Soil Moisture Regional Estimation Approach to Determine Irrigation Demands

Abstract

The regional estimation of soil moisture avoids the complexity of implementation and maintenance of automatic irrigation systems. The regional estimate can be derived from a point estimation model, such as the Fuzzy Estimation Approach based on Decision Making (FEADM). However, FEADM requires weather conditions where a point estimate is made. In this work, an intelligent weather adjustment model based on the spatial characteristics of the region (IWeCASF) is developed and used to provide FEADM with the necessary data to make a point estimate. In addition, the integration of IWECASF-FEADM is performed to obtain a regional estimation as a set of point estimates. Fuzzy systems, image processing and decision-making algorithms are utilized. The results obtained are compared with interpolation models. The performance of the models developed better or similar to interpolation. However, the models in this work only require a measurement point to obtain soil moisture, unlike interpolation methods. The integrated approach reduces the operating cost and models the interactions of land features, weather conditions and soil moisture.