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Management of the freshwater resources in a sustained manner requires the information and understanding of the surface water hydrology and streamflow is of key importance in this nexus. This study evaluates the performance of eight different precipitation products (APHRODITE, CHRS CCS, CHRS CDR, CHIRPS, CPC Global, GPCC, GPCP, and PERSIANN) for streamflow prediction in two sub-catchments (Chirah and Dhoke Pathan) of the data-scarce Soan River Basin (SRB) in Pakistan. A modified version of the hydrological model HBV (Hydrologiska Byråns Vattenbalansavdelning) known as HBV-light was used to generate streamflow. The model was separately calibrated and validated with observed and estimated precipitation data for streamflow simulation with optimized parameterization. The values of R2, NSE, KGE and PBIAS obtained during the calibration (validation) period for the Chirah sub-catchment were 0.64, 0.64, 0.68 and −5.6% (0.82, 0.81, 0.88 and 7.4%). On the other hand, values of R2, NSE, KGE, and PBIAS obtained during the calibration (validation) period for the Dhoke Pathan sub-catchment were 0.85, 0.85, 0.87, and −3.4% (0.82, 0.7, 0.73 and 6.9%). Different ranges of values were assigned to multiple efficiency evaluation metrics and the performance of precipitation products was assessed. Generally, we found that the performance of the precipitation products was improved (higher metrics values) with increasing temporal and spatial scale. However, our results showed that APHRODITE was the only precipitation product that outperformed other products in simulating observed streamflow at both temporal scales for both Chirah and Dhoke Pathan sub-catchments. These results suggest that with the long-term availability of continuous precipitation records with fine temporal and spatial resolutions, APHRODITE has the high potential to be used for streamflow prediction in this semi-arid river basin. Other products that performed better were GPCC, GPCP, and CHRS CCS; however, their scope was limited either to one catchment or a specific time scale. These results will also help better understand surface water hydrology and in turn, would be useful for better management of the water resources.

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Reducing emissions from deforestation and forest degradation is a mechanism to cut down GHG emissions and protect the threatened forest ecosystems. Pakistan is suffering from high forest degradation and deforestation rates, but recent plantations under BTTAP have created a significant impact. This study was designed to identify the LULC changes, forest sequestration and emissions from forest degradation in the forest hub districts (Malakand, Mardan, Lower Dir and Upper Dir) of KPK, Pakistan using Landsat imageries. LULC changes were analyzed from 1990 to 2020. In addition, the amount of carbon sequestration and emissions from forest degradation were also calculated. Results of the analysis showed forest area reduction from 1990 to 2009, followed by a sharp increase in the next decade (2010–2020) by 56%. Around 836 km2 of land was found to be covered with forests during BTTAP. The net change was a 32% increase in forest land over three decades. The study offers important information which environment managers and decision-makers can utilize to encourage the plantation of trees and save existing forests in the country to combat climate change.