Stochastic Simulation Of Soil Moisture Dynamics And Irrigation Requirements In Farmland

Hydrologic cycle is the fundamental process in agroecosystem, and it is necessary and valuable to understand and simulate the water balance in cropland. Soil moisture and irrigation requirement, the foundation and key varaiable of cropland water cycle, play an extremely important role in crop growth and development. Meanwhile, it is a significant parameter for improving water use efficiency, water-saving irrigation management, and rational allocation of water resources. Water balance dynamics of cropland, taking the core as soil moisture, are the long-term result of various factor comprehensive roles, including atmosphere, soil, crop, groundwater, irrigation activity. Therefore, they manifest strong nonlinearity and uncertainty. Accordingly, it is essential to interpret and model the dynamics of soil moisture and hydrological elements, providing scientific basis for the evolution analysis of hydrologic cycle and irrigation decision in agroecosystem.This thesis mainly investigated the hydrologic cycle and transformation of summer maize, taking soil moisture dynamics as core, in south of North China Plain, using water balance principle, probability statistics and calculus. The main results are outlined as follow:(1) The annual fluctuations and random distributions of hydrometeorological factors were analyzed during the growing season of summer maize, and the response relationship between soil moisture and climate fluctuations was investigated. The annual coefficient of variation of mean depth of rainfall events(α) and arrival rate of rainfall events(λ) were 0.323 and 0.178 respectively. Moreover, α and λ were testified following a Logistic distribution. The annual coefficient of variation of daily average potential evapotranspiration(Emax) was 0.088, while following a Log Normal distribution. The probability density function of soil moisture emerged a bimodal curve, which suggested that the SPAC system of summer maize trend to switch between two preferential states, one characterized by high average soil moisture and the other characterized by low average soil moisture conditions.(2) The long-term effect of α, λ and Emax variations on evapotranspiration(E) of summer maize was studied, based on Budyko framework of water and energy balance and stochastic soil moisture dynamics. Annual long-term fluctuations of α, λ and Emax reduces the long-term evapotranspiration. This reduction is the maximum when the dryness index(Ep/P) equals 1, and maximum reduction in the evaporation ratio(E/P) can reach about 10%. The relations between the maximum reductions and the coefficient of variation of α, λ �'� Emax follow linear law. The interannual variability of E increases as the increasing of interannual variability of α, λ and Emax, and α is more significant than λ and Emax. The relationship of E, P and Ep during the growing season of summer maize in the study can described by the Fu’s equation with ω of 5.3.(3) A certain universal model of stochastic soil moisture dynamics was built, aiming at the shortcoming of previous researches. Soil saturated hydraulic conductivity(Ks) and a hydraulic parameter(β) were introduced to establish a comparatively complete soil moisture loss function. Afterwards, the probability density functions of soil moisture with different irrigation schemes were derived according to the analytic relation between loss function and probability density function of soil moisture.(4) A novel estimating method of crop irrigation requirement was developed. The model for calculating irrigation requirement is physic-based on stochastic soil moisture dynamics model, which reflect the quantitive relationship among rainfall parameters(α, λ), soil parameters(n, s*, sfc, Ks, β), crop parameters(Emax, Zr) and irrigation parameters(si、st). The new physic-based method is better than empirical method. The irrigation requirement model coupled with water production function provides a theoretical basis to the selection of appropriate irrigation scheme in a changing environment.(5) The capillary flux on the soil moisture and groundwater depth was investigated, and a stochastic model of water transform in soil-plant-atmosphere-groundwater continuum for irrigated cropland was built, offering theoretical basis for studying hydrologic cycle and irrigation management with a shallow groundwater depth.