Detection and mapping of water pollution variation in the Nile Delta using multivariate clustering and GIS techniques

Temporal and spatial variations of surface water quality in the Nile River of Damietta Region, Egypt

Temporal/spatial variations of surface water quality were examined for the Nile River in the Damietta region where it serves as the major source of water for the inhabitants of Damietta Governorate. A total of 32 water quality parameters were monitored at six sampling sites for 12 months from February 2016 to January 2017. Higher values of chemical oxygen demand (COD), biological oxygen demand (BOD), heavy metals, and nutrients were observed upstream. About ~ 70% of the total variance in observations was explained by five main influences using factor analysis. The first factor (24.6% of the variance) was indicative of the mixed sources of natural and anthropogenic inputs. The second (nutritional) and the third (organic) factors were mainly controlled by the discharges from agricultural and domestic sources, respectively. Human activities and natural processes controlled the fourth and fifth factors. Only 11 parameters (K, temperature, COD, HPC, total hardness, DO, NO₂, Na, TDS, Cl, and EC) were necessary for distinguishing temporal variations according to Discriminant analysis (DA). Seven parameters (BOD, PO₄, SiO₃, Al, Turbidity, Fe, and Chlorophyll-a) were the most important variables responsible for spatial variations. Using the results we developed a water quality index (WQI) using only those parameters identified as important. All water quality parameters were below the permissible limits except for turbidity according to the World Health Organization standards, BOD and COD according to the Egyptian regulations. The calculated WQI values ranged between 12.73 and 33.73. According to these values, the Nile River Damietta branch represents a good to an excellent source of drinking water for entering secondary treatment.

Using grey clustering to evaluate nitrogen pollution in estuaries with limited data

Many techniques exist for the evaluation of nutrient pollution, but most of them require large amounts of data and are difficult to implement in countries where accurate water quality information is not available. New methods to manage subjectivity, inaccuracy or variability are required in such environments so that water managers can invest the scarce economic resources available to restore the most vulnerable areas. We propose a new methodology based on grey clustering which classifies monitoring sites according to their need for nitrogen pollution management when only small amounts of data are available. Grey clustering focuses on the extraction of information with small samples, allowing management decision making with limited data. We applied the entropy-weight method, based on the concept of information entropy, to determine the clustering weight of each criterion used for classification. In order to reference the pollution level to the anthropogenic pressure, we developed two grey indexes: the Grey Nitrogen Management Priority index (GNMP index) to evaluate the relative need for nitrogen pollution management based on a spatiotemporal analysis of total nitrogen concentrations, and the Grey Land Use Pollution index (GLUP index), which evaluates the anthropogenic pressures of nitrogen pollution based on land use. Both indexes were then confronted to validate the classification. We applied the developed methodology to eight estuaries of the Southern Gulf of Mexico associated to beaches, mangroves and other coastal ecosystems which may be threatened by the presence of nitrogen pollution. The application of the new method has proved to be a powerful tool for decision making when data availability and reliability are limited. This method could also be applied to assess other pollutants.

Applying Quantitative Microbial Risk Assessment Model in Developing Appropriate Standards for Irrigation Water

This study aimed to apply a quantitative microbial risk assessment (QMRA) model to estimate the annual risk probability of Salmonella infection associated with the consumption of crops, which were irrigated with raw wastewater abstracted by farmers without official permission. Data generated from the model were used to propose realistic standards for Salmonella in irrigation water needed for safe crop production. Results demonstrated the presence of total coliforms, fecal coliforms, fecal streptococci, and Salmonella in wastewater samples. Salmonella was recorded on lettuce and spinach in 3 different harvesting events, although it was not found in data obtained for parsley plant. The QMRA scenario included surface irrigation, consumption of raw crops, and 1-day withholding period before harvest. The annual risk probability of Salmonella infection for consumers exceeded the target tolerable risk (7.7 × 10-4 ) for investigated crops. The Pearson's correlation coefficient between different annual risk probabilities showed significant correlation (p < 0.05). The levels of risk posed from spinach and lettuce were roughly similar, although they tended to be higher for lettuce. The optimum concentrations of Salmonella in irrigation water needed to satisfy the World Health Organization guidelines of disease burden (disability-adjusted life years 10-6 ) per person per year ranged from 34 to 119 via multiple-tube fermentation technique/100 mL, for spinach and lettuce plants, respectively. The study concluded that unofficial reuse of wastewater in irrigation is a principle route for crop contamination. Water quality monitoring programs should be integrated with QMRA investigations for better estimation of risk level. The fit parameters used could be tailored to cover a wide array of local situations in different countries. Models applied for viruses, helminths, and bacteria other than Salmonella are encouraged in future studies. Integr Environ Assess Manag 2020;16:353-361. © 2019 SETAC.

Spatio-temporal variability of dissolved organic nitrogen (DON), carbon (DOC), and nutrients in the Nile River, Egypt

Increases in human activity have resulted in enhanced anthropogenic inputs of nitrogen (N) and carbon (C) into the Nile River. The Damietta Branch of the Nile is subject to inputs from industrial, agricultural, and domestic wastewater. This study investigated the distribution and seasonality of dissolved organic nitrogen (DON), dissolved organic carbon (DOC), and nutrients in the Nile Damietta Branch. Water samples were collected from 24 sites between May 2009 and February 2010. Dissolved organic nitrogen concentrations averaged 251 ± 115 μg/l, with a range of 90.2-671 μg/l, and contributed 40.8 ± 17.7 % to the total dissolved nitrogen (TDN) pool. Relative to autumn and winter, DON was a larger fraction of the TDN pool during spring and summer indicating the influence of bacterioplankton on the nitrogen cycle. Concentrations of DOC ranged from 2.23 to 11.3 mg/l with an average of 5.15 ± 2.36 mg/l, reflecting a high organic matter load from anthropogenic sources within the study area, and were highest during autumn. Higher values of biochemical oxygen demand (BOD), chemical oxygen demand (COD), DON, nitrate, and phosphate occurred downstream of the Damietta Branch and were probably due to anthropogenic inputs to the Nile from the Damietta district. A bacterial incubation experiment indicated that 52.1-95.0 % of DON was utilized by bacteria within 21 days. The decrease in DON concentration was accompanied by an increase in nitrate concentration of 54.8-87.3 %, presumably through DON mineralization. Based on these results, we recommend that water quality assessments consider DON and DOC, as their omission may result in an underestimation of the total organic matter load and impact.

Interdisciplinary assessment of sea-level rise and climate change impacts on the lower Nile delta, Egypt

CLImate-induced changes on WAter and SECurity (CLIWASEC) was a cluster of three complementary EC-FP7 projects assessing climate-change impacts throughout the Mediterranean on: hydrological cycles (CLIMB - CLimate-Induced changes on the hydrology of Mediterranean Basins); water security (WASSERMed - Water Availability and Security in Southern EuRope and the Mediterranean) and human security connected with possible hydro-climatic conflicts (CLICO - CLImate change hydro-COnflicts and human security). The Nile delta case study was common between the projects. CLIWASEC created an integrated forum for modelling and monitoring to understand potential impacts across sectors. This paper summarises key results from an integrated assessment of potential challenges to water-related security issues, focusing on expected sea-level rise impacts by the middle of the century. We use this common focus to illustrate the added value of project clustering. CLIWASEC pursued multidisciplinary research by adopting a single research objective: sea-level rise related water security threats, resulting in a more holistic view of problems and potential solutions. In fragmenting research, policy-makers can fail to understand how multiple issues can materialize from one driver. By combining efforts, an integrated assessment of water security threats in the lower Nile is formulated, offering policy-makers a clearer picture of inter-related issues to society and environment. The main issues identified by each project (land subsidence, saline intrusion - CLIMB; water supply overexploitation, land loss - WASSERMed; employment and housing security - CLICO), are in fact related. Water overexploitation is exacerbating land subsidence and saline intrusion, impacting on employment and placing additional pressure on remaining agricultural land and the underdeveloped housing market. All these have wider implications for regional development. This richer understanding could be critical in making better policy decisions when attempting to mitigate climate and social change impacts. The CLIWASEC clustering offers an encouraging path for the new European Commission Horizon 2020 programme to follow.

Optimization of integrated water quality management for agricultural efficiency and environmental conservation

The scarcity of water resources in Egypt has necessitated the use of various types of lower quality water. Agricultural drainage water is considered a strategic reserve for meeting increasing freshwater demands. In this study, a novel model series was applied to a drainage basin in the Nile Delta to optimize integrated water quality management for agriculture and the aquatic environment. The proposed model series includes a waste load allocation model, an export coefficient model, a stream water quality model, and a genetic algorithm. This model series offers an optimized solution for determining the required removal levels of total suspended solids (TSS), the chemical oxygen demand (COD) at point and non-point pollution sources, and the source flows that require treatment to meet a given water quality target. The model series was applied during the summer and winter to the El-Qalaa basin in the western delta of the Nile River. Increased pollutant removal and treated fractions at point and non-point sources reduced violations of the TSS standards from 732.6 to 238.9 mg/L in summer and from 543.1 to 380.9 mg/L in winter. Likewise, violations of the COD standards decreased from 112.4 mg/L to 0 (no violations) in summer and from 91.7 mg/L to no violations in winter. Thus, this model is recommended as a decision support tool for determining a desirable waste load allocation solution from a trade-off curve considering costs and the degree of compliance with water quality standards.