Journal of Hydrology
Absent local weather stations, a gridded weather dataset can provide information useful for water management in irrigated areas including potential crop evapotranspiration calculations. In estimating crop irrigation requirements and surface evaporation in Utah, United States of America, methodology and software were developed using the ASCE Standardized Penman-Monteith Reference Evapotranspiration equation with input climate drivers from the North American Land Data Assimilation System (NLDAS) gridded weather forcing dataset and a digital elevation model. A simple procedure was devised to correct bias in NLDAS relative humidity and air temperature data based on comparison to weather data from ground stations. Potential evapotranspiration was calculated for 18 crops (including turfgrass), wetlands (large and narrow), and open water evaporation (deep and shallow) by multiplying crop coefficient curves to reference evapotranspiration with annual curve dates set by summation of Hargreaves evapotranspiration, cumulative growing degree days, or number of days. Net potential evapotranspiration was calculated by subtracting effective precipitation estimates from the Daymet gridded precipitation dataset. Analysis of the results showed that daily estimated potential crop evapotranspiration from the model compared well with estimates from electronic weather stations (1980–2014) and with independently calculated potential crop evapotranspiration in adjacent states. Designed for this study but open sourced for other applications, software entitled GridET encapsulated the GIS-based model that provided data download and management, calculation of reference and potential crop evapotranspiration, and viewing and analysis tools. Flexible features in GridET allows a user to specify grid resolution, evapotranspiration equations, cropping information, and additional datasets with the output being transferable to other GIS software.
Lewis, C.S., Allen, L.N. Potential crop evapotranspiration and surface evaporation estimates via a gridded weather forcing dataset (2017) Journal of Hydrology, 546, pp. 450-463.
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