Water quality index (WQI) is a mathematical tool used to transform large quantities of water quality data into a single number which present water quality level. The aim of the present study is to evaluate the quality of Koudiat Medouar Dam in Batna (Algeria) to assess its suitability for drinking purposes. Samples were assessed for ten (10) physicochemical settings namely pH, electrical conductivity, total hardness, nitrate, sulphate, chloride, calcium, magnesium, dissolved oxygen and turbidity. The calculation of WQI was done via weighted arithmetic index method. The WQI values ranged from 99.097 to 174.92 during 2015. It reflected that the water samples were in February in the range of very poor quality and ranged to be in unsuitable for drinking rang in the all other months. The WQI of the present study reveals dam water is contaminated and not suitable for drinking purpose without giving treatment.
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.
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