The increasing concentration of nitrogen compounds in the groundwater is of a growing concern in terms of human health and groundwater quality. Although an excess of nitrogen compounds in the groundwater of the Kathmandu Valley has been reported, the seasonal variations of the fate of the nitrogen compounds and their relationships to the subsurface sediments are unknown. In this study, spatially distributed shallow dug well samples were collected during both the dry and wet seasons of 2016, and the nitrogen compound, chloride (Cl⁻), and iron (Fe²⁺) concentrations were analyzed. Two shallow dug wells and one deep tube well were monitored monthly for 2 years. Although NH₄-N concentrations were similar in the clay-dominated areas during both seasons (1 and 0.9 mg-N/L), they were lower in the gravel-dominated areas during wet season (1.8 > 0.6 mg-N/L). The NO₃-N concentration differed depending upon the soil type which increased during the wet season (clay 4.9 < 13.6 mg-N/L and gravel 2.5 < 6.8 mg-N/L). The Fe²⁺ concentration, however, was low during the wet season (clay 2.7 > 0.4 mg/L and gravel 2.8 > 0.3 mg/L). Long-term analysis showed higher fluctuation of nitrogen compounds in the gravel-bearing areas than in the clay-bearing areas.

To develop effective groundwater pollution control strategies for the Kathmandu Valley, Nepal, seasonal variations in microbial quality and their underlying mechanisms must be understood. However, to date, there are no studies that address these topics. In this study, groundwater samples from dug wells were collected during the dry and wet seasons from 2009 to 2012, and Escherichia coli (E. coli) and total coliforms were analysed. Three wells were monitored each month for a year. Microbial concentrations in shallow groundwater were significantly higher during the wet season than during the dry season. Analyses of rainfall and E. coli concentrations in different seasons indicated that a high level of faecal material infiltration during the rainy season may have caused the seasonal variations in microbial quality. A moderate to strong relationship between E. coli concentrations and groundwater level suggested that the rise in groundwater levels during the wet season may be another reason for this variation. This long time-scale survey detected a significant decline in the microbial quality of shallow groundwater during the wet season as compared with the dry season. We propose that the infiltration of contaminants and change in groundwater level are the two probable mechanisms for the observed seasonal differences.

Shallow groundwater is the main water source among many alternatives in the Kathmandu Valley, Nepal, which has a rapidly growing population and intermittent piped water supply. Although human pathogens are detected in groundwater, its health effects are unclear. We estimated risk of diarrhoea from shallow groundwater use using quantitative microbial risk assessment. Escherichia coli, Giardia cyst and Cryptosporidium oocyst levels were analysed in dug and tube wells samples. E. coli concentrations were converted to those of enteropathogenic E. coli (EPEC). Risks from EPEC in dug wells and from Cryptosporidium and Giardia in both dug and tube wells were higher than the acceptable limit (<10⁻⁴ infections/person-year) for both drinking and bathing exposures. Risk from protozoan enteropathogens increased the total risk 10,000 times, indicating that ignoring protozoans could lead to serious risk underestimation. Bathing exposure considerably increased risk, indicating that it is an important pathway. Point-of-use (POU) water treatment decreased the risk six-fold and decreased risk overestimation. Because removal efficiency of POU water treatment has the largest impact on total risk, increasing the coverage and efficiency of POU water treatment could be a practical risk management strategy in the Kathmandu Valley and similar settings.

In Nepal, the number of diarrhoea hospitalizations in all ages is seriously high. According to the World Health Organization, diarrheal diseases can be substantially prevented through safe drinking water sources. In the Kathmandu Valley, because of the shortage of piped water, local residents use alternative water sources, such as groundwater, jars and tanker water. However, these alternative water sources can be contaminated. This study aimed to clarify the relationship between diarrhoea risk and the combinations of drinking water sources. A survey using multiple questionnaires on diarrhoea occurrence, water sources and water treatment was conducted three time between 2015 and 2016. The odds ratios (ORs) of developing diarrhoea were significantly high for drinking jar (OR 6.1) and tanker water (OR 8.4) compared with not drinking. The combined drinking of jar and tanker water obtained the 1 log higher OR compared with drinking only piped water. Conversely, drinking groundwater had a low OR, implying that the residents refrained from drinking polluted groundwater. In conclusion, diarrhoea occurrence was related not only to the level of water contamination, but also to a behavioural factor, i.e. people's careful management of the choice of multiple water sources.

Control of non-point source pollution, particularly in terms of nutrients, has advanced to a new phase where the identification of pollution sources and processes is necessary for complex river systems. The Soil and Water Assessment Tool (SWAT) is a process-based model that has been applied to manage aquatic environments in multiple river basins worldwide. In this study, nitrogen (N) loads from point and non-point pollution sources in the Cau River Basin, one of the three most polluted river basins in Vietnam, were simulated. Three scenarios with different combinations of pollution sources were developed to evaluate the major contributions of natural sources, cultivation, industry, households, craft villages and livestock in the study area. A set of hydrological and water quality parameters was successfully calibrated and validated with data observed over multiple years. The model results showed good performance in stream flow simulations at all four hydrological stations. The best performance for the N load simulation was under a scenario representing the dominant contribution of the non-point sources, which caused high amounts of N runoff and was likely triggered by rainfall. The modelling approach presented in this study provides an example for establishing a modelling platform for complex pollution systems.