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Summary Transboundary data sharing is widely recognised as a necessary element in the successful handling of water-related climate change issues, as it is a means towards integrated water resources management (IWRM). However, in practice it is often a challenge to achieve it. The Mekong River Commission (MRC), an inter-governmental agency established by Cambodia, Lao PDR, Thailand and Vietnam, has adopted IWRM in its water strategy plan in order to properly manage the transboundary waters of the Mekong River. In this context, data sharing procedures were institutionalised and have been officially implemented by the four member countries since 2001. This paper uses a systematic approach to identify the extent of data sharing and the factors influencing the willingness of key individuals in the Vietnam National Mekong Committee and its Primary Custodians to share data. We find that the initial objectives of the Procedures for Data and Information Exchange and Sharing (PDIES) have not been fully achieved and, further, that Vietnam has much to gain and little to lose by engaging in data sharing in the MRC context. The primary motivation for data sharing stems from the desire to protect national benefits and to prevent upstream countries from overexploiting the shared water resources. However, data sharing is hindered by a lack of national regulations in the Vietnam context concerning data sharing between state agencies and outdated information management systems. [ABSTRACT FROM AUTHOR]

Summary Increasing attention is being paid to the importance and potential of crowd-sourced data to complement current environmental data-streams (i.e. in-situ observations and RS data). In parallel, the diffusion of Information Communication Technologies (ICTs) that are interactive and easy to use have provided a way forward in facing extreme climatic events and the threatening hazards resulting from those. The combination of these two trends is referred to as ICT-enabled ‘citizen observatories’ of the environment. Nevertheless, the success of these citizen observatories hinges on the continued involvement of citizens as central actors of these initiatives. Developing strategies to (further) engage citizens requires in-depth understanding of the behavioral determinants that encourage or impede individuals to collect and share environment-related data. This paper takes the case of citizen-sensed weather data using Personal Weather Stations (PWSs) and looks at the drivers and barriers for sharing such data via online amateur weather networks. This is done employing a behavioral science lens that considers data sharing a decision and systematically investigates the influential factors that affect this decision. The analysis and findings are based on qualitative empirical research carried out in the Netherlands, United Kingdom and Italy. Subsequently, a model was developed that depicts the main drivers and barriers for citizen participation in weather observatories. This resulting model can be utilized as a tool to develop strategies for further enhancing ICT-enabled citizen participation in climatic observations and, consequently, in environmental management. [ABSTRACT FROM AUTHOR]

Summary Management of water resources in Texas (United States) is a challenging endeavor due to rapid population growth in the recent past coupled with significant spatiotemporal variations in climate. While climate conditions impact the availability of water, over-usage and lack of efficient management further complicate the dynamics of supply availability. In this paper, we provide the first look at the impact of climate change projections from an ensemble of Coupled Model Intercomparison Project Phase 5 (CMIP5) on 21st century drought characteristics under three future emission trajectories: Representative Concentration Pathway (RCP) 2.6, RCP 4.5 and RCP 8.5, using the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI). In addition, we evaluate the performance of the ensemble in simulating historical (1950–1999) observations from multiple climate divisions in Texas. Overall, the ensemble performs better in simulating historical temperature than precipitation. In semi-arid locations such as El Paso and Laredo, decreasing precipitation trends are projected even under the influence of climate policies represented by the RCP 4.5. There is little variability in the SPI across climate divisions and across RCPs. The SPEI, on the other hand, generally shows a decreasing trend toward the latter half of the 21st century, with multi-year droughts becoming the norm under the RCP 8.5, particularly in regions that are already dry, such as El Paso. Less severe droughts are projected for the sub-humid eastern edge of the state. Considering that state water planning agencies are already forecasting increased water shortages over the next 50 years, we recommend proactive approaches to risk management such as adjusting the planning tools for potential recurrence of multi-year droughts in regions that are already water-stressed. [ABSTRACT FROM AUTHOR]

Summary The water–food–energy Nexus has emerged as a new perspective in debates concerned with balancing potentially conflicting sectoral imperatives of large scale development investments concerned with energy, water or food security. Current frameworks are partial as they largely represent a water-centric perspective. Our hypothesis is that a dynamic Nexus framework that attempts to equally weight sectoral objectives provides a new paradigm for diagnosis and investigation. Dynamic refers here to explicitly understanding (or a diagnosis of) the dynamic relationships and ripple effects whereas static-comparative refers to a comparison of states before and after change. This paper proposes a balanced Nexus framework and presents results from an application to the Mekong basin. The analysis identified the advantages of a sectorally balanced, dynamic Nexus approach, in particular the ability to reveal either the emergence of cross-sectoral connections, or changes in those connections, as a consequence of single sector interventions. [ABSTRACT FROM AUTHOR]

Summary Soil moisture plays an increasingly important role in the cycle of energy–water exchange, climate change, and hydrologic processes. It is usually measured at a point site, but regional soil moisture is essential for validating remote sensing products and numerical modeling results. In the study reported in this paper, the minimal number of required sites (NRS) for establishing a research observational network and the representative single sites for regional soil moisture estimation are discussed using the soil moisture data derived from the “Maqu soil moisture observational network” (101°40′–102°40′E, 33°30′–35°45′N), which is supported by Chinese Academy of Science. Furthermore, the best up-scaling method suitable for this network has been studied by evaluating four commonly used up-scaling methods. The results showed that (1) Under a given accuracy requirement R ⩾ 0.99, RMSD ⩽ 0.02 m 3 /m 3 , NRS at both 5 and 10 cm depth is 10. (2) Representativeness of the sites has been validated by time stability analysis (TSA), time sliding correlation analysis (TSCA) and optimal combination of sites (OCS). NST01 is the most representative site at 5 cm depth for the first two methods; NST07 and NST02 are the most representative sites at 10 cm depth. The optimum combination sites at 5 cm depth are NST01, NST02, and NST07. NST05, NST08, and NST13 are the best group at 10 cm depth. (3) Linear fitting, compared with other three methods, is the best up-scaling method for all types of representative sites obtained above, and linear regression equations between a single site and regional soil moisture are established hereafter. “Single site” obtained by OCS has the greatest up-scaling effect, and TSCA takes the second place. (4) Linear fitting equations show good practicability in estimating the variation of regional soil moisture from July 3, 2013 to July 3, 2014, when a large number of observed soil moisture data are lost. [ABSTRACT FROM AUTHOR]

Summary In this paper, we present a comparative study of bias correction methods for regional climate model simulations considering the distributional parametric uncertainty underlying the observations/models. In traditional bias correction schemes, the statistics of the simulated model outputs are adjusted to those of the observation data. However, the model output and the observation data are only one case (i.e., realization) out of many possibilities, rather than being sampled from the entire population of a certain distribution due to internal climate variability. This issue has not been considered in the bias correction schemes of the existing climate change studies. Here, three approaches are employed to explore this issue, with the intention of providing a practical tool for bias correction of daily rainfall for use in hydrologic models ((1) conventional method, (2) non-informative Bayesian method, and (3) informative Bayesian method using a Weather Generator (WG) data). The results show some plausible uncertainty ranges of precipitation after correcting for the bias of RCM precipitation. The informative Bayesian approach shows a narrower uncertainty range by approximately 25–45% than the non-informative Bayesian method after bias correction for the baseline period. This indicates that the prior distribution derived from WG may assist in reducing the uncertainty associated with parameters. The implications of our results are of great importance in hydrological impact assessments of climate change because they are related to actions for mitigation and adaptation to climate change. Since this is a proof of concept study that mainly illustrates the logic of the analysis for uncertainty-based bias correction, future research exploring the impacts of uncertainty on climate impact assessments and how to utilize uncertainty while planning mitigation and adaptation strategies is still needed. [ABSTRACT FROM AUTHOR]

Summary Ongoing pressures from population growth, recurrent drought, climate, urbanization and industrialization in the Nile Basin raise the importance of finding viable measures to adapt to these stresses. Four tributaries of the Eastern Nile Basin contribute to supplies: the Blue Nile (56%), White Nile-Albert (14%), Atbara (15%) and Sobat (15%). Despite much peer reviewed work addressing conflicts on the Nile, none to date has quantitatively examined opportunities for discovering benefit sharing measures that could protect negative impacts on downstream water users resulting from new upstream water storage developments. The contribution of this paper is to examine the potential for mutually beneficial and sustainable benefit sharing measures from the development and operation of the Grand Ethiopian Renaissance Dam while protecting baseline flows to the downstream countries including flows into the Egyptian High Aswan Dam. An integrated approach is formulated to bring the hydrology, economics and institutions of the region into a unified framework for policy analysis. A dynamic optimization model is developed and applied to identify the opportunities for Pareto Improving measures to operate these two dams for the four Eastern Nile Basin countries: Ethiopia, South Sudan, Sudan, and Egypt. Results indicate a possibility for one country to be better off (Ethiopia) and no country to be worse off from a managed operation of these two storage facilities. Still, despite the optimism of our results, considerable diplomatic negotiation among the four riparians will be required to turn potential gains into actual welfare improvements. [ABSTRACT FROM AUTHOR]

Summary The assessment of climate change impacts on hydrology is subject to uncertainties related to the climate change scenarios, stochastic uncertainties of the hydrological model and structural uncertainties of the hydrological model. This paper focuses on the contribution of structural uncertainty of hydrological models to the overall uncertainty of the climate change impact assessment. To quantify the structural uncertainty of hydrological models, four physically based hydrological models (SWAT, PRMS and a semi- and fully distributed version of the WetSpa model) are set up for a catchment in Belgium. Each model is calibrated using four different objective functions. Three climate change scenarios with a high, mean and low hydrological impact are statistically perturbed from a large ensemble of climate change scenarios and are used to force the hydrological models. This methodology allows assessing and comparing the uncertainty introduced by the climate change scenarios with the uncertainty introduced by the hydrological model structure. Results show that the hydrological model structure introduces a large uncertainty on both the average monthly discharge and the extreme peak and low flow predictions under the climate change scenarios. For the low impact climate change scenario, the uncertainty range of the mean monthly runoff is comparable to the range of these runoff values in the reference period. However, for the mean and high impact scenarios, this range is significantly larger. The uncertainty introduced by the climate change scenarios is larger than the uncertainty due to the hydrological model structure for the low and mean hydrological impact scenarios, but the reverse is true for the high impact climate change scenario. The mean and high impact scenarios project increasing peak discharges, while the low impact scenario projects increasing peak discharges only for peak events with return periods larger than 1.6 years. All models suggest for all scenarios a decrease of the lowest flows, except for the SWAT model with the mean hydrological impact climate change scenario. The results of this study indicate that besides the uncertainty introduced by the climate change scenarios also the hydrological model structure uncertainty should be taken into account in the assessment of climate change impacts on hydrology. To make it more straightforward and transparent to include model structural uncertainty in hydrological impact studies, there is a need for hydrological modelling tools that allow flexible structures and methods to validate model structures in their ability to assess impacts under unobserved future climatic conditions. [ABSTRACT FROM AUTHOR]

Summary Across the southern Canadian Prairies, annual precipitation is relatively low (200–400 mm) and periodic water deficits limit economic and environmental productivity. Rapid population growth, economic development and climate change have exposed this region to increasing vulnerability to hydrologic drought. There is high demand for surface water, streamflow from the Rocky Mountains in particular. This paper describes the application of dendrohydrology to water resource management in this region. Four projects were initiated by the sponsoring organizations: a private utility, an urban municipality and two federal government agencies. The fact that government and industry would initiate and fund tree-ring research indicates that practitioners recognize paleohydrology as a legitimate source of technical support for water resource planning and management. The major advantage of tree-rings as a proxy of annual and seasonal streamflow is that the reconstructions exceed the length of gauge records by at least several centuries. The extent of our network of 180 tree-ring chronologies, spanning AD 549–2013 and ∼20° of latitude, with a high density of sites in the headwaters of the major river basins, enables us to construct large ensembles of tree-ring reconstructions as a means of expressing uncertainty in the inference of streamflow from tree rings. We characterize paleo-droughts in terms of modern analogues, translating the tree-ring reconstructions from a paleo-time scale to the time frame in which engineers and planners operate. Water resource managers and policy analysts have used our paleo-drought scenarios in their various forms to inform and assist drought preparedness planning, a re-evaluation of surface water apportionment policy and an assessment of the reliability of urban water supply systems. [ABSTRACT FROM AUTHOR]

Summary This paper investigates patterns of lake-area and hydro-climatic change in Arctic river basins, and possible influence of permafrost change reflected in such patterns. A salient change pattern, emerging across all investigated basins in both permafrost and non-permafrost areas, is an opposite change direction in runoff ( R ) from that in precipitation ( P ). To explain this change contrast, an increase (decrease) in relative water-balance constrained evapotranspiration ET wb / P is required where R decreases (increases). Increasing temporal variability of daily river discharge ( sdQ ) is found in all basins with spatially extensive lake decrease, which also exhibit decrease in ET wb / P . Clear indication of basin-wide permafrost thaw is found in only one basin, and is possible in two more, but unlikely in the largest of the total four investigated permafrost basins. [ABSTRACT FROM AUTHOR]

Summary Areal reduction factors (ARFs) are commonly used to transform point design rainfall to represent the average design rainfall for a catchment area. While there has been considerable attention paid in the research and engineering communities to the likely changes in rainfall intensity in future climates, the issue of changes to design areal rainfall has been largely ignored. This paper investigates the impact of climate change on ARFs. A new methodology for estimating changes in ARFs is presented. This method is used to assess changes in ARFs in the greater Sydney region using a high-resolution regional climate model (RCM). ARFs under present (1990–2009) and future (2040–2059) climate conditions were derived and compared for annual exceedance probabilities (AEPs) from 50% to 5% for durations ranging from 1 h to 120 h. The analysis shows two main trends in the future changes in ARFs. For the shortest duration events (1-h) the ARFs are found to increase which implies that these events will tend to have a larger spatial structure in the future than the current climate. In contrast, storms with durations between 6 and 72 h are likely to have decreased ARFs in the future, suggesting a more restricted spatial coverage of storms under a warming climate. The extent of the decrease varies with event frequency and catchment size. The largest decreases are found for large catchments and rare events. Although the results here are based on a single RCM and need to be confirmed in future work with multiple models, the framework that is proposed will be useful for future studies considering changes in the areal extent of rainfall extremes. [ABSTRACT FROM AUTHOR]

Summary Changing climates and growing populations have prompted policy makers to shift to more climate resilient, technology-driven water sources, such as seawater desalination. Desalination is a prominent water resource in the Middle East but countries in other parts of the world with similar scarcity issues and good access to sea water, such as Australia, have been comparatively slow to adopt it. This paper explores attitudes to desalination in Perth, Western Australia, and the factors that influence its acceptance. We compared individuals’ acceptance of desalination over two time periods by using identical surveys administered in 2007 and 2012. We then examined the attitudinal factors – attitudes towards desalination and attitudes towards the environment – that influence acceptance. Acceptance of desalination was reasonably high and stable at both times (74% and 73% in 2007 and 2012 respectively). We found that respondents’ attitudes to perceived outcomes and benefits, fairness, environmental obligation and risk were important predictors of their acceptance of desalination in both surveys. However the weight given to these aspects varied over time. The findings show that there is still mixed community sentiment towards desalination, which helps to explain why acceptance has not increased since desalination was introduced in 2006. [ABSTRACT FROM AUTHOR]

Summary Evapotranspiration (ET) is a key variable for hydrologic, climatic and agricultural studies. ET cannot be measured in many situations and its estimation is only possible through the application of mathematical models. ET is commonly calculated relying on reference evapotranspiration (ET o ) or potential evapotranspiration (PET). In particular, temperature-based models (TET) are interesting, because temperature is a widely available climatic variable and it might explain a significant fraction of ET o and PET variability. Nevertheless, most studies about TET models usually provide a local assessment of the studied model performance, usually at regional or national scale. This paper presents the assessment of 11 representative TET methods for estimating ET o and PET considering a very wide climatic spectrum, specifically 4362 climatological stations worldwide. Therefore, the applicability of the different TET approaches was evaluated in relationship to the Köppen climate classification of the stations, considering a monthly timescale and FAO56 Penman Monteith benchmarks (PM56). The encountered correlation indexes confirm the importance of air temperature for modeling ET. In general, the Hargreaves–Samani equation provided the most accurate global average performance in arid, semiarid, temperate, cold and polar climates. The Thornthwaite and McCloud approaches provide the worst average estimates in all climate classes. TET approaches yield high errors and a low average correlation to PM56 in tropical climates. Although a similar comparative analysis might provide other trends at local scale, the presented results might allow for a general selection of suitable TET methods for each climate Köppen class. [ABSTRACT FROM AUTHOR]

Summary Return period and risk of extreme hydrological events are critical considerations in water resources management. The stationarity assumption of extreme events for conducting hydrological frequency analysis to estimate return period and risk is now problematic due to climate change. Two different interpretations of return period, i.e. the expected waiting time (EWT) and expected number of exceedances (ENE), have already been proposed in literature to consider nonstationarity in return period and risk analysis by introducing the time-varying moment method into frequency analysis, under the assumption that the statistical parameters are functions only of time. This paper aimed at improving the characterization of nonstationary return period and risk under the ENE interpretation by employing meteorological covariates in the nonstationary frequency analysis. The advantage of the method is that the downscaled meteorological variables from the General Circulation Models (GCMs) can be used to calculate the nonstationary statistical parameters and exceedance probabilities for future years and thus the corresponding return period and risk. The traditional approach using time as the only covariate under both the EWT and ENE interpretations was also applied for comparison. Both approaches were applied to annual minimum monthly streamflow series of two stations in the Wei River, China, and gave estimates of nonstationary return period and risk that were significantly different from the stationary case. The nonstationary return period and risk under the ENE interpretation using meteorological covariates were found more reasonable and advisable than those of the EWT and ENE cases using time alone as covariate. It is concluded that return period and risk analysis of nonstationary low-flow series can be helpful to water resources management during dry seasons exacerbated by climate change. [ABSTRACT FROM AUTHOR]

Summary In this paper, spatial and temporal changes in water and energy fluxes were investigated over the past 28 years along with relevant factors in the Haihe River Basin in North China, which is currently facing an increasingly severe water shortage. Water and energy fluxes in different topographical regions have been affected by both climate change and human activities. In the plain regions, actual evapotranspiration (ET a ) has generally decreased during the study period, which can be attributed to decreased net radiation, precipitation and rapid urbanization. The water deficit has continued in the plains regions due to extensive pumping for irrigation to meet the deficit of crop water. However, irrigation has led to significant groundwater depletion, which poses a significant challenge to the sustainability of water resources. In the mountain regions, decreases in sensible heat flux and increases in ET a have caused a decrease in the Bowen ratio. These changes in water and energy fluxes have brought a positive ecological effect, but the increase in ET a in the mountain regions has resulted in a substantial reduction of water yield and consequently a negative effect on water resources in this basin. These changes in water and energy fluxes across the Haihe River Basin have made the water issue more complex and require integrated river basin management. [ABSTRACT FROM AUTHOR]

[Display omitted] • River thermal seasons (RTS) are good indicators of climate warming. • The temporal distribution and duration of RTS varies depending on the river size. • Elements of the environment modify properties of RTS. • The method of designation of RTS is universal. Temperature is one of the most important properties of rivers. Interest in river temperature (RT) has been rapidly increasing in the current period of climate change. It is related to among others the application of models for the development of scenarios of RT increase. The article presents an attempt to identify one of the most important elements of fluvial regime: river thermal seasons (RTS). No attempts have been undertaken to date to determine such seasons, although they are among the most important elements of fluvial regime. This paper proposes another approach to the issue of changes in RT. It involves the designation of river thermal seasons RTS based on unique daily data from a period 1961–2020. The thermal season was defined as a sequence of days with intrinsic similarity resulting from mean multiannual water temperature, its variability in the multiannual period, and autocorrelation. A total of 18 types of RTS were designated in 5 groups of RTS: very cold (0.0–1.0 °C), cold (1.1-4.0 °C), moderate (4.1–10.0 °C), warm (10.1–15.0 °C), and very warm (15.1–20.0 °C). Moroever, two sub-periods were designated: namely 1961–1992 and 1993–2020, permitting the identification of the character of RTS in both sub-periods, and the assessment of changes in their distribution. The applied method allowed for conducting comparative analyses between rivers of various sizes. The occurrence of different thermal seasons was evidenced, as well as various directions and effects of changes resulting from climate warming. The greatest contribution in a year was reached by the group of very warm seasons (34.9%). In comparison with sub-period 1961–1992, it increased by 5.1%. A smaller share was determined for the group of cold seasons (29.0%) which also increased (by 10%) in comparison to the earlier sub-season. An increase in the contribution of cold seasons resulted from a considerable reduction of the duration of seasons from the moderate (from 27.5% to 16.5%) and very cold group (from 9.1% to 1.7%). The proposed study method is universal. It can be applied to analyses of river temperature in other climate zones. [ABSTRACT FROM AUTHOR]

• A novel method for assessing prediction of extremal hydrological events. • Bayesian causal modelling tool for predictive assessment. • Hybridization of Classical and new Hydrology based on Artificial Intelligence. • HydroPredicT_Extreme as a new tool for the prediction of potential flooding events. • Applicability to different time scales of extreme and sudden events. Disastrous losses related to high-flow events have increased dramatically over the past decades largely due to an increase in flood-prone regions settlements and shift in hydrological trends largely due to Climate Change. To mitigate the societal impact of hydrological and hydraulic extremes, knowledge of the processes leading to these extreme events is vital. Hydrological modelling is one of the main tools in this quest for knowledge but comes with uncertainties. For that it is necessary to deeply study the impact of hydrological models' structure on the magnitude and timing of extreme rainfall-runoff events. This paper is mainly aimed to show the development of a method called "HydroPredicT_Extreme" based on Bayesian Causal Modelling (BCM), a technique within Artificial Intelligence (AI). This method may enhance predictive capacity of extreme rainfall-runoff events. "HydroPredicT_Extreme" follows an iterative methodology that comprise 2 main stages. First one comprises a mixed graphical/analytical method from Hydrograph. This stage is conditioned by two initial constraints which are, a) pluviometry station is representative of hydrograph downstream flow behaviour; b) there must be independence of events. This first stage comprises sub-phases such as: 1.1. Calculation of Response Time (RT) through a mixed graphical/analytical approach, 1.2 Subtraction of RT from the flow series to remove the Rainfall-Flow delay; 1.3 Calculation base flow rate; 1.4 Subtraction base-flow from flow series to work on absolute inputs. Second man stage is called Bayesian Causal Modelling Translation (BCMT) that comprises the 2.1 Learning, 2.2 Training, 2.3 Simulation through BCM modelling, 2.4 Sensitivity Analysis-Validation. This whole methodology will become a digital application and software that could be extrapolated to several similar case studies. This may be coupled with posterior devices for the prevention of catastrophic flood consequences in the form of MultiHazard-Early Warning System (MH-EWS) or others. [ABSTRACT FROM AUTHOR]

[Display omitted] • Wildfires are becoming more severe and frequent and their effects increasingly expose water resources to stress. • Climate, wildfire, streamflow records (1975 to 2018), topography, and landcover data from 92 catchments were combined to quantify the contribution of wildfire to streamflow variability across Australian temperate forests. • On average wildfire regimes relatively results in 8.8% increases in streamflow across Australian temperate forests. • Wildfire effects on regional streamflow varied spatially depending on hydroclimate factors, particularly precipitation. As wildfires become more frequent and severe, there are concerns regarding their impacts on water yield from forested catchments. While there are many studies in Australia about the effects of individual wildfires on streamflow at fine scales (<1 km2) in specific geographic settings, the effects of wildfire regimes on streamflow at broad spatial scales across temperate forests in Australia are not well understood. In this paper, we combined climate, wildfire, streamflow records (1975 to 2018), topographic, and landcover data from 92 catchments (74 – 4740 km2) in the Australian temperate zone to quantify the contribution of wildfire regimes over time to streamflow variability in different hydroclimatic settings (humid, dry sub-humid, and semi-arid) and geographic regions (Southeast Australia (SEA), Southwest Western Australia (SWWA), and Tasmania (TAS)). Wildfire regimes were represented by two metrics: the burnt area to drainage area (BDA) ratio for wildfire events in each year and a spatially averaged metric of Time Since Fire (TSF), which is a spatial average of time since the last wildfire in the catchment. By comparing prefire and postfire runoff ratios our study found that on average there was a short-term increase in runoff ratio (∼3% in year 1 and ∼6% in year 2 post-fire) after wildfires with BDA > 25%. No influence of fire was found in the long-term (15–20 years after the wildfire) runoff ratio. We found that wildfire regime, measured by TSF, explained ∼8.8% of the variation in annual streamflow across the Australian temperate zone, and that with decreasing TSF (i.e., increased wildfire impact), the average streamflow increased. Streamflow variation explained by wildfire regimes varied with hydroclimate. The explained variance of streamflow by wildfire regimes in semi-arid catchments (23%) and dry sub-humid catchments (13%) were higher than humid catchments (5%). Our results provide a broad-scale understanding of how wildfire regimes influence streamflow variability at broad temporal and spatial scales, and provided important context and baseline information for determining the implications of changes in climate and fire regimes for regional water availability. [ABSTRACT FROM AUTHOR]

• Comparison of Budyko-based methods to separate catchment and climate effects on flow. • Probabilistic nature of catchment parameter and its uncertainty considered. • New, improved Two-Stage Decomposition method proposed for separation. • Proposed method considers uncertainty in evaporative index using bootstrap method. • Proposed method more robust than using any single earlier-practiced method. Streamflow variability is affected by both climate change and direct human impacts within the catchment. Quantification of the role of these two factors have significant implications for water resources. In recent years, Budyko-based analytical methods have been widely used for such quantification due to their simplicity and efficacy. This paper presents a comparison of such methods to attribute changes in streamflow in four Model Parameter Estimation Experiment (MOPEX) catchments in the contiguous United States. Further, a new, improved Two-stage Decomposition method to separate the role of climate and catchment changes on streamflow is proposed, considering the uncertainty in the catchment parameter that further leads to a range of evaporative index values within a catchment. We find that climate and catchment effects are sensitive to the choice of Budyko equation, disaggregation algorithm and approximation technique. Further, the catchment parameter can be expressed probabilistically, to account for the uncertainty because of limited hydro-meteorological records. The proposed approach employs a bootstrap analysis to obtain the stochastic range of the catchment parameter, considering different choices of Budyko equations. We argue that rather than relying on a single Budyko-based approach for separation of climate and catchment effects on streamflow, the proposed method offers a more robust way by considering the entire range of uncertainty of the catchment parameter. [ABSTRACT FROM AUTHOR]

Summary Both drought and aridity indicate imbalance in water availability. While drought is a natural temporal hazard, aridity is a constant climatic feature. This paper investigates the changes in drought characteristics across different aridity zones with and without consideration of potential evapotranspiration (PET), as a means to better assess drought in a warming climate. Two drought indexes are employed: (1) Standardized precipitation index (SPI), which is solely based on precipitation; and (2) Reconnaissance drought index (RDI), which, in addition to precipitation, takes PET into account. The two indexes are first employed to observed precipitation and PET data for the period 1960–2009 from the CRU (Climate Research Unit, University of East Anglia) TS 3.1 database. The results indicate that although all the aridity zones experience both downward and upward drought trends, no significant trend is found over large parts of the zones. However, the agreement between SPI and RDI reduces from the hyper-arid zone on one extreme toward the humid zone on the other. In the three more humid zones (i.e. semi-arid, sub-humid, and humid), the indexes exhibit different trends, with RDI showing more decreasing trends (i.e. becoming drier). While SPI generally shows more drought prone areas than RDI for the pre-1998 period, the opposite is observed for the post-1998 period. Given the known changes to PET in observed records, and also expected increases as global warming intensifies, these results suggest that RDI will be consistently different to the SPI as global warming intensifies. This hypothesis is further tested for historic and future climate projections from the CSIRO (Commonwealth Scientific and Industrial Research Organisation, Australia) Mk3.6 global climate model (GCM), with use of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and RCP8.5 (Representative Concentration Pathways). In this case, PET is calculated using FAO56-PM model for assessment of RDI. The results suggest that agreement between SPI and RDI is affected and decreases remarkably over time (between 1850 and 2100). All these lead to the conclusion that, in the face of climate change, PET, an important component in the hydrologic cycle, should not be ignored in drought modeling. [ABSTRACT FROM AUTHOR]

Summary This paper assesses the implications of climate and anthropic pressures on short to long-term changes in water resources in a Mediterranean karst using wavelet analysis. This approach was tested on 38-year (1974–2011) hydrogeological time series recorded at the Lez spring (South France), which is exploited for water supply. Firstly, we investigated inter-relationships in the frequency domain by cross-correlation across multiresolution levels. Our results showed that rainfall and spring discharge are highly correlated in the high frequency domain which reflects the hydrogeological response during flood events of typical highly karstified systems. Pumping and groundwater level are correlated in a lower frequency domain, illustrating seasonal to multi-year relationships. Secondly, continuous wavelet transform was applied to characterize the temporal variability of the inter-relationships involved. On the contrary to examples of “non-managed” karst aquifers in the literature, our results showed that the 10-year rainfall component was attenuate in the discharge signal. We assume that the reason is that the storage variations are strongly affected by pumping. This interesting result shows that possible long-term impacts of rainfall variability due to climate change may be masked by a high pumping rate. We showed also that despite an increase of the pumping rate from the 1980s, the stress on the groundwater resource does not increase from year to year. The present pumping strategy does not affect the drawdown in the long term, avoiding an over-exploitation of the aquifer. Finally, this study highlights the effectiveness of wavelet analysis in characterizing the response variability of karst systems where the hydrogeological regime is modified by pumping. [ABSTRACT FROM AUTHOR]

Summary Floodplain wetlands and their hydrological connectivity with main river channels in the Australian wet–dry tropics are under increasing pressure from global climate change and water resource development, and there is a need for modelling tools to estimate the time dynamics of connectivity. This paper describes an integrated modelling framework combining conceptual rainfall–runoff modelling, river system modelling and hydrodynamic (HD) modelling to estimate hydrological connectivity between wetlands and rivers in the Flinders and Gilbert river catchments in northern Australia. Three historical flood events ranging from a mean annual flood to a 35-year return period flood were investigated using a two dimensional HD model (MIKE 21). Inflows from upstream catchments were estimated using a river network model. Local runoff within the HD modelling domain was simulated using the Sacramento rainfall–runoff model. The Shuttle Radar Topography Mission (SRTM) derived 30 m DEM was used to reproduce floodplain topography, stream networks and wetlands in the HD model. The HD model was calibrated using stream gauge data and inundation maps derived from satellite (MODIS: MODerate resolution Imaging Spectroradiometer) imagery. An algorithm was developed to combine the simulated water heights with the DEM to quantify inundation and flow connection between wetlands and rivers. The connectivity of 18 ecologically important wetlands on the Flinders floodplain and 7 on the Gilbert floodplain were quantified. The impacts of climate change and water resource development on connectivity to individual wetlands were assessed under a projected dry climate (2nd driest of 15 GCMs), wet climate (2nd wettest of 15 GCMs) and dam conditions. The results indicate that changes in rainfall under a wetter and drier future climate could have large impacts on area, duration and frequency of inundation and connectivity. Topographic relief, river bank elevation and flood magnitude were found to be the key factors contributing to the level of connectivity. Under a wetter future climate the average duration of connection of wetlands to the main river channel increased by 7% and under a drier climate it decreased by 18%. Construction of a 248 GL dam in the Flinders catchment and two (498 and 271 GL capacity) in the Gilbert catchment could reduce the average duration of connectivity by 1% and 2% in the Flinders and Gilbert catchments respectively. This information is potentially useful to future studies on the flood-dependent ecology in this region. [ABSTRACT FROM AUTHOR]

Summary Many hydro-climatological applications require use of General Circulation Models (GCMs) outputs. However, the raw information as available from GCMs often contains significant systematic biases when compared with observations. This necessitates some kind of statistical adjustment to be carried out on the GCM fields before their use in any application. It is common to correct the GCM simulations by removing the systematic biases at the time scale of interest, usually individually for each GCM variable that is needed. The outcome is a set of bias corrected variables that are not assessed for bias in their joint dependence structure, nor biases in all attributes at other time scales (such as daily and monthly and annual) except the one under consideration. In this paper, we present a bias correction approach that simultaneously adjusts for the biases in multiple variables across multiple time scales. The proposed Multivariate Recursive Nesting Bias Correction (MRNBC) approach simultaneously corrects many GCM variables and repeats the procedure across different levels of temporal aggregation to impart observed distributional and persistence properties at multiple time scales. The bias corrected series exhibits improvements across all variables and over all the time scales considered. The use of the approach in hydrology and water resources related downscaling applications is expected to deliver better results. [ABSTRACT FROM AUTHOR]

Summary Groundwater plays a major role in supplying domestic water to millions of people in Africa. In the future, the ability to increase reliable water supplies for domestic and possibly irrigation purposes will depend on groundwater development. Groundwater storage is a key property because it controls the buffering behavior of the aquifer as it is subjected to time-varying conditions such as increased pumping or land-use change. However, quantitative knowledge of groundwater storage in Africa is very limited. This lack of knowledge is a major concern in hard rocks, which cover about 40% of the surface area of Africa. This paper presents a unique quantitative assessment of groundwater storage in different types of hard rocks and a first estimate of the capacity of hard rock aquifers to buffer changes in climatic and anthropogenic conditions. Our study area in Benin (West Africa) is composed of various grades of metamorphic rocks. We used the latest developments in the application of the magnetic resonance geophysical method to confront the methodological difficulty of quantifying groundwater storage. We successfully conducted 38 magnetic-resonance measurements in eight (8) different geological units; each measurement was quantitatively interpreted in terms of groundwater storage. We determined the groundwater storage of our study area to be 440 mm ± 70 mm (equivalent water thickness). To assess the buffer capacity of aquifers, we compared groundwater storage to groundwater discharge. Groundwater discharge is the sum of natural discharge plus human abstraction. We estimated natural discharge (i.e. deep drainage plus evapotranspiration) from water table fluctuations monitored in six (6) piezometers. Human abstraction was calculated based on the number of operating boreholes and their average daily abstraction. We found that human abstraction (0.34 mm/year ± 0.07 mm) is far less than natural discharge (108 mm/year ± 58 mm). We conclude that increased abstraction due to population growth will probably have a smaller impact on storage than observed land-use change, which may lead to a change in the evapotranspiration rate. We calculated buffer capacity as the ratio of current storage to total discharge, and obtained a result of 6 years ± 47 months. This buffer capacity confirms groundwater’s ability to buffer changes. Finally, our study is intended to promote a more quantitative approach to assessing groundwater resources in Africa and to support our ability to adapt to current and future changes. [ABSTRACT FROM AUTHOR]

Summary This paper presents a review of trend analysis of extreme precipitation and hydrological floods in Europe based on observations and future climate projections. The review summaries methods and methodologies applied and key findings from a large number of studies. Reported analyses of observed extreme precipitation and flood records show that there is some evidence of a general increase in extreme precipitation, whereas there are no clear indications of significant trends at large-scale regional or national level of extreme streamflow. Several studies from regions dominated by snowmelt-induced peak flows report decreases in extreme streamflow and earlier spring snowmelt peak flows, likely caused by increasing temperature. The review of likely future changes based on climate projections indicates a general increase in extreme precipitation under a future climate, which is consistent with the observed trends. Hydrological projections of peak flows show large impacts in many areas with both positive and negative changes. A general decrease in flood magnitude and earlier spring floods are projected for catchments with snowmelt-dominated peak flows, which is consistent with the observed trends. Finally, existing guidelines in Europe on design flood and design rainfall estimation are reviewed. The review shows that only few countries have developed guidelines that incorporate a consideration of climate change impacts. [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 Conflicting approaches to water governance at multiple scales within large international river basins may have detrimental effects on the productivity of water resources and consequently the economic activities of the basin. In the Indus River Basin, local scale water productivity decisions are affected by international and intra-national scale water governance. Water availability and productivity is modulated by the Indus Waters Treaty between India and Pakistan, and within Pakistan by the agreements governing water allocation between and within provinces. Much of the literature on governance at multiple scales in the Indus basin, and others, has employed qualitative methods of institutional analysis. This paper extends that approach with quantitative modeling of surface water allocation rules at multiple scales and the consequent economic impact on water use and productivity in the Indus River of Pakistan. The effects of the existing water allocation mechanisms on the ability to adapt to possible future climate conditions are examined. The study is conducted using the Indus Basin Model Revised – Multi-Year (IBMR–MY), a hydro-agro-economic model of the Indus River within Pakistan that simulates river and canal flows, groundwater pumping, water use and economic activities with a distributed, partial equilibrium model of the local scale agro-economic activities in the basin. Results suggest that without changes in response to changing conditions, the current governance mechanisms impede the provinces’ ability to adapt to changing climate conditions, in ways that are significant, inflicting economic costs under both high and low flow conditions. However surface water allocation between the provinces does not appear to hinder adaptation. The greatest gains for economic water allocation are achieved at the sub-provincial level. The results imply that adaptive mechanisms for water allocation that allow response to changing climate conditions within provinces may be a promising adaptive response in the Indus Basin. [ABSTRACT FROM AUTHOR]

Summary This paper presents an assessment of the effects of climate change on river flow regimes in representative English catchments, using the UKCP09 climate projections. These comprise a set of 10,000 coherent climate scenarios, used here (i) to evaluate the distribution of potential changes in hydrological behaviour and (ii) to construct relationships between indicators of climate change and hydrological change. The study uses six catchments, and focuses on change in average flow, high flow (Q5) and low flow (Q95). There is a large range in hydrological change in each catchment between the plausible UKCP09 climate projections, with differences between catchments largely due to differences in catchment geology and baseline water balance. The range in change between the UKCP09 projections is in most catchments smaller than the range between changes with scenarios based on the CMIP3 ensemble of climate models (although the shape of the distribution of changes is different), and earlier UK scenarios produce changes that tend towards the lower (drier) end of the UKCP09 range. The difference between emissions scenarios is small compared to the range across the 10,000 scenarios. Changes in high flows are largely driven by changes in winter precipitation, whilst changes in low flows are determined by changes in summer precipitation and temperature. [ABSTRACT FROM AUTHOR]

Summary The objective of this paper is to investigate the effects of hydrological model structure and calibration on climate change impact results in hydrology. The uncertainty in the hydrological impact results is assessed by the relative change in runoff volumes and peak and low flow extremes from historical and future climate conditions. The effect of the hydrological model structure is examined through the use of five hydrological models with different spatial resolutions and process descriptions. These were applied to a medium sized catchment in Belgium. The models vary from the lumped conceptual NAM, PDM and VHM models over the intermediate detailed and distributed WetSpa model to the fully distributed MIKE SHE model. The latter model accounts for the 3D groundwater processes and interacts bi-directionally with a full hydrodynamic MIKE 11 river model. After careful and manual calibration of these models, accounting for the accuracy of the peak and low flow extremes and runoff subflows, and the changes in these extremes for changing rainfall conditions, the five models respond in a similar way to the climate scenarios over Belgium. Future projections on peak flows are highly uncertain with expected increases as well as decreases depending on the climate scenario. The projections on future low flows are more uniform; low flows decrease (up to 60%) for all models and for all climate scenarios. However, the uncertainties in the impact projections are high, mainly in the dry season. With respect to the model structural uncertainty, the PDM model simulates significantly higher runoff peak flows under future wet scenarios, which is explained by its specific model structure. For the low flow extremes, the MIKE SHE model projects significantly lower low flows in dry scenario conditions in comparison to the other models, probably due to its large difference in process descriptions for the groundwater component, the groundwater–river interactions. The effect of the model calibration was tested by comparing the manual calibration approach with automatic calibrations of the VHM model based on different objective functions. The calibration approach did not significantly alter the model results for peak flow, but the low flow projections were again highly influenced. Model choice as well as calibration strategy hence have a critical impact on low flows, more than on peak flows. These results highlight the high uncertainty in low flow modelling, especially in a climate change context. [ABSTRACT FROM AUTHOR]

Summary Understanding the fresh groundwater lens (FGL) behavior and potential threat of climatic-induced seawater intrusion (SWI) are significant for the future water resources management of many small islands. In this paper, the FGL of Kish Island, an arid-region case in the Persian Gulf, Iran, is modeled using two-dimensional (2D) and three-dimensional (3D) simulations. These simulations are based on the application of SUTRA, a density-dependent groundwater numerical model. Also, the numerical model parameters are calibrated using PEST, an automated parameter estimation code. Firstly a detailed conceptualization of the FGL model is completed to understand the sensitivity of the FGL to some particular aspects of the model prior to analysis of climate change simulations. For these investigations, the FGL system is defined based on Kish Island system to accomplish the integrated comparison of features of a conceptual model that are representative of real-world systems. This is the first study which adopts such an approach. The comparison of cross-sectional simulations suggests that the two-layer properties of the Kish Island aquifer have a significant influence on the FGL while the impacts of lateral-boundary irregularities are negligible. The impacts of sea-level rise (SLR), associated land-surface inundation (LSI), and variations in recharge rate on the FGL salinization of Kish Island are investigated numerically. Variations of SLR value (1–4 m) and net recharge rate (17–24 mm/year) are considered to cover a possible range of climatic scenarios in this arid-region island. The 2D and 3D simulation results demonstrate that LSI caused by SLR and recharge rate variation impacts are more important factors in the FGL in comparison to estimated SLR impacts without LSI. It is also shown that climate change impacts on the FGL are long-term to reach a new FGL equilibrium in the case of Kish Island’s aquifer system. The comparative analysis of 2D and 3D results shows that three-dimensionality is a significant factor, especially in large-scale 3D systems of small islands. The results of this study are expected to have implications for the understanding and management of the fresh groundwater resources of Kish Island and are also expected to be relevant to the study of the impact of climate change on groundwater resources on islands worldwide. [ABSTRACT FROM AUTHOR]

Summary European water policy developments are essentially linked to the implementation of the EU Water Framework Directive and parent legislation, which is built upon the principle of river basin management planning with the objective of achieving good status for all European water bodies. Recent policy developments in the climate change area call for ‘climate proofing’ of EU actions through mainstreaming of adaptation measures into policies and programmes. These policy trends are very closely related to the capacity to get access to supporting scientific information and to bridge the knowledge gap. This paper is about these features, serving as an introduction to the special issue of Journal of Hydrology on climatic change impact on water: overcoming data and science gaps. [ABSTRACT FROM AUTHOR]

Summary Flash floods and debris flows develop at space and time scales that conventional observation systems for rainfall, streamflow and sediment discharge are not able to monitor. Consequently, the atmospheric, hydrological and geomorphic controls on these hydrogeomorphic processes are poorly understood, leading to highly uncertain warning and risk management. On the other hand, remote sensing of precipitation and numerical weather predictions have become the basis of several flood forecasting systems, enabling increasingly accurate detection of hazardous events. The objective of this paper is to provide a review on current European and international research on early warning systems for flash floods and debris flows. We expand upon these themes by identifying: (a) the state of the art; (b) knowledge gaps; and (c) suggested research directions to advance warning capabilities for extreme hydrogeomorphic processes. We also suggest three areas in which advancements in science will have immediate and important practical consequence, namely development of rainfall estimation and nowcasting schemes suited to the specific space–time scales, consolidating physical, engineering and social datasets of flash floods and debris-flows, integration of methods for multiple hydrogeomorphic hazard warning. [ABSTRACT FROM AUTHOR]

Summary Integrated Water Resources Management (IWRM) was introduced in 1980s to better optimise water uses between different water demanding sectors. However, since it was introduced water systems have become more complicated due to changes in the global water cycle as a result of climate change. The realization that climate change will have a significant impact on water availability and flood risks has driven research and policy making on adaptation. This paper discusses the main similarities and differences between climate change adaptation and IWRM. The main difference between the two is the focus on current and historic issues of IWRM compared to the (long-term) future focus of adaptation. One of the main problems of implementing climate change adaptation is the large uncertainties in future projections. Two completely different approaches to adaptation have been developed in response to these large uncertainties. A top-down approach based on large scale biophysical impacts analyses focussing on quantifying and minimizing uncertainty by using a large range of scenarios and different climate and impact models. The main problem with this approach is the propagation of uncertainties within the modelling chain. The opposite is the bottom up approach which basically ignores uncertainty. It focusses on reducing vulnerabilities, often at local scale, by developing resilient water systems. Both these approaches however are unsuitable for integrating into water management. The bottom up approach focuses too much on socio-economic vulnerability and too little on developing (technical) solutions. The top-down approach often results in an “explosion” of uncertainty and therefore complicates decision making. A more promising direction of adaptation would be a risk based approach. Future research should further develop and test an approach which starts with developing adaptation strategies based on current and future risks. These strategies should then be evaluated using a range of future scenarios in order to develop robust adaptation measures and strategies. [ABSTRACT FROM AUTHOR]

Summary Glacier and snow cover changes with related impacts on melt runoff can seriously affect human societies which are depending on fresh water from cryospheric sources. Observed trends and projected future evolutions of climatic and cryospheric variables clearly show the need to adapt to these changes. Accordingly, the topics addressed herein have been put on the agendas of many larger funding agencies. This article provides a brief overview on major ongoing activities on glacier, snow and related runoff research in order to then analyze data gaps and research needs from a climate change adaptation perspective. Major data needs are identified with respect to the spatial and temporal coverage of local-scale data and related needs for (data) services that distribute and maintain these data sets. Moreover, clear research needs are also recognized at the local scale where process knowledge needs to be improved (e.g., the influence of albedo on snow and ice or debris cover on glaciers) in order to derive plausible climate change impacts assessments. The paper then discusses directions on how to move forward to better serve the practical needs for climate change adaptation planning. In the future, substantial support by large funding agencies might be key for capacity building in target regions of climate change adaptation programs, for longer-term and more sustainable commitments, and for the development of approaches, which aim at assessing the transferability of data, techniques, and tools. [ABSTRACT FROM AUTHOR]

Summary Glacier shrinkage caused by climate change is likely to trigger diminished and less consistent stream flow in glacier-fed watersheds worldwide. To understand, model, and adapt to these climate-glacier-water changes, it is vital to integrate the analysis of both water availability (the domain of hydrologists) and water use (the focus for social scientists). Drawn from a case study of the Santa River watershed below Peru’s glaciated Cordillera Blanca mountain range, this paper provides a holistic hydro-social framework that identifies five major human variables critical to hydrological modeling because these forces have profoundly influenced water use over the last 60 years: (1) political agendas and economic development; (2) governance: laws and institutions; (3) technology and engineering; (4) land and resource use; and (5) societal responses. Notable shifts in Santa River water use—including major expansions in hydroelectricity generation, large-scale irrigation projects, and other land and resource-use practices—did not necessarily stem from changing glacier runoff or hydrologic shifts, but rather from these human variables. Ultimately, then, water usage is not predictable based on water availability alone. Glacier runoff conforms to certain expected trends predicted by models of progressively reduced glacier storage. However, societal forces establish the legal, economic, political, cultural, and social drivers that actually shape water usage patterns via human modification of watershed dynamics. This hydro-social framework has widespread implications for hydrological modeling in glaciated watersheds from the Andes and Alps to the Himalaya and Tien Shan, as well as for the development of climate change adaptation plans. [ABSTRACT FROM AUTHOR]

Summary The climate elasticity of runoff is an important indicator that is used to quantify the relationship between changes in runoff and changes in climate variables. It is a function of both climate and catchment characteristics. Recently, Yang and Yang (2011) proposed an analytical derivation of climate elasticity (YY2011), in which a parameter n was used to represent the impact of the catchment characteristics. In China, both climate and catchment characteristics have large spatial variations. To understand the spatial variation of hydrologic response to climate change, this paper divided China into 210 catchments, further calculated the parameter n , and then estimated the climate elasticity and evaluated the contribution of climate change to runoff for each catchment. The results show that n ranges from 0.4 to 3.8 (with a mean of 1.3 and a standard deviation of 0.6), which has a logarithmic relationship with catchment slope; the precipitation elasticity ranges from 1.1 to 4.8 (with a mean of 1.9 and a standard deviation of 0.6), which shows a large regional variation, smaller values (1.1–2.0) mainly appearing in Southern China, the Songhua River basin and the Northwest, and larger values (2.1–4.8) mainly appearing in the Hai River basin, the Liao River basin and the Yellow River basin. In addition, climate contribution to runoff exhibits a large regional variation, the largest positive values (1.1–3.1%/a) occurring in the Northwest, the largest negative values (−1.0 to −0.5%/a) occurring in the Hai River basin and the middle reach of the Yellow River basin. In theory, the YY2011 method is a first-order approximation. The approximation underestimates the precipitation ( P ) contribution to runoff when P increases and overestimates that when P decreases, and the relative error has a median of ∼3% and a maximum of ∼20% when 10% precipitations change in those catchments of China. [ABSTRACT FROM AUTHOR]

Summary This paper uses past hydrological records in Northeastern Illinois to disentangle the combined effects of urban development and climatic variability at different spatial scales in the Greater Chicago Area. A step increase in annual precipitation occurred in Northeastern Illinois during 1965–1972 according to climate records. Urbanization has occurred as a gradual process over the entire Greater Chicago Area, both before and after the abrupt annual precipitation increase. The analysis of streamflow trends at each gaging station is supplemented by the comparison of the evolution of streamflow indicators in a group of urban and agricultural watersheds, thanks to an original use of the Mann–Whitney test. Results suggest that urban expansion in the Greater Chicago Area has led to widespread increases in a wide variety of streamflow metrics, with the exceptions being spring flows and some of the peak flow indicators. The increases detected in small (<100 km 2 ) urban watersheds are mitigated in large (>200 km 2 ) ones, over which the changes in streamflow are relatively homogeneous. While the impacts of land-use change are identified across a wide range of flow indicators and spatial scales, there are indications that some of these effects are mitigated or made negligible by other factors. For example, while impervious surfaces are found to increase flooding, stormwater management facilities, an adaptation to increased flooding, mitigate their impacts at a wide range of scales. While impervious surfaces are known to reduce infiltration and baseflow, a low flow increase was triggered by water withdrawals from Lake Michigan, as a response to a rising water demand which made on-site groundwater extraction unsustainable. Our analysis thus highlights the impacts of adaptive planning and management of water resources on urban hydrology. [ABSTRACT FROM AUTHOR]

Summary Accurate quantification of dissolved organic carbon (DOC) in surface and soil pore waters is crucial for understanding changes in water resources under the influence of climate and land use changes. Sampling and laboratory analysis of DOC content at a sufficient temporal frequency are especially difficult to achieve for natural DOC sources like the extensive boreal and arctic mire landscapes due to their remoteness. Therefore, the goals of this paper are (1) to investigate the performance of a portable, high-resolution ultraviolet–visible light spectroscopic method for determining the DOC content of surface and soil pore water samples from a boreal mire complex and (2) to compare the spectroscopic method with other DOC measurement techniques, e.g., the wet heated persulfate oxidation method and a laboratory, expulsion-based spectrophotometric method and (3) to assess different multivariate models that relate absorbance measurements with DOC contents. The study indicates that high-resolution spectroscopic measurements provide a simple, robust and non-destructive method for measuring DOC content. These measurements are of short duration (<1 min) and the sample analysis is portable, rendering this method particularly advantageous for in situ investigations at remote field locations. The study also demonstrates that if absorbances at specific wavelengths are used as proxies for DOC concentration, it is recommended to create site-specific calibration models that include more than one wavelength to achieve the optimal accuracy of the proxy-based DOC quantification. [ABSTRACT FROM AUTHOR]

Summary Spatial variability of climate can negatively affect catchment streamflow predictions if it is not explicitly accounted for in hydrologic models. In this paper, we examine the changes in streamflow predictability when a hydrologic model is run with spatially variable (distributed) meteorological inputs instead of spatially uniform (lumped) meteorological inputs. Both lumped and distributed versions of the EXP-HYDRO model are implemented at 41 meso-scale (500–5000 km 2 ) catchments in the Pacific Northwest region of USA. We use two complementary metrics of long-term spatial climate variability, moisture homogeneity index ( I M ) and temperature variability index ( I TV ), to analyze the performance improvement with distributed model. Results show that the distributed model performs better than the lumped model in 38 out of 41 catchments, and noticeably better (>10% improvement) in 13 catchments. Furthermore, spatial variability of moisture distribution alone is insufficient to explain the observed patterns of model performance improvement. For catchments with low moisture homogeneity ( I M < 80%), I M is a better predictor of model performance improvement than I TV ; whereas for catchments with high moisture homogeneity ( I M > 80%), I TV is a better predictor of performance improvement than I M . Based on the results, we conclude that: (1) catchments that have low homogeneity of moisture distribution are the obvious candidates for using spatially distributed meteorological inputs, and (2) catchments with a homogeneous moisture distribution benefit from spatially distributed meteorological inputs if they also have high spatial variability of precipitation phase (rain vs. snow). [ABSTRACT FROM AUTHOR]

• A hydrological modeling approach was proposed to distinguish the relative contribution of climate changes and human activities on Daihai Lake's recession. • In the absence of natural runoff and human-induced water withdrawal observations, the natural state's lake water storage changes were reconstructed. • Without considering the high water years, the anthropogenic factor took the responsibility for the lake shrinkage about 58%, while the climatic factor took roughly about 42% in period 1974–2018. • This investigation serves as a useful example of applying a distributed model to the assessment of lake hydrology, especially for the lake catchments with limited observations. In recent decades, water levels in many closed inland lakes over north-western China experienced severe declines, among which the Daihai Lake in Inner Mongolia, China was particularly significant. Remotely sensed investigations indicated that the Daihai Lake had shrunk approximately 64% in an area with the dramatic decline of water level approximately 9 m from the 1980 s to 2010 s, which has caused serious concern on the sustainable development of the surrounding region. Consequently, several previous studies have concentrated on the possible causes of lake shrinkage. However, predicting climate variability and anthropogenic activities' relative contributions to lake water decline is challenging due to the lack of direct water consumption upstream and watershed-scale natural runoff observations. In this paper, a hydrological modeling approach was presented to quantitatively evaluate and separate the relative contributions of climate variations and intensifying anthropogenic activities. The simulation accuracy was evaluated through comparisons with observed data and cross-validation with previous studies. Based on a baseline period, the natural streamflow draining into the lake was reconstructed using the model. The results revealed that the water loss of the Daihai Lake was caused predominately by human activities rather than climate variability. Specifically, for wet conditions, the climate factors posed a negative effect on the water level decline of the lake and delayed the shrinking process of the lake area. The anthropogenic factors took a dominant role (roughly 58%) of lake shrinkage at the annual average scale for normal and dry conditions, while the climate factors accounted for approximately 42%. Hence, the rational policy for water resource management, ecological restoration, and dam and reservoir constructions/operations should be the essential precautions for sustainable development of the Daihai Lake and its surroundings. Additionally, the hydrological modeling approach adopted in this investigation serves as a useful example of the quantitative assessment of climate variations and human activities, especially for the ungauged catchments. [ABSTRACT FROM AUTHOR]

• The mean groundwater table depth in China dropped by approximately 0.2 m (P < 0.01) during 1979–2018. • The Noah-MP land model forced with reanalysis climate data can reasonably capture terrestrial water and radiation processes across China. • Incorporating the groundwater lateral flow process enhances the seasonality of modeled terrestrial water and radiation processes on a regional scale. Faced with intensified climate change and ever-increasing water demand, the groundwater table depth is vital to sustaining terrestrial environments in a country such as China; however, on a regional scale, insufficient research has been conducted on its variability thus far. Using a land model forced with reanalysis climate data, this paper investigates groundwater table depth changes across China for the 1979–2018 period. The results show a significant overall reduction in the groundwater table depth in China during the past 40 years without explicit consideration of direct human influence. There is an approximately 0.2 m decrease on average, but it is approximately 0.5 m in southern China and 0.8 m to the north of 35°N despite a 1.2 m rise in part of this region due to an increasingly wet climate and a topographic water convergence. The findings provide a first-order pattern of historical groundwater table responses to climate change, highlighting inherent links among subsurface-surface-atmosphere water cycles and worsened terrestrial water availability in China. A model evaluation compared with in situ observations has demonstrated the model's ability to realistically portray terrestrial water and energy balances on regional scales, as well as the enhancement of their seasonality with incorporated lateral groundwater flow processes. This ability gives us reasonable confidence in the simulated trends and spatial variability. Nonetheless, the mean groundwater table still shows large biases relative to observations, and the problems of human influence, two-way interactions between groundwater and surface water, and local topographical complexity have yet to be properly addressed in the present study and deserve further research. [ABSTRACT FROM AUTHOR]

• Simple approach to evaluate the impact of climate change on groundwater. • Correlation between meteorological and groundwater indices. • Regional climate model outputs to estimate future groundwater levels. This paper investigates the impacts of climate change on groundwater droughts making use of regional projections and standardized indices: the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Groundwater Index (SGI). The method adopted, using historical precipitation and temperature data and water levels collected in monitoring wells, first investigates the possible correlations between meteorological and groundwater indices at each well. Then, if there is a correlation, a linear regression analysis is used to model the relationships between SGIs and SPIs, and SGIs and SPEIs. The same relationships are used to infer future SGIs from SPI and SPEI projections obtained by means of an ensemble of Regional Climate Models (RCMs), under different climate scenarios (RCP 4.5 and RCP 8.5). This methodology has been applied to data collected in northern Tuscany (Italy) in an area served by a water company, where historical series of daily climate variables (since 1934) and daily records for 16 wells, covering the period 2005–2020, are available. The impacts on groundwater have been computed in the short- (2006–2035), medium- (2036–2065) and long-term (2066–2095). The analysis indicates that, in the historical period and for most of the monitoring wells, there is a good correlation between SGIs and SPIs or SPEIs. The results point out that making use of the SGI-SPI relationships, slight variations in the availability of groundwater are expected in the future. However, in a global warming scenario, the influence of temperature on evapotranspiration phenomena cannot be overlooked and, for this reason, the SGI-SPEI relationships seem more suitable to forecast groundwater droughts. According to these relationships, negative effects on groundwater levels in almost all wells are estimated for the future. For the RCP 4.5 scenario, the largest decline in groundwater level is expected in the medium-term, while for the RCP 8.5 scenario future SGIs will significantly decrease over the long-term. Due to the type of data required and its simplicity, this methodology can be applied to different areas of interest for a quick estimate of groundwater availability under climate change scenarios. [ABSTRACT FROM AUTHOR]

• DRASTIC-AgLU-CC is applied to examine future groundwater contamination risk. • Climate and land use factors are treated as dynamic model inputs. • The influence of land use scheme complexity on model output is assessed. • Detailed agricultural land use representation may improve model predictions. • Predicted contamination risk varies depending on land use representation. Rural regions, which are commonly reliant on groundwater for water supply, often face groundwater quality challenges related to agricultural activity. To sustainably manage and protect groundwater resources, it is necessary to have a clear understanding of inherent groundwater vulnerability and the contamination risk posed by pollutant loading. Index-based methods typically assess groundwater contamination risk in a static manner and commonly represent agricultural land as a single land use class despite the complexity of land management practices that may be present. This paper illustrates modification of the conventional DRASTIC-LU methodology, through a newly developed DRASTIC-AgLU-CC approach, to better understand how groundwater contamination risk may change by mid-century while simultaneously examining the potential influence of land use scheme complexity on model performance and prediction. Recharge, depth to water table, and land use are treated as dynamic factors through the integration of downscaled global climate model data, empirically estimated water table fluctuation and recharge, and trend-based land change modelling. The Upper Parkhill watershed in southwestern Ontario, Canada serves as a case study for method application. Study results indicate that more detailed agricultural land use representation, specifically the inclusion of crop rotation and tile drainage data, has the potential to improve model predictive ability; furthermore, predicted future changes in groundwater contamination risk may vary depending on the manner in which land use is represented. Within the Upper Parkhill watershed, mid-century land use and climate conditions may increase groundwater contamination risk, although minimal change is anticipated. The presented approach provides a valuable screening tool to better understand the potential for changing groundwater contamination risk in rural regions and can be used to guide groundwater monitoring programs and water supply development. [ABSTRACT FROM AUTHOR]

• Proposes an analytic framework to identify when a adaptation operating rule is needed. • Introduces the probability change-point analysis technique into failure warning time. • Evaluates the proposed framework based on a real-world case study in China. This paper presents a methodology for the identification of the time tipping point where historical operating rules of a reservoir system should be replaced by new alternatives due to climate change. The time tipping point is a time indicator of the failure probability change point of the historical operating rules for the reservoir system under future climate change, called the failure warning time. For this study, the primary purpose of the reservoir system is hydropower generation. We first estimate the probability density function of the annual benefit of hydropower generation. Then, based on the estimated probability density function and the given risk tolerance level of the reservoir system, we determine the risk-based warning threshold, and further identify the failure warning time of the historical operating rules via the probability change-point analysis technique. We apply the proposed methodology to the Xiluodu-Xiangjiaba-Three Gorges cascade reservoir system on the Yangtze River in China. The results indicate that the failure warning time for the cascade reservoir system will occur in at least another 10 years in the future under climate change. We also find that the failure response in the cascade reservoir system is determined by both the reservoir that has the first failure occurrence and its storage capacity. The developed methodology can be used to determine the time tipping point to launch adaptation strategies for the river basin management, and further can help policymakers cope with climate change. [ABSTRACT FROM AUTHOR]

• IBIS may be more impacted by climate change in UIB than local hydrology. • Sedimentation combined with climate change exacerbates dry season water shortages. • Water availability reductions in the dry season could impact Pakistan's food security. Pakistan relies greatly on the water of the Upper Indus basin (UIB) for its vast agriculture in the Indus Basin Irrigation System (IBIS). There are already concerns about the extent of unsustainable water use in the IBIS, particularly of groundwater, and these concerns are likely to increase in the future due to population increase and associated increased demand for food. In addition, climate change, continuing reservoir sedimentation in the major dams, and other impacts on water supply and demand are likely to have an impact on the practical implementation of the landmark inter-provincial Water Apportionment Accord (the Accord), which governs surface water allocation in the IBIS. There is, therefore, a need to assess the sustainability of irrigation in light of the potential variations of water availability in the basin under a series of plausible climate change and reservoir sedimentation scenarios. In this paper, we examine the impact of continuing reservoir sedimentation and climate change by 2050 on the water balance of canal commands in the IBIS. Firstly, we used a river system model, the first to include water management rules as in the Accord, to propagate climate induced changes on flows in the UIB and their impact on IBIS flow regulation and canal deliveries (I cw), with and without reservoir sedimentation. Secondly, we used a selection of General Circulation Models (GCMs) that showed skill at simulating the local climate of the IBIS to assess the projected changes to rainfall (P n) and evapotranspiration (ET a). The analysis revealed that water balances in IBIS canal command areas are more significantly affected by changed inflows from the UIB than by localised climate induced changes (i.e. P n and ET a). Continuing reservoir sedimentation in the dams to 2050 will diminish the capacity of the system to store flows during the wet summer Kharif season for its later release in the dry winter Rabi season. This will decrease the supply of I cw in the Rabi season to the downstream IBIS areas in Sindh and Balochistan provinces, and potentially increase supplies in the Kharif season. The impact of reservoir sedimentation on the Rabi water supply (33 mm (13%) decrease in median I cw , equivalent to 1.89 km3), is greater than the impact of projected localised climate change within the IBIS (2 mm (12%) decrease in median P n , equivalent to 0.13 km3). Sedimentation combined with climate change decreases the median I cw by 51 mm (20%, equivalent to 2.91 km3) in Rabi in the low flow scenario and increases it by 48 mm (8%, equivalent to 2.72 km3) in Kharif in the high flow scenario. In the upstream Punjab province, however, reservoir sedimentation will have limited impact by 2050 due to lower ET a in Rabi and the availability of groundwater. Continued reservoir sedimentation beyond 2050 will also affect Punjab, again diminishing the supply of I cw in Rabi and increasing it in Kharif. Concurrently, declining I cw could lead to a substantial reduction in crop areas in the Rabi season. To avoid this undesirable scenario, Pakistan needs to explore both demand and supply management options to achieve food and economic security, as well as controlling sedimentation rates in reservoirs. [ABSTRACT FROM AUTHOR]

• An observation-based natural and human-impacted catchment comparison method is proposed. • Human influence are quantified based on gridded socio-economic and land use data. • Climatic and anthropogenic influences on drought propagation are investigated. • Climate change accelerates the response of hydrological drought to meteorological drought. • Human activities delay the propagation from meteorological to hydrological drought. It is crucial to investigate how a precipitation deficit is transformed into hydrological drought and how climate change and human activities affect this transformation process, which is helpful to gain a deep understanding of drought propagation process in this changing environment. This study proposed an observation-based natural and human-impacted catchment comparison method to assess the impacts of climate change and human activities on propagation from meteorological drought to hydrological drought. The method mainly consists of the following three steps: (1) selection of natural catchments through analysis of trends and change points of hydro-meteorological data, as well as statistics analysis of human influence based on land use and socio-economic indicators data sets; (2) calculation of drought propagation characteristics (e.g., drought severity, duration, and propagation time) based on run theory and the Pearson correlation coefficient; and (3) comparison of drought propagation characteristics of natural catchments between undisturbed and disturbed periods to identify the impacts of climate change on drought propagation, and comparison of the propagation characteristics between natural and human-impacted catchments during the disturbed period to investigate human influence on drought propagation. The Laohahe basin (with eleven sub-catchments), located in northern China, was evaluated via the proposed procedure, and standardized precipitation index (SPI) and standardized runoff index (SRI) were used to characterize meteorological and hydrological droughts, respectively. The results demonstrate that the proposed method is suitable tool for distinguishing natural and human-impacted catchments, and separating the impacts of climate change and human activities on drought propagation. Furthermore, the comparison results of different schemes show that climate change accelerates the propagation from meteorological drought to hydrological drought in the Laohahe basin, shortening it by approximately 3 months. Human activities, however, disturb and then delay the natural propagation from meteorological drought to hydrological drought, retarding it by 11–12 months. Although the Laohahe basin was selected as a case study in this paper, the proposed method can be applied in other regions as well to improve drought prediction and water resources management. [ABSTRACT FROM AUTHOR]

• Use of distributed storage with optimised layout and control reduces peak flows. • Two-step optimisation identifies contribution of layout/RTC to peak flow reduction. • Peak flow reductions due to distributed storage range from 5% to 40% • RTC achieves higher relative peak flow reduction for a smaller storage volume. • Flood hydrograph analysis provides insights on peak flow reduction mechanisms. The impact of urban flooding is increasing due to the effects of increasing urbanisation and climate change. The use of storages is a relatively well-established approach to reduce peak flows and therefore reduce the need for costly upgrades to stormwater conveyance infrastructure. Recently, real-time control (RTC) has been considered as a means of increasing the performance of these storages. However, previous RTC studies have generally focussed on evaluating RTC with pre-determined storage layouts, i.e., storage locations and volumes, and have ignored the impact of optimising the storage layout. Hence, the objectives of this paper are (i) to introduce a two-step approach to minimising peak flows at the catchment scale by firstly optimising the layout of distributed storages and then optimising their RTC strategies, and (ii) to test the effectiveness of this approach on a real catchment in Adelaide, South Australia. Results show that distributed storage with optimised layouts can achieve significantly higher peak flow reductions than more commonly used end-of-system storage. These range from 5% for 100 m3 of system storage up to 40% for 700 m3 of system storage – whereas end-of-system storage achieved no peak flow reduction for up to 700 m3 of storage. The addition of optimised RTC to distributed storages is able to achieve an additional 10% in peak flow reduction. This increase in performance due to RTC is more significant for smaller system storage volumes. Analysis of the flood hydrographs shows the system peak flow reductions are achieved by attenuating hydrographs at individual storages, as well as delaying hydrographs to reduce their coincidence at the confluence of sub-catchments. These results highlight the potential for using optimised distributed storage layout and RTC as an alternative approach to end-of-system storage to reduce flood peaks. [ABSTRACT FROM AUTHOR]

Summary: Conventional techniques for quantifying and then managing flood risks are invalid under ‘non-stationary’ climate conditions. Trend detection and attribution are problematic given that the outcome depends on the start and end date of the record, choice of index and test statistic, assumed behaviour of the system, and many non-climatic confounding factors. Analyses are further hampered by short and non-homogeneous flow records. In this paper, we use an objective weather classification scheme to reconstruct the atmospheric drivers of fluvial flood occurrence and magnitude in England, Scotland and Wales since the 1870s. We demonstrate the index using long (>50year) annual maximum (AMAX) and peak over threshold (POT) flood records for 114 stations. Synoptic indices show modest skill at hindcasting multi-decadal variations in flood frequency at national, regional and catchment scales, but not for flood magnitudes. Flood rich episodes are identified in the periods 1908–1934, 1977–1988 and from 1998 onwards. We find that five weather types account for 68% of flood occurrence, and just three types were linked to the most widespread winter floods. These flood-generating systems generally show no sustained changes in frequency, persistence, relative contribution, or rain-bearing properties since the 1930s. However, there are emergent patterns in the day-to-day persistence (declining) and mean precipitation yield (rising) of anticyclonic weather types that merit further investigation. Based on our evaluation, we recommend use of objective weather indices derived from observed atmospheric pressure patterns when interpreting fluvial flood risk linked to climate drivers. [Copyright &y& Elsevier]

Summary: Statistical downscaling of precipitation is required as part of many climate change studies. Statistical downscaling based on regression models requires one to sample from the conditional distribution to preserve the variance of observed precipitation. In this paper, we present a new technique for downscaling precipitation. The proposed method employs quantile regression rather than traditional linear regression models to determine the conditional distribution for a given day. This eliminates the need for some of the assumptions required in standard linear regression, including the assumption of normally-distributed errors with constant variance. The quantile regression model also allows considerable flexibility in selecting predictor variables in that different subsets of predictors can be used for different parts of the conditional distribution. A Bayesian method adapted to quantile regression is used to select predictor variables. The method is illustrated through an application to five weather stations in Canada. It is found that the proposed method has distinct advantages over the conventional regression model for predicting summer precipitation, while for winter precipitation there is not much difference between the two methods. [Copyright &y& Elsevier]

Summary: This paper presents an assessment of the impacts of climate change on a series of indicators of hydrological regimes across the global domain, using a global hydrological model run with climate scenarios constructed using pattern-scaling from 21 CMIP3 (Coupled Model Intercomparison Project Phase 3) climate models. Changes are compared with natural variability, with a significant change being defined as greater than the standard deviation of the hydrological indicator in the absence of climate change. Under an SRES (Special Report on Emissions Scenarios) A1b emissions scenario, substantial proportions of the land surface (excluding Greenland and Antarctica) would experience significant changes in hydrological behaviour by 2050; under one climate model scenario (Hadley Centre HadCM3), average annual runoff increases significantly over 47% of the land surface and decreases over 36%; only 17% therefore sees no significant change. There is considerable variability between regions, depending largely on projected changes in precipitation. Uncertainty in projected river flow regimes is dominated by variation in the spatial patterns of climate change between climate models (hydrological model uncertainty is not included). There is, however, a strong degree of consistency in the overall magnitude and direction of change. More than two-thirds of climate models project a significant increase in average annual runoff across almost a quarter of the land surface, and a significant decrease over 14%, with considerably higher degrees of consistency in some regions. Most climate models project increases in runoff in Canada and high-latitude eastern Europe and Siberia, and decreases in runoff in central Europe, around the Mediterranean, the Mashriq, central America and Brasil. There is some evidence that project change in runoff at the regional scale is not linear with change in global average temperature change. The effects of uncertainty in the rate of future emissions is relatively small. [Copyright &y& Elsevier]