The study presented herein proposes a multi-criteria decision-making tool to identify flood susceptibility areas on a regional scale. The adopted approach is based on the integration of multi-criteria analysis, geographical information systems (GIS) and remote sensing (RS) techniques. Accordingly, flood susceptibility maps were prepared depending on information from six flood-conditioning factors namely Rainfall, Elevation, Slope, Land use/cover, Soil type, and Distance from the river. The relative importance of each factor on the flood susceptibility was assigned based on experts’ judgements and then connected to weight values. Two techniques were employed for weight calculation; the analytical hierarchy process (AHP) and the Fuzzy analytic hierarchy process (FAHP). The presented approach was applied to the Biskra basin, located north-eastern Algeria at the Sahara limits. The obtained maps indicate flood susceptibility areas, with high and very high flood susceptibility, mainly occurring at the northern areas of the basin which receive more rainfall, and also in urban areas all over the basin close to drainage networks. The performances of the two models were evaluated using the receiver operating characteristic (ROC) curve and the area under the curve (AUC) by comparing the obtained maps to an inventory map of past flood events. The evaluation results indicated that both the AHP and the FAHP models were found to be suited in predicting flood prone areas in the Biskra basin with AUC values of 93,61% and 96,61% respectively. Nevertheless, the FAHP model is preferred due to its ability to minimize vagueness and uncertainty associated with human judgements.

Soil erosion by water is a major problem that the Northern part of Algeria witnesses nowadays; it reduces: the productivity of agricultural areas due to the loss of lands, and leads to the loss of storage capacity in reservoirs, the deterioration of water quality etc. The aim of this study is to evaluate the soil losses due to water erosion, and to identify the sectors which are potentially sensitive to water erosion in the Bouhamdane watershed, that is located in the northeastern part of Algeria. To this end, the Revised Universal Soil Loss Equation (RUSLE) was used. The application of this equation takes into account five parameters, namely the rainfall erosivity, topography, soil erodibility, vegetative cover and erosion control practices. The product of these parameters under GIS using the RUSLE mathematical equation has enabled evaluating an annual average erosion rate for the Bouhamdane watershed of 11.18 t·ha^-1·y^-1. Based on the estimates of soil loss in each grid cell, a soil erosion risk map with five risk classes was elaborated. The spatial distribution of risk classes was 16% very low, 41% low, 28% moderate, 12% high and 3% very high. Most areas showing high and very high erosion risk occurred in the lower Bouhamdane watershed around Hammam Debagh dam. These areas require adequate erosion control practices to be implemented on a priority basis in order to conserve soil resources and reduce siltation in the reservoir.

The objective of the study presented herein is to provide an accurate climate classification on the basis of aridity in northern Algeria. The aridity indices used in this study were the De Martonne index (I _DM), the Emberger index (I _Emberger), and the United Nations Environment Program index (I _UNEP), generally admitted in the Mediterranean region. The data required for their calculation were taken from 37 meteorological stations, and processed in a Geographical Information System (GIS) environment to generate climate classification maps according to each index. Generally, the three indices revealed the prevalence of semi-arid conditions in the study area. Similar climate classifications were identified with the I _UNEP and the I _DM, while the I _Emberger has identified larger arid extent. The obtained maps were then validated against the long-term soil moisture data extracted from a gridded global data set. The validation results indicated that the three indices gave very satisfactory results since they showed strong correlation coefficients with the soil moisture data. However, the I _Emberger slightly outperformed the I _UNEP and the I _DM with coefficients of determination (R ²) of 0.80, 0.78, and 0.77, respectively. The seasonal investigation of aridity allowed to identify regions and seasons in which irrigation is needed for the main crops cultivated in the study area.

Algeria is amongst the African countries most affected by climate change impacts especially by drought which caused considerable economic losses in the past decades. In this paper, drought monitoring for the period between 1970 and 2011 was conducted in the Seybouse watershed by analysing annual rainfall data in terms of variability and trends along with the calculation of the standardized precipitation index (SPI). The results indicated important inter-annual rainfall fluctuation and a significant increasing trend. The estimated drought indices indicated that the Seybouse watershed experienced in the past a long dry period with a moderate severity followed by a long wet period at the majority of the study area. Moreover, the interpolation of the standardized precipitation indices (SPI) on the entire Seybouse basin in GIS allowed visualizing and evaluating the spatial-temporal evolution of drought in the region which should help the decision-makers in the management of water resources, agriculture and other activities that may be affected by drought.

The construction of dams in rivers can offer many advantages, however the consequences resulting from their failure could result in major damage, including loss of life and property destruction. To mitigate the threats of dam break it is essential to appreciate the characteristics of the potential flood in realistic manner. In this study an approach based on the integration of hydraulic modelling and GIS has been used to assess the risks resulting from a potential failure of Zardezas dam, a concrete dam located in Skikda, in the North East of Algeria. HEC-GeoRAS within GIS was used to extract geometric information from a digital elevation model and then imported into HEC-RAS. Flow simulation of the dam break was performed using HEC-RAS and results were mapped using the GIS. Finally, a flood hazard map based on water depth and flow velocity maps was created in GIS environment. According to this map the potential failure of Zardezas dam will place a large number in people in danger. The present study has shown that Application of Geographical Information System (GIS) techniques in integration with hydraulic modelling can significantly reduce the time and the resources required to forecast potential dam break flood hazard which can play a crucial role in improving both flood disaster management and land use planning downstream of dams.