Mapping of Evapotranspiration and Determination of the Water Footprint of a Potato Crop Grown in Hyper-Arid Regions in Saudi Arabia

Rangaswamy Madugundu (), Khalid A. Al-Gaadi, ElKamil Tola, Salah El-Hendawy and Samy A. Marey
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Rangaswamy Madugundu: Precision Agriculture Research Chair, Deanship of Scientific Research, King Saud University, Riyadh 11451, Saudi Arabia
Khalid A. Al-Gaadi: Precision Agriculture Research Chair, Deanship of Scientific Research, King Saud University, Riyadh 11451, Saudi Arabia
ElKamil Tola: Precision Agriculture Research Chair, Deanship of Scientific Research, King Saud University, Riyadh 11451, Saudi Arabia
Salah El-Hendawy: Department of Plant Production, College of Food and Agriculture Sciences, King Saud University, Riyadh 11451, Saudi Arabia
Samy A. Marey: Agricultural Engineering Research Institute (AEnRI), Agricultural Research Centre, Giza 12618, Egypt

Sustainability, 2023, vol. 15, issue 16, 1-16

Abstract: Seasonal quantification of a crop’s evapotranspiration (ET) and water footprint (WF) is essential for sustainable agriculture. Therefore, this study was conducted to estimate the ET and WF of an irrigated potato crop using satellite imagery of Landsat and Sentinel-2 sensors. The Simplified Surface Energy Balance (SSEB) algorithm was used to evaluate the crop water use (ET a ) for potato fields belonging to the Saudi Agricultural Development Company, located in the Wadi-Ad-Dawasir region, Saudi Arabia. Normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and land surface temperature (LSD) were computed for Landsat and Sentinel-2 datasets, which were used as inputs for mapping the potato tuber yield and, subsequently, the WF. The results indicated that the NDVI showed the best accuracy for the prediction of the potato tuber yield (R 2 = 0.72, P > F = 0.021) followed by the SAVI (R 2 = 0.64, P > F = 0.018), compared to the field harvested actual yield (Y A ). A comparison between the satellite-based ET a and the actual amount of water applied (W A ) for irrigation showed a good correlation (R 2 = 0.89, RMSE = 4.4%, MBE = 12.9%). The WF of the potatoes in the study area was estimated at values between 475 and 357 m 3 t −1 for the early (September–December) and late (December–April) growing periods, respectively. A major portion (99.2%) of the WF was accounted for from irrigation with variations of 18.5% and 3.5% for early- and late-planted potatoes, respectively, compared to the baseline (crop planted in season). In conclusion, the results showed the possibility of satisfactorily estimating the WF using the SSEB algorithm by integrating the Landsat-8 and Sentinel-2 datasets. In general, the high rates of ET in the early planting season led to higher WF values compared to the in-season and late planting dates; this will help in selecting suitable planting dates for potato crops in the study area and areas with similar environments, which enhances the opportunities for sustainable management of irrigation water.

Keywords: satellite data; vegetation indices; SSEB; CROPWAT; water footprint (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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