Remote-sensing estimation of the water stress coefficient and comparison with drought evidence

Abstract

Drought assessment of croplands and sylvo-pastoral areas is crucial in semi-arid regions. Satellite remote sensing offers an opportunity for such assessment. This study presents a method of spatial and temporal estimation of drought index in Medjerda basin (23,700 km 2 ) using satellite data and its validation with in situ investigation of areas with crop damage realized by the ministry of agriculture. To estimate drought index, potential evapotranspiration (PET) is calculated using Penman-Monteith equation and modified FAO-56 crop coefficient (K c ) approach combined with remote-sensing data and actual evapotranspiration is derived from the Meteosat Second Generation platforms. The period of study is the 2010 water year. PET estimations show good accuracy with corrected pan evaporation observations up to 0.9. In comparison, the water stress coefficient (K s ) aggregated by land-cover type shows the coefficient of determination with the fraction of drought damage areas of 0.5 for the third decade of March and first decade of April in croplands areas and 0.8 for the second and third decades of May in croplands and sylvo-pastoral areas. This study showed that satellite data approaches could successfully be used to monitor drought in river basins in the Northern Africa and Mediterranean region.

Estimation of potential groundwater recharge by a drywell in sandy clay soil

“…This finding verifies that during the drought period in both years, ET decreased due to water stress effect, indicating a reduced soil water availability and an increased water demand for grass. This result demonstrates the importance of considering water stress coefficient (K s ) ( Figure 8) in evapotranspiration variation analysis throughout a year (Abid et al, 2018).…”

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“…We estimate the crop coefficient Kc based on the FAO-56 dual crop coefficient approach (Allen et al 1998) which is commonly used in the literature (Er-Raki et al 2010). Kc is calculated as a function of Kcb and Ke (Rocha et al 2010;Abid et al 2018):…”

“…In different parts of the world, flux tower data were used to verify the accuracy of actual evapotranspiration using as reported from satellite observations (Cleugh et al 2007;Paca et al 2019). Here we propose to compare remote-sensing estimated evapotranspiration under drought conditions, with field evidence of crop damage (Abid et al 2018). Tunisia's economy is vulnerable to drought and particularly cereal crop droughts.…”

Advances in remote-sensing applications in silvo-pastoral systems

“…This methodology can be used for future drought monitoring and early warning for risk-based drought planning. Abid, Bargaoui, and Mannaerts (2018) present a method of spatial and temporal estimation of drought index in Medjerda basin (Tunisia) for the 2010 water year, using satellite data and its validation with in situ investigation of areas showing crop damage realized by the Tunisia Ministry of Agriculture. To estimate drought index, potential evapotranspiration (PET) was calculated using the Penman-Monteith equation and the modified FAO-56 crop coefficient (Kc) approach combined with remote-sensing data, being the actual evapotranspiration derived from the MSG platforms.…”

“…This special issue has contributed in providing new insights in methodological and operational issues associated with SPS mapping, assessment, and monitoring by using remote-sensing and ground-based approaches. It has also demonstrated the wide range of applications able to be explored using different remote-sensing platforms, proximal sensors, and derived products, which include spaceborne/satellite-based applications (Abid, Bargaoui, and Mannaerts 2018;Allen et al 2018;Cárdenas et al, 2018;Demisse et al 2018;Lourenço et al 2018;Soares et al 2018;Filizzola et al, 2018;Godinho, Guiomar, and Gil 2018);…”