Simulation method for soil water-heat balance-erosion control and fertilizer production synergistic process under protective tillage

Abstract

The application discloses a simulation method for a soil water-heat balance-erosion control and fertilizer cultivation collaborative process under protective tillage, and particularly relates to the technical field of agricultural soil process simulation. Meteorological, soil, topographic, covering and nutrient data of a protective tillage plot are acquired, and water, heat, erosion and fertility state variables are established. A water-heat deviation index is generated based on a water-heat matching relationship, a fertility response lag index is generated based on a historical water-heat change and a fertility process response relationship, and a collaborative error correction factor is formed. The factor is used to dynamically adjust the transmission weight between models, correct soil temperature, erosion amount, nutrient loss amount and fertility evolution result, and output water-heat balance, erosion control and fertilizer cultivation and collaborative effect evaluation result. The application can reduce the accumulation and amplification of water-heat error, erosion error and fertility error in multi-year continuous simulation, and improve the accuracy of water-heat balance judgment, erosion control effect evaluation and fertility trend prediction under protective tillage conditions.

Description

Technical Field

[0001] This invention relates to the field of agricultural soil process simulation technology, specifically to a simulation method for the synergistic process of soil water and heat balance-erosion control and fertilization under conservation tillage. Background Technology

[0002] Conservation tillage, by reducing soil disturbance, retaining crop residues, and improving surface cover, can enhance soil water retention, regulate soil temperature, reduce slope runoff erosion, and promote soil organic matter accumulation to a certain extent. Therefore, it is widely used in simulating farmland soil and water conservation and soil fertility improvement processes. Existing techniques typically establish separate models for soil moisture, heat, erosion, and fertility processes, coupling them in a fixed order within the same time step, and then using the output of the previous model as the input for continuous iteration. However, this type of method lacks the identification and correction of error propagation relationships between models and the lag characteristics of fertility process response. When there are deviations in the calculation of soil moisture content, evaporation, or temperature, these deviations are amplified step by step as they are passed from the moisture model, heat model, erosion model, and fertility model. This is especially problematic in conservation tillage scenarios involving continuous simulations over many years, extreme rainfall, changes in straw cover, or significant fluctuations in hydrothermal conditions. This can easily lead to distortions in the results of soil temperature, erosion, nutrient loss, and fertility evolution, thus affecting the accurate evaluation of soil water and heat balance, erosion control, fertilization, and their synergistic effects.

[0003] Therefore, there is an urgent need for a collaborative process simulation method that can dynamically identify hydrothermal deviations and fertility response lags, and adjust the weights transferred between models accordingly. Summary of the Invention

[0004] The purpose of this invention is to provide a simulation method for the synergistic process of soil water and heat balance, erosion control and fertilization under conservation tillage, so as to overcome the shortcomings of the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for simulating the synergistic process of soil water and heat balance-erosion control and fertilization under conservation tillage, comprising: Acquire initial data on meteorology, soil, topography, cover, and nutrients for conservation tillage plots, establish state variables for moisture, heat, erosion, and fertility, and calculate soil moisture content and soil temperature based on state variables within the current time step to obtain initial hydrothermal simulation results. A hydrothermal deviation index is generated based on the matching relationship between changes in soil moisture content and changes in soil temperature, and a fertility response lag index is generated based on the response relationship between historical hydrothermal changes and organic matter decomposition, nitrogen mineralization and nutrient release. A synergistic error correction factor is formed based on the hydrothermal deviation index and the fertility response hysteresis index; The collaborative error correction factor is used to dynamically adjust the result transfer weights between the moisture model, heat model, erosion model and fertility model, and the soil temperature, erosion amount, nutrient loss and fertility evolution results are corrected according to the adjusted transfer weights. The corrected soil moisture content, soil temperature, surface cover, soil nutrient content, and soil condition are used as inputs for the next time step. The simulation is repeated until the end of the preset period, and the results of the evaluation of water and heat balance, erosion control and fertilization and synergistic effects under conservation tillage are output.

[0006] Preferably, obtaining the initial hydrothermal simulation results within the current time step includes the following steps: Initial data on meteorology, soil, topography, cover, and nutrients were assigned time, spatial, and soil layer numbers, respectively. Based on differences in soil profiles, surface cover, and vertical nutrient distribution, conservation tillage plots were divided into several hydrothermal fertility response units. Within each hydrothermal fertility response unit, state variables for moisture, heat, erosion, and fertility were established. Tillage memory identifiers were set based on surface cover and soil disturbance conditions. Joint pre-calculation of moisture and heat transfer processes was performed using state variables with tillage memory identifiers to obtain initial hydrothermal simulation results associated with the hydrothermal fertility response units.

[0007] Preferably, the division of the hydrothermal fertility response unit and the setting of the tillage memory identifier include the following steps: Soil profile zones are formed based on soil layer thickness, soil texture, and bulk density; cover zones are formed within soil profile zones based on surface cover, crop residue cover type, and soil disturbance state; and hydrothermal fertility response units are formed based on the distribution order of organic matter, nitrogen, phosphorus, and potassium in each soil layer. The source of cover, type of disturbance, and duration of impact are written into the tillage memory identifier and stored synchronously with soil moisture content, soil temperature, land cover, and soil nutrient content.

[0008] Preferably, generating the hydrothermal deviation index includes the following steps: The direction and magnitude of soil moisture content change, the direction and magnitude of soil temperature change between the current time step and the previous time step are extracted from the initial hydrothermal simulation results to form a hydrothermal change sequence. The hydrothermal response benchmark relationship is determined based on historical records with the same tillage memory identifier. The hydrothermal response benchmark relationship includes the benchmark direction relationship, the benchmark amplitude relationship, and the benchmark response sequence relationship. By matching the hydrothermal change sequence with the hydrothermal response benchmark, the non-coordinated changes between soil moisture content and soil temperature are identified. Based on the tillage memory identifier, the non-coordinated change portion is divided into the allowable lag portion and the deviation portion, and the hydrothermal deviation index is generated according to the duration of the deviation portion, the number of affected soil layers, and the degree of deviation.

[0009] Preferably, generating the fertility response lag index includes the following steps: Extract hydrothermal disturbance fragments that occur synchronously with changes in soil moisture content and soil temperature from the historical state variables of the hydrothermal fertility response unit; By associating hydrothermal disturbance fragments with corresponding tillage memory identifiers, a historical hydrothermal disturbance sequence with protective tillage impact attributes is formed; Along the subsequent time steps of the historical hydrothermal disturbance sequence, the continuous changes in organic matter decomposition, nitrogen mineralization, and nutrient release were extracted and matched with the hydrothermal disturbance fragments in time. Based on the tillage memory identifier, the permissible delay caused by the persistence effect of land cover and soil disturbance is removed, the effective lag is retained, and the fertility response lag index is generated accordingly.

[0010] Preferably, the synergistic error correction factor is formed based on the hydrothermal deviation index and the fertility response hysteresis index, including the following steps: Pair the hydrothermal deviation index and the fertilizer response lag index of the same hydrothermal fertilizer response unit in the current time step to form a joint error state; Based on the joint error state, the error dominance type is identified, which includes hydrothermal deviation dominance, fertility lag dominance, and joint dominance of hydrothermal deviation and fertility lag. The direction of the weakening transmission from the water model to the heat model, from the heat model to the fertility model, and from the water model to the fertility model is determined based on the error dominance type. The direction of the weakening is correlated with the initial hydrothermal simulation results at the current time step to form a cooperative error correction factor.

[0011] Preferably, the result transfer weights among the moisture model, heat model, erosion model, and fertility model are dynamically adjusted using a collaborative error correction factor, including the following steps: The transfer attenuation coefficients from the water model to the heat model, from the heat model to the fertility model, and from the water model to the fertility model are read from the cooperative error correction factor. Each propagation attenuation coefficient is applied to the original propagation weights between the corresponding models to obtain the corrected propagation weights for the current time step. When the dominant error type is hydrothermal bias, the transfer from the moisture model to the heat model and from the moisture model to the fertility model is weakened first. When the error-dominant type is fertility lag-dominant, the transmission from the heat model to the fertility model and from the water model to the fertility model is weakened first. When the error-dominant type is co-dominant, the transmission in all three directions is weakened simultaneously.

[0012] Preferably, the soil temperature, erosion, nutrient loss, and fertility evolution results are corrected based on the adjusted transfer weights, including the following steps: The soil moisture content of the previous time step is used to replace the initial soil moisture content of the current time step for heat calculation, so as to obtain a temperature baseline value that does not introduce the influence of the current moisture update. Based on the corrected transfer weight from the moisture model to the heat model, the temperature contribution of the initial soil moisture content to heat transfer is weakened or maintained, resulting in the corrected soil temperature. Based on the weighting of the correction from the water model to the fertility model, the runoff, erosion, and nutrient loss caused by erosion and runoff are simultaneously corrected. Based on the correction transfer weights from the thermal model to the fertility model and the fertility response lag index, lag balance treatment is applied to organic matter decomposition, nitrogen mineralization, and nutrient release to obtain the fertility evolution results at the current time step.

[0013] Preferably, the corrected soil moisture content, soil temperature, land cover, soil nutrient content, and soil condition are used as inputs for the next time step, including the following steps: Write the corrected soil moisture content, soil temperature, surface cover, soil nutrient content, and soil layer status into the current time step status record; determine the water replenishment amount based on the corrected runoff, and allocate the water replenishment amount to the corresponding soil layer according to the effective pore capacity of each soil layer, and update the soil moisture content input for the next time step.

[0014] Preferably, the cyclic simulation continues until the preset period ends and the synergistic effect evaluation results are output, including the following steps: the thickness of the topsoil layer is deducted first based on the corrected erosion amount, and the soil state after deduction is used to update the water storage space, heat transfer path and nutrient distribution location of the next time step; after the preset period is reached, the water and heat balance, erosion control and fertilization and synergistic effect evaluation results under conservation tillage are output according to the water and heat balance evaluation results, erosion control evaluation results and fertilization evaluation results.

[0015] The technical effects and advantages provided by the present invention in the above technical solution are as follows: The core technical approach of this invention, which distinguishes it from existing technologies, lies in its method of not transmitting moisture, heat, erosion, and fertility models unidirectionally in a fixed order, but rather introducing a hydrothermal deviation index and a fertility response lag index at each time step, and forming a coordinated error correction factor accordingly. This approach can identify the uncoordinated transmission between changes in soil moisture content and soil temperature, as well as the lag phenomenon in the effects of hydrothermal changes on organic matter decomposition, nitrogen mineralization, and nutrient release, thus determining the source of error at its origin and preventing the direct inheritance of biases from previous models into subsequent models.

[0016] This invention can dynamically adjust the result transfer weights between the moisture model, heat model, erosion model, and fertility model according to the dominant error type, and synchronously correct the results of soil temperature, erosion, nutrient loss, and fertility evolution. Compared with existing fixed coupling methods, this invention can reduce the cumulative amplification of hydrothermal errors, erosion errors, and fertility errors in multi-year continuous simulations, improve the accuracy of water and heat balance judgment, erosion control effect assessment, and fertility improvement trend prediction under conservation tillage conditions, and make the evaluation of synergistic effects more consistent with the actual farmland evolution process. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0018] Figure 1 This is a flowchart illustrating a simulation method for the synergistic process of soil water and heat balance, erosion control, and fertilization under conservation tillage, according to the present invention.

[0019] Figure 2 This is a flowchart of the method for adjusting the result transfer weights between the moisture model, heat model, erosion model and fertility model according to the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Example 1, please refer to Figure 1 As shown in this embodiment, a simulation method for the synergistic process of soil water-heat balance-erosion control and fertilization under conservation tillage includes: Initial data on meteorology, soil, topography, cover, and nutrients of conservation tillage plots are obtained. State variables of moisture, heat, erosion, and fertility are established. Soil moisture content and soil temperature are calculated based on the state variables within the current time step to obtain the initial hydrothermal simulation results.

[0022] This implementation method is used to generate initial hydrothermal simulation results that reflect the impact of conservation tillage in the initial stage of the simulation. First, it receives initial meteorological, soil, topographic, cover, and nutrient data for conservation tillage plots, and adds time number, spatial number, and soil layer number to each type of data; wherein, meteorological data is stored according to time number, soil, cover, and nutrient initial data are stored according to spatial number and soil layer number, and topographic data is stored according to spatial number, so that data from different sources can correspond at the same plot spatial location and the same soil layer depth.

[0023] Conservation tillage plots were divided into units based on differences in soil profile, surface cover, and vertical nutrient distribution. The division process began with soil profile zoning, using soil layer thickness, texture, and bulk density as the first criterion. Within each soil profile zoning, surface cover, crop residue type, and soil disturbance status were used as the second criterion to create cover zoning. Finally, within each cover zoning, the distribution order of organic matter, nitrogen, phosphorus, and potassium in each soil layer was used as the third criterion to create hydrothermal fertility response units. Adjacent sampling locations were grouped into the same hydrothermal fertility response unit if all three criteria were met; otherwise, they were grouped into different units. After the division, initial meteorological, soil, topographic, cover, and nutrient data were written into the datasets of the corresponding hydrothermal fertility response units.

[0024] Within each hydrothermal fertility response unit, state variables for moisture, heat, erosion, and fertility were established. Moisture state variables included soil water content, infiltration, evaporation, and inter-soil water exchange at each soil layer; heat state variables included soil temperature at each soil layer, surface heat absorption, and inter-soil heat exchange; erosion state variables included land cover, soil disturbance, and soil thickness; and fertility state variables included organic matter content, nitrogen content, phosphorus content, and potassium content. Based on land cover and soil disturbance at each hydrothermal fertility response unit, tillage memory markers were set for soil moisture content, soil temperature, land cover, and soil nutrient content.

[0025] Tillage memory identifiers are used to record the persistent effects of conservation tillage on state variables. The identifiers include the source of the cover, the type of disturbance, and the duration of the effect. They are stored synchronously with the corresponding state variables so that the state variables retain the conservation tillage effect attributes in subsequent time steps.

[0026] Joint pre-calculations for the current time step are performed using state variables with conservation tillage impact attributes. For the water transfer process, rainfall and irrigation volume at the current time step are used as water inputs. Surface runoff, evaporation, crop transpiration, and deep seepage are deducted sequentially, and the remaining water is allocated to the corresponding soil layers to obtain the initial soil moisture content for each layer. For the heat transfer process, air temperature, surface cover, initial soil moisture content, and soil temperature from the previous time step are used as inputs. The surface heat received is first determined, and then, based on the influence of soil moisture content on the soil layer's heat transfer capacity, surface heat is transferred along the soil layer direction to obtain the initial soil temperature for each layer.

[0027] The initial soil moisture content and initial soil temperature results for each hydrothermal fertility response unit are associated and encapsulated. During association and encapsulation, the initial soil moisture content, initial soil temperature, spatial number, soil layer number, and tillage memory identifier within the same hydrothermal fertility response unit are written into the same data record, and an initial hydrothermal simulation result is formed according to the time number. This initial hydrothermal simulation result serves as the input for subsequent hydrothermal deviation index calculations, enabling subsequent calculations to simultaneously utilize soil moisture changes, soil temperature changes, and conservation tillage impact attributes.

[0028] A hydrothermal deviation index is generated based on the matching relationship between changes in soil moisture content and changes in soil temperature, and a fertility response lag index is generated based on the response relationship between historical hydrothermal changes and organic matter decomposition, nitrogen mineralization and nutrient release.

[0029] In this embodiment, after obtaining the initial hydrothermal simulation results, for the hydrothermal fertility response unit numbered i and the soil layer numbered k, the soil moisture content Wcurik at the current time step t, the soil moisture content Wpreik at the previous time step, the soil temperature Tcurik at the current time step t, and the soil temperature Tpreik at the previous time step are read. The change range of soil moisture content is denoted as DWik, and the calculation expression is: The range of soil temperature variation is denoted as DTik, and its calculation expression is: .

[0030] The direction of change in soil moisture content is denoted as DWir. When, DWir=1; when hour, ;when When DWir=0. The direction of soil temperature change is denoted as DTir. When, DTir=1; when At 1 o'clock, ;when At this time, DTir=0. The hydrothermal change sequence for the current time step is formed by DWik, DTik, DWir, and DTir.

[0031] The hydrothermal response baseline relationship is determined by historical records with the same tillage memory identifier within the same hydrothermal fertility response unit. The 30 consecutive valid time steps preceding the current time step are selected as the baseline window; if there are fewer than 30 valid time steps, all valid time steps preceding the current time step are used. The baseline directional relationship is denoted as Bik, and its calculation process is as follows: within the baseline window, the product of the direction of soil moisture change and the direction of soil temperature change is calculated for each time step, resulting in a sequence of directional products. The median sign of this sequence is then taken as Bik. The baseline amplitude relationship is denoted as Rik, and its calculation expression is: Rik = median(DTih ÷ (DWih + 0.001)), where h is the time step number within the baseline window, median represents the median, and 0.001 is used to avoid a denominator of 0.

[0032] The baseline response sequence is denoted as Lik. During calculation, the soil moisture content variation sequence within the baseline window is denoted as X, and the soil temperature variation sequence is denoted as Y. Misalignment comparisons are performed at 0, 1, 2, and 3 time steps, respectively. The correlation value at any misalignment step number 'a' is denoted as Corra, and its calculation expression is: , where Xavg is the average value of the X sequences involved in the alignment, and Yavg is the average value of the Y sequences involved in the alignment. Let Lik be the value of 'a' corresponding to the maximum |Corra|.

[0033] The hydrothermal change sequence is matched with the hydrothermal response baseline. The directional consistency value is denoted as Adik, and its calculation expression is: when DWir × DTir = Bik, Adik = 0; when DWir × DTir ≠ Bik, Adik = 1. The amplitude consistency value is denoted as Amik, and its calculation expression is: The value is 0 when Amik < 0 and 1 when Amik > 1. The response chronology value is denoted as Alik. During calculation, the absolute correlation between the soil moisture content variation series and the soil temperature variation series is first calculated within the current time step and the three time steps prior, at 0 to 3 misalignment steps. The misalignment step number where the absolute correlation value is maximum is denoted as Lpik. Then, the expression is used... Calculation. The non-coordinated change value is denoted as Cik, and the calculation expression is: Cik = 0.4 × Adik + 0.4 × Amik + 0.2 × Alik.

[0034] The land cover persistence value Pi and soil disturbance persistence value Qi are retrieved from the tillage memory identifier. Both Pi and Qi range from 0 to 1. The allowable lag value is denoted as Hik, and its calculation expression is: Hik = 0.6 × Pi + 0.4 × Qi. The deviation component is denoted as Eik, and its calculation expression is: When Eik < 0, take 0; when Eik > 1, take 1.

[0035] The average Eik of all K soil layers within the same hydrothermal fertility response unit is used to obtain the mean deviation Eiavg for the current time step. The calculation expression is: Eiavg = sum(Eik) ÷ K. The duration of continuous deviation is denoted as Nit, and the calculation process is as follows: trace back the number of consecutive time steps from the current time step where Eiavg > 0. If the number of traced steps exceeds 5, it is counted as 5. The hydrothermal deviation index is denoted as Iwhit, and the calculation expression is: Iwhit = Eiavg × (1 + Nit ÷ 5); when Iwhit > 1, it is taken as 1. Iwhit is stored together with the corresponding initial hydrothermal simulation results, spatial number, soil layer number, and time number.

[0036] When calculating the fertility response hysteresis index, the historical state variables of the corresponding hydrothermal fertility response unit are read. Continuous records in the historical time step that simultaneously satisfy DWik > 0.005 cm³ / cm³ and DTik > 0.1℃ are taken as hydrothermal disturbance segments. Each hydrothermal disturbance segment is associated with a tillage memory identifier within the same time period, forming a historical hydrothermal disturbance sequence with conservation tillage impact attributes.

[0037] Following the historical hydrothermal disturbance sequence, the continuous changes in organic matter decomposition (O), nitrogen mineralization (N), and nutrient release (M) were extracted from 0 to 7 time steps. The comprehensive disturbance sequence of the hydrothermal disturbance segment is denoted as Z, and its calculation expression is: Z = 0.5 × DWik + 0.5 × DTik. The misalignment correlations of Z with O, N, and M were calculated for 0 to 7 time steps. The misalignment step number is denoted as Lo when the absolute value of the correlation with O is the largest; Ln when the absolute value of the correlation with N is the largest; and Lm when the absolute value of the correlation with M is the largest.

[0038] The allowed delay steps are denoted as G, and the calculation expression is: G = round(1 + 3 × Pi + 2 × Qi), where round represents rounding to the nearest integer; when G < 1, it is rounded to 1, and when G > 6, it is rounded to 6. The effective lag steps are denoted as Elo, Eln, and Elm, and the calculation expressions are: ; if any calculation result is less than 0, it is taken as 0. The number of fertility processes involved in the lag is denoted as U, where U is the number of Elo, Eln, and Elm values ​​greater than 0.

[0039] Response consistency is denoted as V. First, calculate the average effective lag step count, Lavg, using the following expression: Next, calculate the standard deviation of the effective lag steps, Lstd, using the following expression: Then V is calculated, and its expression is: The value is 0 when V < 0 and 1 when V > 1. The fertility response hysteresis exponent is denoted as Iflit, and its calculation expression is: Iflit = (Lavg ÷ 7) × (U ÷ 3) × V; it is 1 when Iflit > 1. Iflit and Iwhit are both associated with the current time step, providing input for the formation of the subsequent cooperative error correction factor.

[0040] A synergistic error correction factor is formed based on the hydrothermal deviation index and the fertility response hysteresis index.

[0041] In this embodiment, within the current time step t, the hydrothermal deviation index Iwhit and the fertilizer response lag index Iflit corresponding to the same hydrothermal fertilizer response unit are read. The values ​​of Iwhit and Iflit range from 0 to 1, where 0 indicates no corresponding error was identified, and 1 indicates that the corresponding error has reached the maximum normalization level within that time step. Iwhit and Iflit are paired according to the same spatial number, time number, and hydrothermal fertilizer response unit number to form a joint error state Jit. Jit includes the hydrothermal deviation component Iwhit, the fertilizer lag component Iflit, the error difference Dit, and the joint intensity Sit; wherein, the calculation expression for Dit is: The expression for Sit is: Sit = (Iflit + Iflit) ÷ 2.

[0042] The error-dominant type is determined based on Dit. The error-dominant determination difference is set to 0.15, which is 15% of the length of the Iwhit and Iflit value range (1), to avoid frequent type switching due to small fluctuations when the two are close. When Dit ≥ 0.15, the current time step is recorded as hydrothermal deviation-dominant; when... When, the current time step is denoted as fertility lag-dominated; when At this time step, the error type is recorded as jointly dominated by hydrothermal deviation and fertility lag. After the determination is completed, the error type is recorded as Typeit and written together with Jit into the current time step record.

[0043] Based on Typeit, the transmission weakening directions from the moisture model to the heat model, from the heat model to the fertility model, and from the moisture model to the fertility model are determined. The transmission weakening coefficient from the moisture model to the heat model is denoted as Fwt, from the heat model to the fertility model as Ftf, and from the moisture model to the fertility model as Fwf. The values ​​of the three transmission weakening coefficients range from 0.20 to 1, where 1 indicates that the original transmission weight is maintained, and 0.20 indicates that 20% of the original transmission weight is retained. A lower limit of 0.20 is used to avoid completely severing the physical connection between any process, ensuring that the basic transmission relationship between moisture, heat, and fertility is maintained in continuous simulations.

[0044] When Typeit is dominated by hydrothermal bias, it preferentially weakens the transfer from the moisture model to the heat model and from the moisture model to the fertility model. The calculation expression is as follows: If any calculated result is less than 0.20, it is counted as 0.20.

[0045] When Typeit is dominated by fertility lag, the transfer from the heat model to the fertility model and from the water model to the fertility model is preferentially weakened. The calculation expression is as follows: If any calculated result is less than 0.20, it is counted as 0.20.

[0046] When Typeit is dominated by both hydrothermal deviation and fertility lag, it weakens simultaneously in all three transmission directions, and the calculation expression is: If any calculated result is less than 0.20, it is counted as 0.20.

[0047] After calculating Fwt, Ftf, and Fwf, a transfer correction relationship Rit is formed, which includes Typeit, Fwt, Ftf, and Fwf. Rit is associated with the initial hydrothermal simulation results of the current time step using the same spatial number, soil layer number, and time number, forming a cooperative error correction factor Cit. Cit serves as the input for subsequent result transfer weight adjustments, multiplying the original transfer weights from the moisture model to the heat model by Fwt, from the heat model to the fertility model by Ftf, and from the moisture model to the fertility model by Fwf. The transfer processes of runoff, erosion, and nutrient loss involved in the erosion model are adjusted synchronously with the transfer weakening coefficient Fwf from the moisture model to the fertility model, thereby preventing hydrothermal bias and fertility lag from continuing to expand in a fixed order within the current time step.

[0048] Please see Figure 2 As shown, the collaborative error correction factor is used to dynamically adjust the result transfer weights between the moisture model, heat model, erosion model and fertility model, and the soil temperature, erosion amount, nutrient loss and fertility evolution results are corrected according to the adjusted transfer weights.

[0049] In this embodiment, at the current time step t, the transfer correction relationship Rit in the cooperative error correction factor Cit is read. Rit includes Fwt, Ftf, and Fwf. The original transfer weights Pwt0 from the moisture model to the heat model, Ptf0 from the heat model to the fertility model, and Pwf0 from the moisture model to the fertility model are read; if not preset, Pwt0, Ptf0, and Pwf0 are all set to 1. The corrected transfer weights within the current time step are denoted as Pwt, Ptf, and Pwf, respectively, and the calculation expressions are: Pwt = Pwt0 × Fwt, Ptf = Ptf0 × Ftf, Pwf = Pwf0 × Fwf. Any corrected transfer weight below 0.20 is counted as 0.20, and above 1 is counted as 1, so that the transfer relationship between processes is maintained.

[0050] When correcting for soil temperature, the initial soil moisture content (Winitik), the previous time step soil moisture content (Wpreik), the initial soil temperature (Tinitik), and the previous time step soil temperature (Tpreik) of soil layer k within the hydrothermal fertility response unit (i) are read. The same heat calculation process is then re-executed using Wpreik instead of Winitik to obtain the temperature baseline value (Tbaseik) without incorporating the current moisture update. The temperature contribution from moisture in heat transfer is denoted as Twaterik, and its calculation expression is: The corrected soil temperature is denoted as Tcorik, and its calculation expression is: Tcorik = Tbaseik + Pwt × Twaterik.

[0051] When Pwt=1, the current moisture change maintains its original effect on heat transfer; when Pwt is less than 1, the effect of the current moisture change on soil temperature is included in the heat calculation according to the proportion of Pwt, thereby reducing the direct transfer of moisture deviation to soil temperature results.

[0052] When correcting for erosion, the initial runoff result Rinitit, the initial erosion result Sinitit, the land cover value Coverit, and the topographic influence value Topoit are read from the current time step. The land cover and topographic influence values ​​remain unchanged from their original calculations; only the runoff participation intensity caused by water transfer is corrected. The corrected runoff is denoted as Rcorit, and its calculation expression is: Rcorit = Rinitit × Pwf. The corrected erosion is denoted as Scorit, and its calculation expression is: Scorit = Sinitit × (Rcorit ÷ (Rinitit + 0.001)), where 0.001 is used to avoid a denominator of 0. Through this process, the erosion is adjusted synchronously with the correction transfer weight from the water model to the fertility model, preventing runoff bias from being included in the erosion calculation without correction.

[0053] When correcting for nutrient losses, the initial losses of organic matter, nitrogen, phosphorus, and potassium are read and denoted as LossOinit, LossNinit, LossPinit, and LossKinit, respectively. The corrected organic matter loss LossOcor, nitrogen loss LossNcor, phosphorus loss LossPcor, and potassium loss LossKcor are calculated using the following expressions: LossOcor = LossOinit × Pwf × (Scorit ÷ (Sinitit + 0.001)), LossNcor = LossNinit × Pwf × (Scorit ÷ (Sinitit + 0.001)), LossPcor = LossPinit × Pwf × (Scorit ÷ (Sinitit + 0.001)), LossKcor = LossKinit × Pwf × (Scorit ÷ (Sinitit + 0.001)).

[0054] When Sinitit is 0, 0.001 is added to the denominator before being included in the calculation, and the calculation result is then treated as 0 to avoid nutrient loss under non-erosion conditions.

[0055] When correcting for fertility evolution, the initial amounts of organic matter decomposition (Odecinit), nitrogen mineralization (Nmininit), and nutrient release (Mrelinit) are read. The temperature correction ratio (Rt) is determined by comparing the corrected soil temperature (Tcorik) with the initial soil temperature (Tinitik), calculated as: Rt = (Tcorik + 273.15) ÷ (Tinitik + 273.15). The fertility lag balance ratio is denoted as Rdelay, calculated as: When Rdelay is less than 0, it is taken as 0; when it is greater than 1, it is taken as 1. The organic matter decomposition amount Odecit, nitrogen mineralization amount Nminit, and nutrient release amount Mrelit that enter the fertility calculation at the current time step are calculated using the following expressions: Odecit = Odecinit × Rt × Rdelay, Nminit = Nmininit × Rt × Rdelay, Mrelit = Mrelinit × Rt × Rdelay. The portions not entering the current time step are denoted as Oholdit, Nholdit, and Mholdit, respectively, and their calculation expressions are: , , And it will be postponed to the next time step for fertility calculation.

[0056] The fertility evolution results at the current time step include corrected organic matter content, nitrogen content, phosphorus content, and potassium content. Taking organic matter content as an example, the corrected organic matter content (Osoilcor) is calculated as follows: Calculate; nitrogen, phosphorus and potassium contents are updated according to the same income and expenditure method, respectively, with corresponding input, release, absorption and corrected loss.

[0057] Therefore, the collaborative error correction factor first changes the transfer weights between models, and then sequentially corrects the soil temperature, erosion, nutrient loss and fertility evolution results, so that the deviation of the previous process is no longer completely transferred to the next process in a fixed order.

[0058] The corrected soil moisture content, soil temperature, surface cover, soil nutrient content, and soil condition are used as inputs for the next time step. The simulation is repeated until the end of the preset period, and the results of the evaluation of water and heat balance, erosion control and fertilization and synergistic effects under conservation tillage are output.

[0059] In this embodiment, after correcting the soil temperature, erosion, nutrient loss, and fertility evolution results at the current time step t, the corrected state variables are uniformly written into the current time step state record and used as input data for the next time step t+1. The current time step state record includes at least the corrected soil moisture content Wcorik, the corrected soil temperature Tcorik, the corrected land cover Covercorit, the corrected soil nutrient content Nutcorik, and the corrected soil layer state Layercorik, where i represents the hydrothermal fertility response unit number and k represents the soil layer number.

[0060] The corrected soil moisture content Wcorik is retained from the moisture calculation result of the current time step and stored together with the correction record of the cooperative error correction factor Cit. If there is water replenishment due to runoff correction in the current time step, the water volume that did not participate in the runoff output is recalculated into the soil moisture content of the corresponding soil layer. The water replenishment amount is denoted as Wbackit, and the calculation expression is: Wbackit = Rinitit − Rcorit. When Wbackit is less than 0, it is taken as 0. Wbackit is allocated to the corresponding soil layer according to the proportion of the current effective pore capacity of each soil layer to obtain the replenishment amount Wbackik for each soil layer, and the soil moisture content is updated according to the expression Wcorik = Winitik + Wbackik; when there is no water replenishment, Wcorik is taken as Winitik.

[0061] The corrected soil temperature Tcorik uses the calculation result of the current time step after weighting and is used as the initial temperature for the heat calculation of the next time step. To ensure smooth transfer of soil temperature between consecutive time steps, Tcorik and the soil temperature Tpreik of the previous time step are written into the temperature history record and used to calculate the magnitude of soil temperature change, the direction of soil temperature change, and the hydrothermal deviation index in the next time step.

[0062] The revised land cover (Covercorit) is updated based on crop cover, stubble cover, and erosion transport at the current time step. The initial land cover result is denoted as Coverinit, the increase in cover is denoted as Coveradd, the reduction due to stubble decomposition is denoted as Coverdec, and the reduction due to erosion transport is denoted as Coverero. The expression for calculating Covercorit is: .

[0063] Covercorit is set to 0 when it is less than 0, and to 1 when it is greater than 1. Covercorit is written into the tillage memory identifier so that the next time step can continue to identify the continuation of the effects of conservation tillage cover on hydrothermal and fertility responses.

[0064] The corrected soil nutrient content Nutcorik is updated separately for organic matter, nitrogen, phosphorus, and potassium. Taking any nutrient X as an example, the soil nutrient content of the previous time step is denoted as Xpreik, the input amount of the current time step is denoted as Xinputik, the crop uptake amount is denoted as Xuptakeik, the corrected nutrient loss amount is denoted as Xlosscorik, and the conversion and release amount is denoted as Xrelcorik. The calculation expression for the corrected nutrient content Xcorik of the current time step is: .

[0065] When Xcorik is less than 0, it is set to 0. After the same budget update is performed on organic matter, nitrogen, phosphorus and potassium, Nutcorik is formed and used as the initial nutrient state for the fertility model in the next time step.

[0066] The corrected soil state Layercorik is updated based on the corrected erosion value Scorit at the current time step. The initial soil thickness is denoted as Layerinitik, and the soil reduction thickness calculated at the current time step is denoted as Dlayerik. The expression for calculating Layercorik is: .

[0067] Layercorik determines the amount of reduction based on the distribution of Scorit in each soil layer, prioritizing the reduction from the topsoil layer. When the thickness of the topsoil layer is reduced to 0, the remaining reduction continues to act on the next soil layer. Layercorik writes the status record to the next time step to update the water storage space, heat transfer paths, and nutrient distribution locations.

[0068] After updating Wcorik, Tcorik, Covercorit, Nutcorik, and Layercorik, these are used as the initial state variables for the next time step t+1. The process of data reading, initial hydrothermal simulation, hydrothermal deviation index calculation, fertility response lag index calculation, synergistic error correction factor formation, weight adjustment, and result correction is repeated until the preset period is reached. The preset period can be set as a crop growing season, annual, or multi-year continuous simulation period. The cycle ends when the simulation date reaches the preset end date or the cumulative number of time steps reaches the preset number.

[0069] After the cycle is completed, the simulation results are summarized and output according to the hydrothermal fertility response units and time steps. The hydrothermal balance evaluation results include changes in soil water storage, soil moisture stability, soil temperature variation range, and soil temperature stability; the erosion control evaluation results include runoff, erosion amount, changes in soil layer thickness, and erosion reduction effect; the fertility improvement evaluation results include changes in organic matter content, changes in nitrogen, phosphorus, and potassium content, nutrient loss, and fertility retention effect.

[0070] The synergistic effect evaluation results are jointly determined by the hydrothermal balance evaluation results, corrosion control evaluation results, and fertilization evaluation results. The hydrothermal balance score is denoted as Scorewh, the corrosion control score as Scoreer, and the fertilization score as Scorefer, all ranging from 0 to 1. The comprehensive synergistic evaluation result Scoreall is calculated as: Scoreall = 0.35 × Scorewh + 0.30 × Scoreer + 0.35 × Scorefer.

[0071] Among them, hydrothermal balance and fertilization have a long-lasting impact on the long-term effects of conservation tillage, with a weight of 0.35 each; erosion control has a direct impact on soil retention, with a weight of 0.30. The output includes state variables at each time step, hydrothermal deviation index, fertility response lag index, synergistic error correction factor, corrected model results, and the final Scoall, used to evaluate the simulation effect of soil hydrothermal balance, erosion control, fertilization, and synergistic processes under conservation tillage.

[0072] Example 2: To verify the simulation effect of the method of the present invention on the soil water and heat balance and the synergistic process of erosion control and fertilization under conservation tillage, a sloping farmland conservation tillage experimental plot was selected as the verification object. The experimental plot had a slope of 6°, the soil type was loam, the tillage method was no-till combined with straw mulch, the initial straw coverage was 0.68, the simulation period was one maize growing season, with a total of 120 time steps, each time step being 1 day. The experimental plot was divided into three soil layers according to soil depth: 0-10 cm, 10-20 cm, and 20-40 cm, and further divided into three water, heat, and fertility response units according to differences in soil profile, surface cover, and vertical nutrient distribution. For comparison, Comparative Example 1 is set up. Comparative Example 1 adopts the existing fixed-order coupling method, that is, it calculates in the order of "moisture model, heat model, erosion model, fertility model" and directly uses the output of the previous model as the input of the next model. Example 1 adopts the method of the present invention, generates the hydrothermal deviation index and fertility response lag index in each time step, and forms a collaborative error correction factor to dynamically correct the weight of result transfer between models.

[0073] During the experiment, meteorological data, soil moisture content, soil temperature, runoff, erosion, organic matter content, total nitrogen content, and available phosphorus content were collected. Soil moisture content and soil temperature were recorded daily using field sensors, runoff and erosion were collected after rainfall events, and nutrient content was collected at the start and end of the simulation. After the simulation, the simulation results of Comparative Example 1 and Example 2 were compared with the measured results. Evaluation indicators included the mean absolute error of soil moisture content, the mean absolute error of soil temperature, the relative error of erosion, the relative error of organic matter content, the relative error of total nitrogen content, and the comprehensive synergistic evaluation score.

[0074] Table 1

[0075] Referring to Table 1, during the simulation, when the changes in soil moisture content and soil temperature at a certain time step do not conform to the hydrothermal response benchmark relationship of the corresponding hydrothermal fertility response unit, the method of this invention generates a hydrothermal deviation index; when the organic matter decomposition, nitrogen mineralization, and nutrient release after historical hydrothermal disturbances do not respond within the allowable delay range, the method of this invention generates a fertility response lag index. Then, based on the synergistic error correction factor formed by the two, the transfer weights from the moisture model to the heat model, from the heat model to the fertility model, and from the moisture model to the fertility model are corrected. Taking the calculation on the 47th day after the heavy rainfall on the 46th day as an example, the hydrothermal deviation index of hydrothermal fertility response unit 1 is 0.42, the fertility response lag index is 0.31, and the error difference is 0.11, which belongs to the joint dominance of hydrothermal deviation and fertility lag. The method of this invention simultaneously weakens the three transfer directions, so that the moisture deviation is no longer completely transferred to the heat calculation and fertility calculation.

[0076] Table 2

[0077] As shown in Table 2, in the time step of hydrothermal abrupt change after heavy rainfall, Comparative Example 1, due to the direct use of the moisture model output in the calculation of heat, erosion, and fertility, had an overestimation of soil moisture content, which further led to an underestimation of soil temperature, runoff, and erosion. Example 1, by using a collaborative error correction factor, weakened the transmission of abnormal moisture results to subsequent models, making soil temperature, runoff, erosion, and nitrogen loss closer to the measured values.

[0078] After the simulation period ended, the results of 120 time steps were statistically analyzed. The mean absolute error of soil moisture content was calculated as the average of the absolute values ​​of the differences between the simulated and measured moisture contents for each soil layer at each time step; the mean absolute error of soil temperature was calculated as the average of the absolute values ​​of the differences between the simulated and measured temperatures for each soil layer at each time step; the relative error of erosion was calculated by dividing the absolute value of the difference between the simulated and measured cumulative erosion by the measured value; and the relative errors of organic matter and total nitrogen were calculated by dividing the absolute value of the difference between the simulated and measured nutrient contents at the end of the simulation by the measured value.

[0079] Table 3

[0080] As shown in Table 3, compared with Comparative Example 1, the method of the present invention reduces the average absolute error of soil moisture content from 0.031 cm³ / cm³ to 0.014 cm³ / cm³, the average absolute error of soil temperature from 1.86℃ to 0.74℃, the relative error of cumulative erosion from 24.7% to 8.9%, and the relative error of nitrogen loss from 22.5% to 9.6%.

[0081] Meanwhile, because the method of this invention identifies the lag in fertility response and extends the amount of organic matter decomposition, nitrogen mineralization, and nutrient release that have not entered the current time step to subsequent time steps for calculation, the errors of organic matter and total nitrogen are significantly reduced at the end of the simulation.

[0082] Furthermore, the triggering of collaborative error correction factors at each time step within the simulation period was statistically analyzed. Example 2 identified 37 time steps requiring correction, of which 14 were dominated by hydrothermal deviation, 9 by fertility lag, and 14 by a combination of both. These results indicate that under conservation tillage conditions, errors do not always occur in a single direction but rather dynamically change under the combined effects of rainfall, cover changes, and fertility response delays. The method of this invention determines the transmission weakening direction for different error dominance types, allowing the transmission weights between models to adjust with time steps, thus avoiding the problem in existing fixed-sequence coupling methods where the deviation of the previous process is completely inherited by the next.

[0083] Therefore, the data in this embodiment can prove that the method of the present invention achieves the linkage correction of soil moisture, soil temperature, erosion, nutrient loss and fertility evolution results through continuous calculation of the hydrothermal deviation index, fertility response lag index and synergistic error correction factor. This correction does not simply change the final output result, but changes the result transmission relationship between models in each time step, thereby reducing the error accumulation in multi-year or whole-season simulations and improving the accuracy of hydrothermal balance, erosion control and fertilization and synergistic effect evaluation under conservation tillage.

[0084] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A simulation method for the synergistic process of soil water-heat balance-erosion control and fertilization under conservation tillage, characterized in that, include: Acquire initial data on meteorology, soil, topography, cover, and nutrients for conservation tillage plots, establish state variables for moisture, heat, erosion, and fertility, and calculate soil moisture content and soil temperature based on state variables within the current time step to obtain initial hydrothermal simulation results. A hydrothermal deviation index is generated based on the matching relationship between changes in soil moisture content and changes in soil temperature, and a fertility response lag index is generated based on the response relationship between historical hydrothermal changes and organic matter decomposition, nitrogen mineralization and nutrient release. A synergistic error correction factor is formed based on the hydrothermal deviation index and the fertility response hysteresis index; The collaborative error correction factor is used to dynamically adjust the result transfer weights between the moisture model, heat model, erosion model and fertility model, and the soil temperature, erosion amount, nutrient loss and fertility evolution results are corrected according to the adjusted transfer weights. The corrected soil moisture content, soil temperature, surface cover, soil nutrient content, and soil condition are used as inputs for the next time step. The simulation is repeated until the end of the preset period, and the results of the evaluation of water and heat balance, erosion control and fertilization and synergistic effects under conservation tillage are output.

2. The simulation method for the synergistic process of soil water-heat balance-erosion control and fertilization under conservation tillage as described in claim 1, characterized in that, Obtaining the initial hydrothermal simulation results within the current time step includes the following steps: Initial data on meteorology, soil, topography, cover, and nutrients were assigned time, spatial, and soil layer numbers, respectively. Based on differences in soil profiles, surface cover, and vertical nutrient distribution, conservation tillage plots were divided into several hydrothermal fertility response units. Within each hydrothermal fertility response unit, state variables for moisture, heat, erosion, and fertility were established. Tillage memory identifiers were set based on surface cover and soil disturbance conditions. Joint pre-calculation of moisture and heat transfer processes was performed using state variables with tillage memory identifiers to obtain initial hydrothermal simulation results associated with the hydrothermal fertility response units.

3. The simulation method for the synergistic process of soil water-heat balance-erosion control and fertilization under conservation tillage as described in claim 2, characterized in that, The division of the hydrothermal fertility response units and the setting of tillage memory identifiers include the following steps: Soil profile zones are formed based on soil layer thickness, soil texture, and bulk density; cover zones are formed within soil profile zones based on surface cover, crop residue cover type, and soil disturbance state; and hydrothermal fertility response units are formed based on the distribution order of organic matter, nitrogen, phosphorus, and potassium in each soil layer. The source of cover, type of disturbance, and duration of impact are written into the tillage memory identifier and stored synchronously with soil moisture content, soil temperature, land cover, and soil nutrient content.

4. The simulation method for the synergistic process of soil water-heat balance-erosion control and fertilization under conservation tillage according to claim 1, characterized in that, The process of generating the hydrothermal deviation index includes the following steps: The direction and magnitude of soil moisture content change, the direction and magnitude of soil temperature change between the current time step and the previous time step are extracted from the initial hydrothermal simulation results to form a hydrothermal change sequence. The hydrothermal response benchmark relationship is determined based on historical records with the same tillage memory identifier. The hydrothermal response benchmark relationship includes the benchmark direction relationship, the benchmark amplitude relationship, and the benchmark response sequence relationship. By matching the hydrothermal change sequence with the hydrothermal response benchmark, the non-coordinated changes between soil moisture content and soil temperature are identified. Based on the tillage memory identifier, the non-coordinated change portion is divided into the allowable lag portion and the deviation portion, and the hydrothermal deviation index is generated according to the duration of the deviation portion, the number of affected soil layers, and the degree of deviation.

5. The simulation method for the synergistic process of soil water-heat balance-erosion control and fertilization under conservation tillage according to claim 1, characterized in that, The generation of the fertility response hysteresis index includes the following steps: Extract hydrothermal disturbance fragments that occur synchronously with changes in soil moisture content and soil temperature from the historical state variables of the hydrothermal fertility response unit; By associating hydrothermal disturbance fragments with corresponding tillage memory identifiers, a historical hydrothermal disturbance sequence with protective tillage impact attributes is formed; Along the subsequent time steps of the historical hydrothermal disturbance sequence, the continuous changes in organic matter decomposition, nitrogen mineralization, and nutrient release were extracted and matched with the hydrothermal disturbance fragments in time. Based on the tillage memory identifier, the permissible delay caused by the persistence effect of land cover and soil disturbance is removed, the effective lag is retained, and the fertility response lag index is generated accordingly.

6. The simulation method for the synergistic process of soil water-heat balance-erosion control and fertilization under conservation tillage according to claim 5, characterized in that, A synergistic error correction factor is formed based on the hydrothermal deviation index and the fertility response hysteresis index, including the following steps: Pair the hydrothermal deviation index and the fertilizer response lag index of the same hydrothermal fertilizer response unit in the current time step to form a joint error state; Based on the joint error state, the error dominance type is identified, which includes hydrothermal deviation dominance, fertility lag dominance, and joint dominance of hydrothermal deviation and fertility lag. The direction of the weakening transmission from the water model to the heat model, from the heat model to the fertility model, and from the water model to the fertility model is determined based on the error dominance type. The direction of the weakening is correlated with the initial hydrothermal simulation results at the current time step to form a cooperative error correction factor.

7. The simulation method for the synergistic process of soil water-heat balance-erosion control and fertilization under conservation tillage according to claim 6, characterized in that, The result transfer weights among the moisture model, heat model, erosion model, and fertility model are dynamically adjusted using a collaborative error correction factor, including the following steps: The transfer attenuation coefficients from the water model to the heat model, from the heat model to the fertility model, and from the water model to the fertility model are read from the cooperative error correction factor. Each propagation attenuation coefficient is applied to the original propagation weights between the corresponding models to obtain the corrected propagation weights for the current time step. When the dominant error type is hydrothermal bias, the transfer from the moisture model to the heat model and from the moisture model to the fertility model is weakened first. When the error-dominant type is fertility lag-dominant, the transmission from the heat model to the fertility model and from the water model to the fertility model is weakened first. When the error-dominant type is co-dominant, the transmission in all three directions is weakened simultaneously.

8. The simulation method for the synergistic process of soil water-heat balance-erosion control and fertilization under conservation tillage according to claim 7, characterized in that, The soil temperature, erosion, nutrient loss, and fertility evolution results were corrected based on the adjusted transfer weights, including the following steps: The soil moisture content of the previous time step is used to replace the initial soil moisture content of the current time step for heat calculation, so as to obtain a temperature baseline value that does not introduce the influence of the current moisture update. Based on the corrected transfer weight from the moisture model to the heat model, the temperature contribution of the initial soil moisture content to heat transfer is weakened or maintained, resulting in the corrected soil temperature. Based on the weighting of the correction from the water model to the fertility model, the runoff, erosion, and nutrient loss caused by erosion and runoff are simultaneously corrected. Based on the correction transfer weights from the thermal model to the fertility model and the fertility response lag index, lag balance treatment is applied to organic matter decomposition, nitrogen mineralization, and nutrient release to obtain the fertility evolution results at the current time step.

9. The simulation method for the synergistic process of soil water-heat balance-erosion control and fertilization under conservation tillage according to claim 8, characterized in that, The corrected soil moisture content, soil temperature, land cover, soil nutrient content, and soil condition are used as inputs for the next time step, including the following steps: Write the corrected soil moisture content, soil temperature, surface cover, soil nutrient content, and soil layer status into the current time step status record; determine the water replenishment amount based on the corrected runoff, and allocate the water replenishment amount to the corresponding soil layer according to the effective pore capacity of each soil layer, and update the soil moisture content input for the next time step.

10. The simulation method for the synergistic process of soil water-heat balance-erosion control and fertilization under conservation tillage according to claim 9, characterized in that, The simulation is repeated until the preset period ends and the synergistic effect evaluation results are output, including the following steps: the thickness of the topsoil layer is deducted first based on the corrected erosion amount, and the soil state after deduction is used to update the water storage space, heat transfer path and nutrient distribution location in the next time step; after the preset period is reached, the water and heat balance, erosion control and fertilization and synergistic effect evaluation results under conservation tillage are output according to the water and heat balance evaluation results, erosion control evaluation results and fertilization evaluation results.

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