Abstract
This study evaluated the performance of four state-of-the-art precipitation (P; CHIRPSv2, MSWEPv2.2, PERSIANN-CDR, and ERA5) and three state-of-the-art evaporation (Ea; GLEAMv3.3a, SSEBopv4.0, and ERA5) products in the data-scarce province of Balochistan, Pakistan. The P products were evaluated through a point-to-pixel comparison at the monthly, annual, and seasonal temporal scales using data from 17 gauges. The modified Kling-Gupta efficiency (KGE’) and the root mean square error (RMSE) were used as statistical indices to evaluate the performance of the P products. We used the Budyko framework to evaluate the Ea component due to unavailability of ground-based Ea data. For this purpose, we calculated the multi-annual mean Ea — defined as Ea_WB — for 12 defined catchments for a period of 16 years (2003–2018). Subsequently, the estimated Ea_WB was used as the reference to evaluate the performance of the Ea products. The results of the study revealed that among the P products generally MSWEPv2.2 closely followed by ERA5 presented the best spatio-temporal KGE’ performance over most of the stations and across the province. CHIRPSv2 and PERSIANN-CDR relatively showed poor KGE’ performance. Whereas, for the Ea component, ERA5 generally outperformed the other two products — i.e., GLEAMv3.3a and SSEBopv4.0 — in most of the evaluated catchments except for those located over the north-eastern region where GLEAMv3.3a performed the best. The results of this study can be beneficial to shift towards a proactive water management approach that can serve as a basis to improve the decision-making process in the region.
MODELLING SPATIO-TEMPORAL CHANGES OF TROPICAL FOREST COVER IN THE NORTH-EASTERN REGION OF BANGLADESH: CONTEXT OF TRADITIONAL AND CO-MANAGEMENT PARADIGMS
