Can remote sensing and sebal fill the gap on evapotranspiration? A case study: Kunduz catchment, Afghanistan

Remote sensing-based approaches developed to solve the limits of direct measurement methods for Evapotranspiration (ET). The purpose of this study was to explore the capability of Landsat-8 OLI imagery and the Surface Energy Balance Algorithm for Land (SEBAL) model for estimating instantaneous (ET-Inst) and daily (ET-24) ET to fill the gap of ET estimation in lower part of Kunduz Catchment Afghanistan. 27th of September 2016 dated Landsat 8 OLI/TIRS data was used to calculate NDVI, LAI, LST and Surface Albedo values in the area. Pixel wise surface energy components including Net Radiation (Rn), Soil Heat Flux (G) and Sensible Heat Flux (H) were calculated for different land cover types. SEBAL results varied from 0.0 mm/day at bare lands where is no water or vegetation to 17.4 mm/day at snow cover. Accuracy of estimated ET from Landsat-8 OLI/TIRS was evaluated based on the observed data using Penman-Monteith (PM), Priestly and Taylor (PT), Makkink (MAK), Hargreaves (HS), Lin and Abtew (Abt) methods. PM has the lowest value for all statistical analysis methods and, it means that PM methods gave the closest results to SEBAL. Using remote sensing data with very limited observed data can calculate the spatial variation of ET, which is crucial for planning and determining the amount of available water in terms of catchment management.