Groundwater is a major water resource in the North Chengdu Plain, China. The research objective is to determine the quality and suitability of groundwater for drinking purposes within the vicinity of a shallow, unconsolidated aquifer of Quaternary age. In this study, a detailed investigation was conducted to define the hydrochemical characteristics that control the quality of groundwater, based on traditional methods. Considering the uncertainties linked with water resources and the environmental complications, the fuzzy logic method was used in the determination of groundwater quality for more precise findings that support decision-making. To achieve such an objective, sixteen water quality guidelines were used to determine groundwater quality status in six selected wells. The results showed that the groundwater is neutral, very hard, and fresh in nature. Dominating cations and anions are in the order of Ca ${}^{2+}$ > Na ${}^{+}$ > Mg ${}^{2+}$ > K ${}^{+}$ and HCO ${}_3^{-}$ > SO ${}_4^{2-}$ > Cl ${}^{-}$ . The Piper trilinear diagram demonstrates that the hydrochemical facies of groundwater are mostly of Ca-HCO ${}_3$ type. Statistical analysis denotes a positive correlation between most of the chemical parameters. The study took the results of the fuzzy logic evaluation method into consideration, to classify the samples into five groups according to the Chinese groundwater quality standard (GB/T 14848-93) for their suitability for domestic use. The results demonstrated that the quality of the groundwater samples is within grade II and III, and is suitable for drinking purposes. The comprehensive evaluation of groundwater quality is critical to aid sensitive policy decisions, and the proposed approach can guarantee reliable findings to that effect. The results of this study would also be helpful to future researches related to groundwater quality assessment.

The present study proposes a new approach for indexing heavy metals ions to examine groundwater quality in North Kurdufan Province, Sudan. The new approach is developed based on the most frequently used methods for indexing heavy metals pollution in water. It is created in order to avoid the weaknesses of the current indexing systems. As per the new indexing approach, heavy metal contamination in water samples is evaluated by two types of indices: the negative evaluation index (NEI) and positive evaluation index (PEI). The water worthiness is assessed based on a pair of indices, NEI and PEI. Water quality increases with the decrease of PEI and NEI values. NEI indicates the contribution of heavy metals with a concentration not exceeding the highest desirable limit ( $I_i$ ) in the water sample, while vice versa regarding the PEI. If all heavy metals concentrations in the water sample do not exceed $I_i$ , the sum of NEI should be less than zero, but not less than −100, implying that the sum of PEI will be zero. When all heavy metals concentration exceeds $I_i$ , the sum of NEI should be equal to zero, and PEI will be greater than zero. The results of the newly proposed approach have been discussed and compared with the existing indexing methods as regards to the best and worst samples. The spatial distribution of NEI and PEI are in complete agreement with the metals spatial distribution. The comparison result showed that the new index is robust, with fair calculations, and gives the best classification of groundwater quality.

Deterioration of groundwater quality due to drastic human interventions is rising at an alarming rate particularly in lower- and middle-income countries. Yet, limited research effort has been devoted to monitoring and ascertaining groundwater quality. The present study develops a comprehensive irrigation water quality index (IWQI) for rating water quality of shallow and deep aquifers in North Kurdufan province, Sudan. The new approach is developed to overcome the deficiencies of the existing irrigation indices and coming up with a unified decision for classifying water quality for irrigation purposes. Because of these indices like permeability index (PI), sodium absorption ratio (SAR), etc., depending on specific elements, entirely subjective, as well as the great variations in their results, particularly when classifying water quality. Thus, IWQI is created based on eight indices that are generally used to evaluate irrigation water quality, plus three physicochemical parameters have been proven an impact on water quality. The analytic hierarchy process (AHP) is applied to minimize the subjectivity at assign parameter weights under multiple criteria decision analysis tools (MCDA). The spatial distribution of IWQI agrees with the spatial distribution of the most parameters. The results of our approach reveal that the majority of samples are suitable for irrigation uses for both aquifers except few wells in the confined aquifer. Also, noted that there are very variations in the irrigation indices results for classifying water quality. The comparison result showed that the new index robust, fair calculations and has best classifying of water quality.

To improve the management of operation system for the Roseires reservoir it is necessary to know the hydrological system of the Blue Nile river, which is the main water source of the reservoir. In this work, a Modified Thomas Fiering model for generating and forecasting monthly flow is used. The methodological procedure is applied on the data obtained at the gauging station of Eldeim in Blue Nile, Sudan. The study uses the monthly flows data for years 1965 to 2009. After estimation the model parameters, the synthetic time series of monthly flows are simulated. The results revealed that the model maintained most of the basic statistical descriptive parameters of historical data. Also, the Modified Thomas Fiering model is applied to predict the values of the next fifty-five years, with excellent results that conserved most basic statistical characteristics of runoff historical series. The Modified Thomas Fiering model is able to realistically reconstruct and predict the annual data and shows promising statistical indices.