Content area
Soil moisture is the core of the hydrological cycle in agroecosystems, and most of the studies on soil moisture dynamics modeling adopt deterministic research methods, which are not well suited to study the hydrological processes in agricultural fields under changing conditions. Therefore, the present study adopts a stochastic approach to reveal the distribution characteristics of soil moisture in agroecosystems under the effects of soil, climate, vegetation, and other influencing factors. Using soil moisture and precipitation data and based on a stochastic model of soil moisture dynamics, the point-scale soil moisture dynamic characteristics and soil moisture probability density function of farmland systems in the Songnen Plain region were investigated. The soil moisture of maize in the study area showed a certain degree of stochasticity, and the curve characteristics of the probability density function of soil moisture p(s) obtained from the simulation were very close to those of the measured p(s). It shows that the stochastic model can effectively simulate the probability density function of soil moisture in the study area, which can provide a theoretical basis and scientific method for efficiently using soil and water resources in the area.
Details
Soil dynamics;
Agricultural land;
Stochasticity;
Agricultural ecosystems;
Soil moisture;
Water resources;
Stochastic models;
Probability density functions;
Soil water;
Hydrologic data;
Dynamic characteristics;
Time series;
Probability distribution;
Hydrologic studies;
Hydrologic processes;
Hydrologic cycle;
Simulation;
Vegetation;
Precipitation;
Groundwater;
Precipitation data;
Research methods;
Soil moisture dynamics;
Runoff;
Soil moisture models;
Probability density function;
Climate and vegetation
