The population growth and urbanization are rapidly increasing in both central and peripheral areas of the Kathmandu Valley (KV) watershed. Land use/cover (LULC) change and climate variability/change are exacerbating the hydrological cycle in the KV. This study aims to evaluate the extent of changes in hydrology due to changes in climate, LULC and integrated change considering both factors, with KV watershed in central Nepal as a case study. Historical LULC data were extracted from satellite image and future LULC are projected in decadal scale (2020 to 2050) using CLUE-S (the Conversion of Land Use and its Effects at Small regional contest) model. Future climate is projected based on three regional climate models (RCMs) and two representative concentration pathways (RCPs) scenarios, namely, RCP4.5 and RCP8.5. A hydrological model in soil and water assessment tool (SWAT) was developed to simulate hydrology and analyze impacts in hydrology under various scenarios. The modeling results show that the river runoff for RCP4.5 scenarios is projected to increase by 37%, 21%, and 12%, respectively, for climate change only, LULC only, and integrated changes of both. LULC change resulted in an increase in average annual flow, however, a decrease in base-flow. Furthermore, the impacts of integrated changes in both LULC and climate is not a simple superposition of individual changes.

Kathmandu Upatyaka Khanepani Limited (KUKL) has planned to harness water from outside the valley from Melamchi as an inter-basin project to supply water inside the ring road (core valley area) of the Kathmandu Valley (KV). The project, called the “Melamchi Water Supply Project (MWSP)”, is expected to have its first phase completed by the end of September 2018 and its second phase completed by the end of 2023 to supply 170 MLD (million liters a day) through the first phase and an additional 340 MLD through the second phase. The area has recently faced a severe water deficit and KUKL’s existing infrastructure has had a limited capability, supplying only 19% of the water that is demanded in its service areas during the dry season and 31% during the wet season. In this context, this study aims to assess the temporal trends and spatial distribution of household water security index (WSI), defined as a ratio of supply to demand for domestic water use for basic human water requirements (50 L per capita per day (lpcd)) and economic growth (135 lpcd) as demand in pre- and post-MWSP scenarios. For this purpose, data on water demand and supply with infrastructure were used to map the spatial distribution of WSI and per capita water supply using ArcMap. Results show a severe water insecurity condition in the year 2017 in all KUKL service areas (SAs), which is likely to improve after completion of the MWSP. It is likely that recent distribution network and strategies may lead to inequality in water distribution within the SAs. This can possibly be addressed by expanding existing distribution networks and redistributing potable water, which can serve an additional 1.21 million people in the area. Service providers may have to develop strategies to strengthen a set of measures including improving water supply infrastructures, optimizing water loss, harnessing additional water from hills, and managing water within and outside the KUKL SAs in the long run to cover the entire KV.

This study is the first to assess land subsidence in the Kathmandu Valley, Nepal. Land subsidence simulations were based on a fully calibrated groundwater (GW) flow model developed using a coupled surface–subsurface modelling system. Subsidence is predicted to occur as a result of deep aquifer compaction due to excessive GW abstraction. The north and north-east areas at the periphery of the GW basin are hotspots for this subsidence. The estimated subsidence is most sensitive to changes in land cover within the recharge areas. The model shows the Melamchi water supply project assists in the control of subsidence to some extent. In the absence of land subsidence measurements, this paper highlights the location and the potential levels of the subsidence hazard which will be useful for hazard prevention management. Additionally, this work provides a basis to design field investigations, monitoring networks for land subsidence and upgrading the present GW monitoring network. Although the study has presented a preliminary analysis, a more comprehensive model inclusive of clay subsidence is required to address the subsidence vulnerability of the central densely populated core of the valley, which reflects the need for a comprehensive database of the hydrogeology in the valley.

Intense monsoonal rain is one of the major triggering factors of floods and mass movements in Nepal that needs to be better understood in order to reduce human and economic losses and improve infrastructure planning and design. This phenomena is better understood through intensity-duration-frequency (IDF) relationships, which is a statistical method derived from historical rainfall data. In Nepal, the use of IDF for disaster management and project design is very limited. This study explored the rainfall variability and possibility to establish IDF relationships in data-scarce situations, such as in the Central-Western hills of Nepal, one of the highest rainfall zones of the country (~4500 mm annually), which was chosen for this study. Homogeneous daily rainfall series of 8 stations, available from the government’s meteorological department, were analyzed by grouping them into hydrological years. The monsoonal daily rainfall was disaggregated to hourly synthetic series in a stochastic environment. Utilizing the historical statistical characteristics of rainfall, a disaggregation model was parameterized and implemented in HyetosMinute, software that disaggregates daily rainfall to finer time resolution. With the help of recorded daily and disaggregated hourly rainfall, reference IDF scenarios were developed adopting the Gumbel frequency factor. A mathematical model [i = a(T)/b(d)] was parameterized to model the station-specific IDF utilizing the best-fitted probability distribution function (PDF) and evaluated utilizing the reference IDF. The test statistics revealed optimal adjustment of empirical IDF parameters, required for a better statistical fit of the data. The model was calibrated, adjusting the parameters by minimizing standard error of prediction; accordingly a station-specific empirical IDF model was developed. To regionalize the IDF for ungauged locations, regional frequency analysis (RFA) based on L-moments was implemented. The heterogeneous region was divided into two homogeneous sub-regions; accordingly, regional L-moment ratios and growth curves were evaluated. Utilizing the reasonably acceptable distribution function, the regional growth curve was developed. Together with the hourly mean (extreme) precipitation and other dynamic parameters, regional empirical IDF models were developed. The adopted approach to derive station-specific and regional empirical IDF models was statistically significant and useful for obtaining extreme rainfall intensities at the given station and ungauged locations. The analysis revealed that the region contains two distinct meteorological sub-regions highly variable in rain volume and intensity.