Validation of remotely-sensed evapotranspiration and NDWI using ground measurements at Riverlands, South Africa

• Published in: Water S. A. Vol. 40; no. 2; pp. 211 - 220
• Main Authors: Jovanovic, Nebo, Garcia, Cesar L, Teich, Ingrid, Rodriguez, Carlos M. Garcia, Bugan, Richard D.H
• Format: Journal Article
• Language: English
• Published: Gezina Water Research Commission (WRC) 01-04-2014; Water Research Commission
• Subjects: Correlation coefficient; Environment; Evapotranspiration; Freshwater; Fynbos; Hydrologic cycle; LandSAF ET; Mathematical models; Moisture content; Remote sensing; Satellites; Scintillometry; Soil (material); Soil depth; Soil water; SPOT-Vegetation NDWI; Trends; Validation studies; Vegetation; Water balance; Water content; Water resources management; South Africa; South Africa, Western Cape
• ISSN: 0378-4738; 0378-4738
• DOI: 10.4314/wsa.v40i2.3

Quantification of the water cycle components is key to managing water resources. Remote sensing techniques and products have recently been developed for the estimation of water balance variables. The objective of this study was to test the reliability of LandSAF (Land Surface Analyses Satellite Applications Facility) evapotranspiration (ET) and SPOT-Vegetation Normalised Difference Water Index (NDWI) by comparison with ground-based measurements. Evapotranspiration (both daily and 30 min) was successfully estimated with LandSAF products in a flat area dominated by fynbos vegetation (Riverlands, Western Cape) that was representative of the satellite image pixel at 3 km resolution. Correlation coefficients were 0.85 and 0.91 and linear regressions produced R2 of 0.72 and 0.75 for 30 min and daily ET, respectively. Ground-measurements of soil water content taken with capacitance sensors at 3 depths were related to NDWI obtained from 10-daily maximum value composites of SPOT-Vegetation images at a resolution of 1 km. Multiple regression models showed that NDWI relates well to soil water content after accounting for precipitation (adjusted R2 were 0.71, 0.59 and 0.54 for 10, 40 and 80 cm soil depth, respectively). Changes in NDWI trends in different land covers were detected in 14-year time series using the breaks for additive seasonal and trend (BFAST) methodology. Appropriate usage, awareness of limitations and correct interpretation of remote sensing data can facilitate water management and planning operations.