Assessment of channel shifting of Karnali Megafan in Nepal using remote sensing and GIS

River flow exhibits morphological changes over time. The shifting of river channels is a common natural phenomenon which often poses risk to life and property. Channel shifting is mostly associated..

Farmers’ Perception of Climate Change and Its Impacts on Agriculture

Climate change and climate variability drive rapid glacier melt and snowpack loss, extreme precipitation and temperature events, and alteration of water availability in the Himalayas. There is increasing observational evidence of climate change impacts on water resource availability and agricultural productivity in the central Himalayan region. Here, we assess the farmers’ perception of climate change and its impacts on agriculture in western Nepal. We interviewed 554 households and conducted eight focus group discussions to collect farmers’ perceptions of temperature and rainfall characteristics, water availability, onset and duration of different seasons, and the impacts of such changes on their lives and livelihoods. Our results indicate that the farmers’ perceptions of rising annual and summer temperatures are consistent with observations. Perception, however, contradicts observed trends in winter temperature, as well as annual, monsoon, and winter precipitation. In addition, farmers are increasingly facing incidences of extreme events, including rainfall, floods, landslides, and droughts. These hazards often impact agricultural production, reducing household income and exacerbating the economic impacts on subsistence farmers. Integrated assessment of farmers’ perceptions and hydrometeorological observations is crucial to improving climate change impact assessment and informing the design of mitigation and adaptation strategies

Application of hydrological model to simulate streamflow contribution on water balance in Himalaya river basin, Nepal

Hydrological models are widely used and often regarded as reliable tools for accurately estimating various components of the water balance. In a remote Himalayan catchment, such as Tamakoshi basin, where limited hydrometric dataset is available, such models often provide essential insights that are crucial to water researchers and planners. In this regard, we employed the semi-distributed HBV-light (version 4.0.0.25) hydrological model for glacierized Tamakoshi river basin and attempted to quantify various water balance components. For our model tests, using the daily streamflow records, we selected two distinct periods, i.e., 2004–2008 as a calibration period whilst 2011–2012 for model validation. Based on our findings, the model was able to reasonably predict the streamflow (validation efficiency: Nash-Sutcliffe Efficiency of 0.82 and percent bias −21%). At our site, HBV-light model predicted that the change in streamflow was mostly governed by monsoonal rain (62%) followed by baseflow (20%), glacier melt (13%) and snowmelt (5%). As expected, the streamflow peaked during the month of August where monsoon-induced rain and melting of glaciers significantly contributed to river flow. As a result, monsoon period showcased largest fluctuation in water storage while negligible change was observed during post-monsoon season. Nonetheless, our findings revealed that the baseflow contribution to streamflow was maximum during the month of October and lowest during February. Our findings indicated that the water balance of the Tamakoshi basin is largely influenced by monsoonal rain during June–September window as well as baseflow and glacier melt during the dry season. Runoff components contribution to streamflow was increasing but water storage changes was decreasing in recent decade (2011–2020). We believe our findings are crucial for future initiatives involving water resources, water-induced disaster management, and studies of climate change may benefit from the findings of this study, especially in a region with limited hydrometric data availability

Appraising the Potential of Using Satellite‐Based Rainfall Estimates for Evaluating Extreme Precipitation: A Case Study of August 2014 Event Across the West Rapti River Basin, Nepal

Heavy precipitation events are recurrently occurring in Nepal, affecting lives and properties every year, especially in the summer monsoon season (i.e., June-September). We investigated an extreme (heavy) precipitation event of August 2014 over the West Rapti River (WRR) Basin, Nepal. First, we forced a rainfall-runoff model with ground-based (gauge) hourly rainfall data of nine stations. Second, we validated against hourly water level at an outlet of the WRR Basin. This study then evaluated the performance of different satellite-based rainfall estimates (SREs) in capturing an extreme precipitation event. We considered the use of half-hourly data of Integrated Multi-satellite Retrievals for GPM (IMERG) (Early, Late, and Final versions), spatial resolution (10 km), and hourly data of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), spatial resolution (25 km), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS), spatial resolution (4 km). Also, we used 3 h data of Tropical Multi-satellite Precipitation Analysis (TMPA) product real-time (3B42RT), spatial resolution (25 km). In general, we find that all selected SREs depicted a similar pattern of extreme precipitation as shown by the gauge data on a daily scale. However, we find these products could not replicate precisely on a sub-daily scale. Overall, IMERG and TMPA showed a better performance than PERSIANN and PERSIANN-CCS. Finally, we corrected poor-performed SREs with respect to gauge data and also filled data gaps of gauge rainfall using the information of good-performed SREs. Our study reveals that there is a great challenge in local flood simulation employing SREs at high-temporal resolution in Nepal

The evaluation of climate change impact on hydrologic processes of a mountain river basin

The influence of climate change on the catchment-scale hydrologic processes can have a profound impact on river flow and the availability of fresh water. Here, we develop an integrated modeling framework to assess the near- and long-term hydrological response to climate change in a mountain river basin. The framework samples climate model outputs under different representative concentration pathways to force the calibrated hydrologic model and generate daily streamflow projections. We implement a framework in the Modi River basin, with an elevation ranging from 750 m to over 8000 m above sea level. Under the highest warming scenario, the mean annual precipitation and temperature are projected to vary to be as high as 4531 mm and 25.7 °C, respectively. The study results show that the future streamflow of the Modi River basin will increase during the latter time windows, i.e., far future (2075–2099) \u3e \u3e mid future (2050–2074) \u3e \u3e near future (2025–2049). Exploring how climate change can alter different hydrological processes can help improve the fundamental understanding of water balance and hydrologic controls, which are critical in ensuring the functionality of the natural ecosystems

A Model-Based Flood Hazard Mapping on the Southern Slope of Himalaya

Originating from the southern slope of Himalaya, the Karnali River poses a high flood risk at downstream regions during the monsoon season (June to September). This paper presents comprehensive hazard mapping and risk assessments in the downstream region of the Karnali River basin for different return-period floods, with the aid of the HEC-RAS (Hydrologic Engineering Center’s River Analysis System). The assessment was conducted on a ~38 km segment of the Karnali River from Chisapani to the Nepal–India border. To perform hydrodynamic simulations, a long-term time series of instantaneous peak discharge records from the Chisapani gauging station was collected. Flooding conditions representing 2-, 5-, 10-, 50-, 100-, 200-, and 1000-year return periods (YRPs) were determined using Gumbel’s distribution. With an estimated peak discharge of up to 29,910 m3/s and the flood depths up to 23 m in the 1000-YRP, the area vulnerable to flooding in the study domain extends into regions on both the east and west banks of the Karnali River. Such flooding in agricultural land poses a high risk to food security, which directly impacts on residents’ livelihoods. Furthermore, the simulated flood in 2014 (equivalent to a 100-YRP) showed a high level of impact on physical infrastructure, affecting 51 schools, 14 health facilities, 2 bus-stops, and an airport. A total of 132 km of rural–urban roads and 22 km of highways were inundated during the flood. In summary, this study can support in future planning and decision-making for improved water resources management and development of flood control plans on the southern slope of Himalaya