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Automatic or smart irrigation systems benefit irrigation water management. However, measurement sensor networks in automatic irrigation systems are complex, and maintenance is essential. Regional soil moisture estimation avoids the multiple measurements necessary when deploying an irrigation system. In this sense, a fuzzy estimation approach based on decision-making (FEADM) has been used to obtain soil moisture point estimates. However, FEADM requires intelligent weather adjustment based on spatial features (IWeCASF) to perform regional soil moisture estimation. The IWeCASF-FEADM integrated approach for regional soil moisture estimation is developed in this work. IWeCASF provides the inputs for FEADM. FEADM is performed R times; R is the number of checkpoints at which a point estimate is obtained. In this way, regional estimation is achieved when the set of R soil moisture point estimates is completed. Additionally, IWeCASF-FEADM considers the irrigation water records, which are not included in either method individually. This method can detect when the soil moisture is deficient in a region, allowing actions to prevent water stress. This regional estimation reduces an irrigation system's operational and maintenance complexity. This integrated approach has been tested over several years by comparing the results of regional soil moisture estimation with measurements obtained at many points in the study region. [ABSTRACT FROM AUTHOR]