No abstract

In transboundary river basins, climate change is being considered as a concern of higher degree than it is in other parts of the world. The Kabul River Basin, a sub-basin of the Indus River system shared by Pakistan and Afghanistan, is no exception. High level of sensitivity of its flow to temperature makes it imperative to analyse climate change impacts on the flow regime of this important river for efficient water resources management on both sides of the border. The snowmelt runoff model integrated with remote sensing snow cover product MODIS was selected to simulate daily discharges. Future projections were generated for two selected time slices, 2011–2030 (near future) and 2031–2050 (far future), based on output of an ensemble of four GCMs' RCP 4.5 and RCP 8.5 scenarios. Analysis shows a significant temperature increase under both scenarios in the near and far future at a high-altitude region of the basin which mostly receives snowfall that is also found increasing over time. Consequently, it causes a change in the flow regime and more frequent and heavier flooding events, thus calling for a joint strategy of the two riparian countries to mitigate the anticipated impacts in the basin for safety of people and overall prosperity.

Numerical summaries of univariate climatic records, such as temperature and precipitation, are useful for making quantitative decisions for mitigation and adaptation measures. Climate simulations and projections often contain values that lie far away from substance of the data. These values can bias the summary statistics away from values representative for majority of the sample. This problem can be avoided by selecting ensembles approach as well as by using statistics that are resistant to the presence of such outliers. Hence, in addition to typical statistics, resistant statistics are used to investigate spatiotemporal changes in temperature and precipitation extremes over a versatile agro-climatic featured country of Pakistan, by engaging the National Aeronautics and Space Administration Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset under two Representative Concentration Pathways (RCPs) 4.5 and 8.5 that provides statistically downscaled Coupled Model Inter-comparison Project Phase 5 (CMIP5) climate baseline and projections (2021-2050) based on Expert Team on Sector-specific Climate Indices (ET-SCI) method. The results show the following: (a) Shifts in the univariate count statistics under the RCP8.5 are highly prominent with 0.81 degrees deviation in 5th percentile and with a substantial 1.86 degrees deviation in the 95th percentile of the maximum of daily maximum temperature over the projected time series. (b) Standard deviation of historical summer days is placed at 3.7 days with a consistent change under the RCP4.5 emission scenario. Nevertheless, the standard deviation of the summer days hikes by 5.9 days under the RCP8.5 emission scenario. (c) A distressing condition is comprehended under the RCP8.5 emission scenario where changes of 16.5 percent in the 5th and of 19.7 percent in the 95th percentiles are revealed in the warm nights future projections. (d) The maximum rate of simple daily intensity of precipitation in the historical period exists at 0.2 mm/day, however, the RCP4.5 emission scenario thrusts that up to 0.6 mm/day in the projection period. (e) Under the RCP8.5 emission scenario, the standard deviation inflates by 36.4 days while range digresses by an enormous 95 days in the projection period of the consecutive dry days. The outcomes are of applied practice in improving local approaches for hydro-reservoirs and eco-environment controlling, especially in the diverse climatic region of Pakistan.

Subsistence of freshwater resources at high altitude regions has remained a paradox for stakeholder communities at both regional and global levels. To address such an issue, Hydrologiska Byråns Vattenbalansavdelning Light (hereafter HBV) model was used to assess hydro-meteorological shifts triggered under climate change scenarios in snow dominant region of Chitral river basin. The model performed well both during calibration and validation periods with Nash Sutcliffe Efficiency values of 0.91 and 0.81 respectively on daily time scale in the basin. The HBV was thereafter engaged for the projection of streamflow in the Chitral river basin using projected data of four statistically downscaled climate models with four emission scenarios for the 21st century. Multi-model ensemble projections of precipitation revealed an increase of up to 165% in monsoon inception period and an increase in temperature of up to 9.5°C in winter to summer transitioning period for the 2070-2099 time slice under a high-end emission scenario. An increase of up to 122% in evapotranspiration was projected in the peak winter months for the 2070-2099 time slice under the high-end emission scenario. Attributed to the significant increases in the temperature and the liquid precipitation, it was projected that basin streamflow had potential to increase by up to 182 % in the monsoon inception period for the 2070-2099 time slice under the high-end emission scenario. It further indicated that precipitation might be falling as liquid rain most of the year, and snow will hardly accumulate in prognosticated future environements of the basin.

No abstract