Assessing Climate Change Trends and Their Relationships with Alpine Vegetation and Surface Water Dynamics in the Everest Region, Nepal

The Himalayas, especially the Everest region, are highly sensitive to climate change. Although there are research works on this region related to cryospheric work, the ecological understandings of the alpine zone and climate impacts are limited. This study aimed to assess the changes in surface water including glacier lake and streamflow and the spatial and temporal changes in alpine vegetation and examine their relationships with climatic factors (temperature and precipitation) during 1995–2019 in the Everest region and the Dudh Koshi river basin. In this study, Landsat time-series data, European Commission’s Joint Research Center (JRC) surface water data, ECMWF Reanalysis 5th Generation (ERA5) reanalysis temperature data, and meteorological station data were used. It was found that the glacial lake area and volume are expanding at the rates of 0.0676 and 0.0198 km3/year, respectively; the average annual streamflow is decreasing at the rate of 2.73 m3/s/year. Similarly, the alpine vegetation greening as indicated by normalized difference vegetation index (NDVI) is increasing at the rate of 0.00352 units/year. On the other hand, the annual mean temperature shows an increasing trend of 0.0329 °C/year, and the annual precipitation also shows a significant negative monotonic trend. It was also found that annual NDVI is significantly correlated with annual temperature. Likewise, the glacial lake area expansion is strongly correlated with annual minimum temperature and annual precipitation. Overall, we found a significant alteration in the alpine ecosystem of the Everest region that could impact on the water–energy–food nexus of the Dudh Koshi river basin.

Estimating and Analyzing the Spatiotemporal Characteristics of Crop Yield Loss in Response to Drought in the Koshi River Basin, Nepal

The quantitative assessment of crop yield loss in response to drought is crucial in the development of the agricultural sector to improve the productivity. This study estimated and analyzed the spatiotemporal patterns of crop yield loss in response to drought using the Lagrange interpolation method, wavelet analysis, and sequential Mann-Kendall test in the mountain, hill, and Terai (low-land) regions of Nepal's Koshi River Basin from 1987 to 2016. According to the findings, average crop yield loss was common after 2000, with the Terai, hill, and mountain experiencing the greatest loss in maize, rice, and wheat, respectively. Average annual rice and wheat yield losses rate were highest in the mountains, while maize yield losses were highest in the Terai. There was an abrupt change in wheat yield loss in the mountain, with significant increasing trend. In the hill, significant increment in maize and wheat yield loss, and decrement in rice yield loss, were observed. Between 1987 and 2016, periodic variations of maize, rice, and wheat revealed significant yield loss after 2000. The characteristics of the first and second key periods for crop yield loss demonstrated variation period which predicted that crop yield loss would either enter high yield loss or low yield loss period shortly after 2016. The findings of the study provide a detailed intervention in assessing crop yield loss at the river basin level and can provide an important pathway for developing a crop yield loss mitigation plan in the agricultural sector to achieve self-reliance and sustainable agricultural productivity.

Evaluation of the CMIP5 general circulation models for simulating the precipitation and temperature of the Koshi River Basin in Nepal

This study evaluates the performance of 12 different general circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to simulate precipitation and temperature in the Koshi River Basin, Nepal. Four statistical performance indicators: correlation coefficient, normalised root-mean-square deviation (NMRSD), absolute NMRSD, and average absolute relative deviation are considered to evaluate the GCMs using historical observations. Seven different climate indices: consecutive dry days, consecutive wet days, cold spell duration index, warm spell duration index, frost days, very wet days, and simple daily intensity index are considered to identify the most suitable models for the basin and future climate impact assessment studies. Weights for each performance indicator are determined using the entropy method, with compromise programming applied to rank the GCMs based on the Euclidian distant technique. The results suggest that CanESM2 and CSIRO-MK3.6.0 are the most suitable for predicting extreme precipitation events, and BCC-CSM 1.1, CanESM2, NorESM1-M, and CNRM-CM5 for extreme temperature events in Himalayan river basins. Overall, IPSL-CM5A-MR, CanESM2, CNRM-CM5, BCC-CSM 1.1, NorESM1-M, and CSIRO-Mk3.6.0 are deemed suitable models for predicting precipitation and temperature in the Koshi River Basin, Nepal.

Climate Change and Its Impacts on Farmer’s Livelihood in Different Physiographic Regions of the Trans-Boundary Koshi River Basin, Central Himalayas

The impact of climate change on farmers’ livelihoods has been observed in various forms at the local and regional scales. It is well known that the Himalayas region is affected by climate change, as reflected in the basic knowledge of farmers in the region. A questionnaire-based survey involving a total of 747 households was conducted to gather information on climate change and its impact, where the survey addressed four physiographic regions of the trans-boundary Koshi River Basin (KRB). Moreover, climatic data were used to calculate climatic trends between 1980 and 2018. The Mann–Kendall trend test was performed and the Sen’s slope calculated to analyze the inter-annual climatic trends over time. The survey noted that, for the basin, there was an increase in temperature, climate-induced diseases of crops, an increase in the frequency of pests as well as drought and floods and a decrease in rainfall, all which are strong indicators of climate change. It was perceived that these indicators had adverse impacts on crop production (89.4%), human health (82.5%), livestock (68.7%) and vegetation (52.1%). The observed climatic trends for all the physiographic regions included an increasing temperature trend and a decreasing rainfall trend. The rate of change varied according to each region, hence strongly supporting the farmers’ local knowledge of climate change. The highest increasing trend of temperature noted in the hill region at 0.0975 °C/a (p = 0.0002) and sharpest decreasing trend of rainfall in the mountain region by −10.424 mm/a (p = 0.016) between 1980 and 2018. Formulation of suitable adaptation strategies according to physiographic region can minimize the impact of climate change. New adaptation strategies proposed include the introduction of infrastructure for irrigation systems, the development of crop seeds that are more tolerant to drought, pests and disease tolerance, and the construction of local hospitals for the benefit of farming communities.

Space–time variability in soil moisture droughts in the Himalayan region

Soil water is a major requirement for biomass production and, therefore, one of the most important factors for agriculture productivity. As agricultural droughts are related to declining soil moisture, this paper examines soil moisture drought in the transboundary Koshi River basin (KRB) in the central Himalayan region. By applying the J2000 hydrological model, daily spatially distributed soil moisture is derived for the entire basin over a 28-year period (1980–2007). A multi-site and multi-variable approach – streamflow data at one station and evapotranspiration data at three stations – was used for the calibration and validation of the J2000 model. In order to identify drought conditions based on the simulated soil moisture, the soil moisture deficit index (SMDI) was then calculated, considering the derivation of actual soil moisture from long-term soil moisture on a weekly timescale. To spatially subdivide the variations in soil moisture, the river basin is partitioned into three distinct geographical regions, namely trans-Himalaya, the mountains, and the plains. Further, the SMDI is aggregated temporally to four seasons – winter, pre-monsoon, monsoon, and post-monsoon – based on wetness and dryness patterns observed in the study area. This has enabled us to look at the magnitude, extent, and duration of soil moisture drought. The results indicated that the J2000 model can simulate the hydrological processes of the basin with good accuracy. Considerable variation in soil moisture was observed in the three physiographic regions and across the four seasons due to high variation in precipitation and temperature conditions. The year 1992 was the driest year and 1998 was the wettest at the basin scale in both magnitude and duration. Similarly, the year 1992 also has the highest number of weeks under drought. Comparing the SMDI with the standardised precipitation index (SPI) suggested that SMDI can reflect a higher variation in drought conditions than SPI. Our results suggested that both the occurrence and severity of droughts have increased in the Koshi River basin over the last 3 decades, especially in the winter and pre-monsoon seasons. The insights provided into the frequency, spatial coverage, and severity of drought conditions can provide valuable contributions towards an improved management of water resources and greater agricultural productivity in the region.

Macropore domination in runoff generation process: A case study by hydrological modelling in Hilly Watersheds of Koshi River Basin, Himalaya

<p>A recent initiative by the hydrologic community identified processes that control hillslope-riparian-stream-groundwater interactions as one of the major unsolved scientific problems in Hydrology. It is a long-time argument among hydrologists whether to eliminate the minor details from field-based costing a lot of time, effort, and resources to understand the hydrological process in watershed scale. The modelling approaches are helpful is these cases by focusing on the dominant controllers and might/might'nt bypassing the implications from minor details. In this work, a conceptual semi-distributed rainfall-runoff model for hilly watersheds is used with satellite-based hydrometeorological inputs to parameterize, and thus understand by calibration and validation, at Koshi River Basin, a partly hilly watershed in Himalaya. The semi-distributed model is operated by dividing the river basin into small grids of around 1km<sup>2</sup>, each representing a micro-watershed. Majority of the model concept is drawn from fill and spill approach from previous literature, observations from plot-scale hillslope experiments, and macropore characterization from dye-tracer experiments, which are upscaled at micro-watershed scale. The parameterization in the rainfall-runoff model includes the daily average variables namely, threshold for runoff generation (<em>T</em>), gradient of runoff generation rate (<em>S</em>), saturated hydraulic conductivity for hillslope aquifers (<em>Ksat</em>), and aquifer thickness limit (<em>D</em>). Variable ranges of these parameters were simulated to find the best values (<em>T</em> = 1±0.25cm; <em>S</em> = 0.6 – 0.1; <em>Ksat</em> ≈ 10<sup>5</sup> – 10<sup>10</sup> times original Ksat; and <em>D </em>= 1m). These ranges resulted in over (NSE = 0.6; R<sup>2</sup> = 0.65) during calibration and validation for daily flow volume at the outlet. In these simulations, the <em>Ksat </em>multiplied with factors at several orders higher scale and producing good NSE values shows domination of preferential pathways in runoff generation process. This might represent a flow similar to that of overland flow affecting the surface runoff volume at river basin scale. This model could be used for water budgeting studies in hilly watersheds where several hillslopes dominated by macropores are present.</p>