A method for configuring soil conditioning measures for drought and flood mitigation

Abstract

This invention provides a method for configuring soil conditioning measures for drought and flood mitigation, belonging to the field of soil and water conservation technology. This method collects physiographic data and hydrological evolution data for the study area to determine the impact of soil conditioning measures on rainfall-runoff production in different soil units, establishes empirical equations to quantify the regulating capacity of various soil conditioning measures, constructs a drought and flood evaluation index system and verifies its rationality, divides the watershed into suitable areas for the implementation of soil conditioning measures, then quantifies the regulating capacity of individual soil conditioning measures in each sub-basin based on the suitable areas. Using a single-objective spatial optimization method, with the goal of maximizing drought and flood mitigation, the method ultimately determines the spatial layout of soil conditioning measures in the study area. This method achieves an optimal configuration of various soil conditioning measures for the purpose of drought and flood mitigation.

Description

Technical Field

[0001] The present invention belongs to the field of soil and water conservation, and in particular relates to a soil conditioning measure configuration method for drought and flood mitigation. Background Art

[0002] Current climate warming is exacerbating the global water cycle, leading to frequent extreme hydrological events such as droughts, floods, and alternating droughts and floods, and severe reductions in grain production. While gray infrastructure, typically concrete structures like reservoirs and dams, has achieved some success in addressing the risks of droughts and floods in river basins, these structures have not fully leveraged their natural regulation capabilities and have had a significant negative impact on the basin's ecological environment.

[0003] However, soil conditioning measures, such as deep tillage / cultivation, biochar addition, straw return, ridges, and terraces, vary significantly in their impact on the water cycle and their effectiveness in mitigating droughts and floods in complex environments due to differences in their deployment and applicable conditions. To maximize the comprehensive benefits of various soil conditioning measures within a watershed, scholars have sought to optimize their spatial layout using methods such as decision support systems. However, these approaches fail to adequately consider the selection of optimization objectives and the physical mechanisms of soil conditioning measures within the water cycle, resulting in insufficient water storage efficiency. Therefore, how to systematically deploy soil conditioning measures based on the natural endowments of a watershed to maximize soil storage capacity and resilience to drought and flood risks has become an urgent issue. Summary of the Invention

[0004] In response to the above-mentioned deficiencies in the prior art, the present invention provides a method for configuring soil conditioning measures for drought and flood mitigation. The present invention realizes the optimal construction pattern of various soil conditioning measures for the goal of drought and flood mitigation.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] This solution provides a method for configuring soil conditioning measures for drought and flood mitigation, including the following steps:

[0007] S1. Collect and identify the physical geographical information and hydrological evolution data of the study area, and divide the study area into n sub-basins;

[0008] S2. Screen soil conditioning measures to determine their impact on rainfall runoff and soil water holding capacity in different sub-watersheds, and develop empirical equations to quantify the impact of various soil conditioning measures on soil water holding capacity;

[0009] S3. Analyze the historical water supply and demand balance relationship in the study area based on the searched physical geographic information;

[0010] S4. Based on the collected data on the evolution of hydrological conditions and the relationship between water supply and demand, a drought and flood evaluation index system is constructed to classify and verify historical drought and flood events in the study area;

[0011] S5. Based on the division and verification results, determine the construction standards for various soil conditioning measures, select environmental factor constraints, determine the soil conditioning measures in the sub-basins, and, based on the soil conditioning measures in the sub-basins, determine the appropriate construction areas for soil conditioning measures in the basin;

[0012] S6. Based on the empirical equation and the suitable construction area, the regulation capacity of different soil regulation measures implemented in the suitable construction area is obtained;

[0013] S7. Utilize a single-objective spatial optimization method, with maximum drought and flood mitigation as the constraint objective, and based on the regulatory capacity of different soil regulation measures implemented in suitable construction areas, obtain a spatial layout plan for the construction of soil regulation measures in the watershed.

[0014] The beneficial effects of the present invention are as follows: by constructing soil conditioning measures and searching for suitable areas in a watershed, the present invention determines the capacity of different soil conditioning measures implemented in suitable construction areas. This then sets an optimization goal based on drought and flood mitigation, determines the capacity and spatial layout of soil conditioning measures for each control unit in the watershed, and completes a method for configuring soil conditioning measures for drought and flood mitigation. This method can select the optimal solution for the optimization goal from a vast number of available sub-solutions, exploring ways to reduce the occurrence of drought and flood disasters, improve risk resilience, and promote soil and water conservation and sustainable agricultural development.

[0015] Furthermore, step S1 includes the following steps:

[0016] S101. Collect and identify different natural geographical information and hydrological regime evolution data for research;

[0017] S102. Use the ARCGIS platform Hydrology hydrological and hydraulic model to fill depressions, generate flow directions, calculate runoff accumulation, calculate slopes, and generate and encode river networks within the basin to generate sub-basins, thereby dividing the study area into n sub-basins.

[0018] The beneficial effects of the above further scheme are: by searching for relevant information, data support and theoretical basis are provided for the subsequent configuration method of soil conditioning measures, and the data are integrated and the watershed is divided into sub-basins according to different characteristics, which is conducive to the subsequent corresponding soil measure configuration analysis for each sub-basin.

[0019] Furthermore, step S2 includes the following steps:

[0020] S201. Screen soil conditioning measures;

[0021] S202, using the GetData tool to obtain experimental data between the soil conditioning measure control group and the blank group;

[0022] S203. Statistically analyze the experimental data and use OpenMEE software as a tool to quantify the effects of soil conditioning measures on key elements of the water cycle under different environmental factors and calculate the average effect value;

[0023] S204. Classify and integrate the impact mechanisms of soil conditioning measures on water cycle elements and processes based on the average effect values;

[0024] S205. Based on the classification and integration results, as well as the functional classification and construction model generalization of soil conditioning measures, establish empirical equations to quantify the impact of various soil conditioning measures on soil conditioning capacity.

[0025] Furthermore, the expression of the average effect value is as follows:

[0026]

[0027] Where LRR represents the mean effect size, X t and are the mean values ​​of water cycle process indices in the single-sample soil conditioning measures treatment group and the blank control group, respectively, and ln(·) represents the logarithmic function.

[0028] The beneficial effects of the above further scheme are: through literature collection, the impact value of each soil regulation measure on the rainfall-runoff of each sub-basin is determined, and empirical equations for the soil regulation measures on key water cycle processes are established. Combined with the hydrological and meteorological characteristics of each sub-basin, the soil regulation capacity of the soil regulation measures in each sub-basin can be calculated.

[0029] Furthermore, the empirical equations for quantifying the effects of various soil conditioning measures on soil conditioning capacity include:

[0030] The first type of soil conditioning measures includes deep tillage, straw return and biochar addition:

[0031]

[0032] Among them, V i represents the regulating capacity of deep tillage, straw return and biochar addition on water resources in the evaluation unit, A represents the area of ​​the evaluation unit, represents the average effect value of the first type of soil conditioning measures on rainfall-runoff, It represents the mean field water holding capacity of the effective depth of soil. represents the mean value of soil effective depth wilting water content, h0 represents the effective depth of soil unit, It represents the average runoff coefficient of different rainfall events in the evaluation unit before the construction of soil conditioning measures;

[0033] The second type of soil regulation measures to improve water resource regulation capacity is to lay out ridges and furrows on sloping farmland:

[0034]

[0035] Among them, V4 represents the regulatory capacity of ridge and ditch construction on sloping farmland within the evaluation unit, H, D, d and β represent the layout parameters of farmland ridge and ditch, and α represents the original ground slope;

[0036] The third type of soil regulation measures is to improve water resource regulation capacity through terrace construction:

[0037]

[0038] Among them, V5 represents the regulatory capacity of terrace construction within the evaluation unit, and h, b, B and θ are terrace layout parameters.

[0039] The beneficial effect of the above further solution is: by constructing the mechanism equation, it provides support for the calculation of the storage capacity of each soil regulation measure in the subsequent step S6.

[0040] Furthermore, step S3 includes the following steps:

[0041] S301. Based on the searched natural geographic information, a WEP distributed hydrological model of the watershed is constructed;

[0042] S302. Based on the WEP distributed hydrological model of the basin, quantify the historical water supply of the basin and the ecological water use of crops, woodlands and grasslands, and analyze the water supply and demand balance relationship.

[0043] The beneficial effect of the above further scheme is: through the collected historical data, a basin WEP distributed hydrological model based on the study area is established to quantify and output the water supply and demand data in the study area, providing data support for the construction of subsequent drought and flood evaluation indicators.

[0044] Furthermore, step S4 includes the following steps:

[0045] S401. Constructing a drought and flood evaluation index system based on the collected hydrological situation evolution data and the water supply and demand balance relationship, and calculating a water resource profit and loss index based on the drought and flood evaluation index system;

[0046] S402, performing a secondary correction on the weight factor in the water resource profit and loss index;

[0047] S403. Calculate a drought and flood index based on the watershed data and the modified weight factor, perform a secondary correction on the drought and flood index, and classify the modified drought and flood index into different levels.

[0048] S404. Verify the division results based on the actual historical drought and flood disasters in the study area.

[0049] The beneficial effect of the above further scheme is: by outputting water supply and demand data and hydrological situation evolution data, a drought and flood risk assessment index system is established and graded, and then rationality is verified. The above process is conducive to the optimal configuration of subsequent soil adjustment measures and provides a basis for calculating the evaluation results of drought and flood events under different soil adjustment measures.

[0050] Furthermore, the expression of the water resource profit and loss index is as follows:

[0051] Z=K*×ΔW

[0052] ΔW=WS-WD

[0053]

[0054] Among them, Z represents the water resource profit and loss index of each month, ΔW represents the water resource profit and loss, WS represents the water supply of the evaluation unit, and WD represents the total water demand of the evaluation unit. and They represent the multi-year average water supply and demand of the evaluation unit in the corresponding month, and K* represents the uncorrected water resource profit and loss correction coefficient;

[0055] The expression for performing secondary correction on the weight factor in the water resource profit and loss index is as follows:

[0056]

[0057]

[0058]

[0059] Among them, K'* represents the modified weight factor, represents the water resource surplus or deficit of each evaluation unit, K' represents the first approximate value of K'*, represents the average weight of extreme drought, It represents the water resource surplus and deficit of each evaluation unit in the driest 12 months;

[0060] The expression of the drought and flood index is as follows:

[0061]

[0062]

[0063] Among them, FDI i represents the drought and flood index, Z1 represents the water resource profit and loss index of the first month, FDI i-1 represents the drought and flood index in month i-1;

[0064] The expression for performing secondary correction on the drought and flood index is as follows:

[0065]

[0066] Among them, FDI i ' represents the revised drought and flood index for month i, R i represents the outlet flow of the sub-basin in month i, It represents the multi-year mean of runoff in month i during the statistical period.

[0067] The beneficial effects of the above further plan are: establishing a drought and flood evaluation index system based on the water supply and demand balance and hydrological regime evolution under different historical climate scenarios in the basin, and providing support for the construction of suitable areas for subsequent soil regulation measures in the basin.

[0068] Furthermore, step S7 includes the following steps:

[0069] S701. Compare the regulation capacity of each soil regulation measure constructed in each evaluation unit. With the maximum drought and flood mitigation as the constraint objective, locate the soil regulation measures deployed in the evaluation unit to determine the spatial distribution of each soil regulation measure in the sub-watershed.

[0070] S702. Integrate the spatial distribution of various soil conditioning measures in the sub-basin to obtain a spatial layout plan for the construction of soil conditioning measures in the basin.

[0071] The beneficial effect of the above further plan is: based on the regulatory capacity of implementing different soil regulation measures in the suitable construction area, by comparing the regulatory capacity of different soil regulation measures in each sub-basin, under the goal of maximizing drought and flood alleviation, the layout of soil regulation measures in each sub-basin is optimized, and the spatial layout plan of soil regulation measures in the basin is completed. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 Flow chart of the method of the present invention. DETAILED DESCRIPTION

[0073] The specific embodiments of the present invention are described below to facilitate understanding of the present invention by those skilled in the art. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the appended claims, these changes are obvious, and all inventions and creations utilizing the concepts of the present invention are protected.

[0074] Example

[0075] This invention uses spatial optimization of soil conditioning measures in a watershed, takes maximum drought and flood mitigation as the constraint goal, and uses a configuration model to determine the proposed regulation capacity and spatial layout of soil conditioning measures in each control unit (sub-watershed) of the watershed under different climatic conditions based on historical measured data, thus completing a soil conditioning measure configuration method for drought and flood mitigation. Figure 1 As shown, the present invention provides a soil conditioning measure configuration method for drought and flood mitigation, and its implementation method is as follows:

[0076] S1. Collect and identify the physical geographic information and hydrological evolution data of the study area, and divide the study area into n sub-basins. The implementation method is as follows:

[0077] S101. Collect and identify different natural geographical information and hydrological regime evolution data for research;

[0078] S102. Use the ARCGIS platform Hydrology hydrological and hydraulic model to fill depressions, generate flow directions, calculate runoff accumulation, calculate slopes, and generate and encode river networks within the basin to generate sub-basins, thereby dividing the study area into n sub-basins.

[0079] In this embodiment, the natural geographical information of the study area, such as meteorology and hydrology, land use, soil type, slope and multi-year rainfall, is collected and identified, and the area is divided into n sub-basins according to the DEM, flow direction, river network and other information.

[0080] In this embodiment, spatial geographic information of the study area (such as river systems, meteorology and hydrology, soil and vegetation, and land use) is collected through field surveys, literature collection, watershed observations, or government bulletins. Taking the Si River as the study area, relevant meteorology and hydrology, soil and vegetation, and historical drought and flood events are collected through watershed organizations, water conservancy bureaus, and government departments. At the same time, literature on soil regulation measures is searched for in Chinese and English databases such as WOS, Springer, Elesvier, China National Knowledge Infrastructure, VIP, and Wanfang, and the literature is downloaded and sorted.

[0081] In this embodiment, the ARCGIS platform Hydrology hydrological and hydraulic model is used to fill depressions, generate flow directions, calculate the cumulative number of confluences, calculate slopes, and generate and encode river networks within the basin, thereby generating sub-basins. The study basin is divided into n sub-basins, that is, the spatial geographic information data obtained in step S101 is divided into sub-basins according to the DEM area through the ARCGIS platform.

[0082] S2. Screen soil conditioning measures to determine their impact on rainfall runoff and soil water holding capacity in different sub-basins, and develop empirical equations to quantify the impact of various soil conditioning measures on soil water holding capacity. The implementation method is as follows:

[0083] S201. Screen soil conditioning measures;

[0084] S202, using the GetData tool to obtain experimental data between the soil conditioning measure control group and the blank group;

[0085] S203. Statistically analyze the experimental data and use OpenMEE software as a tool to quantify the effects of soil conditioning measures on key elements of the water cycle under different environmental factors and calculate the average effect value;

[0086] S204. Classify and integrate the impact mechanisms of soil conditioning measures on water cycle elements and processes based on the average effect values;

[0087] S205. Based on the classification and integration results, as well as the functional classification and construction model generalization of soil conditioning measures, establish empirical equations to quantify the impact of various soil conditioning measures on soil conditioning capacity.

[0088] In this example, research literature on soil conditioning measures and soil unit infiltration and runoff generation within the study area was collected from databases such as CNKI and WOS to screen soil conditioning measures. Drought or flood disasters were searched as keywords in various Chinese and English databases. Six representative soil conditioning measures were selected, and all relevant literature on their effects on rainfall runoff generation and soil water-holding capacity was downloaded.

[0089] In this example, the GetData tool was used to obtain experimental data on the effects of soil conditioning measures on rainfall runoff and soil water-holding capacity under the influence of different environmental factors. Downloaded research literature was screened using criteria, and those directly relevant to the research topic were selected and categorized. Images within these documents were scanned using GetData software and the experimental data obtained from them was used to provide data support for subsequent research.

[0090] In this example, the obtained experimental data were statistically analyzed, and the OpenMEE software was used as a tool to quantify the effects of different soil conditioning measures on rainfall runoff and soil water holding capacity, and the average effect value (LRR) was calculated. The calculation formula of LRR is as follows:

[0091]

[0092] Where LRR represents the mean effect size, X t and are the mean values ​​of water cycle process indices in the single-sample soil conditioning measures treatment group and the blank control group, respectively, and ln(·) represents the logarithmic function.

[0093] In this example, soil conditioning measures are divided into two categories based on their impact mechanisms: 1. By modifying soil physical and chemical properties, the water resource regulation capacity of the evaluated unit soil can be enhanced within an appropriate soil moisture threshold, such as deep tillage, straw return, and biochar addition. 2. By modifying the micro-topography of the slope, increasing surface roughness and increasing the storage capacity of the slope unit, such as ridge cultivation and terraced fields. Typical soil conditioning measures are categorized according to the aforementioned impact mechanisms.

[0094] In this embodiment, after reviewing the literature, the formula for the first type of soil conditioning measures, including deep tillage, straw return, and biochar addition, is:

[0095]

[0096] Among them, V i It represents the regulating capacity of deep tillage, straw return and biochar addition on water resources in the evaluation unit (unit: m 3 ), i=1,2,3, A represents the evaluation unit area (unit is m 2 ), represents the average effect value of the first type of soil conditioning measures on rainfall-runoff, Indicates the mean field water holding capacity of soil effective depth (unit: cm 3 / cm 3 ), Indicates the average wilting water content of the effective depth of soil (unit: cm 3 / cm 3 ), h0 represents the effective depth of the soil unit (in cm), It represents the average runoff coefficient of different rainfall events in the evaluation unit before the construction of soil conditioning measures;

[0097] The second type of soil regulation measures to improve water resource regulation capacity is to lay out ridges and furrows on sloping farmland:

[0098]

[0099] Among them, V4 represents the regulation capacity of ridge and ditch construction in the evaluation unit (unit: m 3 ), H, D, d, and β all represent farmland ridge and furrow layout parameters, and the basin average value was obtained through field investigation. Among them, H represents ridge height (unit: cm), D represents furrow bottom width (unit: cm), d represents ridge width (unit: cm), β represents the angle between ridge edge and slope surface (unit: °), and α represents the original ground slope;

[0100] The third type of soil regulation measures is to improve water resource regulation capacity through terrace construction:

[0101]

[0102] Among them, V5 represents the terrace construction regulation capacity within the evaluation unit (unit: m 3 ), h, b, B, and θ are terrace layout parameters, and the basin average values ​​were taken through field surveys. Among them, H represents the ridge height (in cm), D represents the ditch bottom width (in cm), d represents the ridge width (in cm), β represents the angle between the ridge edge and the slope (in degrees), and α is the original ground slope.

[0103] S3. Analyze the historical water supply and demand balance relationship in the study area based on the searched natural geographical information. The implementation method is as follows:

[0104] S301. Based on the searched natural geographic information, a WEP distributed hydrological model of the watershed is constructed;

[0105] S302. Based on the WEP distributed hydrological model of the basin, quantify the historical water supply of the basin and the ecological water use of crops, woodlands and grasslands, and analyze the water supply and demand balance relationship.

[0106] In this embodiment, a WEP distributed hydrological model is constructed based on the collected basic terrain data, land use data, soil data, and meteorological and hydrological data. The natural annual and monthly runoff processes of the Shuyuan Station in the Sihe River Basin from 1968 to 2015 are restored as the calibration target. According to the principle of matching the annual runoff first and then the monthly runoff process, and matching the runoff volume first and then the runoff flood and dry values, the model parameters are adjusted based on the physical meaning of the model parameters and their impact on the rainfall-runoff process by automatic optimization combined with manual trial and error. The correlation coefficient (R 2 The simulation effect is evaluated by three indicators: ), Nash coefficient (NSE) and relative error (RE). The correlation coefficient between the simulated and measured runoff is above 0.8, the Nash efficiency coefficient is above 0.6, and the relative error is controlled within 15%. The specific calculation formula is as follows:

[0107]

[0108]

[0109]

[0110] Among them, Q obs (t) and Q sim (t) represents the measured and simulated values ​​of monthly runoff (unit: m 3 / s), and are the average values ​​of measured and simulated runoff respectively. 2 The closer NSE is to 1 and RE is to 0, the better the simulation is.

[0111] In this embodiment, based on the output of the water cycle element process values ​​of the established Sihe River Basin WEP model, the average water supply in different months of each sub-basin from 1968 to 2015 was calculated using the following formula:

[0112] The calculation formula for the water supply (effective precipitation) of the evaluation unit is:

[0113] WS=P+(D 上 +D 漏 )-(R o +R s )-(E c +E e +E w )

[0114] Among them, WS represents the water supply of the evaluation unit (unit is mm), P represents the total precipitation of the evaluation unit (unit is mm), D 上 Indicates the amount of water rising (unit: mm), D 漏 Indicates deep leakage (unit: mm), R o is the surface flow (unit: mm), R s is the flow rate in the soil (unit: mm), E c is the evaporation of impermeable water (unit: mm), E e is the ineffective evaporation between particles (unit: mm), E w is the evaporation amount of water area (unit: mm).

[0115] The water demand calculation formula for the evaluation unit is:

[0116] WD=WD g +WD l +WD c

[0117] Among them, WD represents the total water demand of the evaluation unit (unit is mm), WD g WD l and WD cRepresent the water requirements of cultivated land, forest land and grassland respectively (unit: mm).

[0118] The formula for calculating crop water requirement is:

[0119] ET g =K g ×ET0

[0120] Among them, ET g represents crop water requirement (unit: mm), ET0 is the reference evaporation (unit: mm), K g represents the crop coefficient, which is obtained based on experimental data from literature in the study area (unit: mm).

[0121] ET0 is calculated using the Penman-Monteith method recommended by the Food and Agriculture Organization (FAO):

[0122]

[0123] Among them, R n Represents the net radiation of the surface (unit: MJ·m -1 ·d -1 ), G represents soil heat flux (unit: MJ·m -2 ·d -1 ), u2 represents the wind speed at high altitude (unit: m / s), es represents the saturated water vapor pressure (unit: kPa), ea represents the actual water vapor pressure (unit: kPa), T represents the average daily temperature (°C), Δ represents the slope of the saturated water vapor pressure curve (unit: kPa·°C -1 ), γ represents the psychrometric constant (unit: kPa·℃ -1 ).

[0124] The ecological water demand of forest and grassland in the evaluation unit can be expressed as:

[0125]

[0126] Among them, ET lc represents the ecological water demand of forest and grassland (unit: mm), ET0 represents the reference evaporation (unit: mm), calculated by the above formula, K c It represents the vegetation coefficient. According to the experimental results of predecessors, K of trees, shrubs and grasslands is c The values ​​are 0.62, 0.5385 and 0.263 respectively, S represents the actual soil moisture content; S w represents the soil wilting point, S* represents the critical soil moisture content, and K represents the minimum ecological water requirement for different soil types. s The values ​​are detailed in the table below:

[0127] Soil texture sand loam clay loam clay Ks 0.5484 0.5564 0.5365 0.5387

[0128] S4. Based on the collected data on the evolution of hydrological conditions and the relationship between water supply and demand, a drought and flood evaluation index system was constructed to grade and verify historical drought and flood events in the study area. The implementation method is as follows:

[0129] S401. Constructing a drought and flood evaluation index system based on the collected hydrological situation evolution data and the water supply and demand balance relationship, and calculating a water resource profit and loss index based on the drought and flood evaluation index system;

[0130] S402, performing a secondary correction on the weight factor in the water resource profit and loss index;

[0131] S403. Calculate a drought and flood index based on the watershed data and the modified weight factor, perform a secondary correction on the drought and flood index, and classify the modified drought and flood index into different levels.

[0132] S404. Verify the division results based on the actual historical drought and flood disasters in the study area.

[0133] In this embodiment, a drought and flood evaluation index system is constructed based on the collected meteorological and hydrological data and the acquired water supply and demand data. Specifically, it is necessary to calculate the water resource surplus and deficit amount and the water resource surplus and deficit index. The specific calculation formula is as follows:

[0134] ΔW=WS-WD

[0135] The calculation formula for the water resource profit and loss index (Z) for each month is as follows:

[0136] Z=K*×ΔW

[0137]

[0138] Among them, Z represents the water resource profit and loss index of each month, ΔW represents the water resource profit and loss (unit: mm), WS represents the water supply of the evaluation unit (unit: mm), and WD represents the total water demand of the evaluation unit (unit: mm). and They represent the multi-year average water supply and demand of the evaluation unit in the corresponding month (in mm), and K* represents the uncorrected water resource profit and loss correction coefficient.

[0139] In this embodiment, the K* value is actually inversely proportional to the average value of the absolute value of the water resource surplus or deficit, so the weight factor water resource surplus or deficit correction coefficient K* is corrected based on step S401. The corrected K* calculation formula is as follows:

[0140]

[0141] Among them, the average weight of extreme drought It can be expressed as:

[0142]

[0143] The calculation formula for the first approximation K' of K* is as follows:

[0144]

[0145] Among them, K'* represents the modified weight factor, represents the water resource surplus or deficit of each evaluation unit (unit: mm), K' represents the first approximate value of K'*, represents the average weight of extreme drought, It represents the water resource surplus or deficit of each evaluation unit in the driest 12 months (unit: mm).

[0146] In this embodiment, when evaluating flood events in the evaluation unit, the drought and flood index is first calculated, and then the drought and flood index is corrected twice according to the correction coefficient and compared with the drought and flood grade classification standard. The specific calculation formula of the drought and flood index is:

[0147]

[0148]

[0149] Among them, FDI i It represents the drought and flood index, which is obtained by continuously accumulating FDI1. Z1 represents the water resource profit and loss index of the first month. i-1 Represents the drought and flood index in month i-1.

[0150]

[0151] Among them, FDI i ' represents the revised drought and flood index for month i, R i represents the outlet flow of the sub-basin in month i (unit: m 3 / s), It represents the multi-year mean of runoff in month i during the statistical period, which is obtained from the hydrological data in step S1. If it is lacking, it can be replaced by the output data of the WEP model in step S3.

[0152] The drought and flood classification standards are as follows:

[0153] Drought and Flood Index FDI grade Drought and Flood Index FDI grade FDI≥4.0 extreme flooding -2.0<FDI≤-1.0 Mild drought 3.0≤FDI<4.0 severe flooding -3.0<FDI≤-2.0 moderate drought 2.0≤FDI<3.0 Moderate flooding -4.0<FDI≤-3.0 severe drought 1.0≤FDI<2.0 Minor flooding FDI≤-4.0 extreme drought -1.0<FDI<1.0 normal

[0154] In this embodiment, based on the classification of drought and flood events, the actual drought and flood disasters in the study area from 1968 to 2000 recorded in the "China Meteorological Disaster Encyclopedia: Shandong Volume" are used as a benchmark to verify the rationality of the calculation indicators for classification of drought and flood levels.

[0155] S5. Based on the division and verification results, determine the construction standards for various soil conditioning measures, select environmental factor constraints, determine the soil conditioning measures in the sub-basins, and, based on the soil conditioning measures in the sub-basins, determine the appropriate construction areas for soil conditioning measures in the basin;

[0156] In this embodiment, the construction standards of various soil conditioning measures are investigated: referring to the "Technical Specifications for Comprehensive Soil and Water Conservation", "Technical Specifications for Deep Plowing", "Technical Specifications for Corn Straw Mulching and Returning to Fields", "Technical Specifications for Green Manure Planting and Utilization" and "Technical Specifications for Horizontal Terrace Construction", etc., combined with the results of on-site investigation, with land use, evaluation unit slope and effective soil depth as boundary conditions, the optional soil conditioning measures for the evaluation unit are determined.

[0157] In this example, environmental factor constraints are selected to determine the soil conditioning measures available for different sub-basin evaluation units: the suitable area for terrace construction in the Sihe River Basin is limited to cultivated land, woodland, grassland, and bare land with a slope of 3-35° and an effective soil depth of 40 cm or more; the suitable area for ridge and ditch layout is limited to cultivated land and woodland with a slope of ≤15° and an effective soil depth of ≥60 cm; deep tillage is limited to cultivated land and bare land with a slope of ≤25° and an effective soil depth of ≤100 cm and conditions for mechanical operation.

[0158] In this example, the study area is divided into areas suitable for and unsuitable for construction of watershed soil conditioning measures: the results of the classification of different soil conditioning measures show that the area suitable for terrace construction is only 121.8 km 2 , accounting for 4.7% of the basin area; the suitable construction area for biochar addition is 2013.7km 2 , accounting for about 77% of the total area. The area suitable for straw return to farmland is 1995.3km 2 , accounting for 76.3% of the total area of ​​the basin; the areas suitable for ridge and ditch layout and deep tillage construction account for 54.2% and 53.5% of the total area of ​​the basin respectively.

[0159] S6. Based on the empirical equation and the suitable construction area, the regulation capacity of different soil regulation measures implemented in the suitable construction area is obtained;

[0160] In this embodiment, the soil conditioning capacity of different soil conditioning measures is obtained by combining the empirical equation of soil conditioning measures with the obtained suitable construction area to obtain the conditioning capacity of the suitable construction area.

[0161] S7. Using a single-objective spatial optimization method, with maximum drought and flood mitigation as the constraint objective, and based on the regulatory capacity of different soil regulation measures implemented in suitable construction areas, obtain a spatial layout plan for the construction of soil regulation measures in the watershed. The implementation method is as follows:

[0162] S701. Compare the regulation capacity of each soil regulation measure constructed in each evaluation unit. With the maximum drought and flood mitigation as the constraint objective, locate the soil regulation measures deployed in the evaluation unit to determine the spatial distribution of each soil regulation measure in the sub-watershed.

[0163] S702. Integrate the spatial distribution of various soil conditioning measures in the sub-basin to obtain a spatial layout plan for the construction of soil conditioning measures in the basin.

[0164] In this example, based on historical measured data from the Sihe River Basin, the multi-year average of the absolute value of the drought and flood index of the control unit is used as the representation of the drought and flood mitigation target. A configuration model is used to determine the proposed soil regulation capacity and spatial layout of various facilities for each control unit (sub-basin) in the basin under different climatic conditions. The calculation formula involved is:

[0165]

[0166] in:

[0167]

[0168]

[0169] Among them, FDI ij ' represents the drought and flood index of control unit i in the jth month after considering soil regulation measures, N represents the total number of months in the study period, Z ij ' represents the water resource profit and loss index of control unit i in the jth month after considering the soil regulation measures, R ij and R ij 'represent the outlet flow of control unit i before and after the construction of soil conditioning measures in month j (unit: m 3 / s), k ij ' represents the revised water resource profit and loss correction coefficient, WS ij Indicates the water supply of control unit i in the jth month (unit: mm), WD ij Indicates the water demand of control unit i in the jth month (unit: mm), △W i Indicates the proposed storage capacity of soil conditioning measures (unit: mm), WT i It represents the storage capacity of soil regulation measures in control unit i (unit: mm), A ik Indicates the planned construction area of ​​the kth soil conditioning measure for control unit i (unit: m 2 ), AT ik It represents the total construction area of ​​the kth soil conditioning measure for control unit i (unit: m 2 ),ω ik Indicates the storage capacity per unit area of ​​the kth soil regulation measure (unit: mm / m2 ).

[0170] In this embodiment, the soil regulation measures of each control unit (sub-basin) in the watershed are integrated to obtain a spatial layout plan for the construction of soil regulation measures in the watershed.

Claims

1. A method for configuring soil conditioning measures for drought and flood mitigation, characterized in that: The following steps are involved: S1. Collect and identify the physical geographical information and hydrological evolution data of the study area, and divide the study area into n sub-basins; S2. Screen soil conditioning measures to determine their impact on rainfall runoff and soil water holding capacity in different sub-watersheds, and develop empirical equations to quantify the impact of various soil conditioning measures on soil water holding capacity, including: The first type of soil conditioning measures includes deep tillage, straw return and biochar addition: in, It indicates the regulating capacity of deep tillage, straw return and biochar addition on water resources in the evaluation unit. represents the evaluation unit area, represents the average effect value of the first type of soil conditioning measures on rainfall-runoff, It represents the mean field water holding capacity of the effective depth of soil. It represents the average wilting water content of the effective depth of soil. represents the effective depth of soil unit, It represents the average runoff coefficient of different rainfall events in the evaluation unit before the construction of soil conditioning measures; The second type of soil regulation measures to improve water resource regulation capacity is to lay out ridges and furrows on sloping farmland: in, Indicates the regulatory capacity of ridge and ditch construction on sloping farmland within the evaluation unit. 、 、 and Both represent farmland ridge and ditch layout parameters. Indicates the original ground slope; The third type of soil regulation measures is to improve water resource regulation capacity through terrace construction: in, Indicates the regulatory capacity of terrace construction within the evaluation unit, 、 、 and Average terrace layout parameters; S3. Analyze the historical water supply and demand balance relationship in the study area based on the searched physical geographic information; S4. Based on the collected data on the evolution of hydrological conditions and the relationship between water supply and demand, a drought and flood evaluation index system is constructed to classify and verify historical drought and flood events in the study area; S5. Based on the division and verification results, determine the construction standards for various soil conditioning measures, select environmental factor constraints, determine the soil conditioning measures in the sub-basins, and, based on the soil conditioning measures in the sub-basins, determine the appropriate construction areas for soil conditioning measures in the basin; S6. Based on the empirical equation and the suitable construction area, the regulation capacity of different soil regulation measures implemented in the suitable construction area is obtained; S7. Utilize a single-objective spatial optimization method, with maximum drought and flood mitigation as the constraint objective, and based on the regulatory capacity of different soil regulation measures implemented in suitable construction areas, obtain a spatial layout plan for the construction of soil regulation measures in the watershed.

2. The method for configuring soil conditioning measures for drought and flood mitigation according to claim 1, characterized in that: The step S1 comprises the following steps: S101. Collect and identify different natural geographical information and hydrological regime evolution data for research; S102. Use the ARCGIS platform Hydrology hydrological and hydraulic model to fill depressions, generate flow directions, calculate runoff accumulation, calculate slopes, and generate and encode river networks within the basin to generate sub-basins, thereby dividing the study area into n sub-basins.

3. The method for configuring soil conditioning measures for drought and flood mitigation according to claim 1, characterized in that: The step S2 comprises the following steps: S201. Screen soil conditioning measures; S202, using the GetData tool to obtain experimental data between the soil conditioning measure control group and the blank group; S203. Statistically analyze the experimental data and use OpenMEE software as a tool to quantify the effects of soil conditioning measures on key elements of the water cycle under different environmental factors and calculate the average effect value; S204. Classify and integrate the impact mechanisms of soil conditioning measures on water cycle elements and processes based on the average effect values; S205. Based on the classification and integration results, as well as the functional classification and construction model generalization of soil conditioning measures, establish empirical equations to quantify the impact of various soil conditioning measures on soil conditioning capacity.

4. The method for configuring soil conditioning measures for drought and flood mitigation according to claim 3, characterized in that: The expression of the average effect value is as follows: in, represents the average effect size, X t and represent the mean values ​​of water cycle process indexes of the single sample soil conditioning measures construction treatment group and the blank control group, respectively. Represents the logarithmic function.

5. The method for configuring soil conditioning measures for drought and flood mitigation according to claim 1, characterized in that: The step S3 comprises the following steps: S301. Based on the searched natural geographic information, a WEP distributed hydrological model of the watershed is constructed; S302. Based on the WEP distributed hydrological model of the basin, quantify the historical water supply of the basin and the ecological water use of crops, woodlands and grasslands, and analyze the water supply and demand balance relationship.

6. The method for configuring soil conditioning measures for drought and flood mitigation according to claim 1, characterized in that: The step S4 comprises the following steps: S401. Constructing a drought and flood evaluation index system based on the collected hydrological situation evolution data and the water supply and demand balance relationship, and calculating a water resource profit and loss index based on the drought and flood evaluation index system; S402, performing a secondary correction on the weight factor in the water resource profit and loss index; S403. Calculate a drought and flood index based on the watershed data and the modified weight factor, perform a secondary correction on the drought and flood index, and classify the modified drought and flood index into different levels. S404. Verify the division results based on the actual historical drought and flood disasters in the study area.

7. The method for configuring soil conditioning measures for drought and flood mitigation according to claim 6, characterized in that: The expression of the water resource profit and loss index is as follows: in, Indicates the water resource profit and loss index for each month, Indicates the surplus or deficit of water resources, Indicates the water supply of the evaluation unit, Indicates the total water demand of the evaluation unit, and Respectively represent the multi-year average water supply and demand of the evaluation unit in the corresponding month, represents the uncorrected water resource profit and loss correction factor; The expression for performing secondary correction on the weight factor in the water resource profit and loss index is as follows: in, represents the modified weight factor, Indicates the water resource surplus and deficit of each evaluation unit, express A first approximation of represents the average weight of extreme drought, It represents the water resource surplus and deficit of each evaluation unit in the driest 12 months; The expression of the drought and flood index is as follows: in, represents the drought and flood index, represents the water resource profit and loss index for the first month, express Monthly drought and flood index; The expression for performing secondary correction on the drought and flood index is as follows: in, Indicates the Monthly revised drought and flood index, Indicates the Yuezi Basin outlet flow, Indicates the number of Multi-year mean of monthly runoff.

8. The method for configuring soil conditioning measures for drought and flood mitigation according to claim 1, characterized in that: The step S7 comprises the following steps: S701. Compare the regulation capacity of each soil regulation measure constructed in each evaluation unit. With the maximum drought and flood mitigation as the constraint objective, locate the soil regulation measures deployed in the evaluation unit to determine the spatial distribution of each soil regulation measure in the sub-watershed. S702. Integrate the spatial distribution of various soil conditioning measures in the sub-basin to obtain a spatial layout plan for the construction of soil conditioning measures in the basin.

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