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Economically optimal operational changes and adaptations for California's water supply system are examined for a dry form of climate warming (GFDL CM2.1 A2) with year 2050 water demands and land use. Economically adaptive water management for this climate scenario is compared to a similar scenario with the historical climate. The effects of population growth and land use alone are developed for comparison. Compared with the historic hydrology, optimized operations for the dry climate warming scenario raise water scarcity and total operation costs by $490 million/year with year 2050 demands. Actual costs might be somewhat higher where non-economic objectives prevail in water management. The paper examines the economical mix of adaptation, technologies, policies, and operational changes available to keep water supply impacts to such modest levels. Results from this screening model suggest promising alternatives and likely responses and impacts. Optimized operations of ground and surface water storage change significantly with climate. Dry-warm climate change increases the seasonal storage range of surface reservoirs and aquifers. Surface reservoir peak storage usually occurs about a month earlier under dry-warm climate change. [ABSTRACT FROM AUTHOR]

Numerical modelling is often used for climate impact studies in water resources management. It is, however, not yet highly accessible to many students of hydrology in Central Asia. One big hurdle for new learners is the scripting requirement for the preparation of relevant data prior to the actual modelling. We present a robust, open-source workflow and comprehensive teaching material that aims at bridging the gap between theoretical hydrological modelling know how and applied modelling for climate impact studies in Central Asia. The teaching material has been refined during two consecutive years and is being taken up by several professors teaching hydrological modelling in Central Asia. [ABSTRACT FROM AUTHOR]

• CIRFs are useful for exploring risks of system failure under climate change. • Synthetic streamflow series are generated using SA and linked to climate conditions. • Logistic regression relates system responses to climate drivers. • System failure defined according to performance (reliability) and threshold. • LR model detects climate conditions which would require adaptation. Climate Impact Response Functions (CIRFs) can be useful for exploring potential risks of system failure under climate change. The performance of a water resource system can be synthesized through a CIRF that relates climate conditions to system behavior in terms of a specified threshold of deliveries to demands or environmental flow requirements. However, in highly regulated water resource systems this relationship may be quite complex, depending on storage capacity and system operation. In this paper we define a CIRF for these types of systems through a multivariable logistic regression (LR) model where a binary variable (system response) is explained by two continuous variables or predictors (precipitation and temperature). The approach involves generating multivariate synthetic inflow time series and relating them to specific climate conditions. Next, these inflows are used as inputs in a water management model, and the outcome is coded as a binary variable (failure or its absence) depending on selected vulnerability criteria. To identify the time span before the failure event in which climate variables are relevant, we characterized drought development stages through relative standardized indices. Mean values of precipitation and temperature for the selected time span are computed and used as explanatory variables through a LR model, which is validated using data from several climate models and scenarios. Results show that the predictive capacity of LR models is acceptable, so that they could be used as screening tools to detect challenging climate conditions for the system which would require adaption actions. [ABSTRACT FROM AUTHOR]

The management of water resources is challenging under extreme climate conditions with the acceleration of climate change. Many existing indices for analysing extreme climate conditions focus on the statistical behaviour of a single hydrological variable, such as precipitation or temperature. Such indices have limitations in providing a comprehensive interpretations of elaborate extreme climate conditions. In this study, the hydrological severity index (HSI), which is defined as the ratio of precipitation to the sum of evapotranspiration, runoff, and terrestrial water storage from the water balance equation, was proposed and calculated using Global Land Data Assimilation System datasets for 1980–2010. Mean HSI was relatively high in tropical regions due to the high sensitivity of precipitation, while it was relatively low in semi‐arid and arid regions due to low precipitation and high evaporative demand. HSI showed a good representation of hydrological severity based on the spatial pattern of the absolute correlation coefficient as well as the opposite pattern of the coefficient of variation calculated from HSI and the radiative index of dryness. Based on the aforementioned phenomenon, temporal anomaly HSI (HSIanom) was applied to Pakistan and Australia as case studies to analyse the 2010 Pakistan Flooding and the Australian Millennium Drought (especially in 2002 and 2006). The HSIanom was able to capture the severity of extreme climate events and to provide underlying causes accompanying the physical climate forcing system. Specifically, the spatial pattern of HSIanom was useful for analysing regions with high severity to extreme climate conditions. The HSI can be used to establish water management policies that consider regional hydrological features in order to cope with intensified climate change. In addition, stand‐alone HSI could be used to predict future climate trends based on precise simulations of hydrological variables. Spatial distributions of the hydrological severity index and radiative index of dryness (ϕ); (a) mean HSI, (b) absolute correlation coefficient, (c) coefficient of variation of HSI, and (d) CV of ϕ. [ABSTRACT FROM AUTHOR]

Recent literature outlines significant impacts from climate change on many areas of the world, with much focus on causes and impacts. However the long-term trends demand adaptation strategies. While a variety of solutions have been suggested, some politically viable, others not, perhaps the most significant barrier to a cohesive approach to climate adaptation is the failure from the public and policy-makers to realize that different areas will be affected differently and that "one-size-fits-all" policy solutions will not be successful. In addition, as one area may identify and respond to challenges in their location, others should be supportive of those efforts, realizing that while such actions may be neither desirable nor appropriate for them, they may need support for solutions in the future in their areas. This project was designed as a framework to identify solutions and demonstrate differences between small regions and locales based on field conditions. The State of Florida was used as a case example to outline these differences because Florida is faced with significant challenges in the coming years related to water resources, the use of funds and political capital, and the potential for economic disruption. The intent is that the results of this project will lead to a series of recommendations and action steps for policy makers to conserve the state's assets. A similar approach can be used in other states and countries to assess the likely policy and infrastructure needs for different locales. [ABSTRACT FROM AUTHOR]

Evaluating the impact of climate change on water resources is necessary for improving water resource management and adaptation measures at the watershed level. This study evaluates the impact of climate change on streamflow in South Korea using downscaled climate change information based on the global climate model (GCM) and hydrological simulation program–FORTRAN model. Representative concentration pathway (RCP) scenarios 4.5 and 8.5 W/m2 were employed in this study. During the distant future (2071–2099), the flow increased by 15.11% and 24.40% for RCP scenarios 4.5 and 8.5 W/m2, respectively. The flow is highly dependent on precipitation and evapotranspiration. Both precipitation and evapotranspiration increased, but the relative change of precipitation was greater than the relative change of evapotranspiration. For this reason, the flow would show a significant increase. Additionally, for RCP 8.5 W/m2, the variability of the flow according to the GCM also increased because the variability of precipitation increased. Moreover, for RCP 8.5 W/m2, the summer and autumn flow increased significantly, and the winter flow decreased in both scenarios. The variability in autumn and winter was so great that the occurrence of extreme flow could intensify further. These projections indicated the possibility of future flooding and drought in summer and winter. Regionally, the flow was expected to show a significant increase in the southeastern region. The findings presented for South Korea could be used as primary data in establishing national climate change adaptation measures. [ABSTRACT FROM AUTHOR]