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The complexity of climate system dynamics calls for more elaborate drought evaluation and trend projection under different future climate scenarios. In this study, the meteorological drought stress over the Yellow River basin (YRB) of China for the next forty years (2021–2060) is comprehensively evaluated based on meteorological simulations of eight climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) with three representative concentration pathway scenarios (RCP2.6, RCP4.5 and RCP8.5). The standardized precipitation evapotranspiration index (SPEI) is used as a metric of drought magnitude at multiple temporal scales, while the multi‐threshold run analysis is conducted for the definition of drought events and derivation of drought characteristics (e.g., frequency, duration and severity). The Mann–Kendall test is adopted as a universal tool to analyse the trends in climate variables (precipitation and temperature), multi‐temporal SPEI drought indices and drought characteristics (duration and severity). Our preliminary conclusions include that partially increasing precipitation and generally rising temperature are likely to be seen in the YRB from 2021 to 2060. More importantly, a warmer YRB may undergo either a nearly regular atmospheric regime (e.g., comparable to the baseline period of 1961–2000) with RCP2.6 scenario or significantly drying processes with RCP4.5 and RCP8.5 scenarios. Meanwhile, the enhanced spatiotemporal variability/heterogeneity of meteorological forcing (e.g., precipitation and temperature) and drought characteristics (e.g., magnitude, frequency, duration and severity) would also increase future uncertainty of meteorological drought stress over the YRB, such as the encounter of drought with long duration and/or high severity and relevant increasing trends. Understanding the spatiotemporal influences of specific climate and emission scenarios on projected drought vulnerability might help improving our knowledge of climate‐human interactions and selecting rational development strategy (like the low emission scenario of RCP2.6 or so) for regional adaptation to future climate change. [ABSTRACT FROM AUTHOR]

Drought projection is of critical significance for designing long-term drought adaptation strategies to cope with changing climate. This study presents an application of multi-class models for characterizing future droughts in the Yellow River basin (YRB). Using meteorological observations and simulations of three CMIP5 climatic models as input into VIC hydrologic model, the standardized Palmer drought index-based joint drought index (SPDI-JDI) is calculated to investigate spatiotemporal patterns and possible changes of future drought in the YRB, through an approach of bivariate modeling and analysis. It is concluded that moderate drought will be alleviated with decreased duration and severity, but extreme drought risk is likely to increase for future climate scenarios (2021–2050) relative to baseline period (1961–2000). From the perspective of bivariate analyses, the concurrence probability of drought events with extreme duration and severity might rise in the future, while increasing variability and heterogeneity of duration, severity and bivariate joint/concurrent return period would also increase the stochastic occurrence of extreme drought over time and space. These findings can provide insights into projection of climate change impacts on drought trends for the next 30 years, and help to preparations for strict control of socio-economic water consumption as well as eco-environmental protection and restoration in the YRB. [ABSTRACT FROM AUTHOR]

The Palmer indices (PIs) that have been most widely used for drought monitoring and assessment are criticized for two main drawbacks: coarse hydrological accounting processes with a simplified two-stage bucket soil water balance model and arbitrary rules for defining drought properties and standardizing index values through limited calibration and comparison. In this study, we introduce a new proposal of the VIC hydrologic model-based Palmer drought scheme, where traditional PIs (e.g. PDSI) can readily be calculated on the basis of distributed finescale hydrologic simulations. Moreover, recent variants of PI (i.e., SPDI and SPDI-JDI) also provide a preferable standardization strategy that allows probabilistic invariability and better spatio-temporal comparability of computed drought indices. Using gridded meteorological forcing, soil and vegetation data to drive the three-layer VIC model, both non-VIC and VIC-based PIs are investigated to examine their performances for drought characterization and detection. Results indicate that VIC hydrologic model would allow for adjustments in statistical properties of computed PDSI and VIC-based SPDI is also preferable to PDSI for better statistical robustness and spatio-temporal consistency/comparability. Moreover, the joint SPDI-JDI has the strength of integrating multi-scale probabilistic properties and drought information released by individual SPDI, providing overall drought conditions that take into account the onset, persistence and termination of droughts. At proposed 0.25° grid scale, the VIC-based SPDI-JDI indicates high frequency and long total time of drought condition in the Yellow River basin (YRB), China. Although no significant temporal trends are found in identified drought duration and severity, both the seasonal and annual drought index values demonstrate a downward trend (higher drought intensity) for considerable proportions of the YRB. These findings imply high drought risk and potential drying stress for this region. The new framework of hydrologic model-based PIs can help to strengthen our knowledge and/or practices in regional drought monitoring and assessment. [ABSTRACT FROM AUTHOR]

Quantitative evaluation of future climate change impacts on hydrological drought characteristics is one of important measures for implementing sustainable water resources management and effective disaster mitigation in drought-prone regions under the changing environment. In this study, a modeling system for projecting the potential future climate change impacts on hydrological droughts in the Weihe River basin (WRB) in North China is presented. This system consists of a large-scale hydrological model driven by climate outputs from three climate models (CMs) for future streamflow projections, a probabilistic model for univariate drought assessment, and a copula-based bivariate model for joint drought frequency analysis under historical and future climates. With the observed historical climate data as the inputs, the Variable Infiltration Capacity hydrological model projects an overall runoff reduction in the WRB under the Intergovernmental Panel on Climate Change A1B scenario. The univariate drought assessment found that although fewer hydrological drought events would occur under A1B scenario, drought duration and severity tend to increase remarkably. Moreover, the bivariate drought assessment reveals that future droughts in the same return period as the baseline droughts would become more serious. With these trends in the future, the hydrological drought situation in the WRB would be further deteriorated. [ABSTRACT FROM AUTHOR]

Climate change is a significant force influencing catchment hydrological processes, such as baseflow, i.e., the contribution of delayed pathways to streamflow in drought periods and is associated with catchment drought propagation. The Weihe River Basin is a typical arid and semi-arid catchment on the Loess Plateau in northwest China. Baseflow plays a fundamental role in the provision of water and environmental functions at the catchment scale. However, the baseflow variability in the projected climate change is not well understood. In this study, forcing meteorological data were derived from two climate scenarios (RCP4.5 and RCP8.5) of three representative general circulation models (CSIRO-Mk3-6-0, MIROC5, and FGOALSg2) in CMIP5 and then were used as inputs in the Soil and Water Assessment Tool (SWAT) hydrological model to simulate future streamflow. Finally, a well-revised baseflow separation method was implemented to estimate the baseflow to investigate long-term (historical (1960–2012) and future (2010–2054) periods) baseflow variability patterns. We found (1) that baseflow showed a decreasing trend in some simulations of future climatic conditions but not in all scenarios (p < 0.05), (2) that the contribution of baseflow to streamflow (i.e., baseflow index) amounted to approximately 45%, with a slightly increasing trend (p ≤ 0.001), and (3) an increased frequency of severe hydrological drought events in the future (2041–2053) due to baseflows much lower than current annual averages. This study benefits the scientific management of water resources in regional development and provides references for the semi-arid or water-limited catchments. [ABSTRACT FROM AUTHOR]