Spatial and Temporal Errors in Estimating Regional Evapotranspiration

Abstract

Current methods of computing regional crop evapotranspiration (ET), the prime variable in estimating irrigation demand, largely ignore the spatial and temporal variability of ET parameters, thus introducing errors. In this research, a methodology was developed to estimate regional ET while considering the spatial and temporal variability of parameters. To consider this variability, spatial databases were developed for agricultural land-use, relevant climatic parameters, and topographic data using geographic information systems (GIS). The Cache la Poudre Basin was selected as the study area due to the availability of field verified land-use survey data. A spatial simulation ET model (GISETMA) was used to develop a baseline estimation of regional ET, incorporating analytical GIS functions of map algebra and map overlay to calculate ET for each field in the system and for each day of the growing season. Various scenarios were developed and compared to the baseline scenario to explore spatial and temporal errors from point estimate of climate data and weather station use, daily versus monthly time-steps, and land-use classification.