Abstract
Projections of hydrological changes are associated with large uncertainties from different sources, which should be quantified for an effective implementation of water management policies adaptive to future climate change. In this study, a modeling chain framework to project future hydrological changes and the associated uncertainties in the Xijiang River basin, South China, was established. The framework consists of three emission scenarios (ESs), four climate models (CMs), four statistical downscaling (SD) methods, four hydrological modeling (HM) schemes, and four probability distributions (PDs) for extreme flow frequency analyses. Direct variance method was adopted to analyze the manner by which uncertainty sources such as ES, CM, SD, and HM affect the estimates of future evapotranspiration (ET) and streamflow, and to quantify the uncertainties of PDs in future flood and drought risk assessment. Results show that ES is one of the least important uncertainty sources in most situations. CM, in general, is the dominant uncertainty source for the projections of monthly ET and monthly streamflow during most of the annual cycle, daily streamflow below the 99.6% quantile level, and extreme low flow. SD is the most predominant uncertainty source in the projections of extreme high flow, and has a considerable percentage of uncertainty contribution in monthly streamflow projections in July–September. The effects of SD in other cases are negligible. HM is a non-ignorable uncertainty source that has the potential to produce much larger uncertainties for the projections of low flow and ET in warm and wet seasons than for the projections of high flow. PD contributes a larger percentage of uncertainty in extreme flood projections than it does in extreme low flow estimates. Despite the large uncertainties in hydrological projections, this work found that future extreme low flow would undergo a considerable reduction, and a noticeable increase in drought risk in the Xijiang River basin would be expected. Thus, the necessity of employing effective water-saving techniques and adaptive water resources management strategies for drought disaster mitigation should be addressed.
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