Projections of Future Climate Change in the Vu Gia Thu Bon River Basin, Vietnam by Using Statistical DownScaling Model (SDSM)

Abstract

Future projections of anthropogenic climate change play a pivotal role in devising viable countermeasures to address climate-related risks. This study strove to construct future daily rainfall and maximum and minimum temperature scenarios in Vu Gia Thu Bon river basin by employing the Statistical DownScaling Model (SDSM). The model performance was evaluated by utilizing a Taylor diagram with dimensioned and dimensionless statistics. During validation, all model-performance measures show good ability in simulating extreme temperatures and reasonable ability for rainfall. Subsequently, a set of predictors derived from HadCM3 and CanESM2 was selected to generate ensembles of each climatic variables up to the end of 21st century. The generated outcomes exhibit a consistent increase in both extreme temperatures under all emission scenarios. The greatest changes in maximum and minimum temperature were predicted to increase by 2.67–3.9 °C and 1.24–1.96 °C between the 2080s and reference period for the worst-case scenarios. Conversely, there are several discrepancies in the projections of rainfall under different emission scenarios as well as among considered stations. The predicted outcomes indicate a significant decrease in rainfall by approximately 11.57%–17.68% at most stations by 2099. Moreover, all ensemble means were subjected to the overall and partial trend analysis by applying the Innovative-Şen trend analysis method. The results exhibit similar trend patterns, thereby indicating high stability and applicability of the SDSM. Generally, it is expected that these findings will contribute numerous valuable foundations to establish a framework for the assessment of climate change impacts at the river basin scale.

Extreme Temperature and Rainfall Events and Future Climate Change Projections in the Coastal Savannah Agroecological Zone of Ghana

“…This value is projected to increase by 0.5 • C between 2030 and 2052 [43]. Consequently, climate-related threats to humans and natural systems are widespread [1, [44][45][46][47][48][49][50].…”

“…GCMs are recognized as appropriate tools for assessing climate change and variability [49]. However, the horizontal resolution of GCMs, which ranges from 250 to 600 km, is insufficient for most local impact studies [44,45]. In addition, the application of GCMs requires significant computational resources, making it unrealistic for most developing nations [45].…”

Assessing the Impact of Human Activities and Climate Change Effects on Groundwater Quantity and Quality: A Case Study of the Western Varamin Plain, Iran

“…In this study, SDSM 4.2 (statistical downscaling model) software was employed in which multiple linear regression was used for temperature and precipitation projection [27]. This software has been widely used, and it is a reliable tool for downscaling climate data [28][29][30][31][32][33].…”

Evaluating Climate Change Impact of Rainfed Maize Production Yield in Southern Ethiopia

“…General circulation models (GCMs) are greatly supportive of the assessment of potential climate change impacts on multiple sectors on a global scale. However, a horizontal resolution of GCMs is typically between 250 and 600 km, which cannot meet the requirements of most local impact studies (Phuong et al, 2020). Hence, many dynamical and statistical downscaling methods have arisen to overcome these key disadvantages of GCMs.…”