Dynamic simulation method of the effect of surface straw on soil moisture

Abstract

The present invention provides a dynamic simulation method for the influence of surface straw on soil moisture, by simulating the dynamic process of surface straw decomposition, the simulation results of daily surface straw content are obtained; wherein, the parameters involved in the simulation of the dynamic decomposition process include: the amount of straw after cultivation, the temperature influencing factor, the straw moisture content influencing factor, and the straw carbon-nitrogen ratio influencing factor; according to the simulation results of the surface straw content, the constraint of surface straw on soil moisture is simulated to obtain the simulation results of soil moisture content; wherein, the parameters involved in the simulation of soil moisture constraint include: the interception amount of surface straw, the actual evapotranspiration under the influence of straw, and the runoff under the influence of straw; according to the daily simulation results of surface straw content and the simulation results of soil moisture content, the influence results of surface straw on soil moisture content are obtained. Beneficial effects of the present invention: It has important practical significance for ensuring national food security, ecological environmental protection and sustainable agricultural development.

Description

Technical Field

[0001] The invention belongs to the field of environmental simulation, and in particular relates to a dynamic simulation method for the influence of surface straw on soil moisture. Background Art

[0002] The frequent extreme weather events caused by climate change have affected the stability and high yield of my country's grain production, especially in a large agricultural country like China. Returning straw to the fields, as a common conservation tillage method, has a significant effect on improving soil structure, increasing soil organic matter content, reducing soil erosion and greenhouse gas emissions. By leaving the residues of crops after harvest (such as wheat, corn, rice, etc.) directly in the fields or turning them into the soil, the soil carbon content can be increased, microbial activity can be promoted, and the soil's ability to retain water and fertilizer can be enhanced, which helps to alleviate the adverse effects of climate change.

[0003] However, existing soil moisture dynamic simulation models often ignore the dynamic decomposition of surface crop straw and its impact on soil moisture; this leads to limited accuracy of model predictions and the inability to fully reflect changes in soil moisture under actual farmland conditions; therefore, incorporating straw return and tillage processes into soil moisture dynamic simulations can enable soil moisture dynamic simulations to more accurately reflect the impact of surface straw on soil moisture, provide more scientific decision-making support for agricultural production, and help farmers adapt to climate change and achieve sustainable food production. Summary of the invention

[0004] In view of this, the present invention aims to propose a dynamic simulation method for the influence of surface straw on soil moisture, in the hope of solving at least one of the above-mentioned technical problems.

[0005] To achieve the above object, the technical solution of the present invention is achieved as follows:

[0006] The dynamic simulation method of the effect of surface straw on soil moisture includes:

[0007] The dynamic process of surface straw decomposition was simulated to obtain the simulation results of the daily surface straw content; the parameters involved in the simulation of the dynamic decomposition process included: the amount of straw after tillage, the temperature influencing factor, the straw moisture content influencing factor, and the straw carbon-nitrogen ratio influencing factor;

[0008] According to the simulation results of the surface straw content, the constraint of the surface straw on soil moisture is simulated to obtain the simulation results of soil moisture content; among them, the parameters involved in simulating the soil moisture constraint include: surface straw interception, actual evapotranspiration under the influence of straw, and runoff under the influence of straw;

[0009] According to the daily surface straw content simulation results and soil moisture content simulation results, the effect of surface straw on soil moisture content is obtained.

[0010] Furthermore, the calculation process of the simulation result of the daily surface straw content includes:

[0011] ;

[0012] Among them, R(i) is the amount of straw on the i-th day, F T F(i) is the factor affecting the temperature on the i-th day on the decomposition of straw, Fw(i) is the factor affecting the moisture content of straw on the i-th day on the decomposition of straw, C / N It is the influencing factor of straw carbon-nitrogen ratio on straw decomposition.

[0013] Furthermore, the calculation process of the amount of straw after tillage includes:

[0014] ;

[0015] Among them, R(i) is the amount of straw on the i-th day, Residue is the amount of straw on the surface before tillage, and Ptill is the percentage of straw entering the soil after tillage.

[0016] Furthermore, the calculation process of the calculated temperature influence factor includes:

[0017] According to the temperature range suitable for microbial growth and the temperature threshold of microbial dormancy, a piecewise function of the temperature influencing factor is established:

[0018] ;

[0019] Among them, F T (i) is the factor affecting the temperature on the i-th day on the decomposition of straw, T a (i) is the air temperature on the i-th day.

[0020] Furthermore, the calculation process of the straw moisture content influencing factor includes:

[0021] ;

[0022] Among them, F W (i) is the influencing factor of straw moisture content on straw decomposition on the i-th day, RSW(i) is the straw moisture content on the i-th day, RSAT(i) is the maximum water holding capacity of the straw on the i-th day, and RLL is the minimum moisture content of the straw.

[0023] Furthermore, the calculation process of the straw carbon-nitrogen ratio influencing factor includes:

[0024] ;

[0025] Among them, F C / Nis the influencing factor of straw carbon-nitrogen ratio on straw decomposition, CN is the straw carbon-nitrogen ratio, and the straw carbon-nitrogen ratio of different types of straw is different.

[0026] Furthermore, the calculation process of the soil moisture simulation result includes:

[0027] ;

[0028] Where SW(i) is the soil moisture content on the i-th day, P(i) is the precipitation on the i-th day, RUNOFF R (i) is the runoff affected by straw on the i-th day, ETa R (i) is the actual evapotranspiration affected by straw on the i-th day, C R is the straw interception amount.

[0029] Furthermore, the calculation process of the surface straw interception amount includes:

[0030] ;

[0031] Among them, RSAT(i) is the saturated moisture content of straw on the i-th day, , R(i) is the amount of surface straw on the ith day;

[0032] RSW(i) is the moisture content of straw on the i-th day, , ES(i) is the potential evaporation, RLL is the minimum moisture content of straw;

[0033] PINF(i) is the moisture reaching the straw surface on the i-th day; , P(i) is the precipitation on the i-th day, RUNOFF R (i) is the runoff under the influence of straw on the i-th day.

[0034] Furthermore, the calculation process of the runoff under the influence of the straw includes:

[0035] ;

[0036] Among them, P(i) is the precipitation on the i-th day;

[0037] S(i) is the water retention coefficient on the i-th day, ; CN(i) is the runoff coefficient affected by straw on the i-th day, ;

[0038] Where, CN is the runoff coefficient;

[0039] F C (i) is the soil coverage percentage on day i, , R(i) is the amount of surface straw on the i-th day, and Am is the unit straw coverage area.

[0040] Furthermore, the calculation process of the actual evapotranspiration under the influence of the straw includes:

[0041] ;

[0042] Among them, F C (i) is the soil cover percentage on the i-th day, ETa(i) is the actual evapotranspiration on the i-th day, and ETa R (i) is the actual evapotranspiration affected by straw on the i-th day.

[0043] Compared with the prior art, the dynamic simulation method of the effect of surface straw on soil moisture of the present invention has the following beneficial effects:

[0044] By introducing the dynamic changes of surface straw and its influence on soil moisture in the process of soil moisture dynamic simulation, a more accurate simulation of farmland water cycle is achieved. The soil moisture dynamic simulation of the present invention can not only provide more accurate guidance for farmland moisture management, but also provide strong technical support for agricultural adaptation to climate change, optimization of resource utilization and improvement of food production efficiency, which has important practical significance for ensuring national food security, ecological environmental protection and sustainable agricultural development. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0046] Figure 1 It is a schematic flow chart of a dynamic simulation method of the influence of surface straw on soil moisture according to an embodiment of the present invention;

[0047] Figure 2 This is a schematic diagram of the simulation result of the amount of straw on the ground surface according to an embodiment of the present invention;

[0048] Figure 3 Schematic diagram of soil moisture simulation results before model improvement according to an embodiment of the present invention (including Figure 3 a. Figure 3 b. Figure 3 c. Figure 3 d);

[0049] Figure 3 a is a schematic diagram of the measured value of soil water storage in the range of 0-40 cm in T1 treatment and the simulated value before improvement;

[0050] Figure 3 b is a schematic diagram of the measured value of soil water storage in the range of 0-40 cm in the T3 treatment and the simulated value before improvement;

[0051] Figure 3c is a schematic diagram of the measured values ​​of soil water storage in the range 0-40 cm under NT1 treatment and the simulated values ​​before improvement;

[0052] Figure 3 d is a schematic diagram of the measured values ​​of soil water storage in the range of 0-40 cm in the NT3 treatment and the simulated values ​​before improvement;

[0053] Figure 4 Schematic diagram of soil moisture simulation results after the improved model according to the embodiment of the present invention (including Figure 4 a. Figure 4 b. Figure 4 c. Figure 4 d);

[0054] Figure 4 a is a schematic diagram of the measured value and improved simulated value of soil water storage in 0-40 cm in T1 treatment;

[0055] Figure 4 b is a schematic diagram of the measured value and improved simulated value of soil water storage in 0-40 cm in T3 treatment;

[0056] Figure 4 c is a schematic diagram of the measured value and improved simulated value of soil water storage in 0-40 cm under NT1 treatment;

[0057] Figure 4 d is a schematic diagram of the measured values ​​and improved simulated values ​​of soil water storage in the 0-40 cm range under NT3 treatment. DETAILED DESCRIPTION

[0058] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0059] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0060] like Figure 1 Shown: Dynamic simulation method of the effect of surface straw on soil moisture, including:

[0061] The dynamic process of surface straw decomposition was simulated to obtain the simulation results of the daily surface straw content; the parameters involved in the simulation of the dynamic decomposition process included: the amount of straw after tillage, the temperature influencing factor, the straw moisture content influencing factor, and the straw carbon-nitrogen ratio influencing factor;

[0062] According to the simulation results of the surface straw content, the constraint of the surface straw on soil moisture is simulated to obtain the simulation results of soil moisture content; among them, the parameters involved in simulating the soil moisture constraint include: surface straw interception, actual evapotranspiration under the influence of straw, and runoff under the influence of straw;

[0063] According to the daily surface straw content simulation results and soil moisture content simulation results, the effect of surface straw on soil moisture content is obtained.

[0064] Straw is the main source of organic matter in farmland soil. Straw decomposition is the result of soil microbial life activities. The decomposition rate is mainly affected by straw composition, tillage methods and environmental factors. The straw type and tillage methods are fully considered, and on this basis, various environmental factors affecting each step of the process, such as temperature, moisture and carbon-nitrogen ratio, are taken into account to simulate the decomposition of surface straw. Therefore, the calculation process of the simulation results of daily surface straw content includes:

[0065] ;

[0066] Among them, R(i) is the amount of straw on the i-th day, F T F(i) is the factor affecting the temperature on the i-th day on the decomposition of straw, Fw(i) is the factor affecting the moisture content of straw on the i-th day on the decomposition of straw, C / N It is the influencing factor of straw carbon-nitrogen ratio on straw decomposition.

[0067] The straw remaining on the surface after crop harvest will enter the soil through tillage. Different tillage methods directly affect the amount of surface straw. The straw distribution percentage after each tillage is used to calculate the final amount of surface straw. The percentage of straw incorporation after different tillage methods is obtained. The traditional tillage method is 40% and the no-tillage method is 0. Therefore, the calculation process of the amount of straw after tillage includes:

[0068] ;

[0069] Among them, R(i) is the amount of straw on the i-th day, Residue is the amount of straw on the ground before tillage (unit: kg·hm -2 ), Ptill is the percentage of straw entering the soil after tillage (input parameter, unit: kg·hm -2 ).

[0070] Among the many factors that affect the decomposition of crop straw, temperature and humidity are the most important. Temperature and humidity affect the decomposition rate of crop straw by changing the physiological activity of microorganisms. The most suitable temperature for the growth of soil microorganisms is 25-40℃. When the temperature is below 0℃ or above 60℃, it is generally believed that microorganisms are dormant at this time.

[0071] Soil microorganisms are tested to obtain the temperature range suitable for microbial growth and the temperature threshold for microbial dormancy. A piecewise function of the temperature influence factor is established based on the temperature range and temperature threshold. Therefore, the calculation process of the temperature influence factor includes:

[0072] According to the temperature range suitable for microbial growth and the temperature threshold of microbial dormancy, a piecewise function of the temperature influencing factor is established:

[0073] ;

[0074] Among them, F T (i) is the factor affecting the temperature on the i-th day on the decomposition of straw, T a (i) is the air temperature on the ith day (input value, daily data, unit: °C).

[0075] The effect of humidity on straw decomposition is similar to that of temperature. Under suitable temperature conditions, the decomposition rate of straw increases with the increase of humidity. Therefore, the calculation process of the influencing factor of straw moisture content includes:

[0076] ;

[0077] Among them, F W (i) is the influencing factor of straw moisture content on the i-th day on straw decomposition, RSW(i) is the straw moisture content on the i-th day (mm), RSAT(i) is the maximum water holding capacity of the straw on the i-th day (mm), and RLL is the minimum moisture content of the straw (mm).

[0078] Nitrogen is a key element for the synthesis of microbial cells. The C / N ratio is used to describe the effect of straw with different carbon-nitrogen ratios on its decomposition. The carbon-nitrogen ratio of wheat straw is 100, and that of corn straw is 75. The calculation process of the straw carbon-nitrogen ratio influencing factor includes:

[0079] ;

[0080] Among them, F C / N is the influencing factor of straw carbon-nitrogen ratio on straw decomposition, CN is the straw carbon-nitrogen ratio, and the straw carbon-nitrogen ratio of different types of straw is different.

[0081] The dynamic simulation of soil moisture comprehensively considers precipitation, irrigation, runoff, crop interception and evapotranspiration. The simulation of soil moisture adopts the soil moisture balance formula. Surface straw can change the soil moisture content, which in turn affects plant growth and development. The impact of straw mulching on soil moisture is mainly reflected in straw interception, runoff and soil evaporation. Therefore, the calculation process of soil moisture simulation results includes:

[0082] ;

[0083] Where SW(i) is the soil moisture content on the i-th day, P(i) is the precipitation on the i-th day, RUNOFF R (i) is the runoff affected by straw on the i-th day, ETa R (i) is the actual evapotranspiration affected by straw on the i-th day, C R is the straw interception amount.

[0084] The calculation process of the above-mentioned surface straw interception amount includes:

[0085] ;

[0086] The effect of surface crop straw on soil moisture is calculated by the amount of straw and the moisture content of the straw. The maximum amount of water in the surface straw, RSAT, is proportional to the amount of surface straw, R. The straw can withstand up to 3.8 times its weight in water, from which the saturated moisture content of the straw, RSAT, can be obtained.

[0087] RSAT(i) is the saturated moisture content of straw on day i:

[0088] , R(i) is the amount of surface straw on the ith day;

[0089] RSW(i) is the moisture content of straw on day i:

[0090] , ES(i) is the potential evaporation, RLL is the minimum moisture content of straw;

[0091] PINF(i) is the moisture reaching the straw surface on the i-th day; , P(i) is the precipitation on the i-th day, RUNOFF R (i) is the runoff under the influence of straw on the i-th day.

[0092] The calculation process of runoff under the influence of straw includes:

[0093] ;

[0094] Among them, P(i) is the precipitation on the i-th day;

[0095] S(i) is the water retention coefficient on the i-th day, ;

[0096] CN(i) is the runoff coefficient affected by straw on the i-th day:

[0097] ;

[0098] Where, CN is the runoff coefficient;

[0099] F C (i) is the soil coverage percentage on day i, , R(i) is the amount of surface straw on the i-th day, and Am is the unit straw coverage area.

[0100] The process of calculating the evapotranspiration of soil under the influence of straw includes: the soil moisture in the straw can be used for evaporation, which can reduce the potential evaporation (ES) of the soil; the soil evaporation after straw covering is calculated by the soil covering percentage, per unit straw covering area (Am), corn is 0.00040hm 2 kg -1 , wheat is 0.00045hm 2 kg -1 Therefore, the calculation process of actual evapotranspiration under the influence of straw includes:

[0101] ;

[0102] Among them, F C (i) is the soil cover percentage on the i-th day, ETa(i) is the actual evapotranspiration on the i-th day, and ETa R (i) is the actual evapotranspiration affected by straw on the i-th day.

[0103] Specific working process:

[0104] The measured data of the summer corn field test conducted in Huyi District, Xi'an in 2020 were used to evaluate the ability of soil moisture models with and without the influence of straw return to simulate the decomposition of surface wheat straw and soil water content. The soil temperature and humidity automatic monitoring system was used to measure and record the dynamic changes of soil volume water content at an interval of 10 minutes. Soil temperature and moisture sensors were placed in the test plots, avoiding the edge rows of the plots. The soil moisture measurement depths of 20cm, 40cm and 60cm were used to calculate the soil water storage capacity of 0-60cm.

[0105] like Figure 2 As shown in the figure, the straw return module was evaluated using the surface straw amount data at the mature stage of summer corn. The RMSE and NRMSE of the measured value of the surface straw amount and the simulated value of the straw return module were 122.5 kg·hm -2 and 8.1%, respectively. This indicates that the straw return module has a good simulation effect on the decomposition of surface straw.

[0106] Figure 2 Medium parameter annotation: Conventional tillage + wheat straw 2000kg∙hm -2 (T1), conventional tillage + wheat straw 6000kg∙hm -2 (T3), no-tillage + wheat straw 2000kg∙hm -2 (NT1) and no-tillage + wheat straw 6000 kg∙hm -2 (NT3).

[0107] like Figure 3 , Figure 4As shown: The measured soil moisture data of the summer corn season after straw return in 2020 was used to evaluate the ability of the wheat-corn double-cropping production system model with and without straw return to simulate soil moisture dynamics:

[0108] The RMSE and NRMSE of the measured value and the simulated value of the 0-40 cm soil water storage in the T1 treatment were 13.9 mm and 10.7%, respectively. Figure 3 a), the RMSE and NRMSE of the measured value and the improved simulated value are 11.0 mm and 8.5%, respectively ( Figure 4 a);

[0109] The RMSE and NRMSE of the measured value and the simulated value before improvement of the 0-40 cm soil water storage in T3 treatment were 6.1 mm and 5.5%, respectively. Figure 3 b), the RMSE and NRMSE of the measured value and the improved simulation value are 5.9 mm and 5.4%, respectively ( Figure 4 b);

[0110] The RMSE and NRMSE of the measured and simulated values ​​of soil water storage in the 0-40 cm range in the NT1 treatment were 10.3 mm and 9.2%, respectively. Figure 3 c), the RMSE and NRMSE of the measured value and the improved simulation value are 9.9 mm and 8.9%, respectively ( Figure 4 c);

[0111] The RMSE and NRMSE of the measured and simulated values ​​of soil water storage in the 0-40 cm range in the NT3 treatment were 14.6 mm and 11.7%, respectively. Figure 3 d), the RMSE and NRMSE of the measured value and the improved simulation value are 8.0 mm and 6.4%, respectively ( Figure 4 d).

[0112] R of the model after adding the straw module 2 All of them were improved, among which NT3 treatment had the largest improvement. In the simulation of the precipitation process from June 15 to 17, the increase in straw's interception effect on the precipitation process made the increased soil water storage after precipitation closer to the measured value, indicating that the addition of the straw module improved the model's simulation of precipitation infiltration.

[0113] When there is no irrigation and precipitation, the decrease in soil moisture content is mainly due to soil evaporation and crop transpiration. The soil water storage capacity simulated by the model without the straw module decreases faster than the measured value. After adding the straw return module, the straw has a slowing effect on soil evaporation, making the downward trend of the simulated value closer to the measured value, thereby improving the accuracy of the model's soil moisture simulation.

[0114] Therefore, the model with the straw module added has a good simulation effect on the soil moisture content under different straw return methods, improves the simulation of soil moisture content, and can well reflect the soil moisture dynamics after straw covering.

[0115] Those of ordinary skill in the art will appreciate that the units and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0116] In the several embodiments provided in the present application, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the division of the units described above is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. The above-mentioned units may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0117] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

[0118] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A dynamic simulation method for the effect of surface straw on soil moisture, characterized in that: include: The dynamic process of surface straw decomposition was simulated to obtain the simulation results of the daily surface straw content; the parameters involved in the simulation of the dynamic decomposition process included: the amount of straw after tillage, the temperature influencing factor, the straw moisture content influencing factor, and the straw carbon-nitrogen ratio influencing factor; According to the simulation results of the surface straw content, the constraint of the surface straw on soil moisture is simulated to obtain the simulation results of soil moisture content; among them, the parameters involved in simulating the soil moisture constraint include: surface straw interception, actual evapotranspiration under the influence of straw, and runoff under the influence of straw; According to the daily surface straw content simulation results and soil moisture content simulation results, the effect of surface straw on soil moisture content is obtained; The calculation process of the simulation result of the daily surface straw content includes: R(i+1)=R(i)-0.1×R(i)×F T (i)×F W (i)×F C / N ; Among them, R(i) is the amount of straw on the i-th day, F T F(i) is the factor affecting the temperature on the i-th day on the decomposition of straw, Fw(i) is the factor affecting the moisture content of straw on the i-th day on the decomposition of straw, C / N is the influencing factor of straw carbon-nitrogen ratio on straw decomposition; The calculation process of the straw moisture content influencing factor includes: Among them, F W (i) is the influencing factor of straw moisture content on straw decomposition on the i-th day, RSW(i) is the straw moisture content on the i-th day, RSAT(i) is the maximum water holding capacity of the straw on the i-th day, and RLL is the minimum moisture content of the straw; The calculation process of the straw carbon-nitrogen ratio influencing factor includes: Among them, F C / N is the influencing factor of straw carbon-nitrogen ratio on straw decomposition, CN is the straw carbon-nitrogen ratio, and the straw carbon-nitrogen ratio of different types of straw is different; The calculation process of the soil moisture simulation result includes: SW(i+1)=SW(i)+P(i)-RUNOFF R (i)-ETa R (i)-C R (i); Where SW(i) is the soil moisture content on the i-th day, P(i) is the precipitation on the i-th day, RUNOFF R (i) is the runoff affected by straw on the i-th day, ETa R (i) is the actual evapotranspiration affected by straw on the i-th day, C R is the amount of straw interception; The calculation process of the surface straw interception amount includes: RSAT(i) is the saturated moisture content of straw on the i-th day, RSAT(i) = 3.8 × 10 -4 ×R(i), R(i) is the amount of surface straw on the ith day; RSW(i) is the moisture content of straw on the i-th day, ES(i) is the potential evaporation, RLL is the minimum moisture content of straw; PINF(i) is the moisture reaching the straw surface on the i-th day; PINF(i) = P(i) - RUNOFF R (i), P(i) is the precipitation on the i-th day, RUNOFF R (i) is the runoff under the influence of straw on the i-th day; The calculation process of the runoff under the influence of straw includes: Among them, P(i) is the precipitation on the i-th day; S(i) is the water retention coefficient on the i-th day, CN(i) is the runoff coefficient affected by straw on the i-th day, Where, CN is the runoff coefficient; F C (i) is the soil coverage percentage on the i-th day, F C (i) = 1-e (-Am×R(i)) , R(i) is the amount of surface straw on the ith day, Am is the unit straw coverage area; The calculation process of the actual evapotranspiration under the influence of straw includes: ETa R (i)=ETa(i)×(1-0.8×F C (i)); Among them, F C (i) is the soil cover percentage on the i-th day, ETa(i) is the actual evapotranspiration on the i-th day, and ETa R (i) is the actual evapotranspiration affected by straw on the i-th day.

2. The dynamic simulation method for the effect of surface straw on soil moisture according to claim 1, characterized in that: The calculation process of the amount of straw after tillage includes: R(i)=Residue×(1.0-Ptill); Among them, R(i) is the amount of straw on the i-th day, Residue is the amount of straw on the surface before tillage, and Ptill is the percentage of straw entering the soil after tillage.

3. The dynamic simulation method for the effect of surface straw on soil moisture according to claim 1, characterized in that: The calculation process of the temperature influence factor includes: According to the temperature range suitable for microbial growth and the temperature threshold of microbial dormancy, a piecewise function of the temperature influencing factor is established: Among them, F T (i) is the factor affecting the temperature on the i-th day on the decomposition of straw, T a (i) is the air temperature on the i-th day.

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