Detection of Irrigated Crops from Sentinel-1 and Sentinel-2 Data to Estimate Seasonal Groundwater Use in South India

Sylvain Ferrant (1) , Adrien Selles (2) , Michel Le Page (1) , Pierre-Alexis Herrault (3) , Charlotte Pelletier (1) , Al Bitar Ahmad (1) , Stéphane Mermoz (1) , Simon Gascoin (4) , Alexandre Bouvet (5) , Mehdi Saqalli (3) , Benoît Dewandel (6) , Yvan Caballero (6) , Shakeel Ahmed (7) , Jean-Christophe Maréchal (6) , Yann H. Kerr (1)

1 CESBIO - Centre d'études spatiales de la biosphère
2 UPMC - Université Pierre et Marie Curie - Paris 6
3 GEODE - Géographie de l'environnement
4 SISYPHE - Structure et fonctionnement des systèmes hydriques continentaux
5 IES - JRC Institute for Environment and Sustainability
6 BRGM - Bureau de Recherches Géologiques et Minières (BRGM)
7 IFCGR - Indo-French Center for Groundwater Research

range from 49.5 ± 0.78 mm (1.5% uncertainty) in Rabi 2016, and 44.9 ± 2.9 mm (6.5% uncertainty) in the Kharif season, to 226.2 ± 5.8 mm (2.5% uncertainty) in Rabi 2017. This variation must be related to groundwater recharge estimates that range from 10 mm to 160 mm•yr −1 in the Hyderabad region. These dynamic agro-hydrological variables estimated from Sentinel remote sensing data are crucial in calibrating runoff, aquifer recharge, water use and evapotranspiration for the spatially distributed agro-hydrological models employed to quantify the impacts of agriculture on water resources.

Keywords: crop cover mapping; random forest; Sentinel-1; Sentinel-2; radar and optical synergy; agro-hydrology; rice irrigation; groundwater shortage monitoring

Domains: Environmental Sciences; Environmental and Society

Sylvain Ferrant, Adrien Selles, Michel Le Page, Pierre-Alexis Herrault, Charlotte Pelletier, et al.. Detection of Irrigated Crops from Sentinel-1 and Sentinel-2 Data to Estimate Seasonal Groundwater Use in South India. Remote Sensing, 2017, 9 (11), ⟨10.3390/rs9111119⟩. ⟨hal-01683534⟩