Flooding is globally one of the most damaging natural hazard. Flood risk will most likely increase in the near future due to increases in flood frequency attributed to climate change and growth in population and wealth in flood prone areas. This growth in wealth and population is increasingly considered as a major driver for the increase in flood losses in the last decades. Floodplains are susceptible to floods, but historically people have always been settling in floodplains. The growth of population in floodplains, which is a substantial cause for increased flood risk, is essential to consider for decision making in floodplain development, as improper development increases flood exposure and aggravates flood risk. The science of socio-hydrology tries to capture the interaction between humans and floods in the floodplain. But, it is necessary to identify these mechanisms on a broader scale. A way of doing this, is to look at the development of floodplain population density over the years, but population data is not available on a long temporal scale. Therefore, Nighttime light data was used to model the gaps in the availability of population data. Nighttime light data data captures the illumination on earth, and is available on a large temporal and spatial scale, and has a high correlation with population data. However, the relationship between Nighttime light data and population data is not straightforward. This study tries to model a population proxy through the use of Nighttime light data data and explains when and why it does or does not work. Validation of the model shows that in some regions the predicted data is relatively precise, but ultimately, due to the lack of data, the accuracy is unknown. This study shows that understanding the behaviour of NTL is valuable, because it has the potential to map Socio-Economic variables in data-scarce areas.

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.