Performance evaluation of various techniques in estimating precipitation record of a sparsely gauged mountainous watershed.

Comprehensive precipitation data is essential for hydrological, agricultural, and climatological studies. Yet, gaps and sparse rain gauge distribution pose challenges, requiring imputation algorithms to fill data gaps. The aim of this research is to evaluate the performance of several approaches for estimating incomplete precipitation data in the Upper Indus Basin (UIB). Eight various imputation approaches were used on sparsely gauged mountainous UIB on a monthly time series of twenty-four meteorological observatories. Following that, the estimation approaches were evaluated using a rank-based approach comprising four different statistical indicators. The results indicate that multiple linear regression is the best-performing strategy for most of the stations regardless of season or orography, followed by the arithmetic average method and inverse distance weighing method.

Future climate projections using the LARS-WG6 downscaling model over Upper Indus Basin, Pakistan.

This study investigates the projections of precipitation and temperature at the local scale in the Upper Indus Basin (UIB) in Pakistan using six Regional Climate Models (RCMs) from CORDEX under two Representative Concentration Pathways (RCP 4.5 and RCP 8.5). For twenty-four stations spread across the study area, the Long Ashton Research Station Weather Generator, version six (LARS-WG6), was used to downscale the daily data from the six different RCMs for maximum temperature (Tmax), minimum temperature (Tmin), and precipitation (pr) at a spatial resolution of 0.44°. Investigations were made to predict changes in mean annual values of Tmax, Tmin, and precipitation during two future periods, i.e., the mid-century (2041-2070) and end-century (2071-2100). The model results from statistical and graphical comparison validated that the LARS-WG6 can simulate the temperature and the precipitation in the UIB. Each of the six RCMs and their ensemble revealed a continuously increased temperature projection in the basin; nevertheless, there is variation in projected magnitude across RCMs and between RCPs. The rise in average Tmax and Tmin was more significant under RCP 8.5 than RCP 4.5, possibly due to unmitigated greenhouse gas emissions (GHGs). The precipitation projections follow the non-uniform trend, i.e., not all RCMs agree on whether the precipitation will increase or decrease in the basin, and no orderly variations were detected during any future periods under any RCP. However, an overall increase in precipitation is projected by the ensemble of RCMs.

Elevated Temperature Performance of Reactive Powder Concrete Containing Recycled Fine Aggregates.

This study examines the effect of elevated temperature on various properties of reactive powder concrete (RPC) containing varying percentages of recycled fine aggregates as sand replacement. Recycled fine aggregates were collected from two sources, i.e., demolished normal strength concrete and demolished RPC. The specimens were prepared using 25%, 50%, and 75% replacement of natural sand with recycled fine aggregates, exposed to two different curing conditions and were subjected to four temperatures, i.e., 25, 200, 400, and 600 °C. Later, the specimens were tested for mass loss, compressive strength test, split-tensile strength test, flexural strength test, and water absorption test at all temperature ranges. Results determined that although the mechanical properties degraded with the temperature rise, the recycled aggregates can be employed as a partial replacement of natural sand in RPC without causing a significant decrease in the performance of RPC, and can help to produce more sustainable RPC by using recycled aggregates.