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Summary: The overall goal of the present study is to show through a simulation experiment the value of adaptive management under climatic variability and change. The Northern California water resources management system is used as an example of a multi-agency, multi-site, multi-objective water resources management system that supports a trillion dollar economy to demonstrate the utility of the methods and to exemplify the assessment studies. Simulations are performed using an adaptation of the Integrated Forecast and Reservoir Management (INFORM) system of Northern California with 6-hourly 1.4° input from the CCSM3.0 climate model for historical/control (1970–2019) and future periods (2050–2099). The present paper examines the assessment of the hydroclimatological sensitivities and a companion paper () examines the assessment of reservoir management sensitivities. The future period was based on the moderate CCSM3.0 A1B scenario. The INFORM system includes an intermediate complexity regional model for dynamic downscaling of the CCSM3.0 scenario output to produce surface precipitation and temperature fields with a 10×10km2 resolution, and snow–soil-channel modeling of all the watersheds upstream of the major reservoirs in Northern California. The flow results indicate a shift in the monthly average flow volume toward earlier times in the year and higher flow variability for the future period. Higher average temperatures in the future period and, consequently, earlier snow pack melt are mainly responsible for these flow changes. Both daytime and nighttime average monthly temperatures are higher in the simulation of the future period for the entire domain with the northern catchments experiencing higher temperature increases. Simulated monthly average precipitation for the future period is higher in the southern high Sierras and lower in the northern drainage basins than the historical period precipitation. The uncertainty in the assessments for Northern California mentioned may be estimated with additional simulations similar to those shown in this work using high spatial and temporal resolution output from different climate models. [ABSTRACT FROM AUTHOR]

Summary An increase in water demands, exacerbated by climate change and the tightening of environmental requirements, leads to a reduction in available water resources for economic uses. This situation poses challenges for water resource planning and management. Water accounting has emerged as an appropriate tool to improve transparency and control in water management. There are multiple water accounting approaches, but they generally involve a very exhaustive list of accounted concepts. According to our findings in this research, one of the best water accounting methodologies is the Australian Water Accounting Standard. However, its implementation for integrated water resource planning and management purposes calls into questioning the amount of information and level of detail necessary for the users of water accounts. In this paper, we present a different method of applying the Australian Water Accounting Standard in relation to water resource management, which improves its utility. In order to compare the original approach and that proposed here, we present and discuss an application to the Júcar Water Resource System, in eastern Spain. [ABSTRACT FROM AUTHOR]

Summary: Water companies in the United Kingdom have considered climate change in their water resources plans for more than a decade through studies funded by UK Water Industry Research (UKWIR). This paper presents an initial assessment of the impact of the UK Climate Projections 2009 (UKCP09) on river flows at a national scale for the 2020s under the A1B scenario and the implications for water resource planning. A daily hydrological modelling framework based on two conceptual model structures and the Generalized Likelihood Uncertainty Estimation (GLUE) methodology has been applied to 70 catchments across the UK. A Latin Hypercube Sampling approach was adopted to handle the probabilistic nature of UKCP09. Results show a decrease in mean annual flow over most of the UK, with negative median values of all monthly changes except in winter over the western and northern mountainous areas. Furthermore the results indicate a high likelihood of a significant decline in summer flows. An analysis of variance shows that the main uncertainty in river flow changes comes from the spread in climate projections. Finally results are found to be consistent with a previous UKWIR assessment based on individual projections from 6 Global Climate Models (GCMs) under the A2 scenario. The reduction in summer low-flows, critical for water resources, appears however more limited with UKCP09. Although most expected changes are within natural variability, the drier conditions overall and the greater spread of results with respect to previous assessments indicates a need for testing the robustness of water resource plans. [Copyright &y& Elsevier]

Summary: This paper presents an analysis on the hydrological regimes from several rivers flowing from the western slope of the Andes Cordillera. We compiled a database of 40 unimpaired average monthly streamflow records located in central and southern Chile, spanning the region between latitudes 30°S and 40°S and the period between years 1961 and 2006. River categories encompass snowmelt, mixed and rainfall dominated watersheds. The water year hydrograph center of timing (CT) is used as an indicator of flow regime and as a proxy for streamflow distribution throughout the year. The CT for each river is correlated to local climatic variables such as seasonal temperature and precipitation, and to large-scale circulation indexes. We assess CT trends using the Mann–Kendall test for varying time windows within the study period. Overall results for the 1961–2006 period show a significant (95% confidence level) negative trend (CT date shifting towards earlier in the year) for 23 out of the 40 analyzed series. However, when studying time windows within the entire period there seems to be a break in the trend during the late 1970s, with positive or null changes for the latter half of the study period for most of the stations analyzed. We found that even though the CT is significantly correlated (r >0.5) to temperature indexes in the snowfed watersheds, there has been no significant change in CT timing for most of these watersheds despite documented warming on the region. CT for all types of watersheds present clear correlation to precipitation indexes (r >0.8), and we observed high and significant correlation between CT and ONI, SOI and MEI indexes for all the study region: higher (lower) precipitation amounts during El Niño (La Niña), rather than temperature variations, seem to be the most important factor controlling CT timing during these episodes. In order of importance, the CT showed higher correlation with annual precipitation amounts and timing, MEI, ONI and SOI, mean winter and spring temperature, and finally PDO. The detected trends are consistent only with trends in precipitation, as rivers that showed high correlation to temperature do not show any trend. These conclusions suggest that rivers on the region show a different response to temperature changes when compared to rivers of similar regime in the northern hemisphere, and that precipitation amount and timing are the source of most of the variability in streamflow timing for both snowmelt and rainfall dominated watersheds. Temperature induced variability in streamflow timing should be studied with more precise hydrological models, as the CT has a complex behavior due to multiple climatical dependencies. Studying such behavior using only historical data might be insufficient for drawing more precise conclusions. [Copyright &y& Elsevier]

Summary: Concern has been expressed regarding the impacts of climate change on freshwater aquatic ecosystems in arctic regions. Populated with lakes controlled by flooding from spring break-up ice jams, arctic deltas such as the Mackenzie Delta in northern Canada are particularly sensitive to changing ice break-up conditions and the hydroclimatic controls on break-up and ice-jam flooding. An understanding of these controls is necessary for assessing future climate change effects. This paper presents an assessment of hydroclimatic conditions controlling break-up over the period 1974–2006, with a focus on extreme flood events. Both the upstream driving force, capturing elements of the spring discharge hydrograph, and the downstream resistance force, describing the competence of the downstream ice cover, were quantified with reference to the Mackenzie River at Arctic Red River hydrometric station such that the contribution of each to the severity and timing of break-up could be explored. Results show that the severity of peak break-up stage is most influenced by upstream discharge and the balance between upstream and downstream melt, while timing is related to delta ice conditions and the rise of the spring hydrograph. The highest peak stage events require a rapid rise in discharge and high peak discharge. Minimal downstream melting degree-days and greater ice thickness are also important, although no relationship of these appears to control the level of backwater produced from broken ice and ice jamming effects. The pattern of rapid (protracted) upstream melt and lower (higher) intensity melt in the delta characterizes the highest (lowest) break-up events. For the most severe events, upstream forces are important in controlling discharge-driven events, while an altered hydrologic response occurring for ice-driven events was noted, meriting future examination. Finally, trends toward a longer prebreak-up melt interval, lower peak discharge, rate of rise in discharge, and ice thickness, and higher freeze-up stage were observed, with greater variability of these controls and break-up severity in the most recent decade. [Copyright &y& Elsevier]

Summary: Understanding the process of groundwater recharge is fundamental to the management of groundwater resources. Quantifying the future evolution of recharge over time requires not only the reliable forecasting of changes in key climatic variables, but also modelling their impact on the spatially varying recharge process. This paper presents a physically based methodology that can be used to characterize both the temporal and spatial effect of climate change on groundwater recharge. The method, based on the hydrologic model HELP3, can be used to estimate potential groundwater recharge at the regional scale with high spatial and temporal resolution. In this study, the method is used to simulate the past conditions, with 40years of actual weather data, and future changes in the hydrologic cycle of the Grand River watershed. The impact of climate change is modelled by perturbing the model input parameters using predicted changes in the regions climate. The results of the study indicate that the overall rate of groundwater recharge is predicted to increase as a result of climate change. The higher intensity and frequency of precipitation will also contribute significantly to surface runoff, while global warming may result in increased evapotranspiration rates. Warmer winter temperatures will reduce the extent of ground frost and shift the spring melt from spring toward winter, allowing more water to infiltrate into the ground. While many previous climate change impact studies have focused on the temporal changes in groundwater recharge, our results suggest that the impacts can also have high spatial variability. [Copyright &y& Elsevier]

Summary: This paper explores the potential impacts of climate change upon flood frequency for the gauged, Lossie catchment in the northeast of Scotland, UK. This catchment has significant flooding problems, but only limited data availability (particularly with respect to rainfall). A continuous simulation methodology, which uses a stochastic rainfall model to drive the rainfall-runoff model TOPMODEL, is utilised. Behavioural parameter sets for TOPMODEL are identified prior to the climate change runs using the Generalised Likelihood Uncertainty Estimation (GLUE) methodology. The “Low Emissions”, “Medium-Low Emissions”, “Medium-High Emissions” and “High Emissions” UKCIP02 climate change scenarios, obtained from the HadCM3 global climate model (GCM) and HadRM3 regional climate model (RCM) simulations, are used at the catchment scale. Two further scenarios (“H-Dry” and “H-Wet”), based upon the model uncertainty margins available for the UKCIP02 “High Emissions” scenario, are also developed in order to explore the possible range of changes to daily rainfall and temperature estimated from GCMs other than HadCM3. It is demonstrated that, while flood magnitude changes under all six of the climate change scenarios considered, the magnitude and direction of that change is dependent upon the choice of scenario. An overlap between the likelihood weighted uncertainty bounds estimated under the conditions of the current climate and those estimated under the four UKCIP02 scenarios and the “H-Dry” scenario is also observed. These findings highlight the need to consider multiple climate change scenarios and account for model uncertainties when estimating the possible effects of climate change upon flood frequency. [Copyright &y& Elsevier]

Abstract: The perception of a changing climate, which impacts also hydrological processes, is now generally admitted. However, the way of handling the changing nature of climate in hydrologic practice and especially in hydrological statistics has not become clear so far. The most common modelling approach is to assume that long-term trends, which have been found to be omnipresent in long hydrological time series, are ‘deterministic’ components of the time series and the processes represented by the time series are nonstationary. In this paper, it is maintained that this approach is contradictory in its rationale and even in the terminology it uses. As a result, it may imply misleading perception of phenomena and estimate of uncertainty. Besides, it is maintained that a stochastic approach hypothesizing stationarity and simultaneously admitting a scaling behaviour reproduces climatic trends (considering them as large-scale fluctuations) in a manner that is logically consistent, easy to apply and free of paradoxical results about uncertainty. [Copyright &y& Elsevier]

• 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]