Assessment of Climate Change Impact on Reservoir Inflows Using Multi Climate-Models under RCPs—The Case of Mangla Dam in Pakistan

Abstract

Assessment of climate change on reservoir inflow is important for water and power stressed countries. Projected climate is subject to uncertainties related to climate change scenarios and Global Circulation Models (GCMs). This paper discusses the consequences of climate change on discharge. Historical climatic and gauging data were collected from different stations within a watershed. Bias correction was performed on GCMs temperature and precipitation data. After successful development of the hydrological modeling system (SWAT) for the basin, streamflow was simulated for three future periods (2011-2040, 2041-2070, and 2071-2100) and compared with the baseline data to explore the changes in different flow indicators such as mean flow, low flow, median flow, high flow, flow duration curves, temporal shift in peaks, and temporal shifts in center-of-volume dates. From the results obtained, an overall increase in mean annual flow was projected in the basin under both RCP 4.5 and RCP 8.5 scenarios. Winter and spring showed a noticeable increase in streamflow, while summer and autumn showed a decrease in streamflow. High flows were predicted to increase, but median flow was projected to decrease in the future under both scenarios. Flow duration curves showed that the probability of occurrence of high flow is likely to be more in the future. It was also noted that peaks were predicted to shift from May to July in the future, and the center-of-volume date of the annual flow may vary from −11 to 23 days in the basin, under both RCP 4.5 and RCP 8.5. As a whole, the Mangla basin will face more floods and less droughts in the future due to the projected increase in high and low flows, decrease in median flows and greater temporal and magnitudinal variations in peak flows. These outcomes suggest that it is important to consider the influence of climate change on water resources to frame appropriate guidelines for planning and management.

Development of Threshold Levels and a Climate-Sensitivity Model of the Hydrological Regime of the High-Altitude Catchment of the Western Himalayas, Pakistan

“…The effect of altitude becomes negligible without snow and glacier cover [2]. The authors of reference [43] also investigated the impact of climate on the hydrological regime of the western Himalayas and reported that temperature and precipitation play major roles in the hydrological regime. Snow-melting processes in the high-altitude catchment are governed by temperature and precipitation.…”

“…Projected future temperature and precipitation trends were determined in the western Himalayas [1]. Similarly, different climate models have been used to predict the impact of future climate change on this region, without taking into account historical meteorological and hydrological time-series data [42,43]. The authors of [44] investigated the temperature and snow-melt process in the western Himalayas.…”

Assessing uncertainty of climate change impacts on long-term hydropower generation using the CMIP5 ensemble—the case of Ecuador

“…the delta factor approach (Fowler et al 2007). Data was bias-corrected using precipitation and PET values from the observed baseline period CRU datasets and using a multiplier on a monthly basis (Babur et al 2016). This paper uses only the RCP4.5 scenario for the uncertainty analysis.…”

“…The argument for this type of model over more complex physical models, such as distributed models (Vetter et al 2015), is that application of these latter can be challenging since their inputs can be difficult to acquire in developing countries especially in the spatially continuous manner, thus hindering the calibration and validation process (Babur et al 2016). Intercomparison between catchment basins is also made possible with conceptual models since historical precipitation and temperature values are more likely to exist for a larger number of basins (De Lucena et al 2009).…”

Variability and Trend Detection in the Sediment Load of the Upper Indus River

“…The temporal variations and changes in SSLs are also an important indicator of the effectiveness of existing watershed management practices or tectonic and land-sliding activities in the catchment area. Being a water stressed country amongst the top ten most climate-affected countries [6,7], Pakistan has a total water storage capacity of only 30 days (equal to 10% of the annual available water), which has been depleting due to heavy sedimentation transported through the Indus River system from the young Hindukush-Karakoram-Himalaya (HKH) ranges [8]. For example, amongst three big reservoirs, the Tarbela dam has lost 35% of its storage capacity since 1974 due to trapping of approximately 8 km 3 of sediment in the reservoir ponding area [9].…”