This paper aims to turn complex groundwater data into comprehensible information by indexing the different factors numerically comparative to the standards of World Health Organization (WHO) to produce Water Quality Index (WQI). Water Quality Index (WQI) has been used to assess groundwater quality and Geographic Information Systems (GIS) has been used to create maps representing the spatial distribution of groundwater categories in Assiut governorate, Egypt. Water Quality Index has been computed by Un-weighted Arithmetic Water Quality Index (WQIUA) method and applied on 796 wells over eight years from 2006 to 2013. The results showed that WQIUA values for drinking purposes were high and most of them reached higher or close to 100, which indicated that the groundwater was polluted and unsafe for drinking. On the other hand, the quality index of groundwater for irrigation purposes in most of the study area ranges between 55.78 and 78.38 (poor and very poor category); this means that groundwater is moderately polluted and rather suitable for irrigation.

This paper aims to turn complex groundwater data into comprehensible information by indexing the different factors numerically comparative to the standards of World Health Organization (WHO) to produce Water Quality Index (WQI). Water Quality Index (WQI) has been used to assess groundwater quality and Geographic Information Systems (GIS) has been used to create maps representing the spatial distribution of groundwater categories in Assiut governorate, Egypt. Water Quality Index has been computed by Un-weighted Arithmetic Water Quality Index (WQIUA) method and applied on 796 wells over eight years from 2006 to 2013. The results showed that WQIUA values for drinking purposes were high and most of them reached higher or close to 100, which indicated that the groundwater was polluted and unsafe for drinking. On the other hand, the quality index of groundwater for irrigation purposes in most of the study area ranges between 55.78 and 78.38 (poor and very poor category); this means that groundwater is moderately polluted and rather suitable for irrigation.

This paper aims to turn complex groundwater data into comprehensible information by indexing the different factors numerically comparative to the standards of World Health Organization (WHO) to produce Water Quality Index (WQI). Water Quality Index (WQI) has been used to assess groundwater quality and Geographic Information Systems (GIS) has been used to create maps representing the spatial distribution of groundwater categories in Assiut governorate, Egypt. Water Quality Index has been computed by Un-weighted Arithmetic Water Quality Index (WQIUA) method and applied on 796 wells over eight years from 2006 to 2013. The results showed that WQIUA values for drinking purposes were high and most of them reached higher or close to 100, which indicated that the groundwater was polluted and unsafe for drinking. On the other hand, the quality index of groundwater for irrigation purposes in most of the study area ranges between 55.78 and 78.38 (poor and very poor category); this means that groundwater is moderately polluted and rather suitable for irrigation.

Two DRASTIC models have been used in this study, which are generic and pesticide to get the groundwater vulnerable levels to pollution in the Nile aquifer along Assiut governorate. Groundwater vulnerability maps were produced using Geographic Information Systems (GIS). It has been found in map of generic DRASTIC model that the most of the study area is covered by moderate vulnerable and high vulnerable; where 55.2 % of the area is moderately vulnerable and 35.4 % has high level of vulnerability. However in the vulnerability map generated by pesticide DRASTIC model, the results concluded that about 64% of the study area has an extreme to high vulnerability to contamination, 34.6% has a moderate vulnerability and small areas occupy about 1.4% and has a low vulnerability.

Two DRASTIC models have been used in this study, which are generic and pesticide to get the groundwater vulnerable levels to pollution in the Nile aquifer along Assiut governorate. Groundwater vulnerability maps were produced using Geographic Information Systems (GIS). It has been found in map of generic DRASTIC model that the most of the study area is covered by moderate vulnerable and high vulnerable; where 55.2 % of the area is moderately vulnerable and 35.4 % has high level of vulnerability. However in the vulnerability map generated by pesticide DRASTIC model, the results concluded that about 64% of the study area has an extreme to high vulnerability to contamination, 34.6% has a moderate vulnerability and small areas occupy about 1.4% and has a low vulnerability.

Two DRASTIC models have been used in this study, which are generic and pesticide to get the groundwater vulnerable levels to pollution in the Nile aquifer along Assiut governorate. Groundwater vulnerability maps were produced using Geographic Information Systems (GIS). It has been found in map of generic DRASTIC model that the most of the study area is covered by moderate vulnerable and high vulnerable; where 55.2 % of the area is moderately vulnerable and 35.4 % has high level of vulnerability. However in the vulnerability map generated by pesticide DRASTIC model, the results concluded that about 64% of the study area has an extreme to high vulnerability to contamination, 34.6% has a moderate vulnerability and small areas occupy about 1.4% and has a low vulnerability.

Two DRASTIC models have been used in this study, which are generic and pesticide to get the groundwater vulnerable levels to pollution in the Nile aquifer along Assiut governorate. Groundwater vulnerability maps were produced using Geographic Information Systems (GIS). It has been found in map of generic DRASTIC model that the most of the study area is covered by moderate vulnerable and high vulnerable; where 55.2 % of the area is moderately vulnerable and 35.4 % has high level of vulnerability. However in the vulnerability map generated by pesticide DRASTIC model, the results concluded that about 64% of the study area has an extreme to high vulnerability to contamination, 34.6% has a moderate vulnerability and small areas occupy about 1.4% and has a low vulnerability.

This work proposes a new optimization method called root tree optimization algorithm (RTO). The robustness and efficiency of the proposed RTO algorithm is validated on a 23 standard benchmark nonlinear functions and compared with well-known methods by addressing the same problem. Simulation results show effectiveness of the proposed RTO algorithm in term of solution quality and convergence characteristics. In order to evaluate the effectiveness of the proposed method, 3-unit, 30 Bus IEEE, 13-unit and 15-units are used as case studies with incremental fuel cost functions. The constraints include ramp rate limits, prohibited operating zones and the valve point effect. These constraints make the economic dispatch (ED) problem a non-convex minimization problem with constraints. Simulation results obtained by the proposed algorithm are compared with the results obtained using other methods available in the literature. Based on the numerical results, the proposed RTO algorithm is able to provide better solutions than other reported techniques in terms of fuel cost and robustness.

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