Chamelia (catchment area = 1603 km), a tributary of Mahakali, is a snow-fed watershed in Western Nepal. The watershed has 14 hydropower projects at various stages of development. This study simulated the current and future hydrological system of Chamelia using the Soil and Water Assessment Tool (SWAT). The model was calibrated for 2001-2007; validated for 2008-2013; and then applied to assess streamflow response to projected future climate scenarios. Multi-site calibration ensures that the model is capable of reproducing hydrological heterogeneity within the watershed. Current water balance above the Q120 hydrological station in the forms of precipitation, actual evapotranspiration (AET), and net water yield are 2469 mm, 381 mm and 1946 mm, respectively. Outputs of five Regional Climate Models (RCMs) under two representative concentration pathways (RCPs) for three future periods were considered for assessing climate change impacts. An ensemble of bias-corrected RCM projections showed that maximum temperature under RCP4.5 (RCP8.5) scenario for near-, mid-, and far-futures is projected to increase from the baseline by 0.9 °C (1.1 °C), 1.4 °C (2.1 °C), and 1.6 °C (3.4 °C), respectively. Minimum temperature for the same scenarios and future periods are projected to increase by 0.9 °C (1.2 °C), 1.6 °C (2.5 °C), and 2.0 °C (3.9 °C), respectively. Average annual precipitation under RCP4.5 (RCP8.5) scenario for near-, mid-, and far-futures are projected to increase by 10% (11%), 10% (15%), and 13% (15%), respectively. Based on the five RCMs considered, there is a high consensus for increase in temperature but higher uncertainty with respect to precipitations. Under these projected changes, average annual streamflow was simulated to increase gradually from the near to far future under both RCPs; for instance, by 8.2% in near-, 12.2% in mid-, and 15.0% in far-future under RCP4.5 scenarios. The results are useful for planning water infrastructure projects, in Chamelia and throughout the Mahakali basin, to ensure long-term sustainability under climate change.

With the objective to provide a basis for regional climate models (RCMs) selection and ensemble generation for climate impact assessments, we perform the first ever analysis of climate projections for Western Nepal from 19 RCMs in the Coordinated Regional Downscaling Experiment for South Asia (CORDEX‐SA). Using the climate futures (CF) framework, projected changes in annual total precipitation and average minimum/maximum temperature from the RCMs are classified into 18 CF matrices for two representative concentration pathways (RCPs: 4.5/8.5), three future time frames (2021–2045/2046–2070/2071–2095), three geographic regions (mountains/hills/plains) and three representative CF (low‐risk/consensus/high‐risk). Ten plausible CF scenario ensembles were identified to assess future water availability in Karnali basin, the headwaters of the Ganges. Comparison of projections for the three regions with literature shows that spatial disaggregation possible using RCMs is important, as local values are often higher with higher variability than values for South Asia. Characterization of future climate using raw and bias‐corrected data shows that RCM projections vary most between mountain and Tarai plains with increasing divergence for higher future and RCPs. Warmer temperatures, prolonged monsoon and sporadic rain events even in drier months are likely across all regions. Highest fluctuations in precipitation are projected for the hills and plains while highest changes in temperature are projected for the mountains. Trends in change in annual average discharge for the scenarios vary across the basin with both precipitation and temperature change influencing the hydrological cycle. CF matrices provide an accessible and simplified basis to systematically generate application‐specific plausible climate scenario ensembles from all available RCMs for a rigorous impact assessment.

Systematic mapping assesses the nature of an evidence base, answering how much evidence exists on a particular topic. Perhaps the most useful outputs of a systematic map are an interactive database of studies and their meta-data, along with visualisations of this database. Despite the rapid increase in systematic mapping as an evidence synthesis method, there is currently a lack of Open Source software for producing interactive visualisations of systematic map databases. In April 2018, as attendees at and coordinators of the first ever Evidence Synthesis Hackathon in Stockholm, we decided to address this issue by developing an R-based tool called EviAtlas, an Open Access (i.e. free to use) and Open Source (i.e. software code is freely accessible and reproducible) tool for producing interactive, attractive tables and figures that summarise the evidence base. Here, we present our tool which includes the ability to generate vital visualisations for systematic maps and reviews as follows: a complete data table; a spatially explicit geographical information system (Evidence Atlas); Heat Maps that cross-tabulate two or more variables and display the number of studies belonging to multiple categories; and standard descriptive plots showing the nature of the evidence base, for example the number of studies published per year or number of studies per country. We believe that EviAtlas will provide a stimulus for the development of other exciting tools to facilitate evidence synthesis.

No abstract

No abstract

No abstract

Abstract. The densely populated plains of the lower Indus Basin largely depend on water resources originating in the mountains of the transboundary upper Indus Basin. Recent studies have improved our understanding of this upstream–downstream linkage and the impact of climate change. However, water use in the mountainous part of the Indus and its hydropolitical implications have been largely ignored. This study quantifies the comparative impact of upper Indus water usage, through space and time, on downstream water availability under future climate change and socio-economic development. Future water consumption and relative pressure on water resources will vary greatly across seasons and between the various sub-basins of the upper Indus. During the dry season, the share of surface water required within the upper Indus is high and increasing, and in some transboundary sub-basins future water requirements exceed availability during the critical winter months. In turn this drives spatiotemporal hotspots to emerge in the lower Indus where seasonal water availability is reduced by over 25 % compared to natural conditions. This will play an important, but previously unaccounted for, compounding role in the steep decline of per capita seasonal water availability in the lower Indus in the future, alongside downstream population growth. Increasing consumption in the upper Indus may thus locally lead to water scarcity issues, and increasingly be a driver of downstream water stress during the dry season. Our quantified perspective on the evolving upstream–downstream linkages in the transboundary Indus Basin highlights that long-term shared water management here must account for rapid socio-economic change in the upper Indus and anticipate increasing competition between upstream and downstream riparian states.

Abstract:While the water-energy-food nexus approach is becoming increasingly important for more efficient resource utilization and economic development, limited quantitative tools are available to incorporate the approach in decision-making. We propose a spatially explicit framework that couples two well-established water and power system models to develop a decision support tool combining multiple nexus objectives in a linear objective function. To demonstrate our framework, we compare eight Nepalese power development scenarios based on five nexus objectives: minimization of power deficit, maintenance of water availability for irrigation to support food self-sufficiency, reduction in flood risk, maintenance of environmental flows, and maximization of power export. The deterministic multi-objective optimization model is spatially resolved to enable realistic representation of the nexus linkages and accounts for power transmission constraints using an optimal power flow approach. Basin inflows, hydropower plant specifications, reservoir characteristics, reservoir rules, irrigation water demand, environmental flow requirements, power demand, and transmission line properties are provided as model inputs. The trade-offs and synergies among these objectives were visualized for each scenario under multiple environmental flow and power demand requirements. Spatially disaggregated model outputs allowed for the comparison of scenarios not only based on fulfillment of nexus objectives but also scenario compatibility with existing infrastructure, supporting the identification of projects that enhance overall system efficiency. Though the model is applied to the Nepalese nexus from a power development perspective here, it can be extended and adapted for other problems.