Like other cities in Kathmandu Valley, Bhaktapur faces rapid urbanisation and population growth. Unsafe, new settlements are partly located at the floodplains and the government lags behind in implementing proper land-use policy to control unrestrained settlement. The rivers are not only constrained by uncontrolled settlements, but also by insufficient width and freeboard of bridges, and waste blockages causes problems. Combined with more extreme rain events during the monsoon due to climate change, flooding has become a reoccurring problem in Bhaktapur. To gain better understanding of the river and the corresponding flood risk, historical data is essential. Unfortunately, historical databases of water levels are non-existent for this river. Only starting from monsoon 2019, water levels and discharge have been measured on a regular basis. To reconstruct the missing historical data for a return level analysis, this research introduces the Classical Model for Structured Expert Judgment (SEJ) in combination with citizen science (CS). The objective of this research was to use Structured Expert Judgment in a flood risk analysis for the city of Bhaktapur. As a result of using SEJ, we were able to obtain sufficient water level data and estimate the return levels of extreme water levels of Hanumante river by fitting a Generalized Extreme Value distribution (GEV). This eventually led to a reverse Weibull fit, which in this case does not seem accurate. This research discusses in detail the advantages and issues of using Structured Expert Judgement in situations like this and also discusses the reliability of the results.

Kathmandu is a prime example of a city exhibiting both rapid metropolitan region expansion and a population boom. This growth leads to a water stress and pollution of the surface and groundwater. The lack of proper waste management and sanitation results in the ongoing deterioration of the water quality in the Kathmandu Valley. The situation is worsened by the lack of a complete and safe drinking water network leading citizens to pivot on conventional water sources like stone spouts and bore wells. Consequently, groundwater extraction, from the aquifer under the Kathmandu Valley, is expected to keep increasing and the groundwater table to drop as the recharge is less than the extraction rate. This research aims to address the influences of land-use on the quantity and quality of water sources in the Kathmandu Valley and how the necessary data can be collected by citizen science in the future. The fieldwork took place in August 2017 when groundwater level, water quality and land-use data were collected from seven watersheds within the Kathmandu Valley in Nepal. At the same time, existing citizen science precipitation data were processed and juxtaposed with respective satellite data, namely IMERG GPM. On the one hand, the results confirm our initial assumption that the quality of the river water dramatically deteriorates (except for nitrite, nitrate and phosphate) while flowing through the agricultural and urban areas. Another observation is that spout water quality (except E. coli, turbidity and iron) is also negatively influenced by human activities. On the other hand, there is no clear link between land-use and wells’ water quality. A strange finding is that spouts and wells water quality do not behave similarly showcasing that they do not originate from the same aquifer. A health risk analysis was conducted with the results indicating that some water quality parameters have values exceeding the WHO standards. Regarding the option of implementing satellite data to facilitate citizen science, the contingency analysis shows that satellite products can detect the general temporal precipitation pattern although they perform poorly when it comes to estimating the correct amounts of rainfall. An extended network of rain gauges within the Kathmandu Valley is vital to establish a strong linear relationship between ground and satellite data which is, in turn, essential to enable GPM to enhance the temporal resolution of the citizen science measurements. Furthermore, the implementation of land-use and water quality measurements into citizen science shows increasing potential especially when taking into account the contribution of ODK. The accuracy of the citizen science ground truthing was found to be 33% when compared to the experts. Proper training of the citizen scientists is essential to improve performance. During research temperature, EC and turbidity were labelled as indication parameters. Those parameters are used to indicate the range of other water quality parameters which cannot be measured easily. The indication parameters, however, can be measured with affordable equipment and together with water quality strips prove to be powerful tools in the hands of citizen science. Finally, the groundwater recharge for the monsoon period was determined, but it is expected to be drastically reduced the rest of the year. A solid conclusion about the relation between recharge and land-use can’t be made unless a more substantial number of wells is regularly sampled.

The Kathmandu Valley in Nepal is facing the combined effects of population growth, rapid urbanization, economic development, and climate change. This results in serious water management challenges: growing freshwater demands, declining water tables, drying of streams, and deteriorating water quality. Insufficient surface water supplies have led to increased reliance on groundwater, especially during the dry winter and pre-monsoon seasons (November - May). Despite groundwater’s importance, it is sparsely measured, poorly understood, and insufficiently managed. As it is difficult and costly to measure all groundwater extractions in the Valley, a water balance approach is an alternative method to estimate total net groundwater pumping. Therefore, the aim of this research was to develop and evaluate potential methods for quantifying total pre-monsoon baseflow supplies by extrapolating baseflow measurements of a subsample of watersheds to unmeasured watersheds. Estimated baseflow was used, together with other water balance fluxes and changes in storage, to evaluate net groundwater pumping in the Valley. Three different methods were used: (1) Spatial Analysis, (2) Regression Model, and (3) Black Box (machine learning). All methods relied on streamflow data from 2017 to 2019, collected by citizen scientists from S4W-Nepal. Based on the three methods we presented, we cautiously conclude that it is possible to determine the pre-monsoon baseflow contributions from a sub-sample of head water catchments. Total baseflow estimates for the Valley using Spatial Analysis, Regression Model, Black Box were 2.32, 2.30, 2.65 m3/s respectively. These values show orders of magnitude that correspond with expected values. By using the average baseflow values of all three methods, we were able to close the water balance and make an assumption for the net groundwater pumping in the Valley. Based on a population of 3.5 million, a net groundwater extraction of 96 L/person/day during pre-monsoon was found. This striking outcome emphasizes the need for more discharge and groundwater extraction measurements, to decrease the uncertainties and to refine the methods.

Globally, growing demand for fresh water and declining water availability puts significant pressure on water resources. Due to rapid urbanization and insufficient water resource planning and waste water management, the Kathmandu Valley (Valley) is facing both a water quantity and quality crisis. Annually, groundwater extractions in the Valley significantly exceed recharge rates, resulting in a serious groundwater table declines. While streams often constitute an important linkage between surface water and groundwater systems, from both a quantity and quality perspective, understanding stream-aquifer interactions in the Valley are limited. To improve this understanding, we performed topographic surveys of water levels, and measured water quality, in streams and adjacent hand dug wells (shallow aquifer) in three watersheds (total of 16 stream-well pairs) during 2018 pre-monsoon (April and May) and eight watersheds (including the same three from pre-monsoon; total of 35 stream-well pairs) during 2018 post-monsoon (September and October). In pre-monsoon, we found 88 % of water levels in wells lower than adjacent streams with an average of -0.82 m, indicating a loss of stream water to the aquifer. However, in post-monsoon 69 % of wells had water levels higher than adjacent streams with an average water level difference of 0.44 m, indicating that monsoon rainfall recharged the shallow aquifer, causing streams to transition from losing to gaining. No recurring trend in water level difference was seen longitudinally from upstream to downstream. Our results indicate statistically significant correlations between electrical conductivity, ammonia, chloride, hardness, and alkalinity measured in streams and adjacent wells. Both stream and groundwater quality of adjacent wells depletes longitudinally from upstream to downstream. In order to prevent further deterioration of groundwater resources, stream-aquifer interactions should be taken into account for sustainable water resource management. Further research is essential to quantify the groundwater flow, and to investigate the long-term trends and reversibility of the problem. Our findings highlight the importance of managing streams and aquifers as a single integrated resource, from both a water quantity and quality perspective. For example, improper waste management in the Valley’s streams is having a clear and negative impact on the shallow aquifer. The population of Kathmandu will become increasingly dependent on the government for water supply, potentially increasing the cost of living.