Abstract
Water scarcity is one of the main factors limiting agricultural development in semi-arid areas. Remote sensing has long been used as an input for crop water balance monitoring. The increasing availability of high resolution high repetitivity remote sensing (forthcoming Sentinel-2 mission) offers an unprecedented opportunity to improve this monitoring. In this study, regional crop water consumption was estimated with the SAMIR software (SAtellite Monitoring of IRrigation) using the FAO-56 dual crop coefficient water balance model fed with high resolution NDVI image time series providing estimates of both the actual basal crop coefficient and the vegetation fraction cover. Three time series of SPOT5 images have been acquired over an irrigated area in central Tunisia along with a SPOT4 time series acquired in the frame of the SPOT4-Take5 experiment, which occurred during the first half of 2013. Using invariant objects located in the scene, normalization of the SPOT5 time series was realized based on the SPOT4-Take5 time series. Hence, a NDVI time profile was generated for each pixel. The operationality and accuracy of the SAMIR tool was assessed at both plot scale (calibration based on evapotranspiration ground measurements) and perimeter scale (irrigation volumes) when several land use types, irrigation and agricultural practices are intertwined in a given landscape. Results at plot scale gave after calibration an average Nash efficiency of 0.57 between observed and modeled evapotranspiration for two plots (barley and wheat). When aggregated for the whole season, modeled irrigation volumes at perimeter scale for all campaigns were close to observed ones (resp. 135 and 121 mm, overestimation of 11.5%). However, spatialized evapotranspiration and irrigation volumes need to be improved at finer timescales.
Highlights
In arid and semi-arid regions, water availability is a major limitation for crop production
For the SPOT4-take5 time series acquired in 2012–2013, the longest gap was at the beginning of the period, as the first correct image was acquired on 10/03/2015, which means 40 days without image data
In our case, this gap was filled using the SPOT5 satellite which successfully acquired two images, thanks to the programming capabilities of this sensor and its oblique viewing agility allowing to observe areas on cloud free days. This is an interesting result showing that combining Sentinel-2 data with other sensors (Landsat 8, SPOT6, etc.) may still be necessary in many places to get consistent high resolution time series
Summary
In arid and semi-arid regions, water availability is a major limitation for crop production. Efficient agricultural water management is a major issue, especially in irrigated areas. The design of tools that provide regional estimates of the water balance may help the sustainable management of water resources in these regions. Evapotranspiration (ET) is one of the most important fluxes of the water balance in semi-arid areas; it is a key factor for optimizing irrigation water management [1]. Remote sensing (RS) capabilities for monitoring vegetation and its physical properties on large areas have been identified for years [2]. It provides spatialized and periodic information about some major drivers of ET such as albedo, surface temperature and vegetation properties. Several methods for estimating ET using remotely-sensed data have been developed [3,4,5,6,7]
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