LAUSR

Agricultural ponds are an important alternative source of water for crop irrigation to conserve surface and ground water resources. In recent years more such ponds have been constructed in Mississippi and around the world. There is currently, however, a lack of a tool to simultaneously estimate crop irrigation demand and pond water availability. In this study, a Pond-Irrigation Model (PIM) was developed to meet this need using STELLA (Structural Thinking, Experiential Learning Laboratory with Animation) software. PIM simulated crop land and agricultural pond hydrological processes such as surface runoff, soil drainage, and evapotranspiration as well as crop irrigation demand and pond water availability. More importantly, PIM was able to decide when to conduct crop irrigation based on management allowable depletion (MAD) root zone soil water content and to determine optimal ratios of agricultural pond size to crop land with sufficient pond water available for crop irrigation. As a case demonstration, the model was applied to concomitantly estimate row crops (i.e., corn, cotton, and soybeans) water irrigation demand and pond water availability in a farm located at East-central Mississippi. Simulations revealed that corn used more soil water for growth than soybeans, whereas soybeans needed more irrigation water than corn and occurred due to less rainwater available for soybeans growth. We also found that there was one time for corn, zero time for cotton, and two times for soybeans when the pond water level was drawn to near zero for irrigation from 2005 to 2014. PIM developed in this study is a useful tool for estimating crop irrigation demand and pond water availability simultaneously.