Dynamic probabilistic analytical modeling for estimating rainfall–runoff transformation rates in drylands

Abstract

Precipitation-runoff changes used in the development of precipitation-runoff models depict general runoff mechanisms in physical precipitation-runoff processes. For this purpose, it must be able to adequately express the characteristics of the physical system. Similar to other water resources management models, analytical-probabilistic models may be developed with different levels of complexity according to different types of rainfall–runoff developments. In this research, a log-normal probabilistic model was used to estimate the return period of rainfall and Soil and Water Assessment Tool (SWAT) software was used to convert rainfall values into discharge and runoff height in agricultural lands. The slope and the level of plant shade cover were considered the two basic factors in the estimation of the subsurface flow used in agriculture. Slopes of less than 0.015 and land cover level of more than 70% of extreme points were obtained to ensure subsurface water sources and prevent erosion. HIGHLIGHTS The use of probabilistic models in estimating runoff and precipitation is one of the most reliable flood management methods.; Using the probabilistic dynamic model to evaluate the impact of runoff on land use is one of the goals of this research.; Multivariate models have a positive effect on the estimation of flow volume and velocity in dry areas.;

Keywords

• agricultural lands
• evapotranspiration
• land cover
• runoff flow rate
• soil texture