Impact of climate change on hydro-meteorological drought over the Be River Basin, Vietnam

Abstract

In this paper, the responses of hydro-meteorological drought to changing climate in the Be River Basin located in Southern Vietnam are investigated. Climate change scenarios for the study area were statistically downscaled using the Long Ashton Research Station Weather Generator tool, which incorporates climate projections from Coupled Model Intercomparison Project 5 (CMIP5) based on an ensemble of five general circulation models (Can-ESM2, CNRM-CM5, HadGEM2-AO, IPSL-CM5A-LR, and MPI-ESM-MR) under two Representative Concentration Pathway (RCP) scenarios (RCP4.5 and RCP8.5). The Soil and Water Assessment Tool model was employed to simulate streamflow for the baseline time period and three consecutive future 20 year periods of 2030s (2021–2040), 2050s (2041–2060), and 2070s (2061–2080). Based on the simulation results, the Standardized Precipitation Index and Standardized Discharge Index were estimated to evaluate the features of hydro-meteorological droughts. The hydrological drought has 1-month lag time from the meteorological drought and the hydro-meteorological droughts have negative correlations with the El Niño Southern Oscillation and Pacific Decadal Oscillation. Under the climate changing impacts, the trends of drought severity will decrease in the future; while the trends of drought frequency will increase in the near future period (2030s), but decrease in the following future periods (2050 and 2070s). The findings of this study can provide useful information to the policy and decisionmakers for a better future planning and management of water resources in the study region.

The Impact of Climate Change on Hydro-Meteorological Droughts in the Chao Phraya River Basin, Thailand

“…The SWAT is a physically semi-distributed, continuous time hydrologic model [20,21] developed by the Agricultural Research Service (ARS) of the United States Department of Agriculture (USDA), Texas A&M University, and several federal agencies [22,23]. SWAT is one of the most widely used models in the world and has proven to be effective in simulating hydrology and hydro-meteorological extremes in river basins of varying scales around the world, particularly in Southeast Asia [24,25], where the quality of hydro-climatic data remains problematic [5,26]. It has demonstrated the potential to provide valuable insights into the impacts of land use, land management practices, and extreme climatic conditions.…”

“…Many studies have used standardized drought indices, such as Standardized Precipitation Index (SPI), Standardized Streamflow Index (SSI), and Standardized Precipitation Evapotranspiration Index (SPEI), to characterize droughts [9,14,24,[58][59][60][61][62][63][64][65] because they are the most widely used, they are easy to calculate and interpret, they have multiple scales, and they can be compared across space and time to assess the effectiveness of drought mitigation strategies [66]. In this study, the SPI and SSI were used to investigate the meteorological and hydrological perspectives of drought in the CPRB.…”

Future precipitation changes in the Central Ethiopian Main Rift under CMIP5 GCMs

“…The uncertainties originate from the selection of the emission scenarios, GCM outputs, downscaling techniques, and hydrological models (Hoan et al 2018;Vesely et al 2019). In this study, for assessing the future precipitation simulation, the multimodel ensemble (MME) mean approach with different climate scenarios was utilized, which could help to reduce the uncertainty associated with using a single climate emission scenario and GCM in climate predictions (Fenta & Disse 2018;Bekele et al 2021;Khoi et al 2021).…”

“…In recent years, many studies have been conducted to assess the future precipitation changes using the LARS-WG model. For instance, Khoi et al (2021) used the LARS-WG tool to predict future climate in the Be River Basin in Southern Vietnam using an ensemble of five CMIP5 GCMs (Can-ESM2, CNRM-CM5, HadGEM2-AO, IPSL-CM5A-LR, and MPI-ESM-MR) under two RCP scenarios (RCP4.5 and RCP8.5). They discovered that annual precipitation will decrease by 4.0% in the 2030s and rise by 1.6 and 6.4% in the 2050s and 2070s for the RCP4.5.…”