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Bai et al. ([3]) in their article «Impact of climate change on water transfer scale of inter-basin water diversion project» present a systematic approach for runoff prediction, impact analysis, and risk assessment under climate change. Elnashar and Elyamany ([8], [9]) in the paper «Managing Risks of Climate Change on Irrigation Water in Arid Regions», propose a systematic approach to identify, analyse, and respond to the risks of climate change on irrigation water in arid regions using a Risk Management process. In the paper «Complex policy mixes are needed to cope with agricultural water demands under climate change» by Martinez-Valderrama et al. ([23]) the authors argue that the forecast of the water gap (difference between agricultural water use and annual supply of water resources) will continue to widen, affecting the water security of a large part of the world's population. Elnashar and Elyamany ([8], [9]) in the paper «Adapting Irrigation Strategies to Mitigate Climate Change Impacts: A Value Engineering Approach» accept the fact that climate change will increase water demand and decrease crop yields. [Extracted from the article]

The Mediterranean basin is particularly prone to climate change and vulnerable to its impacts. One of the most relevant consequences of climate change, especially for the southern Mediterranean regions, is certainly water scarcity as result of a reduction of surface runoff and groundwater levels. Despite the progress achieved in recent years in the field of climate change and its impact on water resources, results and outcomes should be treated with due caution since any future climate projection and derived implications are inevitably affected by a certain degree of uncertainty arising from each different stage of the entire modeling chain. This work offers a comprehensive overview of recent works on climate change in the Mediterranean basin, mainly focusing on the last ten years of research. Past and future trends on different components of the hydrological balance are discussed in a companion paper (Noto et al. 2022), while the present paper focuses on the problem of water availability and water scarcity. In addition, the work aims to discuss the most relevant sources of uncertainty related to climate change with the aim to gain awareness of climate change impact studies interpretation and reliability. [ABSTRACT FROM AUTHOR]

Water scarcity is exacerbating in many regions across North America because of climate change compounded by population growth, overexploitation of freshwater resources, and lack of proper management. Considering the regional urgency, there is an immense need to find more equitable solutions for water management. Therefore, this paper aims to examine the climatic factors impacting the hydrological regime in North America, including changes in surface runoff, groundwater storage, and the forested watershed, based on current trends and future projection scenarios. Moreover, this paper critically overviews need-based solutions for effective water management at a regional scale. The study shows that many areas of North America are exposed to extreme events such as prolonged droughts, devastating floods, wildfires, and altering precipitation patterns. Consequently, these changes are triggering wide-ranging impacts on water resources, leading to water supply deficiencies and influencing water flows and quality in the Southwestern United States, prairie provinces in Canada, and Mexico. The projection of warming around the region experiences spatial and seasonal variations because of the diversity in climatic conditions. Overall, in North America, winter is expected to warm more than other seasons causing earlier runoff and a decline in snowmelt. Given the physical and economic constraints that limit the development of new utilities, emphasis should be placed on strengthening nature-based solutions such as green infrastructure. Thus, the findings suggest an integrated water resource management approach is required, along with climate-induced innovative technologies, to secure the water resources while preparing for the forecasted challenges of tomorrow. [ABSTRACT FROM AUTHOR]

In the last years, the Mediterranean basin has been widely recognized as one of the most vulnerable areas in the world to climate change; because of its high concentration of urban and industrial settlements, it is one of the most impacted areas of the world in terms of water scarcity. The present paper aims at reviewing the main observed and predicted effects of climate change on hydrological processes directly related to water availability in the Mediterranean Basin, mainly focusing on the last ten years of research. While an in-depth discussion about possible future water scarcity problem in the Mediterranean area and the sources of uncertainty affecting future climate projections and impact assessments is presented in a companion paper (Noto et al., 2022), this study highlights how most of the more recent studies for the Mediterranean region are concordant and recognize a general increasing future trajectory in both the mean and extreme values of air temperatures. On the contrary, there is much less agreement about the intensity and directions of future projections for other variables, such as precipitation, evapotranspiration, and runoff, whose changes are less evident and variable in space. [ABSTRACT FROM AUTHOR]

Water scarcity and climate change are posing new challenges to irrigation management. Climate change increases water demand and decreases crop yields. The aim of this paper is to propose a framework to select the most efficient irrigation strategy to mitigate the impacts of climate change and achieve food security. Value engineering (VE) methodology is utilized to assure the functionality of the strategy and add an element of creativity while creating the value alternatives. The life cycle cost (LCC) technique is utilized to provide the optimum irrigation strategy from an economic perspective. The findings showed three different value alternatives for different crops, soil types, and irrigation systems. This paper contributes to the current state of knowledge by a) utilizing the Value Engineering methodology in irrigation management studies; b) evaluating irrigation strategies to ensure efficient irrigation water management; and c) providing policymakers with a tool to incorporate the added value and functionality into their policies regarding irrigation water. [ABSTRACT FROM AUTHOR]

Climate change leads to the extreme occurrence of events, water-related disasters, and pressure on existing water resources. The water resource is important for the ecosystem to create resilient and sustainable settlements. The imbalance between evaporation and precipitation creates either shortage or excess of water in the ecosystem. The shortage leads to water stress whereas excess causes flooding. Out of 28 states in India, Bihar is the most vulnerable state with 16.5 percent of the entire flood-prone area and 22 percent of the total flood-affected population of the country. The paper examines water stress and its relationship with flood damage in north Bihar. The paper's novelty is to identify critical districts facing water stress, flood damage and formulate intervention strategies to create a water-secure region. Using Water Poverty Index (WPI), water stress is estimated for five key components i.e. resource, access, use, capacity, and environment. WPI score is less than 0.35 in 14 districts depicting severe water stress conditions. Flood Damage Index (FDI) estimates the severity of the flood and it's impact considering three parameters i.e. population affected, area affected, and economic loss due to crop damage. Darbhanga district has a maximum FDI score of 0.84 and the least WPI score of 0.22, making it the most critical district. The analysis of WPI and FDI shall be used to devise water and disaster-related policies to alleviate water stress and promote flood-resilient development in flood-affected areas. [ABSTRACT FROM AUTHOR]

Recent years have witnessed climate change characterized by increasingly frequent extreme precipitation events, and the assumption of stationarity in traditional frequency analyses is gradually being questioned. In terms of the current research status in China, there is a lack of thorough investigations on the linkage between extreme precipitation and climate change. This paper aims to determine the dominant climate indices as well as the corresponding significant time scales and periods affecting extreme precipitation over China for dynamic assessments of the upcoming rainstorm risk. Correlations between 15 climate indices and precipitation extremes, as well as the correlations among climate indices, are fully explored to identify potential predictors for non-stationary modeling. Then, 21 non-stationary generalized extreme value (GEV) models are constructed, and the optimal covariates as well as their lag times with extreme precipitation at 769 stations are ascertained in a Bayesian framework. Finally, a complete predictive process is developed, and the national rainstorm risk under non-stationary conditions is assessed. The results indicate that precipitation extremes remain stationary only at 74 stations (less than 10%). WPI is dominant in modeling the variability in precipitation extremes for nearly 22% of the total stations, ranking first among all the climate indices. The predominant time scale affecting extreme precipitation at the majority of stations is 3 months. Ignoring the non-stationarity of extreme precipitation inevitably leads to misperceptions of rainstorm risks, and the spatial distribution of the maximum case of the design rainstorms under non-stationary conditions differs remarkably from that under stationary conditions. Our findings have important implications for the in-depth understanding of the real drivers of extreme precipitation non-stationary and enable advanced predictions of rainstorm risks for mitigating subsequent disasters. [ABSTRACT FROM AUTHOR]

Optimising the use of natural resources for food production in the context of changing climate is an increasingly important issue. Optimisation techniques have been shown to be remarkably effective for planning problems, and tools regional planners and farmers can use to determine the viability of agricultural land use planning into the future. This paper systematically reviews the recent literature in this area and draws out the key emerging themes: few studies to date have explicitly incorporated climate projections into optimisation models; increased tension for water resources between stakeholders; and various agricultural production systems of complex versions of crop planning. From this review it can be seen that increasing concentration on the use of climate projection models within agriculturally-oriented optimisation processes is a necessity. [ABSTRACT FROM AUTHOR]

Climate change is impacting people's lives, with management of water resources and food security being major concerns for the future of many countries. In this paper, future water availability, crop water needs, yields, market costs and returns of current crops in a case study area in Australia are evaluated under future climatic conditions. The predictive methods on which the work is based have the advantage of being robust—they are able to simultaneously consider many climate change models—giving greater confidence in determining what the future will hold in this regard. The results indicate business as usual, in terms of the quantity and types of crops that can be grown presently, will not be sustainable in the medium and long term future. Instead, modelling indicates that changes in production and land use to maximise revenue per megalitre of water will be needed to adapt to future conditions and deliver climate-smart agriculture. [ABSTRACT FROM AUTHOR]

Future climate change will alter regional hydrometeorological conditions, which poses significant risks to the operation of inter-basin water diversion projects in the future. Most previous studies focused on adaptive operations under climate change. Few studies examined how to best manage risks and quantify the effect of climate change on objective losses. This paper intends to present a systematic approach for runoff prediction, impact analysis on objectives, and risk assessment under climate models. The Xin'AnJiang hydrological model, single-objective and multi-objective reservoir operation models, and risk assessment model of multiple schemes are integrated into this approach. Taking the inter-basin water diversion project from Hanjiang to Weihe River as a case, the study has made three contributions. First, the negative impacts of climate change on water transfer, net power generation, and transformation ratio between them are quantified. Second, the difference in water transfer scale between single-objective and multi-objective caused by climate change is analyzed. Third, to recommend scheduling schemes balancing benefits and risks and coping strategies to help policymakers mitigate the inevitable harmful effect of climate change. Consequently, it is extremely necessary to prepare to deal with the risks of insufficient water transfer and nip them in the bud. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to analyze the impact of climate change on water resources management and groundwater quantity and quality in the coastal agricultural Almyros Basin, in Greece. Intensive groundwater abstractions for irrigation and nitrogen fertilization for crop production maximization, have caused a large water deficit, nitrate pollution, as well as seawater intrusion in the Almyros aquifer system. Multi-model climate projections for Representative Concentration Pathways (RCPs 4.5 and 8.5) from the Med-CORDEX database for precipitation and temperature have been used to evaluate the impacts of climate change on the study area. The multi-model climate projections have been bias-corrected with Delta, Delta change of Mean and Variance, Quantile Delta Change, Quantile Empirical Mapping, and Quantile Gamma Mapping methods, and statistically tested to find the best GCM/RCM multi-model ensemble. Simulation of coastal water resources has been performed using an Integrated Modelling System (IMS) that contains connected models of surface hydrology (UTHBAL), groundwater hydrology (MODFLOW), nitrate leaching/crop growth (REPIC), nitrate pollution (MT3DMS), and seawater intrusion (SEAWAT). The results indicate that the best climate multi-model ensemble consists of three (3) climate models for both RCP4.5 and RCP8.5 using the Quantile Empirical Mapping bias-correction method. The IMS was applied for historical and future periods with observed and simulated meteorological inputs (e.g. precipitation and temperature) and various irrigation and agronomic scenarios and water storage works development (i.e. reservoirs). The results indicate that at least deficit irrigation and deficit irrigation along with rain-fed cultivation schemes, combined with or without the development and operation of reservoirs, should be applied to overcome the degradation of groundwater quality and quantity in the study basin. Based on the findings of this work, the water resources management should be adaptive to tackle the water resources problems of the Almyros Basin. [ABSTRACT FROM AUTHOR]

Accurate climate projections help policymakers mitigate the negative effects of climatic changes and prioritize environmental issues based on scientific evidences. These projections rely heavily on the outputs of GCMs (General Circulation Models), but the large number of GCMs and their different outputs in each region confuses researchers in their selection. In this paper, we analyzed the performance of a CMIP6 (Climate Model Intercomparison Project Phase 6) multi-model ensemble for Pr (precipitation) data over NE (Northern Europe). First of all, we evaluated the overall performance of 12 CMIP6 models from GCMs in 30 years of 1985–2014. Furthermore, future projections were analyzed between 2071 and 2100 using SSP1-2.6 and SSP5-8.5 (Shared Socioeconomic Pathways). Then, simulations were statistically improved using an ensemble method to correct the systematic error of the CMIP6 models and then the capacity of postprocessed data to reproduce historical trends of climate events was investigated. Finally, the possible spatio-temporal changes of future Pr data were explored in Tana River Basin. The results of this study show that different CMIP6 models do not have the same accuracy in estimating Pr in the study area. However, the ensemble method can be effective in increasing the accuracy of the projections. The results of this study projected a change in the monthly Pr data over Tana River Basin by 2.46% and 2.06% from 2071 to 2100 compared to the historical period, based on SSP1-2.6 and SSP5-8.5, respectively. [ABSTRACT FROM AUTHOR]

Abnormal changes in temperature, precipitation, atmospheric carbon dioxide, or solar radiation are examples of climate change that may affect irrigation water demand. Studies show an increasing trend in the earth's surface temperature, with decreasing trends in rainfall. With most studies focused on predicting the extent of climate change, fewer studies focused on developing appropriate response strategies. This paper aims to propose a systematic approach to identify, analyze, and respond to the risks of climate change on irrigation water in arid regions using the Risk Management process. The compound effect of these risks was analysed using Monte Carlo Simulation, which indicated a 69% loss in crop production due to climate change at a 90% confidence level. The proposed responses to the risks of climate change include strategies to avoid, transfer, mitigate, and/or accept these risks. The study has made three contributions to the state of the art. First, to adopt a well-recognized risk management methodology in climate change studies. Second, to quantify the compound effect of climate change risks on irrigation water in arid regions. Third, to recommend a set of response strategies to help policymakers mitigate the inevitable harmful effect of climate change on irrigation water. [ABSTRACT FROM AUTHOR]

The increasing frequency of extreme rainstorms due to climate changes calls for cost-effective methodologies to optimize drainage networks and flood risk mitigation practices. This paper presents an effective methodology that combines two well-known methods to optimize the drainage network design. The methodology uses the Harmony Search algorithm to identify the best solution for the drainage network and the simulations obtained through the Storm Water Management Model to verify the respect of the hydraulic constraints. The methodology is applied to the literature case study of Anytown, showing a significant reduction of 34.5% of the drainage network design cost compared with the common Rational Method. Moreover, the methodology is able to identify the optimum allocation and volumes of detention ponds for runoff control in case of variations in rainfall regime. The methodology allowed to prevent floods, by decreasing the channel filling degree. [ABSTRACT FROM AUTHOR]

Arid region water reservoirs have different characteristics and solutions from humid regions with the most water shortage in the world socio-economically. This paper outlines possible implementation methodologies, procedures and guidance for water storage in natural and artificial reservoirs for better operation and management rules taking into account the impacts of climate change. The literature is full of methodological applications regarding the impact of climate change on the hydro-meteorological records, but the same is not available in reservoirs (surface and underground), which is the scope of this paper. In addition, reservoir structures offer the necessary mitigation and adaptation activities against the effects of climate change to design, construct, maintain, operate or increase their existing capacity. To increase groundwater reservoir capacity in local aquifers, precipitation, associated flooding and flash flooding should be diverted to artificial groundwater recharges through precipitation and surface runoff harvesting activities. Definitions of fully or partially penetrating underground dams are also explained. The real groundwater feeding application is offered from the Kingdom of Saudi Arabia as arid region representative. Finally, a series of recommendations are presented for the future design and management of reservoirs. [ABSTRACT FROM AUTHOR]

Statistical downscaling of General Circulation Models (GCM) simulations is widely used for projecting precipitation at different spatiotemporal scales. However, the downscaling process is linked with different source of uncertainty including structural/parametric uncertainty of the model and output uncertainty. This research proposes a novel framework to assess the parametric uncertainty of downscaling model, and used this framework to assess the performance of different bias correction methods linked to the regression-based statistical downscaling model. The used downscaling framework in the current paper is Statistical Downscaling Model (SDSM). The conventional bias correction method linked with SDSM is the Variance InFlation method (VIF), this paper substitutes this method with three different bias correction methods including Local Intensity Scaling (LOCI), Power Transformation (PT), and Quantile Mapping (QM) to assess the associated parametric and global uncertainty of each method in different climate by using a new approach. The proposed method is applied to six different stations located in Iran and United States with different climate status. Average Relative Interval Length (ARIL), P-level, and Normalized Uncertainty Efficiency (NUE) are used as uncertainty indicators to evaluate the results. Results represent that in every assessed climate class, LOCI, and PT, work better than conventional VIF in both amount and occurrence modules of SDSM framework. More precisely, LOCI works better in station that has wet summer, while PT performs well in the stations where there is no or very limited precipitation in summer. Substituting LOCI with VIF, result in increasing the value of NUE by at least factor of 3 in occurrence and amount model which means the significant reduction in structural uncertainty. Also applying PT in arid regions improves the NUE indicator at least by factor 2 in occurrence and amount model and by factor 3 in output uncertainty assessment, and results in less parametric and output uncertainty. Results illustrate the important role of bias correction approaches in reducing structural, and output uncertainty and improving the statistical efficiency of the downscaling model. [ABSTRACT FROM AUTHOR]

This paper explores the possibility of using a calibrated rainfall-runoff model as a decision-making tool in sustainable water sharing. Designing institutional arrangements for runoff sharing process in the case of a sub-catchment spread across geopolitical boundary is challenging. For the water sharing arrangement to be sustainable, it must be founded on realistic runoff predictions. The climate uncertainties make the water sharing process more complex and complicated. This context warrants a decision-making tool for helping the water sharing policy makers and its managers in taking a decision. In this study, a decision-making tool for sharing the waters of Parambikulam sub-catchment in Southern Peninsular India is developed. RRL (Rainfall-Runoff Library), RAP (River Analysis Package) and SCL (Stochastic Climate Library) of eWater toolkit are used for developing this tool. In the decision making, it also incorporates the runoff change prediction portrayed in India’s second national communication to UNFCC. The existing institutional arrangement for water sharing of this sub-catchment is revisited in the light of findings of this study. Paper is concluded by explaining how it is useful in synthesizing a range of options on designing a new water sharing paradigm for this sub-catchment. [ABSTRACT FROM AUTHOR]

Climate change impact started to play significant role since the last three decades almost in every aspects of life especially on meteorological and climatological events and their impacts on water resources, which are managed by engineering structures. Its effects on hydro-meteorological data are assessed by means of available methodologies, but the climate change impact of engineering water structures (dams, culverts, channels, wells, highways and their side drainages, levees, etc.) are not treated equally. This paper provides the review of the necessary adaptation, combat and mitigation activities against the climate change for protection, construction or augmentation of the engineering water structures design capacity. Additionally, land use practices and geomorphological changes also trigger the climate changes on the engineering water structures. The main aim of this paper is to present the impact of such changes on the engineering water structure capacity, operation and maintenance. [ABSTRACT FROM AUTHOR]

Climate change affects the hydrological cycle and has a significant influence on water resources, which can lead to environmental and socioeconomic damage caused by droughts. This phenomenon has become more acute in recent years. Among the indices used to assess the extent of droughts, the Reconnaissance Drought Index (RDI) is being adopted throughout the world. The RDI requires a stationarity assumption in its statistical calculations; however, most of the hydro-meteorological time series show non-stationarity. Hence, this paper seeks to assess meteorological droughts by means of RDI by adopting both stationary and non-stationary approaches. Non-stationarity was assessed by applying the Mann–Kendall test for trend detection and the Pettitt test for change point detection. The Thornthwaite method was employed to estimate the potential evapotranspiration required for RDI application. The bias in the future series were corrected employing the Linear Scaling (LS) technique for precipitation series and the Empirical Quantile Mapping (EQM) technique for the temperature series. Historical and future simulated monthly temperature and precipitation data were obtained from 34 meteorological stations located within Parana State, Brazil. The results showed that the maximum drought magnitude, duration, and intensity have increased during the 21st Century. When compared with historical patterns up to 2100, the results showed that drought magnitude is expected to increase by 105%, while drought duration is expected to increase by 59% in meteorological drought projections. [ABSTRACT FROM AUTHOR]

The estimation of the Intensity–Duration–Frequency (IDF) relation is often necessary for the planning and design of various hydraulic structures and design storms. It has been an increasingly greater challenge due to climate change conditions. This paper therefore proposes an integrated extreme rainfall modeling software package (SDExtreme) for constructing the IDF relations at a local site in the context of climate change. The proposed tool is based on a temporal downscaling method to describe the relationships between daily and sub-daily extreme precipitation using the scale-invariance General Extreme Value (GEV) distribution. In addition, SDExtreme provides a modified bootstrap technique to determine confidence intervals (CIs) of the estimated IDF curves for current and the future climate conditions. The feasibility and accuracy of SDExtreme were assessed using rainfall data available from the selected rain gauge stations in Quebec and Ontario provinces (Canada) and climate simulations under three different climate change scenarios provided by the Canadian Earth System Model (CanESM2) and the Canadian Regional Climate Model (CanRCM4). [ABSTRACT FROM AUTHOR]

This study investigates the potential impacts of climate change on water management within the Aral Sea basin. By analyzing a wide range of literature the study reviews the anticipated effect of climate change and hydrological patens on water resources in the region. Providing an overview of the current situations and potential scenarios and solutions in the context of changing hydro-climatic conditions is crucial to efficiently managing the water quality and quantity of the Aral Sea basin. By reviewing existing findings and projections, this paper highlights the urgent need for effective water management strategies, sustainable agriculture practices, and regional cooperation to address the complex challenges posed by changing hydro-climatic conditions in the Aral Sea Basin. [ABSTRACT FROM AUTHOR]

The paper presents potential impacts of climate change on rainwater tanks outcomes such as water savings, reliability and water savings efficiency under two projected climate change scenarios; RCP4.5 and RCP8.5 utilising a case study using rainfall data from four stations within the city of Brisbane, Australia. Historical rainfall data were collected from the Australian Bureau of Meteorology website for the selected stations. Projected daily rainfall data were collected from Australian government data portal for the same stations within Brisbane. Using an earlier developed daily water balance model, eTank potential annual water savings were calculated for several weather and climate change scenarios with varied roof areas and rainwater demandValues of 'Seasonality Index (SI)', a commonly used factor representing rainfall variability within a year, were explored to validate earlier developed relationships between SI and water savings efficiency through rainwater tanks. It is found that in most cases water savings in future periods are expected to decrease and such decrease is not necessarily attributed to the expected decrease in rainfall amounts in future, rather also affected by future reductions in rainwater tank reliability. Linear relationships between potential future water savings and reliabilities for all the stations are found. Relationship between SI and water savings efficiency was established, and it is found that the relationship slightly varies with an earlier developed relationship using historical data. Compared to earlier established relationship, for lower SI values water savings efficiency is expected to become better, while for higher SI values the water savings efficiency is expected to become worse. Also, an increase of roof area from 100 m2 to 200 m2 will cause an average increase of water savings efficiency by 25% and an increase of rainwater usage from 200 L/day to 300 L/day will cause an average increase of water savings efficiency by 20%. [ABSTRACT FROM AUTHOR]

The global climate is changing and altering the hydrologic cycle that results in (i) reduction of water supply; (ii) increase in frequency and magnitude of flood and drought events; (iii) damage to the shoreline areas; (iv) increase in irrigation water use; (v) decrease in quality of all freshwater sources; and (vi) increase in functional and operational requirements for the existing water infrastructure. The paper provides the review of water resources management challenges posed by the climate change. In order to provide guidance for including climate change impacts into water management studies, a generic approach is detailed for potential implementation in practice. Methods for selecting global climate models and emission scenarios, followed by bias correction and downscaling are discussed. The paper ends with the description of one practical example, IDF_CC, a web based tool for updating intensity duration frequency curves under changing climate. The tool is designed in response to real needs of water engineering practice and has been in use in Canada since early 2015. [ABSTRACT FROM AUTHOR]

Conducting trend analysis of climatic variables is one of the key steps in many climate change impact studies where trend is often checked against aggregated variables. However, there is also a strong need to investigate the trend of the data in different regimes – examples include high flow versus low flow, and heavy precipitation versus prolonged dry period. For this matter, quantile regression (QR) based methods are preferred as they can reveal the temporal dependencies of the variable in question for not only the mean value, but also its quantiles. As such, the tendencies revealed by the QR methods are more informative and helpful in studies where different mitigation methods need to be considered at different severity levels.In this paper, we demonstrate the use of several quantile regressions methods to analyse the long-term trend of rainfall records in two climatically different regions: The Dee River catchment in the United Kingdom, for which daily rainfall data of 1970–2004 are available; and the Beijing Metropolitan Area in China for which monthly rainfall data from 1950 to 2012 are available. Two quantiles are used to represent heavy rainfall condition (0.98 quantile) and severe dry condition (0.02 quantile). The trends of these two quantiles are then estimated using linear quantile regression before being spatially interpolated to demonstrate their spatial distribution (for Dee river only). The method is also compared with traditional indices such as SPI. The results show that the quantile regression method can reveal patterns for both extremely wet and dry conditions of the areas. The clear difference between trends at the chosen quantiles manifests the utility of QR in this context. [ABSTRACT FROM AUTHOR]

In response to the impacts of extreme precipitation on human or natural systems under climate change, the development of climate risk assessment approach is a crucial task. In this paper, a novel risk assessing approach based on a climate risk assessment framework with copula-based approaches is proposed. Firstly, extreme precipitation indices (EPIs) and their marginal distributions are estimated for historical and future periods. Next, the joint probability distributions of extreme precipitation are constructed by copula methods and tested by goodness-of-fit indices. The future joint probabilities and joint return periods (JRPs) of the EPIs are then evaluated. Finally, change rates of JRPs for future periods are estimated to assess climate risk with the quantitative data of exposure and vulnerability of a protected target. An actual application in Taiwan Island is successfully conducted for climate risk assessment with the impacts of extreme precipitation. The results indicate that most of regions in Taiwan Island might have higher potential climate risk under different scenarios in the future. The future joint probabilities of precipitation extremes might cause the high risk of landslide and flood disasters in the mountainous area, and of inundation in the plain area. In sum, the proposed climate risk assessing approach is expected to be useful for assisting decision makers to draft adaptation strategies and face high risk of the possible occurrence of natural disasters. [ABSTRACT FROM AUTHOR]

Under the influences of climate change and rapid urbanization, extreme rainfall events become more and more intensive and the urban flooding issues have been frequently faced in many cities in the world. Previous practical and scientific experiences have demonstrated that appropriate utilization of detention facilities and low impact development (LID) devices for urban region design could be important and effective ways to the flooding control and drainage service management of an urban stormwater drainage system (USDS). This paper investigates the optimal design and application of detention tank network and LID devices for achieving these multiple objectives in the USDS. The framework and method of LID-based multi-objective optimal design of detention tanks in USDS is first developed in this study, and a practical case in SA city of China is then taken for the application. The results of this study confirm the feasibility and validity of the proposed methodological framework for the LID-based multi-objective optimal design of detention tanks in the USDS. Specifically, both total investment costs and flooding risk have been greatly reduced by the optimal implementation of the detention tank and LID measures. Meanwhile, the results indicate that the LID devices may have global effect to the flooding control and the detention tanks can be locally efficient to reduce the flooding risk. Finally, the findings of this study are discussed in the paper for their practical implications to the practical design and management of USDS. [ABSTRACT FROM AUTHOR]

Concerning the various effects of climate change on intensifying extreme weather phenomena all around the world, studying its possible consequences in the following years has attracted the attention of researchers. As the drought characteristics identified by drought indices are highly significant in investigating the possible future drought, the Copula function is employed in many studies. In this study, the two- and three-variable Copula functions were employed for calculating the return period of drought events for the historical, the near future, and the far future periods. In this paper, bivariate and trivariate of Copula functions were applied to evaluate the return periods of the drought in the historical period and the two near and near future periods. Moreover, the results of considering bivariate and trivariate of Copula functions were compared separately with the results of the calculated return periods for each of the drought characteristics; accordingly, the role of each drought characteristics was considered. The most severe historical drought was selected as the benchmark, and the drought-zoning map for the GCM models was drawn. The results showed that severe droughts could be experienced, especially in the upper area of the basin where the primary water resource is located. In addition, the nature of the drought duration plays a decisive role in calculating the return periods of drought events. [ABSTRACT FROM AUTHOR]

The protection of high quality fresh water in times of global climate changes is of tremendous importance since it is the key factor of local demographic and economic development. One such fresh water source is Vrana Lake, located on the completely karstified Island of Cres in Croatia. Over the last few decades a severe and dangerous decrease of the lake level has been documented. In order to develop a reliable lake level prediction, the application of the artificial neural networks (ANN) was used for the first time. The paper proposes time-series forecasting models based on the monthly measurements of the lake level during the last 38 years, capable to predict 6 or 12 months ahead. In order to gain the best possible model performance, the forecasting models were built using two types of ANN: the Long-Short Term Memory (LSTM) recurrent neural network (RNN), and the feed forward neural network (FFNN). Instead of classic lagged data set, the proposed models were trained with the set of sequences with different length created from the time series data. The models were trained with the same set of the training parameters in order to establish the same conditions for the performance analysis. Based on root mean squared error (RMSE) and correlation coefficient (R) the performance analysis shown that both model types can achieve satisfactory results. The analysis also revealed that regardless of the model types, they outperform classic ANN models based on datasets with fixed number of features and one month the prediction period. Analysis also revealed that the proposed models outperform classic time series forecasting models based on ARIMA and other similar methods. [ABSTRACT FROM AUTHOR]

Reservoirs are key components of water infrastructure that serve many functions (water supply, hydropower generation, flood control, recreation, ecosystem services, etc.). Climate change affects the hydrology of the tributary areas to reservoirs, which may profoundly impact their operation and possibly the reservoirs' water quality, among which the temperature gradient and the total dissolved solids (TDS) are key qualitative characteristics of reservoirs, especially those with irrigation function. This study examines water-quality changes in the Aidoghmoush reservoir (East Azerbaijan-Iran) under climate-change conditions in the period 2026-2039. The temperature and precipitation climate variables are calculated by the HadCM3 model driven by emission scenario A2 in the baseline period (1987-2000), and these variables are then projected over the future period (2026-2039). The average annual runoff under climate-change conditions is simulated by the IHACRES model. The results show the future average annual runoff would decrease by about 1% compared to the baseline conditions. The CE-QUAL-W2 model is employed to simulate the reservoir water quality. It is predicted the surface air temperature would increase by 1.3 °C under the climate-change scenario compared to the baseline condition, and the temperatures of the reservoir's surface- and bottom-waters would increase by 1.19 and 1.24 °C, respectively. The average TDS near the reservoir surface would increase by 44.5 g/m3 (4.3%) relative to baseline TDS. The TDS near the reservoir surface are projected to be highest in autumn and winter for baseline and future conditions. This research shows that changes due to climate change are potentially severe, and presents a methodology that could assist managers and planners to find optimal strategies of reservoir operation to cope with changes in thermal stratification and TDS. This paper results identify the reservoir levels from which to withdraw water with the best water-quality characteristics. [ABSTRACT FROM AUTHOR]

In this paper, an investigation of the temporal rainfall variability, in a large area of southern Italy, has been carried out using a homogeneous monthly rainfall dataset of 559 rain gauges with more than 50 years of observation. The area under investigation is a large portion of the Italian peninsula, ranging from the Campania and the Apulia regions in the North, to Sicily in the South, and covering an area of about 85,000 km2. Possible trends in seasonal and annual rainfall values have been detected by means of a new graphical technique, Şen's method, which allows the trend identification of the low, medium and high values of a series. Moreover, the Mann-Kendall test has been also applied. As a result, different values and tendencies of the highest and of the lowest rainfall data have emerged among the five regions considered in the analysis. In particular, at seasonal scale, a negative trend has been detected especially in winter and in autumn in the whole study area, whereas not well defined trend signals have been identified in summer and spring. [ABSTRACT FROM AUTHOR]

Barriers and constraints to adapting water resources management to climate change in the Mediterranean region are analysed in this paper. First, we analysed the risks to the water resources sector derived from climate change. We then identified the main objective of water adaptation measures: ensuring there is enough water for food, for people, and for ecosystems. This implies visions about availability - being sufficient water -, accessibility - both physical and economic access -, and adequacy - being safe for ecosystems and human consumption. A portfolio of local and collective actions to adapt water management for agriculture to climate change in Mediterranean countries is presented. Adaptation strategies included improved efficiency, optimisation of governance, enhancement of participation, development of risk-based choices, and economic instruments. Finally, the paper categorised the constraints to implement the measures, give specific examples about these issues and also quantify their impact. When considering constraints and opportunities to implement these water management practices, any environmental policy regulating their adoption should be based on recommending the use of extension and training to local actors on the application of the practices. [ABSTRACT FROM AUTHOR]

Changes in climate extremes may cause the variation of occurrence and intensity of floods and droughts. To investigate the future changes in joint probability behaviors of precipitation extremes for water resources management, an approach including three stages for analyzing the spatial variation of joint return periods of precipitation extremes is proposed in this paper. In the first stage, a weather generator model (WGM) was conducted with general circulation models (GCMs) under representative concentration pathway (RCP) scenarios to generate daily rainfall time series during 2021-2040 (S) and 2081-2100 (L) based on the statistics of the observed rainfall data. Four extreme precipitation indices are defined to represent extreme precipitation events. In the second stage, copula methods are adopted to establish the joint distribution of the precipitation extreme indices. The watershed-scale assessment of flood and drought applied in Shih-Men reservoir in northern Taiwan is conducted to demonstrate the possible change of joint return period. In the third stage, the change rates of joint return periods for bivariate extreme indices are demonstrated to present the occurrence possibility of floods or droughts in the future. The results indicate that floods and droughts might occur more frequently in the upstream region of the reservoir during the twenty-first century. The reservoir operations would be more important for water supply and flood mitigation. In conclusion, the possible changes of future joint probability of the precipitation extremes should be paid attention to for water resources management and draft plans to confront potential challenges in the future. [ABSTRACT FROM AUTHOR]

The assessment of climate change and its impacts on hydropower generation is a complex issue. This paper evaluates the application of representative concentration pathways (RCPs, 2.6, 4.5, and 8.5) with the change factor (CF) method and the statistical downscaling method (SDSM) to generate six climatic scenarios of monthly temperature and rainfall over the period 2020-2049 in the Karkheh basin, Iran. The identification of unit hydrographs and component flows from rainfall, evaporation and streamflow data (IHACRES) model was employed to simulate runoff for the purpose of designing a run-of-river hydropower plant in the Karkheh basin. The non-dominated sorting genetic algorithm (NSGA)-II was employed to maximize yearly energy generation and the plant factor, simultaneously. Results indicate the runoff scenarios associated with the SDSM lead to higher run-of-river hydropower generation in 2020-2049 compared to the CF results. [ABSTRACT FROM AUTHOR]

Hydropower represents the world's largest renewable energy source. As a flexible technology, it enhances reliability and security of the electricity system. However, climate change and market liberalization may hinder investment due to the evolution of water runoffs and electricity prices. Both alter expected revenue and bring uncertainty. It increases risk and deters investment. Our research assesses how climate change and market fluctuation affect annual revenue. But this paper focuses on the uncertainty, rather than on forecasting. This transdisciplinary topic is investigated by means of a mixed method, i.e. both quantitative and qualitative. The quantitative approach uses established models in natural sciences and economics. The uncertainty is accounted for by applying various scenarios and various datasets coming from different models. Based on those results, uncertainty is discussed through an analysis discerning three dimensions of uncertainty. Uncertainty analysis requires the assessment of a large panel of models and data sets. It is therefore rarely carried out. The originality of the paper also lies on the combination of quantitative established models with a qualitative analysis. The results surprisingly show that the greenhouse gas scenarios may in fact represent a low source of uncertainty, unlike electricity prices. Like forecasting, the main uncertainties are actually case study related and depend on the investigated variables. It is also shown that the nature of uncertainty evolves. Runoff uncertainty goes from variability, i.e. inherent randomness, to epistemic, i.e. limitation of science. The reverse situation occurs with the electricity price. The implications for scientists and policy makers are discussed. [ABSTRACT FROM AUTHOR]

Adverse effects of climate change are increasing around the world and the floods are posing significant challenges for water managers. With climate projections showing increased risks of storms and extreme precipitation, the use of traditional measures alone is no longer an option. Nature-Based Solutions (NBS) offer a suitable alternative to reduce the risk of flooding and provide multiple benefits. However, planning such interventions requires careful consideration of various factors and local contexts. The present paper provides contribution in this direction and it proposes a methodology for allocation of large-scale NBS using suitability mapping. The methodology was implemented within the toolboxes of ESRI ArcMap software in order to map suitability for four types of NBS interventions: floodplain restoration, detention basins, retention ponds, and river widening. The toolboxes developed were applied to the case study area in Serbia, i.e., the Tamnava River basin. Flood maps were used to determine the volume of floodwater that needs to be stored for reducing flood risk in the basin and subsequent downstream areas. The suitability maps produced indicate the potential of the new methodology and its application as a decision-support tool for selection and allocation of large-scale NBS. [ABSTRACT FROM AUTHOR]

This paper aims to propose a methodology to evaluate and quantify perturbed groundwater budgets considering the projected reduction of Average Snow Fraction of Surface Runoff (ASFSR). Future groundwater budgets are generated considering different CC temporal Scenarios, RCMs, as well as the status of each Groundwater Body (GwB). The proposed methodology is applied to the Central Mountain Range of Iberian Peninsula (Avila Province). Existing studies show a drastic Reduction on Snow Melting (RSM) and on Cumulative Snow Volume (CSV). This leads to a huge reduction of Average Snow Fraction of Surface Runoff (ASFSR) and on groundwater availability calculated through the indicator Perturbed Exploitation Index (PEI). There are important differences depending on the RCM used, on the temporal CC Scenario and on the GwB considered. Main difficulties and challenges comprise the lack of field data and rigorous studies on modelling of groundwater hydrodynamic modelling. Despite of that, research results show a robust and generalized increase in all Exploitation Indexes (EI). EI increase is of 4.17 % for IP1 (Short Term) RCP 4.5, 14.94 % for IP2 (Medium Term) RCP 4.5, 17.65 % for IP3 (Long Term) RCP 4.5. On the other hand, there is an increase of 9.89 % for IP1 RCP 8.5, 19.05 % for IP2 RCP 8.5 and 35.14 % for IP3 RCP 8.5. Thus, there is a generalised and very important decrease of recharge (PARR) of 59.03 % for IP1 RCP 4.5, 88.97 % for IP2 RCP 4.5, 90.02 % for IP3. Likewise, for RCP 8.5, there is a decrease of 72.69 % for IP1 RCP 8.5, 88.97 % for IP2 RCP 8.5 and 97.90 % for IP3. [ABSTRACT FROM AUTHOR]

This paper reviews current optimization technique developed to solve reservoir operation problems in water resources. The application of conventional, especially evolutionary computation, combination of simulation-optimization and multi objectives optimization in reservoir operation will be discussed and investigated. Furthermore, new optimization algorithm from other applications will be presented by focusing on Artificial Bee Colony (ABC) and Gravitational Search Algorithm (GSA) as alternative methods that can be explored by researchers in water resources field. Finally this paper looks into the challenges and issues of climate change in reservoir optimization. [ABSTRACT FROM AUTHOR]

Assessing the impact of climate change on water demand is a challenging task. This paper proposes a novel methodology that quantifies this impact by establishing a link between water demand and weather based on climate change scenarios, via Coupled General Circulation Models. These models simulate the response of the global climate system to increasing greenhouse gas concentrations by reproducing atmospheric and ocean processes. In order to establish the link between water demand and weather, Random Forest models based on weather variables were used. This methodology was applied to a district metered area in Naples (Italy). Results demonstrate that the total district water demand may increase by 9–10% during the weeks with the highest temperatures. Furthermore, results show that the increase in water demand changes depending on the social characteristics of the users. The water demand of employed users with high education may increase by 13–15% when the highest temperatures occur. These increases can seriously affect the capacity and operation of existing water systems. [ABSTRACT FROM AUTHOR]

Some previous studies have proved that prediction models using traditional overall decomposition sampling (ODS) strategy are unreasonable because the subseries obtained by the ODS strategy contain future information to be predicted. It is, therefore, necessary to put forward a new sampling strategy to fix this defect and also to improve the accuracy and reliability of decomposition-based models. In this paper, a stepwise decomposition sampling (SDS) strategy according to the practical prediction process is introduced. Moreover, an innovative input selection framework is proposed to build a strong decomposition-based monthly streamflow prediction model, in which sunspots and atmospheric circulation anomaly factors are employed as candidate input variables to enhance the prediction accuracy of monthly streamflow in addition to regular inputs such as precipitation and evaporation. Meanwhile, the partial correlation algorithm is employed to select optimal input variables from candidate input variables including precipitation, evaporation, sunspots, and atmospheric circulation anomaly factors. Four basins of the U.S. MOPEX project with various climate characteristics were selected as a case study. Results indicate that: (1) adding teleconnection factors into candidate input variables helps enhance the prediction accuracy of the support vector machine (SVM) model in predicting streamflow; (2) the innovative input selection framework helps to improve the prediction capacity of models whose candidate input variables interact with each other compared with traditional selection strategy; (3) the SDS strategy can effectively prevent future information from being included into input variables, which is an appropriate substitute of the ODS strategy in developing prediction models; (4) as for monthly streamflow, the hybrid variable model decomposition-support vector machine (VMD-SVM) models, using an innovative input selection framework and the SDS strategy, perform better than those which have not adopted this framework in all study areas. Generally, the findings of this study showed that the hybrid VMD-SVM model combining the SDS strategy and innovative input selection framework is a useful and powerful tool for practical hydrological prediction work in the context of climate change. [ABSTRACT FROM AUTHOR]

Accurate rainfall prediction is a challenging task. It is especially challenging in Australia where the climate is highly variable. Australia’s climatic zones range from high rainfall tropical regions in the north to the driest desert region in the interior. The performance of prediction models may vary depending on climatic conditions. It is, therefore, important to assess and compare the performance of these models in different climatic zones. This paper examines the performance of data driven models such as the support vector machines for regression, the multiple linear regression, the k-nearest neighbors and the artificial neural networks for monthly rainfall prediction in Australia depending on climatic conditions. Rainfall data with five meteorological variables over the period of 1970–2014 from 24 geographically diverse weather stations are used for this purpose. The prediction performance of each model was evaluated by comparing observed and predicted rainfall using various measures for prediction accuracy. [ABSTRACT FROM AUTHOR]

Groundwater provides close to 40% of California's overall water supply under average hydrologic conditions. It is a critical source of backup during drought when increased pumping occurs to compensate for reduced surface supplies and decreased soil moisture. The conundrum is that in regions of the state where groundwater dependence is already high and rates of recharge are low, over the long term the volume withdrawn, particularly during droughts, generally exceeds replenishment in many regions. The result is overdraft - ongoing declines in groundwater levels over the long-term. To facilitate the reduction or cessation of long-term groundwater overdraft, this paper proposes that sustainable groundwater management must include the development of a drought reserve. The reserve, ideally sourced, sited and used locally, would encompass sufficient water for use during a drought such that the increased withdrawals during a drought do not result in unrecoverable groundwater declines and concomitant negative impacts. The objective is to reduce vulnerability to the state's periodic droughts, as opposed to mitigating seasonal variations in precipitation. This paper first summarizes the issues associated with developing drought reserves, and then examines in detail how two California groundwater management agencies approach establishing and implementing a drought reserve. [ABSTRACT FROM AUTHOR]

Change in the spatiotemporal pattern of precipitation is one the most important effects of climate change. This may result in considerable changes in urban flooding and yield a variation in the rate and volume of stormwater, resulting in the failure of stormwater collection systems. In the current paper, the effects of different downscaling methods on a built urban network have been assessed and compared. The case study is a 320-ha urban watershed with a built stormwater collection system located in the City of Tehran, Iran. Two single (SDSM and DMDM) and two multisite downscaling techniques with a daily temporal resolution have been employed and two sub daily (based of GEV distribution and MOF) methods have been used to further disaggregate the downscaled data. To evaluate the climate change impacts, three climate change scenarios, i.e. RCP 2.6, RCP 4.5 and RCP 8.5, have been used. Based on our findings, DMDM appears to outperform the other techniques in terms of our statistical similarity and dissimilarity metrics for daily downscaling. In addition, the sub-daily disaggregation method via GEV distribution delivers better results in comparison to the MOF. After simulating the stormwater collection system based on the downscaling results, we found that the number of flooded channels and junctions using RCP 8.5 results is significantly higher than RCP 4.5 and RCP 2.6 scenarios, indicating the relatively high risk of urban flooding under RCP 8.5 scenario. [ABSTRACT FROM AUTHOR]

This paper presents the results of studies on water resources management strategies, under the influence of climate change, in the Zarrineh River basin, providing some 41% of the total inflow into the Lake Urmia. Climate change simulation over the period 1992–2050 was performed by downscaling of seven global circulation models. The best model was then selected for modelling the hydrological behavior of the basin using a rainfall-runoff model while an allocation model was used to evaluate future supply and demands. A system dynamics model was further utilized to investigate the sustainability of the dynamic behavior of the basin. Five suggested water resources management strategies for two future climate scenarios were investigated. Results indicated that implementation of the strategy of 40% reduction in agricultural water demand would provide higher degrees of sustainability. Based on this, the average annual inflow to Lake Urmia in the years 2021 to 2050 would be 1029.75 MCM, which is equal to 81.02% of the Lake Urmia's environmental requirement from the river's share. [ABSTRACT FROM AUTHOR]

Climate projections point to modifications in the magnitude, frequency and timing of floods in the future. However, robust methodologies to quantify how climate change will modify the catchment response in flood events are required. Continuous hydrological modelling usually smooth magnitudes of extreme events. This paper proposes a methodology to improve the assessment of flood changes in the future driven by climate change. Climate change projections of the EURO-CORDEX programme obtained under the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) supplied are used. Four catchments located on the Douro River Basin have been considered as case studies. Precipitation and temperature projections have been bias corrected to reduce errors with observations in the control period (1971–2004). The HBV continuous hydrological simulation model has been used to simulate the soil moisture content on the day of occurrence of the maximum annual rainfalls in the four catchments. The modified curve number method has been utilized to obtain the changes expected in the future in flood magnitudes, considering the initial soil moisture contents estimated with the HBV model and the expected changes in annual maximum rainfalls. The methodology has been applied to the control period (1971–2004) to check the validity of the process. Then, the methodology has been applied to the future period (2011–2095), to quantify the changes expected in the future in flood magnitudes under climate change conditions. The combined use of the HBV continuous hydrological simulation with the modified curve number method improves the results provided by the HBV model. The proposed methodology allows a better characterization of the response of catchments in flood events. It also considers the expected variation in the antecedent moisture content in catchments in the future, driven by increasing temperatures and decreasing mean annual precipitations in the future. The results show that flood quantiles will increase in three of the four catchments considered. [ABSTRACT FROM AUTHOR]

Agricultural drought is a natural hazard, often leading to significant crop yield losses and jeopardising food security. Climate change is anticipated to increase the duration and the magnitude of drought events, augmenting also their adverse effects. Recent studies, as well as policy initiatives, emphasise the need of proper farm-level management, for efficient mitigation of drought effects and adaptation to climate change. Towards this objective, robust, practical and comprehensible tools should be employed to support decision making process. In this paper, the Crop Reconnaissance Drought Index (CRDI) is introduced, aiming at assisting in agricultural drought analyses, focusing on specific crops. The proposed CRDI is an adjustment of the widely used Reconnaissance Drought Index (RDI), in which the utilised parameter of reference evapotranspiration is replaced by crop evapotranspiration. Along with this amendment, other issues regarding the calculation of CRDI are discussed, such as the selection of appropriate reference periods and methods of crop evapotranspiration assessment. The significance and the advantages of CRDI are illustrated through an application, considering different crops under Mediterranean conditions, in three regions of Greece. [ABSTRACT FROM AUTHOR]

Climate change triggers changes in temperature, precipitation, evapotranspiration, etc. and has a significant impact on water resources in many regions. Considering the increasing scarcity of water as a result of climate change, conservation of water and groundwater recharge have become crucial factors for water resources planning and management. In this paper, an attempt is made to study the detailed hydrological behaviour of a treated watershed using physically based distributed hydrological modelling system MIKE SHE to assess the impact of conservation measures on watershed hydrology considering future climate change. Three hypothetical management scenarios are simulated for the period 2010–2040. RegCM4 regional climate model is used in the study for RCP 4.5 and RCP 8.5 scenarios. Detailed hydrological water balance is extracted for individual years from 1979 to 2009 to compare relevant components. The evaluation for base period shows 10.06% reduction in surface runoff and 11.33% enhancement in groundwater recharge. Further simulation with RCP 4.5 and RCP 8.5 scenarios show notable reduction in surface runoff and increase in groundwater recharge. The structures in the micro-watershed influence the surface runoff and increase infiltration into the soil, resulting in higher groundwater recharge. MIKE SHE simulations for various structures management scenarios establish the role of conservation measures in reducing surface runoff and enhancing groundwater recharge under substantial effect of climate change. The results will assist in decision-making on watershed development plans in quantitative terms, including planning for water conservation measures in the face of climate change. [ABSTRACT FROM AUTHOR]

Water resources in the Middle East are under enormous stress, due to an increase in population growth and the extensive use of water resources, which exceeds the water demand in this regional bloc. Moreover, climatic changes pose another dimension of stress on water resources; these changes have significant environmental, social, and economic effects. In fact, the governance of these countries has the tendency of increasing this stress or decreasing it, depending on its performance and efficiency in applying policies, legislation and managerial plans towards decreasing the poverty and the vulnerability of the countries specially those suffering from poverty. In this paper, the vulnerability of five countries-Israel, Jordan, Lebanon, Palestine and Syria-will be assessed based on the extent of climate changes and the type of climate governance and their effects on water resources. This paper will introduce a new index, which will be called the Governance and Climate Vulnerability Index (GCVI). The index will measure the vulnerability of each country vis-à-vis water-related issues, while taking into account governance and climatic indicators. The vulnerability of these countries will also be ranked, for purposes of comparison. This paper concludes with the recommendation for governments to develop appropriate water resources management and to improve their environmental policies, including raising awareness on multiple levels. These strategies are expected to lead to decreased vulnerability to climatic changes. [ABSTRACT FROM AUTHOR]

Climate change is likely to have an impact on the discharge of the European river Rhine. To base adaptation strategies, to deal with these changing river discharges, on the best scientific and technical knowledge, it is important to understand potential climate impacts, as well as the capacity of social and natural systems to adapt. Both are characterized by large uncertainties, at different scales, that range from individual to local to regional to international. This review paper addresses three challenges. Dealing with climate change uncertainties for the development of adaptation strategies is the first challenge. We find that communication of uncertainties in support of river basin adaptation planning generally only covers a small part of the spectrum of prevailing uncertainties, e.g. by using only one model or scenario and one approach to deal with the uncertainties. The second challenge identified in this paper is to overcome the current mismatch of supply of scientific knowledge by scientists and the demand by policy makers. Early experiences with 'assess-risk-of-policy' approaches analysis of options, starting from the resilience of development plans, suggests that this approach better responds to policy makers' needs. The third challenge is to adequately capture the transnational character of the Rhine river basin in research and policy. Development and implementation of adaptation options derived from integrated analysis at the full river basin level, rather than within the boundaries of the riparian countries, can offer new opportunities, but will also meet many practical challenges. [ABSTRACT FROM AUTHOR]

Semi-arid river basins often rely on reservoirs for water supply. Small reservoirs may impact on large-scale water availability both by enhancing availability in a distributed sense and by subtracting water for large downstream user communities, e.g. served by large reservoirs. Both of these impacts of small reservoirs are subject to climate change. Using a case-study on North-East Brazil, this paper shows that climate change impacts on water availability may be severe, and impacts on distributed water availability from small reservoirs may exceed impacts on centralised water availability from large reservoirs. Next, the paper shows that the effect of small reservoirs on water availability from large reservoirs may be significant, and increase both in relative and absolute sense under unfavourable climate change. [ABSTRACT FROM AUTHOR]

Debate about irrigation development of water resources in northern Australia has been hampered by a lack of quantitative information to enable accurate assessment of the volume of water that could potentially be regulated in the ‘North’ (north of the tropic of Capricorn). Too often the debate focuses solely on streamflow volumes and quantities of runoff. In this paper we present simple calculations to estimate a representative irrigation requirement and the potential exploitable yield in each of the 12 drainage divisions of Australia in order to more fully inform this on-going debate. Environmental, social, cultural and economic considerations are not examined. The results indicate that, despite northern Australia generating approximately 64% of the continent’s runoff, only 45% of Australia’s potentially exploitable yield is located in that portion of Australia, due to unfavourable streamflow characteristics, storage constraints and large evaporation losses. If exploitable yield and irrigation requirement were the sole factors constraining sustainable irrigation, under a full development scenario, southern Australia could hypothetically support an area of irrigation about 60% greater than that of northern Australia (based on only 36% of the country’s runoff). Using ‘best estimates’ of rainfall and evapotranspiration projected under changes in climate resulting from a moderate emissions scenario, the percentage of Australia’s exploitable yield located in northern Australia is estimated to increase from 45% to 47% by the year 2050, which equates to a 2% increase to the percentage of Australia’s hypothetical area of irrigation that could be located in northern Australia. These results suggest that efforts towards achieving and developing sustainable irrigation practices in the South will remain most important in achieving Australia’s long term irrigation potential. This study also highlights the need for better regional scale information on the potential to regulate streamflow in Australia, under current and future climates. Such information is essential to guide policy and planning, future Government and private investment, and to manage community expectations of Australia’s water resources. [ABSTRACT FROM AUTHOR]