Simulation Method and Device for Coordinated Changes of Land Surface Hydrology and Agricultural Irrigation under the Background of Climate Change

Abstract

The present invention provides a simulation method and device for the co-variation of land surface hydrology and agricultural irrigation under the background of climate change, including: Step I. Developing an irrigation module: estimating the crop irrigation water requirement at the grid scale and calculating the irrigation water volume according to the effective irrigation rate; Step II. Coupling the irrigation module with the land surface-hydrological model; Step III. Improving the irrigation module: calculating the surface water irrigation water intake according to the available surface water volume and further determining the groundwater irrigation water intake; Step IV. Describing the water intake process of agricultural irrigation by using an improved river routing algorithm and a groundwater lateral flow algorithm; Step VI. Constructing and validating the model; Step VII. Simulating the co-variation process: based on the measured data and simulation requirements of the study area, inputting the data and parameter values required by the model, and then running the model to simulate the co-variation process of the land surface process, hydrological process and agricultural irrigation activity intensity within the regional scope under the background of climate change research.

Description

Technical Field

[0001] The present invention belongs to the technical field of hydrological monitoring, and particularly relates to a simulation method and device for the coordinated change of land surface hydrology and agricultural irrigation activity intensity under the background of climate change. Background Art

[0002] Surface water and groundwater, as important components of the hydrological cycle, play important roles in all aspects of human production and life. Among them, agricultural irrigation is the main water - using unit of humans, and irrigation water accounts for 70% of the total water consumption globally. Due to the large water consumption and high intensity of agricultural irrigation, it can often change the hydrological process to a large extent, and even the regional climate conditions.

[0003] In order to describe the impact of agricultural irrigation activities on the hydrological process, scholars have added water intake and use modules for agricultural irrigation in different models. In global hydrological models, such as the global hydrological model H08, the global water use assessment model WaterGAP, and the global hydrological and water resources model PCR - GLOBWB, the irrigation volume and water consumption are estimated based on meteorological conditions, cultivated area, etc., and this part of water volume is deducted from the surface water and / or groundwater reserves. In hydrological models, satellite remote - sensing data such as vegetation type and vegetation cover are used to estimate the irrigation volume, or a simpler soil water deficit method is used to calculate the irrigation volume, and the irrigation water volume is deducted from rivers, lakes, and groundwater.

[0004] The existing simulation methods for agricultural irrigation and hydrological processes have the following problems: (1) In practice, the effective irrigation rate cannot reach 100%, and the irrigation water demand of crops cannot be fully met, resulting in the irrigation water volume estimated in the hydrological model being often higher than the actual irrigation volume; (2) When calculating the irrigation water demand of crops, a simple water balance method is often used to estimate the soil water content, ignoring other relevant land surface processes; (3) In hydrological models, the mutual influence between agricultural irrigation water intake and the hydrological process is often emphasized, such as irrigation causing a decrease in river flow and a decline in groundwater level, and at the same time, the available water volume in rivers, lakes, etc. will limit the irrigation water intake, while the interaction between agricultural irrigation and land surface processes is less considered, and the change process of agricultural irrigation intensity under changing environmental conditions cannot be simulated. Summary of the Invention

[0005] The present invention is made to solve the above - mentioned problems, and aims to provide a simulation method and device for the coordinated change of land surface hydrology and agricultural irrigation under the background of climate change, which can not only completely simulate the land surface process and hydrological process affected by agricultural irrigation activities, but also simulate the change process of irrigation intensity under the change of surface conditions and hydrological elements.

[0006] In order to achieve the above object, the present invention adopts the following solutions:

[0007] <Method>

[0008] As Figure 1 shown, the present invention provides a simulation method for the co-variation of land surface hydrological processes and the intensity of agricultural irrigation activities under the background of climate change, including the following steps:

[0009] Step I. Develop an irrigation module:

[0010] Estimate the crop irrigation water requirement at the grid scale using the global crop water use model method, and calculate the irrigation water volume W according to the effective irrigation rate irr :

[0011] W irr = α·IWR,

[0012] where IWR is the crop water requirement in the grid cell [mm / day]; α is the effective irrigation rate, and its value can generally be determined according to previous research or statistical data;

[0013] Step II. Coupling of the irrigation module with the land surface-hydrological model:

[0014] Develop an irrigation module based on the existing land surface-hydrological process model, and establish a land surface-hydrological-irrigation process model. The specific steps are as follows: ① Transfer the soil moisture simulated by the land surface model to the irrigation module, and calculate the irrigation water volume of the grid cell through the irrigation module; ② Calculate the surface water supply volume according to the river and lake water levels in the surface water module, so as to determine the surface water and groundwater irrigation water intake; ③ Describe the surface water and groundwater intake processes in the surface water and groundwater modules, and realize the description of the agricultural irrigation water use process in the land surface model;

[0015] The coupling method of the present invention is shown in Figure 2 , Figure 3 which shows the structure diagram of the land surface-hydrological-irrigation model;

[0016] Step III. Improvement of the irrigation module:

[0017] Calculate the surface water irrigation water intake according to the available surface water volume, and further determine the groundwater irrigation water intake;

[0018]

[0019] where is the surface water irrigation water intake [m / s], is the groundwater irrigation water intake [m / s], W irr is the irrigation water volume [mm / day], W sf is the available surface water volume [m 3 , and △t is the time step [s];

[0020] Step Ⅳ. Improvement of river confluence calculation and groundwater lateral flow algorithm:

[0021] The improved river confluence algorithm and groundwater lateral flow algorithm are adopted to describe the surface water and groundwater abstraction processes for agricultural irrigation respectively. The specific improvements are as follows:

[0022] ① The surface water irrigation water withdrawal is added as a source-sink term to the surface water module to describe the surface water abstraction process in the surface water module:

[0023]

[0024] In the formula, A flow is the cross-sectional area of the water flow [m 2 , H is the elevation of the free water surface of the river and lake [m], and Q is the flow rate of the grid cell [m 3 / s];

[0025] ② The groundwater irrigation water withdrawal is added as a source-sink term to the groundwater module to describe the groundwater abstraction process in the groundwater module:

[0026]

[0027] In the formula, T is the specific conductance [m 2 / s], μ is the specific yield [m 3 / m –3 , and H g is the elevation of the unconfined groundwater level [m];

[0028] Step Ⅵ. Model construction and verification:

[0029] Based on the above improved modules and algorithms, a land surface - hydrology - irrigation model of the study basin is constructed, and the irrigation module is verified according to the measured irrigation volume;

[0030] Step Ⅶ. Simulation of the co - variation process:

[0031] Based on the measured data and simulation requirements of the study area, the data and parameter values required by the model are input, and then the model is run to simulate the co - variation process of the land surface process, hydrological process and agricultural irrigation activity intensity within the regional scope under the background of research climate change.

[0032] Preferably, for the simulation method of the co - variation of land surface hydrological process and agricultural irrigation activity intensity under the background of climate change provided by the present invention, in Step Ⅰ: the method of the global crop water use model is adopted to estimate the irrigation water requirement of crops:

[0033] IWR C = PET C - AETC ,

[0034] In the formula, IWR C is the irrigation water requirement of crops [mm / day]; PET C is the potential evapotranspiration of crops [mm / day], representing the evapotranspiration of healthy crops under full irrigation conditions, and its value depends on climate conditions, crop types, crop growth status, etc., and is calculated using the crop coefficient method; AET C is the actual crop evapotranspiration [mm / day], and the crops are stressed by water and growth conditions in a changing environment.

[0035] PET C = k C ·ET0,

[0036] In the formula, K C is the dimensionless parameter crop coefficient, characterizing the water requirement laws of different types of crops at different growth stages; ET0 represents the reference crop evapotranspiration [mm / day], calculated according to the FAO Penman-Monteith method;

[0037]

[0038] p = p std + 0.04(5 - PET C ),

[0039] In the formula, K s is the crop water stress coefficient [-]; S max is the total available soil water [mm]; p std is the standard water consumption rate of crops, and its value represents the water consumption rate of crops when the evapotranspiration capacity is 5 mm / day; p represents the water consumption rate of crops under specific meteorological conditions, and its expression can illustrate that when the evaporation capacity is very strong, crop growth may be water-stressed even under high soil water content; S is the soil water available for plants [mm].

[0040] The specific calculation method of the crop irrigation water requirement at the grid scale is as follows:

[0041]

[0042] In the formula, IWR is the water requirement of crops in the unit grid [mm / day]; A is the grid cell area [m 2 ; A k is the area of the k-th crop in the grid cell [m 2 .

[0043] Preferably, for the simulation method for the co-variation of land surface hydrological processes and agricultural irrigation activity intensity under the background of climate change provided by the present invention, in step III, after the irrigation module is coupled with the land surface-hydrological process model, the irrigation module can make full use of the simulation results of the land surface module and the hydrological model. Therefore, the irrigation module can be improved as follows:

[0044] ① Since the land surface model uses a multi-layer soil model to simulate the dynamic changes of surface soil moisture (generally 0-2 m), therefore, the soil moisture available for plants in the irrigation module is no longer estimated by the simple soil moisture balance method, but calculated according to the soil moisture in the crop root zone simulated in the land surface model. The specific calculation formula is as follows:

[0045] S = ∑θ k ·Δz k ,

[0046] In the formula, θ k is the soil moisture of different soil layers in the root zone [m 3 / m 3 (simulated by the land surface model); △z k is the thickness of different soil layers in the root zone [m]; k is the number of layers corresponding to the root zone in the multi-layer soil model;

[0047] ② Since the hydrological model simulates the water levels of rivers and lakes within the grid cell, the surface water irrigation volume in the irrigation module is restricted by the available surface water supply. The specific improvement is as follows:

[0048] W sf = f·(Z water - Z bed )·Δx·Δy,

[0049] In the formula, W sf is the available surface water volume [m 3 , f is the proportion of the water surface area in the grid unit, Z water is the water surface level [m], Z bed is the river bottom elevation [m], and △x and △y are the grid unit precisions [m];

[0050] Calculate the surface water irrigation withdrawal volume based on the available surface water volume, and further determine the groundwater irrigation withdrawal volume;

[0051]

[0052] In the formula, is the surface water irrigation withdrawal volume, is the groundwater irrigation withdrawal volume.

[0053] Preferably, the simulation method for the co-variation of land surface hydrological processes and agricultural irrigation activity intensity provided by the present invention under the background of climate change may further include step V. Improvement of the soil moisture dynamic change algorithm:

[0054] The multi-layer soil module in the land surface model uses the following equation to describe the vertical dynamic change of soil moisture:

[0055]

[0056] In the formula, θ is the soil water content [m 3 / m 3 , z is the soil depth [m], D(θ) is the soil moisture diffusivity [m 2 / s], K(θ) is the soil hydraulic conductivity [m / s], q nat is the natural water flux of the surface soil [m / s];

[0057] The irrigation water volume, as an additional water source, will further affect the vertical movement process of soil moisture and its subsequent land surface processes (such as evaporation, transpiration, etc.). The improvement of the soil moisture dynamic change algorithm by the present invention is as follows:

[0058] Determine the actual irrigation water volume of the grid cell according to the irrigation water withdrawal amount as:

[0059]

[0060] In the formula, is the actual irrigation amount [m / s], and β is the leakage rate of the irrigation water pipe network (this value is determined according to the regional statistical data);

[0061] Add the determined actual irrigation amount as a source-sink term to the multi-layer soil module, and the specific expression is:

[0062]

[0063] In the formula, is the irrigation water volume [m / s].

[0064] Preferably, in step VI of the simulation method for the co-variation of land surface hydrological processes and agricultural irrigation activity intensity provided by the present invention under the background of climate change, since the land surface-hydrology-irrigation model of the present invention involves the simulation of land surface processes, hydrological processes and irrigation amounts, the present invention recommends first constructing a land surface-hydrology model, verifying the land surface module and the hydrological model, and then constructing a land surface-hydrology-irrigation module and verifying the irrigation module. The specific steps are as follows:

[0065] (1) Construct and verify the land surface-hydrology model

[0066] ①Taking the basin as the object, collect geographical data such as elevation, land use type, vegetation coverage area, soil texture, etc. within the study basin, give hydrological characteristic parameters such as river width, depth, and groundwater hydrology within the basin range, and use meteorological data as external forcing to drive the model to construct a land surface - hydrological model for this basin;

[0067] ②According to the existing research results, determine the value range of hydrological parameters within the study basin, further determine the values of hydrological parameters using the parameter calibration method, and verify the model using measured natural flow (selecting periods less affected by human activities or restoring flow data);

[0068] (2) Construct and verify a land surface - hydrological - irrigation model

[0069] ①Use the global crop dataset to describe the types, planting areas, and growth cycles (monthly scale) of crops planted within the study area, give the corresponding parameters for different types of crops according to existing research, and give the effective irrigation rate and leakage rate of the irrigation water conveyance network in the study area based on statistical data to construct an irrigation module for the study area;

[0070] ②Use the constructed land surface - hydrological - irrigation model to simulate the agricultural irrigation activities in the study area, and verify the irrigation model based on the comparison between the measured irrigation volume and the estimated irrigation water withdrawal volume.

[0071] Preferably, the simulation method for the co - variation of land surface hydrological processes and agricultural irrigation activity intensity under the background of climate change provided by the present invention may further have the following features: In step VII, by comparing hydrological elements such as evapotranspiration and return flow under irrigation and non - irrigation scenarios, clarify the impact of agricultural irrigation water withdrawal activities on the water cycle process at the basin scale; by comparing the simulation accuracies of land surface processes (such as evapotranspiration) and hydrological processes (such as the flow at the basin outlet section) under irrigation and non - irrigation scenarios, verify the effectiveness of describing agricultural irrigation activities in improving the simulation accuracies of land surface processes and hydrological processes. The evaluation indicators of simulation accuracy include but are not limited to the Nash efficiency coefficient and relative error.

[0072] <Device>

[0073] Furthermore, the present invention also provides a simulation device for the co - variation of land surface hydrological processes and agricultural irrigation activity intensity under the background of climate change based on the above <Method>.

[0074] Specifically, the simulation device for the co - variation of land surface hydrological processes and agricultural irrigation activity intensity under the background of climate change provided by the present invention includes:

[0075] An irrigation water demand calculation unit, which estimates the crop irrigation water demand at the grid scale using the method of the global crop water model and calculates the irrigation water volume W according to the effective irrigation rate irr :

[0076] W irr = α·IWR,

[0077] where IWR is the water requirement of crops in the grid cell; α is the effective irrigation rate;

[0078] Coupling part: Based on the existing land surface - hydrological process model, an irrigation module is developed to establish a land surface - hydrological - irrigation process model. The specific steps are as follows: ① Transmit the soil moisture simulated by the land surface model to the irrigation module, and calculate the irrigation water volume of the grid cell through the irrigation module; ② Calculate the surface water supply volume according to the water levels of rivers and lakes in the surface water module, so as to determine the surface water and groundwater irrigation water intakes; ③ Describe the surface water and groundwater intake processes in the surface water and groundwater modules, and realize the description of the agricultural irrigation water use process in the land surface model;

[0079] Irrigation water intake calculation part: Calculate the surface water irrigation water intake according to the available surface water volume, and further determine the groundwater irrigation water intake;

[0080]

[0081] where is the surface water irrigation water intake, is the groundwater irrigation water intake, W sf is the available surface water volume, and △t is the time step;

[0082] Confluence improvement part: Adopt the improved river confluence algorithm and the groundwater lateral flow algorithm to describe the surface water and groundwater intake processes of agricultural irrigation respectively. The specific improvement is as follows:

[0083] ① Add the surface water irrigation water intake as a source - sink term to the surface water module to realize the description of the surface water intake process in the surface water module:

[0084]

[0085] where is the surface water irrigation volume per unit area, A flow is the cross - sectional area of the water flow, H is the elevation of the free water surface of the river and lake, and Q is the flow rate of the grid cell;

[0086] ② Add the groundwater irrigation water intake as a source - sink term to the groundwater module to realize the description of the groundwater intake process in the groundwater module:

[0087]

[0088] where T is the unit conductivity; μ is the unit specific yield; H g is the elevation of the unconfined groundwater level;

[0089] A construction and verification unit constructs a land surface - hydrology - irrigation model for the research basin based on the above - improved modules and algorithms, and verifies the irrigation module according to the measured irrigation volume.

[0090] A co - variation process simulation unit, based on the measured data and simulation requirements of the research area, inputs the data and parameter values required by the model, and then runs the model to simulate the co - variation process of land surface processes, hydrological processes, and the intensity of agricultural irrigation activities within the regional scope under the background of research on climate change.

[0091] A control unit is communicatively connected to the irrigation water demand calculation unit, the coupling unit, the irrigation water intake calculation unit, the confluence improvement unit, the construction and verification unit, and the co - variation process simulation unit to control their operations.

[0092] Preferably, the simulation device for the co - variation of land surface hydrological processes and the intensity of agricultural irrigation activities under the background of climate change provided by the present invention further includes: a warning unit communicatively connected to the control unit to estimate the intensity of agricultural irrigation activities and give drought warnings according to the simulation results.

[0093] Preferably, the simulation device for the co - variation of land surface hydrological processes and the intensity of agricultural irrigation activities under the background of climate change provided by the present invention further includes: an input and display unit communicatively connected to the control unit for allowing users to input operation instructions and performing corresponding displays.

[0094] Preferably, the simulation device for the co - variation of land surface hydrological processes and the intensity of agricultural irrigation activities under the background of climate change provided by the present invention further includes: a soil moisture dynamic change simulation unit communicatively connected to the control unit. The multi - layer soil module in the land surface model uses the following equation to describe the vertical dynamic change of soil moisture:

[0095]

[0096] In the formula, θ is the soil water content, z is the soil depth, D(θ) is the soil water diffusivity, K(θ) is the soil hydraulic conductivity, and q nat is the natural water flux of the surface soil;

[0097] The actual irrigation volume of the grid cell is determined according to the irrigation water intake as:

[0098]

[0099] In the formula, is the actual irrigation volume, and β is the leakage rate of the irrigation water pipeline network;

[0100] The determined actual irrigation volume is added as a source - sink term to the multi - layer soil module, and the specific expression is:

[0101]

[0102] In the formula, is the irrigation water volume.

[0103] Functions and Effects of the Invention

[0104] The beneficial effects of the present invention are as follows: The present invention provides a simulation method and device for the coordinated changes of land surface hydrological processes and agricultural irrigation activity intensity under the background of climate change. It not only considers the impacts and interactions of agricultural irrigation activities on land surface processes and hydrological processes under the background of climate change, but also considers the impacts of land surface environment changes (such as the cooling effect of irrigation) and hydrological element changes (such as the available water volume of rivers and lakes) on irrigation water intake. It can be used to simulate the coordinated change process of land surface processes, hydrological processes and agricultural irrigation activity intensity under the background of climate change, so as to scientifically and reasonably estimate the intensity of agricultural irrigation activities and issue drought warnings. Brief Description of the Drawings

[0105] Figure 1 is a flowchart of the simulation method for the coordinated changes of land surface hydrological processes and agricultural irrigation activity intensity under the background of climate change according to the present invention;

[0106] Figure 2 is a coupling method diagram of the land surface - hydrology - irrigation model according to the present invention;

[0107] Figure 3 is a model structure diagram of the land surface - hydrology - irrigation model according to the present invention;

[0108] Figure 4 is a simulated area map of the Yangtze River Basin according to an embodiment of the present invention;

[0109] Figure 5 is a distribution map of hydrological characteristic parameters (river depth) of the Yangtze River Basin according to an embodiment of the present invention;

[0110] Figure 6 is a time series diagram of measured and simulated daily average flow at Yichang Station (a) and Hankou Station (b) from 1980 to 1990 according to an embodiment of the present invention;

[0111] Figure 7 is a map showing the growth period and planting area proportion of crops in the research area according to an embodiment of the present invention. Among them, (a) are perennial plants, (b) are vegetables growing from April to August, (c) are vegetables from April to October, (d) are rice from November to March of the following year, (e) are rice from May to September, (f) are rice from June to October, (g) are seasonal crops from January to May, (h) are seasonal crops from May to September, and (i) are seasonal crops from October to April of the following year;

[0112] Figure 8 This is a comparison graph of the simulated daily average flow and the measured flow in the non-irrigation scenario and the irrigation scenario at Yichang Station (a) and Hankou Station (b) from 1999 to 2003 involved in the embodiments of the present invention. Specific Embodiments

[0113] The following will describe in detail the specific implementation schemes of the simulation method and device for the coordinated changes of land surface hydrology and agricultural irrigation under the background of climate change according to the present invention with reference to the accompanying drawings.

[0114] The simulation method for the coordinated changes of land surface hydrological processes and the intensity of agricultural irrigation activities under the background of climate change provided by this embodiment includes the following steps:

[0115] Step 1, develop an irrigation module. Develop an irrigation module based on the selected land surface - hydrological model NoahMP - HMS. Among them, the method of the global crop water use model GCWM is adopted, and the irrigation water requirement is calculated by combining meteorological conditions (such as precipitation, temperature, radiation, potential evapotranspiration, etc.), plant - available soil moisture (estimated from the soil moisture simulated by the land surface model), crop water requirement parameters for growth (such as crop coefficient K C ) etc., and the irrigation water volume is determined according to the effective irrigation rate.

[0116] Estimate the irrigation water requirement of crops by the method of the global crop water use model (the calculation method is shown in Formulas 1 - 3), and calculate the irrigation water volume according to the effective irrigation rate (the calculation method is shown in Formula 4);

[0117] IWR C =PET C - AET C (1)

[0118] In the formula, IWR C is the irrigation water requirement of crops [mm / day]; PET C is the potential evapotranspiration of crops [mm / day], representing the evapotranspiration of healthy crops under sufficient irrigation conditions, and its value depends on climate conditions, crop types, crop growth conditions, etc., and is calculated by the crop coefficient method (as shown in Formula 2); AET C is the actual crop evapotranspiration [mm / day], and the crop is stressed by water and growth conditions in the changing environment. The calculation formula of AET C is shown in Formula 3.

[0119] PET C =k C ·ET0 (2)

[0120] In the formula, K Cis a dimensionless crop coefficient, characterizing the water requirement rules of different types of crops at different growth stages; ET0 represents the reference evapotranspiration [mm / day], calculated according to the FAO Penman-Monteith method.

[0121] AET C = k s ·PET C (3)

[0122]

[0123] p = p std + 0.04(5 - PET C ) (5)

[0124] In the formula, K s is the crop water stress coefficient [-]; S max is the total available soil water [mm]; p std is the standard water consumption rate of the crop. Its value represents the water consumption rate of the crop when the evapotranspiration capacity is 5 mm / day; p represents the water consumption rate of the crop under specific meteorological conditions. Its expression shows that when the evaporation capacity is very strong, the crop growth may be water stressed even under high soil water content; S is the soil water available for plants [mm], generally calculated using a simple soil water balance formula:

[0125]

[0126] In the formula, P t is the rainfall within this period [mm], E t is the evapotranspiration within this period [mm], is the surface runoff within this period [mm], I t is the leakage within this period [mm], S t and S t-1 are the water requirements in the soil layer within this period and the previous period [mm].

[0127] The mosaic method is used to calculate the crop irrigation water requirement at the grid scale. The specific calculation method is as follows:

[0128]

[0129] In the formula, IWR is the water requirement of the crop in the unit grid [mm / day]; A is the grid cell area [m 2 ; A k is the area of the kth crop in the grid cell [m 2 .

[0130] In practical applications, due to the influence of irrigation facilities, the irrigation water demand often cannot be fully met. Therefore, the effective irrigation rate is used to describe the irrigation water volume:

[0131] W irr = α·IWR (8)

[0132] In the formula, IWR is the irrigation water demand in the grid cell [mm / day]; W irr is the irrigation water volume [mm / day]; α is the effective irrigation rate, and its value can generally be determined according to previous research or statistical data.

[0133] Step 2, model coupling. Embed the irrigation module into the land surface-hydrological model NoahMP-HMS to form the land surface-hydrological-irrigation model NoahMP-HMS-IRR (for the detailed method, see Step II in the invention content).

[0134] Develop the irrigation module based on the existing land surface-hydrological process model and establish the land surface-hydrological-irrigation process model. The specific steps are as follows: ① Transfer the soil moisture simulated by the land surface model to the irrigation module, and calculate the irrigation water volume of the grid cell through the irrigation module; ② Calculate the surface water supply volume according to the river and lake water levels in the surface water module, so as to determine the surface water and groundwater irrigation water intake; ③ Describe the surface water and groundwater intake processes in the surface water and groundwater modules, and realize the description of the agricultural irrigation water use process in the land surface model.

[0135] Step 3, improvement of the irrigation module. Calculate the irrigation water volume according to the improved method, and combine the available surface water volumes such as rivers, lakes, etc. simulated by the hydrological model to determine the surface water irrigation water intake and the groundwater irrigation water intake.

[0136] ① Since the land surface model uses a multi-layer soil model to simulate the dynamic changes of the surface soil moisture (generally 0 - 2m), therefore, the soil moisture available for plants in the irrigation module is no longer estimated by the simple soil moisture balance method, but calculated according to the soil moisture in the crop root zone simulated in the land surface model. The specific calculation formula is as follows:

[0137] S = ∑θ k ·Δz k (9)

[0138] In the formula, θ k is the soil moisture of different soil layers in the root zone [m 3 / m 3 (simulated by the land surface model); △z k is the thickness of different soil layers in the root zone [m]; k is the number of layers corresponding to the root zone in the multi-layer soil model.

[0139] ②Since the hydrological model simulates the water levels in rivers and lakes within grid cells, the surface water irrigation volume in the irrigation module is restricted by the available surface water supply. The specific improvements are as follows:

[0140] W sf = f·(Z water -Z bed )·Δx·Δy (10)

[0141] In the formula, W sf is the available surface water volume [m 3 , f is the proportion of the water surface area within the grid unit, Z water is the water surface level [m], Z bed is the river bottom elevation [m], and △x and △y are the grid unit precisions [m].

[0142] Calculate the surface water irrigation withdrawal volume based on the available surface water volume, and further determine the groundwater irrigation withdrawal volume.

[0143]

[0144] In the formula, is the surface water irrigation withdrawal volume [m / s], is the groundwater irrigation withdrawal volume [m / s], and △t is the time step [s].

[0145] Step 4: Improvement of the river channel flow routing calculation and the groundwater lateral flow algorithm. Add the surface water irrigation withdrawal volume and the groundwater irrigation withdrawal volume as source-sink terms to the surface water and groundwater modules respectively to complete the improvement of the river channel flow routing calculation and the groundwater lateral flow algorithm, and describe the surface water and groundwater water intake processes.

[0146] ① Add the surface water irrigation withdrawal volume as a source-sink term to the mathematical and physical equations of the surface water module (see Formulas 12 - 13) to realize the description of the surface water intake process in the surface water module. The specific expression is:

[0147]

[0148]

[0149] In the formula, H is the elevation of the free surface of rivers and lakes [m], A flow is the cross-sectional area of the water flow [m 2 , Q is the flow rate of the grid cell [m 3 / s], w is the width of the water flow [m]; d is the depth of the water flow [m]; n is the roughness coefficient [s / m 1 / 3 ; m is a dimensionless constant; R is the hydraulic radius [m]; J is the water surface slope [m / m].

[0150] ② Add the groundwater irrigation withdrawal volume The mathematical and physical equations added to the groundwater module as source-sink terms are used to describe the groundwater extraction process in the groundwater module. The specific expression is as follows:

[0151]

[0152] In the formula, T is the unit conductivity [m 2 / s], μ is the unit specific yield [m 3 / m– 3 , and H g is the elevation of the unconfined groundwater level [m].

[0153] Step 5: Improvement of the soil moisture dynamic change algorithm. According to the surface water and groundwater irrigation water extraction amounts determined in Step 3, they are added to the land surface model as effective precipitation amounts and to the multi-layer soil module as source-sink terms to complete the improvement of the soil moisture dynamic change algorithm, describe the agricultural irrigation water process in the land surface process, and further affect the water cycle through the soil moisture movement module, bare soil evaporation module, vegetation transpiration module, etc.

[0154] The multi-layer soil module in the land surface model uses the Richards equation to describe the dynamic change of vertical soil moisture. The specific expression is as follows:

[0155]

[0156] In the formula, θ is the soil water content [m 3 / m 3 , z is the soil depth [m], D(θ) is the soil water diffusivity [m 2 / s], K(θ) is the soil hydraulic conductivity [m / s], and q nat is the natural water flux of the surface soil [m / s].

[0157] The irrigation water amount, as an additional water source, will further affect the vertical movement process of soil moisture and its subsequent land surface processes (such as evaporation, transpiration, etc.). The improvement of the soil moisture dynamic change algorithm in the present invention is as follows:

[0158] The actual irrigation water amount of the grid cell is determined according to the irrigation water extraction amount as:

[0159]

[0160] In the formula, is the actual irrigation amount [m / s], and β is the loss rate of the irrigation water pipe network (this value is determined according to the regional statistical data).

[0161] The determined actual irrigation amount is added to the mathematical and physical equation of the multi-layer soil module as a source-sink term. The specific expression is as follows:

[0162]

[0163] In the formula, is the irrigation water volume [m / s].

[0164] Step 6: Model construction and verification.

[0165] (1) In this embodiment, taking the Yangtze River Basin as the research object, geographical data such as elevation, land use type, vegetation cover, and soil texture within the research area are collected. According to the classical hydraulic geometry model, the channel width and depth within the Yangtze River Basin are given (as shown in Figure 5 ). Taking the groundwater level simulated by the global hydrological model as the initial condition and the measured meteorological data as the forced driving of the model, a land surface - hydrological model of the Yangtze River Basin is constructed. The simulation area map of the land surface - hydrological model of the Yangtze River Basin is shown in Figure 4 , with a spatial accuracy of 20 km and a time accuracy of 30 minutes.

[0166] (2) According to the existing research results, the value ranges of hydrological parameters such as roughness and riverbed hydraulic conductivity of each river section in the Yangtze River Basin are determined, and the parameter values are further determined by the parameter calibration method; the measured daily average flow rates from 1980 to 1986 and from 1987 to 1990 at Yichang Station and Hankou Station are respectively used for parameter calibration and model verification. The results are shown in detail in Figure 6 and Table 1. As can be seen from Figure 6 and Table 1, the NSE of the simulated flow at Yichang Station exceeds 0.85, and the relative error between the simulated and measured flows is less than 4%; the NSE of the simulated flow at Hankou Station exceeds 0.7, and the relative error is less than 1%. It can be seen from this that the constructed land surface - hydrological model can well simulate the hydrological process of the Yangtze River Basin under natural conditions.

[0167] Table 1 Evaluation results of simulated daily average flow under natural conditions at Yichang Station and Hankou Station

[0168]

[0169] Note: NSE is the Nash efficiency coefficient (the calculation formula is shown in Formula 18), and the value range of NSE is (-∞, 1]. The closer it is to 1, the better the simulation effect; PB is the relative error (the calculation formula is shown in Formula 19), and the value range of PB is (-∞, +∞]. The closer it is to 0, the better the simulation effect.

[0170]

[0171]

[0172] Among them, T is the total length of the time series, is the measured flow time series [m 3 / s]; For simulating the flow rate time series [m 3 / s]; For the average value of the measured flow rate time series [m 3 / s]; For the average value of the simulated flow rate time series [m 3 / s];

[0173] (3) In this embodiment, the crop types, planting areas, and growth cycles (monthly scale) in the Yangtze River Basin are extracted from the global high-precision crop dataset MIRCA2000. The 26 crop types in the dataset are classified into four major categories of crops: perennial crops, rice, vegetables, and seasonal crops. Figure 7 The planting areas and growth periods of the four major categories of crops within the simulated area are shown as follows.

[0174] According to existing research, the crop growth and water requirement parameters corresponding to different types of crops are given (such as the crop coefficient K C ). According to statistical data, the effective irrigation rate α of facility agriculture in the Yangtze River Basin is determined to be 0.75, and a land surface - hydrological - irrigation model for the Yangtze River Basin is constructed.

[0175] (4) The constructed land surface - hydrological - irrigation model is used to simulate the agricultural irrigation activities in the Yangtze River Basin. The irrigation model is verified based on the measured irrigation amounts and the simulated irrigation water withdrawal amounts from 1999 to 2003 (the results are shown in Table 2). As can be seen from Table 2, the errors of the simulated annual irrigation amounts relative to the measured irrigation amounts from 1999 to 2003 are within an acceptable range. The five - year average relative error value is 14.8% (the error range is less than ±20%), indicating that the model can better estimate the irrigation water volume in the Yangtze River Basin.

[0176] Table 2 Comparison of measured and simulated irrigation water withdrawal amounts in the Yangtze River Basin from 1999 to 2003

[0177]

[0178] Step 7: Use the verified model to simulate the co - variation process of the intensity of agricultural irrigation activities and the land surface and hydrological processes, and verify its effectiveness in improving the simulation accuracy of the land surface process and hydrological process.

[0179] (1) The process of agricultural irrigation water use will change the water cycle process within the basin, which will further affect irrigation activities. Among the irrigation water volume in the Yangtze River Basin, approximately 9% of the irrigation water returns to the river channels and lakes through surface runoff and groundwater runoff (see Table 3), and most of it is consumed by crop transpiration and bare soil evaporation (the irrigation water volume consumed by evapotranspiration accounts for approximately 90% of the irrigation water volume, see Table 3). It can be seen that in this embodiment, the agricultural irrigation activities in the Yangtze River Basin interact and influence each other with the land surface process and hydrological process within the basin scope.

[0180] Table 3 Irrigation volume, consumption volume, return flow volume in the Yangtze River Basin from 1999 to 2003 and their proportions in the irrigation volume

[0181]

[0182] (2) In this embodiment, by comparing the evapotranspiration amounts in the Yangtze River Basin simulated under irrigation and non-irrigation scenarios from 1999 to 2003, the results are shown in Table 4. It can be seen from Table 4 that compared with the non-irrigation scenario, the evapotranspiration amount in the Yangtze River Basin increases under the consideration of irrigation, and the relative error between its average evapotranspiration amount and the evaporation products decreases from -9.8% to -2.7% (see Table 4). Thus, it can be known that describing agricultural irrigation activities in the model can better estimate the evapotranspiration amount (land surface process).

[0183] Table 4 Comparison of evapotranspiration amounts in the Yangtze River Basin under irrigation and non-irrigation scenarios from 1999 to 2003

[0184]

[0185] Note: The evaporation products include three commonly used evaporation products, namely GLEAM, MTE, and PML.

[0186] (3) In this embodiment, by comparing the simulated cross-sectional river channel flows under irrigation and non-irrigation scenarios from 1999 to 2003, the results are shown in Figure 8 and Table 5. It can be seen from Figure 8 that since the water resources volume in the Yangtze River Basin is abundant and the irrigation volume accounts for a relatively small proportion in the runoff, therefore, the difference in the simulated cross-sectional flows between the irrigation and non-irrigation scenarios is not significant, and both can better reproduce the hydrological process in the Yangtze River Basin.

[0187] In this embodiment, the agricultural irrigation water intake in the Yangtze River Basin mainly comes from surface water, which will lead to a decrease in the river channel water volume. It can be seen from Table 5 that affected by agricultural irrigation activities, the average annual flow at Yichang Station decreases from 14918 m 3 / s (under the irrigation scenario) to 14073 m 3 / s (under the non-irrigation scenario), and the average annual flow at Hankou Station decreases from 25764 m 3 / s to 24480 m 3 / s.

[0188] It can be seen from Table 5 that the relative error between the simulated flow and the measured flow at Yichang Station decreases from 8.9% (non-irrigation scenario) to 2.7% (irrigation scenario), and the NSE increases from 0.84 to 0.87; the relative error of the simulated flow at Hankou Station decreases from 10.9% to 5.3%, and the NSE increases from 0.58 to 0.62. The results show that considering the agricultural irrigation water intake activities helps to better describe the hydrological process of the basin.

[0189] Table 5 Evaluation Results of Simulated Daily Average Flows under Irrigation and Non-Irrigation Scenarios at Yichang and Hankou Stations from 1999 to 2003

[0190]

[0191]

[0192] Note: NSE is the Nash efficiency coefficient, and the value range of NSE is (-∞, 1]. The closer it is to 1, the better the simulation effect; PB is the relative error, and the value range of PB is (-∞, +∞]. The closer it is to 0, the better the simulation effect.

[0193] Furthermore, this embodiment also provides a device capable of automatically implementing the above method. The device includes an irrigation water demand calculation unit, a coupling unit, an irrigation water intake calculation unit, a confluence improvement unit, a construction verification unit, a co-variation process simulation unit, an early warning unit, an input display unit, and a control unit.

[0194] The irrigation water demand calculation unit estimates the crop irrigation water demand at the grid scale using the method of the global crop water use model and calculates the irrigation water volume according to the effective irrigation rate.

[0195] The coupling unit develops an irrigation module based on the existing land surface - hydrological process model to establish a land surface - hydrological - irrigation process model. The specific steps are as follows: ① Transmit the soil moisture simulated by the land surface model to the irrigation module, and calculate the irrigation water volume of the grid cell through the irrigation module; ② Calculate the surface water supply volume according to the river and lake water levels in the surface water module, so as to determine the surface water and groundwater irrigation water intakes; ③ Describe the surface water and groundwater water intake processes in the surface water and groundwater modules, and realize the description of the agricultural irrigation water use process in the land surface model;

[0196] The irrigation water intake calculation unit calculates the surface water irrigation water intake according to the available surface water volume and further determines the groundwater irrigation water intake.

[0197] The confluence improvement unit uses the improved river confluence algorithm and the groundwater lateral flow algorithm to describe the water intake process of agricultural irrigation.

[0198] The construction verification unit constructs a land surface - hydrological - irrigation model for the research basin based on the above - improved modules and algorithms, and verifies the irrigation module according to the measured irrigation volume.

[0199] The co - variation process simulation unit, based on the measured data and simulation requirements of the research area, inputs the data and parameter values required by the model, and then runs the model to simulate the co - variation process of the land surface process, hydrological process, and agricultural irrigation activity intensity within the regional scope under the background of research climate change.

[0200] The early warning unit is communicatively connected to the control unit, and estimates the intensity of agricultural irrigation activities and issues drought early warnings according to the simulation results.

[0201] The soil moisture dynamic change simulation unit enables the multi-layer soil module in the land surface model to use the following equations to describe the dynamic change of vertical soil moisture:

[0202]

[0203] where θ is the soil water content, z is the soil depth, D(θ) is the soil water diffusivity, K(θ) is the soil hydraulic conductivity, and q nat is the natural water flux of the surface soil;

[0204] The actual irrigation water volume of the grid cell is determined according to the irrigation water intake as:

[0205]

[0206] where is the actual irrigation volume, and β is the leakage rate of the irrigation water pipeline network;

[0207] The determined actual irrigation volume is added to the multi-layer soil module as a source-sink term, and the specific expression is:

[0208]

[0209] where is the irrigation water volume.

[0210] The input display unit is communicatively connected to the irrigation water demand calculation unit, the coupling unit, the irrigation water intake calculation unit, the runoff improvement unit, the construction verification unit, the co-variation process simulation unit, and the soil moisture dynamic change simulation unit, and is used to enable the user to input operation instructions and perform corresponding displays.

[0211] The control unit is communicatively connected to the irrigation water demand calculation unit, the coupling unit, the irrigation water intake calculation unit, the runoff improvement unit, the construction verification unit, the co-variation process simulation unit, the soil moisture dynamic change simulation unit, and the input display unit, and controls their operations.

[0212] The above embodiments are merely illustrative examples of the technical solutions of the present invention. The simulation method and device for the co-variation of land surface hydrology and agricultural irrigation under the background of climate change involved in the present invention are not limited to the content described in the above embodiments, but are subject to the scope defined by the claims. Any modification, supplement, or equivalent replacement made by those skilled in the art in the field of the present invention based on this embodiment is within the scope protected by the claims of the present invention.

Claims

1. A simulation method for the co-variation of land surface hydrology and agricultural irrigation under the background of climate change, characterized in that, It includes the following steps: Step Ⅰ. Develop the irrigation module: Estimate the crop irrigation water requirement at the grid scale using the method of the global crop water use model, and calculate the irrigation water volume W according to the effective irrigation rate irr : W irr = α · IWR, where IWR is the water requirement of crops in the grid cell; α is the effective irrigation rate; Step Ⅱ. Coupling of the irrigation module with the land surface - hydrological model: Based on the existing land surface - hydrological process model, develop the irrigation module and establish the land surface - hydrological - irrigation process model. The specific steps are as follows: ① Transfer the soil moisture simulated by the land surface model to the irrigation module, and calculate the irrigation water volume of the grid cell through the irrigation module; ② Calculate the surface water supply volume according to the river and lake water levels in the surface water module, so as to determine the surface water and groundwater irrigation water intake; ③ Describe the surface water and groundwater intake processes in the surface water and groundwater modules, and realize the description of the agricultural irrigation water use process in the land surface model; Step Ⅲ. Improvement of the irrigation module: Calculate the surface water irrigation water intake according to the available surface water volume, and further determine the groundwater irrigation water intake; In the formula, is the surface water irrigation water intake, is the groundwater irrigation water intake, and W sf is the available surface water volume, and △t is the time step; Step Ⅳ. Improvement of the river channel flow routing calculation and groundwater lateral flow algorithm: ① Incorporate the surface water irrigation water intake as a source-sink term into the surface water module to describe the surface water intake process in the surface water module: Where A flow is the cross-sectional area of the water flow, H is the elevation of the free water surface of the river or lake, and Q is the flow rate of the grid cell; ② Incorporate the groundwater irrigation water intake as a source-sink term into the groundwater module to describe the groundwater extraction process in the groundwater module: where T is the unit hydraulic conductivity; μ is the unit specific yield; H g is the elevation of the water table in the unconfined aquifer; Step Ⅵ. Construction and verification of the model: Based on the above improved modules and algorithms, construct the land surface - hydrological - irrigation model of the research basin, and verify the irrigation module according to the measured irrigation volume; Step Ⅶ. Simulation of the co - variation process: Based on the measured data and simulation requirements of the research area, input the data and parameter values required by the model, and then run the model to simulate the co - variation process of the land surface process, hydrological process and agricultural irrigation activity intensity within the regional scope under the background of research climate change.

2. The simulation method for the co - variation of land surface hydrology and agricultural irrigation under the background of climate change according to claim 1, characterized in that: Among them, In step Ⅲ: ① For the soil moisture that can be utilized by plants in the irrigation module, calculate it according to the soil moisture in the crop root zone simulated in the land surface model. The specific calculation formula is as follows: S = ∑θ k ·Δz k , where θ k is the soil moisture of different soil layers in the root zone; △z k is the thickness of different soil layers in the root zone; k is the number of layers corresponding to the root zone in the multi-layer soil model; ② Calculate the surface water consumption using the following formula: W sf = f·(Z water - Z bed )·Δx·Δy, Where W sf is the available surface water volume, f is the proportion of the water surface area in the grid unit, Z water is the water surface level, Z bed is the river bottom elevation, and △x and △y are the grid unit precisions.

3. The simulation method for the co-variation of land surface hydrology and agricultural irrigation under the background of climate change according to claim 1, wherein, It also includes: Step Ⅴ. Improvement of the soil moisture dynamic change algorithm: The multi - layer soil module in the land surface model uses the following equation to describe the vertical dynamic change of soil moisture: where θ is the soil water content, z is the soil depth, D(θ) is the soil water diffusivity, K(θ) is the soil hydraulic conductivity, and q nat is the natural water flux of the surface soil; Determine the actual irrigation water volume of the grid cell according to the irrigation water intake as: Wherein, is the actual irrigation volume, and β is the leakage rate of the irrigation water conveyance pipeline network; The determined actual irrigation amount is added as a source-sink term to the multi-layer soil module, and the specific expression is: In the formula, is the irrigation water volume.

4. The simulation method for the co-variation of land surface hydrology and agricultural irrigation under the background of climate change according to claim 1, It is characterized in that: Among them, in step Ⅵ, first construct the land surface - hydrological model, verify the land surface module and the hydrological model, and then construct the land surface - hydrological - irrigation module and verify the irrigation module. The specific steps are as follows: (1) Construction and verification of the land surface - hydrological model ① Take the basin as the object, collect the geographical data within the research basin, give the hydrological characteristic parameters within the basin scope, and use the meteorological data as the external forcing to drive the model to construct the land surface - hydrological model of the basin; ② Determine the value range of the hydrological parameters within the research basin according to the existing research results, further determine the values of the hydrological parameters using the parameter calibration method, and verify the model using the measured natural flow; (2) Construction and verification of the land surface - hydrological - irrigation model ① Use the global crop dataset to describe the types, planting areas and growth cycles of the crops planted in the research area, give the corresponding parameters for different types of crops according to the existing research, give the effective irrigation rate and the leakage rate of the irrigation pipeline network in the research area according to the statistical data, and construct the irrigation module of the research area; ② Use the constructed land surface - hydrology - irrigation model to simulate the agricultural irrigation activities in the study area, and verify the irrigation model based on the comparison between the measured irrigation volume and the estimated irrigation water withdrawal volume.

5. The simulation method for the co - variation of land surface hydrology and agricultural irrigation under the background of climate change according to claim 1, characterized in that: Among them, In step VII, by comparing the hydrological elements in the irrigation and non - irrigation scenarios, clarify the impact of agricultural irrigation water withdrawal activities on the water cycle process at the basin scale; Verify the effectiveness of describing agricultural irrigation activities in improving the simulation accuracy of land surface processes and hydrological processes by comparing the simulation accuracy of land surface processes and hydrological processes in the irrigation and non - irrigation scenarios.

6. A simulation device for the co-variation of land surface hydrological processes and the intensity of agricultural irrigation activities under the background of climate change, characterized in that, It includes: Irrigation water requirement calculation unit, which estimates the crop irrigation water requirement at the grid scale by using the method of the global crop water use model, and calculates the irrigation water volume W according to the effective irrigation rate irr : W irr = α · IWR, In the formula, IWR is the water requirement of crops in the grid cell; α is the effective irrigation rate; Coupling part: On the basis of the existing land surface - hydrological process model, develop an irrigation module to establish a land surface - hydrology - irrigation process model. The specific steps are as follows: ① Transfer the soil moisture simulated by the land surface model to the irrigation module, and calculate the irrigation water volume of the grid cell through the irrigation module; ② Calculate the surface water supply volume according to the water levels of rivers and lakes in the surface water module, so as to determine the surface water and groundwater irrigation water withdrawal volumes; ③ Describe the surface water and groundwater water intake processes in the surface water and groundwater modules, and realize the description of the agricultural irrigation water use process in the land surface model; Irrigation water withdrawal calculation part: Calculate the surface water irrigation water withdrawal volume according to the available surface water volume, and further determine the groundwater irrigation water withdrawal volume; In the formula, is the surface water irrigation water withdrawal volume, is the groundwater irrigation water withdrawal volume, and W irr is the irrigation water volume, and W sf is the available surface water volume, and △t is the time step; Confluence improvement part: Use the improved river confluence algorithm and groundwater lateral flow algorithm to describe the water intake process of agricultural irrigation: ① Incorporate the surface water irrigation withdrawal volume as a source-sink term into the surface water module to describe the surface water withdrawal process in the surface water module: where A flow is the cross-sectional area of the water flow, H is the elevation of the free water surface of the river or lake, and Q is the flow rate of the grid cell; ② Incorporate the groundwater irrigation withdrawal volume as a source-sink term into the groundwater module to describe the groundwater withdrawal process in the groundwater module: where T is the unit conductivity; μ is the unit specific yield; H g is the elevation of the water table in the unconfined aquifer; Construction and verification part: Based on the above - improved modules and algorithms, construct a land surface - hydrology - irrigation model for the study basin, and verify the irrigation module according to the measured irrigation volume; Co - variation process simulation part: Based on the measured data and simulation requirements of the study area, input the data and parameter values required by the model, and then run the model to simulate the co - variation process of land surface processes, hydrological processes and the intensity of agricultural irrigation activities within the regional scope under the background of climate change research; Control part: Communicates and is connected to the irrigation water requirement calculation part, the coupling part, the irrigation water withdrawal calculation part, the confluence improvement part, the construction and verification part, and the co - variation process simulation part, and controls their operations.

7. The simulation device for the co-variation of land surface hydrology and agricultural irrigation under the background of climate change according to claim 6, wherein It also includes: Early warning part: Communicates and is connected to the control part, and estimates the intensity of agricultural irrigation activities and issues drought early warnings according to the simulation results.

8. The simulation device for the co-variation of land surface hydrology and agricultural irrigation under the background of climate change according to claim 6, characterized in that, It also includes: Input and display part: Communicates and is connected to the control part, and is used to allow users to input operation instructions and perform corresponding displays.

9. The simulation device for the co-variation of land surface hydrology and agricultural irrigation under the background of climate change according to claim 6, wherein, It also includes: Soil moisture dynamic change simulation part: Communicates and is connected to the control part. The multi - layer soil module in the land surface model uses the following equation to describe the vertical dynamic change of soil moisture: where θ is the soil water content, z is the soil depth, D(θ) is the soil water diffusivity, K(θ) is the soil hydraulic conductivity, and q nat is the natural water flux of the surface soil; The actual irrigation water volume of the grid cell is determined according to the irrigation water withdrawal volume as: In the formula, is the actual irrigation volume, and β is the leakage rate of the irrigation water conveyance pipeline network; The determined actual irrigation amount is added as a source-sink term to the multi-layer soil module, and the specific expression is: Wherein, is the irrigation water volume.

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