Soil water storage capacity parameter derivation method considering geographic features of underlying surface

Abstract

A soil water storage capacity parameter derivation method considering underlying surface geographic features comprises the following steps that 1, a plurality of typical drainage basins with rich rainfall runoff observation data are selected, and soil water storage capacity parameters WM in all the typical drainage basins are obtained; step 2, performing statistics on underlying surface geographic feature factors of each typical drainage basin, and performing screening to obtain underlying surface geographic feature factors which have obvious influence on soil water storage capacity parameters; step 3, based on the screened underlying surface geographic feature factors, fitting to obtain a relation function F of the underlying surface geographic feature factors and soil water storage capacity parameters; and 4, extracting underlying surface geographic feature factors of the data-free drainage basin around the typical drainage basin, and obtaining soil water storage capacity parameters in the data-free drainage basin by using the relation function F to realize spatial distribution derivation of the parameters. The method has the advantages of stable and reliable data source, high calculation efficiency, objective and reasonable result and the like, and is worthy of popularization.

Description

Technical Field

[0001] The invention relates to the field of hydrological technology, and in particular to a soil water storage capacity parameter derivation method taking into account the underlying surface geographical characteristics. Background Art

[0002] Small watersheds in mountainous areas are often located in remote areas, making it difficult to deploy a sufficient number of hydrological monitoring stations to monitor water levels and flow rates. It is also difficult to obtain sufficient hydrological observation data in each small watershed in mountainous areas to compile flood forecasting model parameter schemes. As a result, the flood simulation accuracy in small watersheds in mountainous areas without data is usually low, which is not conducive to the widespread development of rapid flood forecasting in remote mountainous areas and poses a huge hidden danger to flood control safety.

[0003] At present, the construction of flood forecast model parameter schemes for small watersheds in mountainous areas without data usually adopts the method of parameter transplantation of adjacent watersheds. This method finds a watershed with a known parameter scheme near the area without data, and keeps the parameter scheme of the area without data consistent with the known parameter scheme. However, the underlying surface characteristics of different watersheds are bound to be different. The simple parameter transplantation method ignores the underlying surface geographical characteristics that affect the parameters. Therefore, it is difficult to improve the accuracy of flood forecasting in a large number of small watersheds in mountainous areas, which restricts the improvement of flood forecasting capabilities in mountainous watersheds.

[0004] In view of the above shortcomings, how to use economical, effective and scientifically reasonable methods in small watersheds in massive mountainous areas to realize the deduction of the spatial distribution of soil water storage capacity parameters taking into account the geographical characteristics of the underlying surface of the watershed, and support the scientific forecasting of floods in data-free mountainous watersheds, is a problem that needs to be solved. Summary of the invention

[0005] In order to avoid the above problems, a method for deriving soil water storage capacity parameters taking into account the geographical characteristics of the underlying surface is provided. It has the advantages of stable and reliable data source, high calculation efficiency, and objective and reasonable results, and is worthy of promotion.

[0006] The present invention provides a method for deriving soil water storage capacity parameters taking into account the underlying surface geographical characteristics, comprising the following steps:

[0007] Step 1: Select several typical watersheds with rich rainfall runoff observation data and obtain the soil water storage capacity parameter W in each typical watershed. M ;

[0008] Step 2: Count the underlying surface geographical characteristic factors of each typical watershed, and screen out the underlying surface geographical characteristic factors that have a significant impact on soil water storage capacity parameters;

[0009] Step 3, based on the screened underlying surface geographical characteristic factors, fitting the relationship function F between the underlying surface geographical characteristic factors and the soil water storage capacity parameters;

[0010] Step 4: Extract the underlying surface geographic characteristic factors of the data-free basins around the typical basin, and use the relationship function F to obtain the soil water storage capacity parameters in the data-free basin to achieve the spatial distribution deduction of the parameters.

[0011] Preferably, the underlying surface geographical feature factors include: the average slope S of the watershed c , soil thickness S t , sand content S d , Powder content S s , clay content S y .

[0012] Preferably, step 1 specifically includes:

[0013] 1.1 Extract water systems based on digital elevation data and identify main river channels;

[0014] 1.2 Select several typical watersheds with abundant rainfall-runoff observation data around the main river channels;

[0015] 1.3 Use intelligent optimization methods to calibrate the soil water storage capacity parameters in each typical watershed.

[0016] Preferably, step 1.2 is specifically as follows: conduct a survey of rainfall, the distribution of hydrological observation stations and the length of water-rainfall observation data series, select several typical river basins with hourly water-rainfall observation data and data series length exceeding 3 years, and each typical river basin is evenly distributed along the main river channel from upstream to downstream and on both sides of the main river channel.

[0017] Preferably, step 1.3 is specifically as follows: constructing a full-storage runoff model in a typical river basin, and based on 3-year water and rainfall observation data, using a cooperative optimization algorithm to carry out parameter optimization calibration of the full-storage runoff model in each typical river basin to obtain the soil water storage capacity parameters in each typical river basin.

[0018] Preferably, step 2 specifically includes:

[0019] 2.1 Statistics of underlying surface characteristic factors of each typical watershed: Average slope S of the watershed c , soil thickness S t , sand content S d , Powder content S s , clay content S y ;

[0020]

[0021] In the formula, S i , S t，i , S d，i , S s，i , S y，iare the slope, soil thickness, sand content, silt content, and clay content of each grid unit in the watershed; N is the number of grid units in the watershed;

[0022] 2.2 Calculate the correlation coefficient γ between soil water storage capacity parameters and underlying surface characteristic factors in a typical watershed:

[0023]

[0024] Where: W represents the water storage capacity of the watershed soil M and θ i The correlation coefficient between i Represents variable S c , S t , S d , S s , S y , i is the number of the variable; E is the mathematical expectation calculation function;

[0025] 2.3 The absolute values ​​of are ranked from large to small, and the top three underlying surface characteristics of the watershed are selected as the main factors affecting the soil water storage capacity parameters.

[0026] Preferably, step 3 specifically includes:

[0027] 3.1 Preliminary fitting of the relationship function f1 between the three main underlying surface geographical characteristics factors and soil water storage capacity parameters:

[0028] Where: They are the three main underlying surface geographical characteristics factors that affect soil water storage capacity;

[0029] 3.2 Use function f1 to calculate the soil water storage capacity parameters in a typical watershed, sort the calculated soil water storage capacity parameters from small to large, and get the sequence LC. Sort the soil water storage capacity parameters obtained by optimization and calibration from small to large to get the sequence LE:

[0030] LC={W M，1 , W M，2 …W M，k …W M，K},

[0031] LE={W M，1 , W M，2 …W M，r …W M，K};

[0032] Where: W M，k represents a typical watershed numbered k, where k ranges from 1 to K and K is the number of typical watersheds; W M，rrepresents a typical watershed numbered r, from 1 to K;

[0033] 3.3 If the soil water storage capacity parameters in the same order in the sequence LC and the sequence LE correspond to the same typical watershed, that is, any k is the same as r, indicating the same typical watershed, then the function f1 is determined as the relationship function F between the underlying surface geographic characteristic factor and the soil water storage capacity parameter;

[0034] If the typical watersheds corresponding to the soil water storage capacity parameters in the same order in the sequence LC and the sequence LE are different, the sequences LE′ and LC′ are adjusted and the operations from step 2.1 to step 3.1 are repeated until the function f1′ is determined as the relationship function F between the underlying surface geographical characteristic factors and the soil water storage capacity parameters.

[0035] Preferably, the method for obtaining the sequences LE′ and LC′ is as follows: select a heavy rainfall process with a long period of drought in the early stage, take the rainfall P as the vertical axis and the runoff R as the horizontal axis, plot the P-R scatter plot for each time period, find the intercept V on the vertical axis of the straight line passing through the P-R scatter points and with a slope of 1, and readjust the order of the soil water storage capacity parameters in LE and LC in the order from small to large according to the V value, so as to obtain LE′ and LC′, so that the order of the soil water storage capacity parameters of each typical watershed in the two sequences is the same.

[0036] Compared with the prior art, the present invention has the following beneficial effects: the present invention provides a method for deducing the spatial distribution of soil water storage capacity parameters taking into account the geographical characteristics of the underlying surface of the watershed. The method is based on the physical factors that affect the soil water storage capacity parameters of small watersheds in mountainous areas, and combines intelligent algorithms to achieve the optimal calibration of soil water storage capacity parameters in the watershed, and reasonably quantifies the influence of the geographical characteristics of the underlying surface of the watershed on the soil water storage capacity parameters. This not only ensures the accuracy and reliability of the calculation results, but also solves the problem of deducing the spatial distribution of soil water storage capacity parameters taking into account the geographical characteristics of the underlying surface of the watershed. In addition, this method mainly uses the digital elevation model of the watershed and the intelligent algorithm, the data source is stable and reliable, and the functional relationship between the variables in the method is clear, which is conducive to the deduction of the spatial distribution of soil water storage capacity parameters taking into account the geographical characteristics of the underlying surface of the watershed, while ensuring the objectivity and rationality of the results, which can further promote the in-depth development of digital hydrology and the rapid improvement of flood control capabilities in mountainous areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a flow chart of a method for deriving soil water storage capacity parameters taking into account the underlying surface geographical characteristics according to a preferred embodiment of the present invention;

[0038] Figure 2 A digital elevation of a certain interval in a preferred embodiment of the present invention;

[0039] Figure 3A water system and typical river basin distribution in a certain area of ​​a preferred embodiment of the present invention;

[0040] Figure 4 The parameter calibration result in a typical watershed of a certain interval of a preferred embodiment of the present invention;

[0041] Figure 5 The slope of each sub-basin in a certain interval of a preferred embodiment of the present invention;

[0042] Figure 6 The soil thickness distribution in each sub-basin of a certain interval of a preferred embodiment of the present invention;

[0043] Figure 7 The distribution of sand content in each sub-basin of a certain interval in a preferred embodiment of the present invention;

[0044] Figure 8 The distribution of powder content in each sub-flow area of ​​a certain interval in a preferred embodiment of the present invention;

[0045] Fig. 9 The distribution of clay content in each sub-basin of a certain interval in a preferred embodiment of the present invention;

[0046] Fig.10 is the average slope in each sub-basin of a certain interval in a preferred embodiment of the present invention;

[0047] Fig.11 The average soil thickness in each sub-basin of a certain interval in a preferred embodiment of the present invention;

[0048] Fig.12 is the average sand content in each sub-basin of a certain interval in a preferred embodiment of the present invention;

[0049] Fig.13 is the average powder content in each sub-basin of a certain interval in a preferred embodiment of the present invention;

[0050] Fig.14 is the average clay content in each sub-basin of a certain interval in a preferred embodiment of the present invention;

[0051] Fig.15 A P-R scatter diagram is shown in a preferred embodiment of the present invention;

[0052] Fig.16 This is the spatial distribution of soil water storage capacity parameters in a certain interval according to a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0053] This embodiment provides a method for deriving soil water storage capacity parameters taking into account the underlying surface geographical characteristics, including the following steps:

[0054] Step 1: Select several typical watersheds with abundant rainfall runoff observation data, and use the intelligent optimization method to calibrate the soil water storage capacity parameters in each typical watershed. The specific steps are as follows:

[0055] 1.1 Extract water systems based on digital elevation data and identify main river channels;

[0056] 1.2 Select several typical watersheds with abundant rainfall-runoff observation data around the main river channels;

[0057] A survey was conducted on the distribution of rainfall and hydrological observation stations and the length of water-rainfall observation data series. Several typical river basins with hourly water-rainfall observation data and data series length of more than 3 years were selected. Each typical river basin was evenly distributed along the main river channel from upstream to downstream and on both sides of the main river channel.

[0058] 1.3 Use intelligent optimization method to calibrate the soil water storage capacity parameters in each typical watershed;

[0059] A full-storage runoff model was constructed in a typical river basin. Based on three years of water and rainfall observation data, the cooperative optimization algorithm (CSA) was used to optimize and calibrate the parameters of the full-storage runoff model in each typical river basin, and the soil water storage capacity parameters in each typical river basin.

[0060] Step 2: Calculate the average slope S of each typical watershed. c , soil thickness S t , sand content S d , Powder content S s , clay content S y The underlying surface geographical characteristic factors such as the following are screened to obtain the underlying surface geographical characteristic factors that have a significant impact on the soil water storage capacity parameters. The specific steps are as follows:

[0061] 2.1 Statistics of the average slope S of each typical river basin c , soil thickness S t , sand content S d , Powder content S s , clay content S y Equivalent underlying surface characteristic factors;

[0062]

[0063] Where: S i , S t，i , S d，i , S s，i , S y，i are the slope, soil thickness, sand content, silt content, and clay content of each grid unit in the watershed; N is the number of grid units in the watershed;

[0064] 2.2 Calculate the correlation coefficient γ between soil water storage capacity parameters and underlying surface characteristic factors in a typical watershed;

[0065] Calculate soil water storage capacity parameter W M Correlation coefficient between the underlying surface characteristic factors:

[0066]

[0067] Where: W represents the water storage capacity of the watershed soil M and θ i The correlation coefficient between i Represents S c , S t , S d , S y Equal variables, i is the number of the variable; E is the mathematical expectation calculation function.

[0068] 2.3 Screening out the underlying surface geographical characteristic factors that have a significant impact on soil water storage capacity parameters;

[0069] Will The absolute values ​​of are ranked from large to small, and the top three underlying surface characteristics of the watershed are selected as the main factors affecting the soil water storage capacity parameters.

[0070] Step 3: Based on the soil water storage capacity parameters in typical watersheds and the selected underlying surface geographical characteristic factors, the relationship function F between the underlying surface geographical characteristic factors and the soil water storage capacity parameters is fitted. The specific steps are as follows:

[0071] 3.1 Preliminary fitting yields the relationship function f1 between the underlying surface geographic characteristic factors and soil water storage capacity parameters:

[0072] Where: They are the three main factors affecting soil water storage capacity. The function form of f1 is generally a three-variable linear equation.

[0073] 3.2 Use function f1 to calculate the soil water storage capacity parameters in a typical watershed, sort the calculated soil water storage capacity parameters from small to large, and obtain the sequence LC; sort the soil water storage capacity parameters obtained by optimization and calibration from small to large, and obtain the sequence LE;

[0074] LC={W M，1 , W M，2 …W M，k …W M，K},

[0075] LE={W M，1 , W M，2 …W M，r…W M，K};

[0076] Where: W M，k represents a typical watershed numbered k, where k ranges from 1 to K and K is the number of typical watersheds; W M，r Represents a typical watershed numbered r, where r ranges from 1 to K.

[0077] If the typical watershed corresponding to the soil water storage capacity parameters in the same order in the sequence LC and the sequence LE is the same, that is, any k is the same as r, indicating the same typical watershed, then the function f1 is determined as the relationship function F between the underlying surface geographical characteristic factor and the soil water storage capacity parameter;

[0078] If the typical watersheds corresponding to the soil water storage capacity parameters in the same order in the sequence LC and the sequence LE are different, the sequences LE′ and LC′ are adjusted, and the operations from step 2.1 to step 3.1 are repeated to determine the function f1′ at this time as the relationship function F between the underlying surface geographical characteristic factors and the soil water storage capacity parameters.

[0079] The method for obtaining the sequences LE′ and LC′ is as follows:

[0080] A heavy rainfall process with a long drought in the early stage was selected, with rainfall P as the vertical axis and runoff R as the horizontal axis, and a P-R scatter plot was plotted for each time period. The intercept V of the straight line on the vertical axis with a slope of 1 passing through the P-R scatter points was found, and the soil water storage capacity parameters in LE and LC were readjusted in the order of V value from small to large to obtain LE′ and LC′, so that the order of soil water storage capacity parameters of each typical basin in the two sequences was the same.

[0081] Step 4: Extract the underlying surface geographic characteristic factors of several watersheds without data around the typical watershed, use the relationship function F to estimate the soil water storage capacity parameters in the watershed without data, and realize the spatial distribution derivation of the parameters. The specific steps are as follows:

[0082] 4.1 According to the method in step 2.1, extract the underlying surface geographic characteristic factors of several watersheds without data around the typical watershed;

[0083] 4.2 Using the relationship function F between the underlying surface geographic characteristic factors and the soil water storage capacity parameters determined in step 3, the underlying surface geographic characteristic factors are taken as input to calculate the soil water storage capacity parameters in each data-free basin to achieve spatial distribution deduction of the parameters.

[0084] Taking a certain interval basin in the upper reaches of the Yangtze River as an example, the controlled area of ​​the basin is about 1 million square kilometers, of which the main catchment area is 55,907 square kilometers. The interval is a rainstorm-prone area in the upper reaches of the Yangtze River. The floods formed by rainstorms are high in frequency, intensity and magnitude, and are affected by the topography and landforms, which have an important impact on the flood control safety and operation scheduling of reservoirs in the region. Taking a certain interval as an example, the present invention takes the A, B, C, D, E, F, G, H, I, J and other basins as typical basins with rich measured data, and applies the method proposed by the present invention to carry out the spatial distribution deduction of soil water storage capacity parameters considering the geographical characteristics of the basin's underlying surface.

[0085] A method for deducing the spatial distribution of soil water storage capacity parameters considering the geographical characteristics of the underlying surface of a watershed, comprising the following steps:

[0086] Step 1: Select several typical watersheds with abundant rainfall runoff observation data, and use the intelligent optimization method to calibrate the soil water storage capacity parameters in each typical watershed. The specific steps are as follows:

[0087] 1.1 Based on digital elevation data (such as Figure 2 ) Extract water systems and identify main river channels;

[0088] 1.2 Select several typical basins with rich rainfall-runoff observation data around the main river channel, see Figure 3 ;

[0089] A survey was conducted on the distribution of rainfall and hydrological observation stations and the length of water-rainfall observation data series. Several typical river basins with hourly water-rainfall observation data and data series length of more than 3 years were selected. Each typical river basin was evenly distributed along the main river channel from upstream to downstream and on both sides of the main river channel.

[0090] The typical watersheds selected in this example are: A, B, C, D, E, F, G, H, I, J, etc. The typical watershed distribution is shown in Figure 3 .

[0091] 1.3 Use intelligent optimization method to calibrate the soil water storage capacity parameters in each typical watershed;

[0092] A full-storage runoff model was constructed in a typical watershed. Based on the three-year water and rainfall observation data, the cooperative optimization algorithm (CSA) was used to optimize the parameters of the full-storage runoff model in each typical watershed. The soil water storage capacity parameters in each typical watershed are shown in Figure 2. Figure 4 .

[0093] Step 2: Calculate the average slope S of each typical watershed. c , soil thickness S t , sand content S d , Powder content Ss , clay content S y The underlying surface geographical characteristic factors such as the following are screened to obtain the underlying surface geographical characteristic factors that have a significant impact on the soil water storage capacity parameters. The specific steps are as follows:

[0094] 2.1 Statistics of the average slope S of each typical watershed c , soil thickness S t , sand content S d , Powder content S s , clay content S y Equivalent underlying surface characteristic factors;

[0095]

[0096]

[0097] Where: S i , S t，i , S d，i , S s，i , S y，i are the slope, soil thickness, sand content, silt content, and clay content of each grid unit in the basin; N is the number of grid units in the basin; the slope, soil thickness, sand content, and clay content of each grid unit in each sub-basin of a certain interval are shown in Figure 5 , 6 , 7, 8, 9; the average slope, average soil thickness, average sand content, average silt content, and average clay content in a sub-basin of a certain interval are shown in Figure 1. Fig.10 , 11 , 12, 13, 14.

[0098] 2.2 Calculate the correlation coefficient γ between soil water storage capacity parameters and underlying surface characteristic factors in a typical watershed;

[0099] Calculate soil water storage capacity parameter W M Correlation coefficient between the underlying surface characteristic factors:

[0100]

[0101] Where: W represents the water storage capacity of the watershed soil M and θ i The correlation coefficient between i Represents ΔE, S w , S c , S t , S d , S y Equal variables, i is the number of the variable; E is the mathematical expectation calculation function.

[0102] 2.3 Screening out the underlying surface geographical characteristic factors that have a significant impact on soil water storage capacity parameters;

[0103] Will The absolute values ​​of are ranked from large to small, and the top three underlying surface characteristics of the watershed are selected as the main factors affecting the soil water storage capacity parameters.

[0104] In this embodiment, the soil water storage capacity parameter W is calculated in a certain interval. M The correlation coefficient between the underlying surface characteristic factor is:

[0105] Soil thickness Sand content Powder content Clay content slope 0.66 0.62 -0.18 -0.16 -0.53

[0106] Therefore, in this embodiment, a certain interval affects the soil water storage capacity parameter W M The main underlying surface characteristics of the basin are: soil thickness, sand content and slope.

[0107] Step 3: Based on the soil water storage capacity parameters in typical watersheds and the selected underlying surface geographical characteristic factors, the relationship function F between the underlying surface geographical characteristic factors and the soil water storage capacity parameters is fitted. The specific steps are as follows:

[0108] 3.1 Preliminary fitting yields the relationship function f1 between the underlying surface geographic characteristic factors and soil water storage capacity parameters:

[0109] Where: They are the three main factors that affect soil water storage capacity, which in this case are soil thickness, sand content and slope. The function form of f1 is generally a three-variable linear equation.

[0110] 3.2 Use function f1 to calculate the soil water storage capacity parameters in a typical watershed, sort the calculated soil water storage capacity parameters from small to large, and obtain the sequence LC; sort the soil water storage capacity parameters obtained by optimization and calibration from small to large, and obtain the sequence LE;

[0111] LC={W M，1 , W M，2 …W M，k …W M，K},

[0112] LE={W M，1 , W M，2 …W M，r …W M，K};

[0113] Where: W M，k represents a typical watershed numbered k, where k ranges from 1 to K and K is the number of typical watersheds; W M，r Represents a typical watershed numbered r, where r ranges from 1 to K.

[0114] If the typical watershed corresponding to the soil water storage capacity parameters in the same order in the sequence LC and the sequence LE is the same, that is, any k is the same as r, indicating the same typical watershed, then the function f1 is determined as the relationship function F between the underlying surface geographical characteristic factor and the soil water storage capacity parameter;

[0115] If the typical watersheds corresponding to the soil water storage capacity parameters in the same order in the sequence LC and the sequence LE are different, the sequences LE′ and LC′ are adjusted, and the operations from step 2.1 to step 3.1 are repeated to determine the function f1′ at this time as the relationship function F between the underlying surface geographical characteristic factors and the soil water storage capacity parameters.

[0116] The method for obtaining the sequences LE′ and LC′ is as follows:

[0117] A heavy rainfall process with a long period of drought was selected, with rainfall P as the vertical axis and runoff R as the horizontal axis, and a scatter plot of P-R for each period was drawn. Fig.15 , find the intercept V of the straight line on the vertical axis that passes through the P~R scatter points and has a slope of 1, and readjust the order of the soil water storage capacity parameters in LE and LC in the order of V value from small to large to obtain LE′ and LC′, so that the order of the soil water storage capacity parameters of each typical watershed in the two sequences is the same.

[0118] In this example, the soil water storage capacity parameters in the same order in the sequence LC and the sequence LE correspond to the same typical watershed, and the final fitted relationship function F is:

[0119] W M =-0.2433×S c +0.0129×S t +0.0363×S d .

[0120] Step 4: Extract the underlying surface geographic characteristic factors of several watersheds without data around the typical watershed, use the relationship function F to estimate the soil water storage capacity parameters in the watershed without data, and realize the spatial distribution derivation of the parameters. The specific steps are as follows:

[0121] 4.1 According to the method in step 2.1, extract the underlying surface geographic characteristic factors of several watersheds without data around the typical watershed;

[0122] 4.2 Using the relationship function F between the underlying surface geographic characteristic factors and the soil water storage capacity parameters determined in step 3, the underlying surface geographic characteristic factors are taken as input to calculate the soil water storage capacity parameters in each data-free basin, and the spatial distribution of the parameters is deduced, see Fig.16 .

[0123] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for deriving soil water storage capacity parameters taking into account the underlying surface geographical characteristics, characterized in that: The steps include: Step 1: Select several typical watersheds with rich rainfall runoff observation data and obtain the soil water storage capacity parameter W in each typical watershed. M ; Step 2: Count the underlying surface geographical characteristic factors of each typical watershed, and screen out the underlying surface geographical characteristic factors that have a significant impact on soil water storage capacity parameters; Step 3, based on the screened underlying surface geographical characteristic factors, fitting the relationship function F between the underlying surface geographical characteristic factors and the soil water storage capacity parameters; Step 4: Extract the underlying surface geographic characteristic factors of the data-free basins around the typical basin, and use the relationship function F to obtain the soil water storage capacity parameters in the data-free basin to achieve the spatial distribution deduction of the parameters.

2. The method for deriving soil water storage capacity parameters taking into account the underlying surface geographical characteristics as claimed in claim 1, characterized in that: The underlying surface geographical characteristics include: the average slope S of the basin c , soil thickness S t , sand content S d , Powder content S s , clay content S y .

3. The method for deriving soil water storage capacity parameters taking into account the underlying surface geographical characteristics as claimed in claim 1, characterized in that: Step 1 specifically includes: 1.1 Extract water systems based on digital elevation data and identify main river channels; 1.2 Select several typical watersheds with abundant rainfall-runoff observation data around the main river channels; 1.3 Use intelligent optimization methods to calibrate the soil water storage capacity parameters in each typical watershed.

4. The method for deriving soil water storage capacity parameters taking into account the underlying surface geographical characteristics as claimed in claim 3, characterized in that: Step 1.2 is as follows: conduct a survey of rainfall, the distribution of hydrological observation stations and the length of water-rainfall observation data series, select several typical river basins with hourly water-rainfall observation data and data series length exceeding 3 years, and each typical river basin is evenly distributed along the main river channel from upstream to downstream and on both sides of the main river channel.

5. The method for deriving soil water storage capacity parameters taking into account the underlying surface geographical characteristics as claimed in claim 4, characterized in that: Step 1.3 is as follows: construct a full-storage runoff model in a typical river basin, and based on three years of water and rainfall observation data, use a cooperative optimization algorithm to perform full-storage runoff model parameter optimization calibration in each typical river basin to obtain the soil water storage capacity parameters in each typical river basin.

6. The method for deriving soil water storage capacity parameters taking into account the underlying surface geographical characteristics as claimed in claim 1, characterized in that: Step 2 specifically includes: 2.1 Statistics of underlying surface characteristic factors of each typical watershed: Average slope S of the watershed c , soil thickness S t , sand content S d , Powder content S s , clay content S y ; In the formula, S i , S t，i , S d，i , S s，i , S y，i are the slope, soil thickness, sand content, silt content, and clay content of each grid unit in the watershed; N is the number of grid units in the watershed; 2.2 Calculate the correlation coefficient γ between soil water storage capacity parameters and underlying surface characteristic factors in a typical watershed: Where: W represents the soil water storage capacity of the watershed M and The correlation coefficient between Represents variable S c , S t , S d , S s , S y , i is the number of the variable; E is the mathematical expectation calculation function; 2.3 The absolute values ​​of are ranked from large to small, and the top three underlying surface characteristics of the watershed are selected as the main factors affecting the soil water storage capacity parameters.

7. The method for deriving soil water storage capacity parameters taking into account the underlying surface geographical characteristics as claimed in claim 6, characterized in that: Step 3 specifically includes: 3.1 Preliminary fitting of the relationship function f1 between the three main underlying surface geographical characteristics factors and soil water storage capacity parameters: Where: They are the three main underlying surface geographical characteristics factors that affect soil water storage capacity; 3.2 Use function f1 to calculate the soil water storage capacity parameters in a typical watershed, sort the calculated soil water storage capacity parameters from small to large, and get the sequence LC. Sort the soil water storage capacity parameters obtained by optimization and calibration from small to large to get the sequence LE: LC={W M，1 ,W M，2 …W M，k …W M，K }, LE={W M，1 ,W M，2 …W M，r …W M，K }; Where: W M，k represents a typical watershed numbered k, where k ranges from 1 to K and K is the number of typical watersheds; W M，r represents a typical watershed numbered r, from 1 to K; 3.3 If the soil water storage capacity parameters in the same order in the sequence LC and the sequence LE correspond to the same typical watershed, that is, any k is the same as r, indicating the same typical watershed, then the function f1 is determined as the relationship function F between the underlying surface geographic characteristic factor and the soil water storage capacity parameter; If the soil water storage capacity parameters in the same order in the sequence LC and the sequence LE correspond to different typical watersheds, the sequence LE is adjusted to ′ and LC ′ , repeat the operations from step 2.1 to step 3.1 until function f1 ′ It is determined as the relationship function F between the underlying surface geographical characteristic factors and the soil water storage capacity parameters.

8. The method for deriving soil water storage capacity parameters taking into account the underlying surface geographical characteristics as claimed in claim 7, characterized in that: Sequence LE ′ and LC ′ The method for obtaining is as follows: select a heavy rainfall process with a long period of drought in the early stage, take the rainfall P as the vertical axis and the runoff R as the horizontal axis, draw a scatter plot of P-R for each time period, find the intercept V of the straight line passing through the P-R scatter points and with a slope of 1 on the vertical axis, and readjust the order of soil water storage capacity parameters in LE and LC in order of V value from small to large, and obtain LE ′ and LC ′ , so that the ranking of soil water storage capacity parameters of each typical watershed in the two sequences is the same.

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