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.

In hydrometric stations, water levels are continuously observed and discharge rating curves are constantly updated to achieve accurate river levels and discharge observations. An adequate spatial distribution of hydrological gauging stations presents a lot of interest in linkage with the river regime characterization, water infrastructures design, water resources management and ecological survey. Due to the increase of riverside population and the associated flood risk, hydrological networks constantly need to be developed. This paper suggests taking advantage of kriging approaches to improve the design of a hydrometric network. The context deals with the application of an optimization approach using ordinary kriging and simulated annealing (SA) in order to identify the best locations to install new hydrometric gauges. The task at hand is to extend an existing hydrometric network in order to estimate, at ungauged sites, the average specific annual discharge which is a key basin descriptor. This methodology is developed for the hydrometric network of the transboundary Medjerda River in the North of Tunisia. A Geographic Information System (GIS) is adopted to delineate basin limits and centroids. The latter are adopted to assign the location of basins in kriging development. Scenarios where the size of an existing 12 stations network is alternatively increased by 1, 2, 3, 4 and 5 new station(s) are investigated using geo-regression and minimization of the variance of kriging errors. The analysis of the optimized locations

<p>Actual evapotranspiration (AET) is a key component of the energy balance and hydrological regime of catchments. Estimating actual evapotranspiration (AET) in agricultural semi-arid regions is important for crop yield and drought assessment. The SEBS model, a physically-based model of energy balance, and the BBH-model, a conceptual water balance model, are used to estimate AET at the 10-day scale in Northern Tunisia using in situ and remote sensing data. Their estimates were compared to those obtained from a satellite product LSA SAF, based on the soil-vegetation-atmosphere model TESSEL. Comparisons are performed at two spatial scales: at the level of the pixel, and aggregating pixels from the same watershed. Eight gauged watersheds were considered with an area varying between 52 and 416 km². The spatial and temporal study of the coefficient of variation of AET indicates that the AET is coherently related to the spatial and temporal variation of ecosystems. Results indicate that the summer and autumn seasons are the most unstable period and the south part is the most unstable area. The comparison of AET-LSA SAF within AET-SEBS estimations results in <em>R</em>² under 0.6 at the pixel scale and <em>R</em>² varying from 0.2 to 0.5 at the basin scale. The SEBS model estimations overvalue those of LSA SAF, with an MAE = 20 mm 10-day<sup>-1</sup> for almost basin. The comparison of AET-LSA SAF and AET-BBH at the basin scale shows an acceptable coefficient of determination (R² = 0.6) at the level of basins situated in the north part of the study area. By cons, a nonsignificant R² was obtained at the level of the basin in the south. The MAE is about 6.5 mm 10-day<sup>-1 </sup>with a general overestimation of AET-BBH comparing to AET-LSA SAF. A good coefficient of determination (R²=0.7) was found when comparing the AET-SEBS and AET-BBH estimations for the basin situated in the south part. The MAE = 16 mm 10-day<sup>-1</sup> and the RMSE = 18 mm 10-day<sup>-1</sup> with an overestimation of AET-SEBS comparing to AET-BBH. These results are encouraging and may help stakeholders to have a range of AET estimations using three different sources and approaches.</p>