorithm is used, and multiple evaluation indicators of runoff simulation are considered simultaneously, such as total runoff error, peak flow error, and peak time error, to obtain the globally optimal parameter combination and improve the accuracy and reliability of the SWAT model in simulating the runoff in the Tongken River Basin.

4. The ecological flow guarantee method based on runoff prediction and recharge according to claim 1 is characterized in that: In step 4, in the precipitation trend analysis, in addition to calculating the Hurst index and R² value, the Mann-Kendall test method is also used to perform a significance test on the precipitation trend. If the test result shows that the precipitation trend is significant, its variation range and possible influencing factors are further analyzed to provide a more reliable basis for precipitation extension prediction.

5. The ecological flow guarantee method based on runoff prediction and recharge according to claim 1 is characterized in that: In step five, when constructing the surface water-groundwater coupling model, the spatial variability of geological structure and stratum lithology factors is fully considered in the process of assigning parameters to the groundwater aquifer, and the geostatistical method is used to spatially interpolate the permeability coefficient, water supply degree and water storage rate parameters to improve the accuracy of parameter assignment, thereby improving the accuracy of the coupling model's simulation of the groundwater system.

6. The ecological flow guarantee method based on runoff prediction and recharge according to claim 1 is characterized in that: In step six, when predicting the groundwater quality, in addition to typical ions, total hardness, total dissolved solids, and chemical oxygen demand indicators are also included to more comprehensively evaluate the changes in groundwater quality; at the same time, in the solute transport simulation, the effects of soil adsorption and ion exchange physical and chemical processes on the migration and transformation of pollutants are considered, and the convection-diffusion equation is combined with chemical reaction terms for simulation to improve the scientificity and accuracy of water quality prediction.

7. The ecological flow guarantee method based on runoff prediction and recharge according to claim 1 is characterized in that: In step seven, when analyzing the water supply and demand balance, a scenario analysis method is used to set different development scenarios, analyze the changing trend of the water supply and demand balance under each scenario, and provide a basis for formulating adaptive water resources management strategies; and in the water demand forecast, the impact of technological progress on water use efficiency is taken into account, and the water use efficiency elasticity coefficient is introduced to dynamically adjust the water demand of each industry.

8. The ecological flow guarantee method based on runoff prediction and recharge according to claim 1 is characterized in that: In step eight, when the ecological flow guarantee measures are formulated, an ecological flow guarantee benefit evaluation index system is established, including ecosystem service value enhancement indicators, socio-economic benefit indicators and environmental improvement indicators, and a quantitative evaluation is conducted on the comprehensive benefits of various guarantee measures. The measures are optimized and ranked according to the evaluation results, and guarantee measures with significant benefits are implemented first.

9. The ecological flow guarantee method based on runoff prediction and recharge according to claim 1 is characterized in that: In step nine, during the monitoring and evaluation process, a combination of satellite remote sensing technology, Internet of Things technology and geographic information system is used to achieve all-round, real-time dynamic monitoring of the water resources and ecological environment in the basin; big data analysis technology is used to deeply mine the monitoring data and establish a quantitative relationship model between water resources and ecological environment-related factors, providing more accurate data support and scientific basis for evaluating the effectiveness of the implementation of guarantee measures.

10. The ecological flow guarantee method based on runoff prediction and recharge according to claim 1, characterized in that: Throughout the implementation of the approach, a public participation mechanism will be established to regularly disclose water resource monitoring data, progress in implementing safeguard measures, and evaluation results of ecological flow safeguard effectiveness to the public, and to solicit public opinions and suggestions. Organize an expert team to conduct scientific analysis and demonstration of public feedback, incorporate reasonable opinions and suggestions into the adjustment and optimization of protection measures, and improve the scientificity, democracy and social recognition of ecological flow protection work.

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