Estimating Daily Reference Evapotranspiration in a Semi-Arid Region Using Remote Sensing Data
| Autor: | Heiko Balzter, Peshawa M. Najmaddin, Mick J. Whelan |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
010504 meteorology & atmospheric sciences
Mean squared error Meteorology Science Cloud cover 0208 environmental biotechnology reference evapotranspiration (ETₒ) 02 engineering and technology remote sensing AIRS/AMSU semi-arid region 01 natural sciences Wind speed 020801 environmental engineering Evapotranspiration Atmospheric Infrared Sounder Advanced Microwave Sounding Unit General Earth and Planetary Sciences Environmental science Relative humidity Penman–Monteith equation 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | Remote Sensing, Vol 9, Iss 8, p 779 (2017) Remote Sensing; Volume 9; Issue 8; Pages: 779 |
| ISSN: | 2072-4292 |
| DOI: | 10.3390/rs9080779 |
| Popis: | Estimating daily evapotranspiration is challenging when ground observation data are not available or scarce. Remote sensing can be used to estimate the meteorological data necessary for calculating reference evapotranspiration ETₒ. Here, we assessed the accuracy of daily ETₒ estimates derived from remote sensing (ETₒ-RS) compared with those derived from four ground-based stations (ETₒ-G) in Kurdistan (Iraq) over the period 2010–2014. Near surface air temperature, relative humidity and cloud cover fraction were derived from the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS/AMSU), and wind speed at 10 m height from MERRA (Modern-Era Retrospective Analysis for Research and Application). Four methods were used to estimate ETₒ: Hargreaves–Samani (HS), Jensen–Haise (JH), McGuinness–Bordne (MB) and the FAO Penman Monteith equation (PM). ETₒ-G (PM) was adopted as the main benchmark. HS underestimated ETₒ by 2%–3% (R2 = 0.86 to 0.90; RMSE = 0.95 to 1.2 mm day−1 at different stations). JH and MB overestimated ETₒ by 8% to 40% (R2= 0.85 to 0.92; RMSE from 1.18 to 2.18 mm day−1). The annual average values of ETₒ estimated using RS data and ground-based data were similar to one another reflecting low bias in daily estimates. They ranged between 1153 and 1893 mm year−1 for ETₒ-G and between 1176 and 1859 mm year−1 for ETₒ-RS for the different stations. Our results suggest that ETₒ-RS (HS) can yield accurate and unbiased ETₒ estimates for semi-arid regions which can be usefully employed in water resources management. |
| Databáze: | OpenAIRE |
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