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The purpose of this paper is to set out the policy guidelines and recommendations to harmonise the Serbian water legislation with European Union standards in the area of water system management as impacted by climate change.

The EU Water Framework Directive is analysed in the context of implementation of the integrated water management policy presented in the Serbian Water Law (2010), as well as the National Water Management Strategy (2016). It has been found that the water management legislation that deals with the impact of climate change on water resources is incomplete. Although there are numerous challenges related to research of climate change and water systems, water policy and legal aspects cannot be neglected. The so-called soft law instruments represented in a form of strategy documents could be a valuable response in terms of an adaptive and integrated water policy approach.

The research is applied to a case study of the Velika Morava River Basin, at Ljubicevski Most hydrological station. Long-term projections suggest a decrease in annual precipitation levels and annual flows up to the year 2100 for climatic scenarios A1B and A2, accompanied by a rapid increase in air temperatures.

This study proposes a water management policy and provides recommendations for the Velika Morava River Basin as impacted by climate change, according to the European Union legislation.

It is now established by the global scientific community that climate change is a hard reality but the changes are complex in nature and to a great extent uncertain. Global circulation models (GCMs) have made significant contributions to the theoretical understanding of potential climate impacts, but their shortcomings in terms of assessing climate impacts soon became apparent. GCMs demonstrate significant skill at the continental and hemispheric scales and incorporate a large proportion of the complexity of the global system. However, they are inherently unable to represent local subgrid-scale features and dynamics. The first generation approaches of climate change impact and vulnerability assessments are derived from GCMs downscaled to produce scenarios at regional and local scales, but since the downscaled models inherit the biases of their parent GCM, they produce a simplified version of local climate. Furthermore, their output is limited to changes in mean temperature, rainfall, and sea level. For this reason, hydrological modeling with GCM output is useful for assessing impacts. The hydrological response due to change in climate variables in the Amu Darya River Basin was investigated using the Soil and Water Assessment Tool (SWAT). The modeling results show that there is an increase in precipitation, maximum and minimum temperature, potential evapotranspiration, surface runoff, percolation, and water yields. The above methodology can be practiced in this region for conducting adaptation and mitigation assessments. This initial assessment will facilitate future simulation modeling applications using SWAT for the Amu Darya River Basin by including variables of local changes (e.g., population growth, deforestation) that directly affect the hydrology of the region.

This paper aims to develop a framework to assist the identification of robust adaptation options that account for uncertainty in future climate change impacts for the water sector.

The water evaluation and planning (WEAP) tool, is to identify future water resource vulnerability in the Glore sub‐catchment within the Moy catchment in the West of Ireland. Where water stress is evident, a detailed hydrological modelling approach is developed to enable an assessment of the robustness to uncertainty of future adaptation decisions. WEAP is coupled with a rainfall runoff model (hydrological simulation model), and forced using climate scenarios, statistically downscaled from three global climate models to account for the key sources of uncertainty. While hydrological models are widely applied, they are subject to uncertainties derived from model structure and the parameterisation of the catchment. Here, random sampling of key parameters is employed to incorporate uncertainty from the hydrological modelling process. Behavioural parameter sets are used to generate multiple future streamflow series to determine where the bounds within future hydrological regimes may lie and the ranges within which future adaptation policy pathways need to function.

This framework allows the identification of adaptation options that are robust to uncertainty in future simulations.

Future research will focus on the development of more site‐specific adaptation options including soft and hard adaptation strategies. This approach will be applied to multiple water resource regions within Ireland.

A robust adaptation assessment decreases the risk of expensive and/or mal‐adaptations in a critical sector for society, the economy and the aquatic environment.

Recent advances in hydrological impact studies point that the response of specific catchments to climate change scenario using a single model approach is questionable. This study was aimed at investigating the impact of climate change on three river basins in China, Ethiopia and Norway using WASMOD and HBV hydrological models.

First, hydrological models' parameters were determined using current hydro‐climatic data inputs. Second, the historical time series of climatic data was adjusted according to the climate change scenarios. Third, the hydrological characteristics of the catchments under the adjusted climatic conditions were simulated using the calibrated hydrological models. Finally, comparisons of the model simulations of the current and possible future hydrological characteristics were performed. Responses were evaluated in terms of runoff, actual evapotranspiration and soil moisture change for incremental precipitation and temperature change scenarios.

From the results obtained, it can be inferred that two equally well calibrated models gave different hydrological response to hypothetical climatic scenarios. The authors' findings support the concern that climate change analysis using lumped hydrological models may lead to unreliable conclusions.

Extrapolation of driving forces (temperature and precipitation) beyond the range of parameter calibration yields unreliable response. It is beyond the scope of this study to reduce this model ambiguity, but reduction of uncertainty is a challenge for further research.

The research was conducted based on the primary time series data using the existing two hydrological models to test the magnitude differences one can expect when using different hydrological models to simulate hydrological response of climate changes in different climate zones.

Hydrological and climatological modeling is increasingly being used with the intent of supporting community-based climate change adaptation (CCA) and disaster risk reduction (DRR) initiatives in the Hindu Kush-Himalaya (HKH), as well as filling critical data gaps in a region that contributes significantly to the water resources and ecosystem diversity of Asia. As the case studies presented in the previous chapters illustrate, the utility of modeling in informing and supporting CCA and DRR initiatives depends on a number of criteria, including:•appropriate model selection;•ability to interpret models to local contexts; and•community engagement that incorporates and addresses underlying vulnerabilities within the community.

There are significant challenges to meeting all three of these criteria. However, when these criteria are met, we find:•There is a clear role for modeling to support CCA. The climate is changing now and will continue to do so for several centuries, even if carbon emissions were to stabilize tomorrow. Models, and other scenario development tools, provide our best insight into what the future climate might be and resulting impacts on dynamic social, environmental, political, and economic systems.•There is a clear role for local CCA. The impacts of climate change will be felt mostly at local levels, necessitating community adaptation responses. At the same time, most of the HKH communities and countries engaged in CCA initiatives have pressing, immediate development and livelihood needs. Making current development and livelihood initiatives incorporate climate adaptation considerations is the best way to ensure that the choices made today can set us on paths of increasing resilience, rather than almost inevitable disaster, for the future.•To achieve the best of both modeling and CCA requires thoughtful and patient application of modeling, tailored to local needs, conditions, and politics, with communities engaged around all stages of generating, interpreting, and applying the results. This requires a rare combination of technical skill, cultural sensitivity, political awareness, and above all, the time to continually engage with and build relationships within the community in order to foster resilient change.

This chapter describes the climatic setting of the Aral Sea region, investigates how the climate might change during the 21st century, and discusses potential impacts on water resources. Temperature and precipitation fields are analyzed to describe the mean climate for the Aral Sea region. Composite analysis has been employed on the precipitation field from the Global Precipitation Climatology Project (GPCP v2.2) to assess the spatial pattern of changes in precipitation during the last several decades. Furthermore, temperature and precipitation projections available from the 2007 Intergovernmental Panel on Climate Change report are synthesized to examine the nature of climate change during this century.

Cold season precipitation has increased during recent decades, particularly over the mountainous terrain east of the Aral Sea. Climate models also project increases (5−20%) in winter precipitation during the 21st century; however, several models suggest decreases (0 to −15%) in precipitation during summer. Despite the increases in cold season precipitation, the large increases in temperature (4°C) during the 21st century are likely to cause increased evaporation which could exacerbate the regional water budget deficit. This may constrain the water supply in the region, particularly during summer and autumn when water demand is highest. To fully understand the impacts of future climate change on regional water resources, hydrologic models that include anthropogenic management of water will be required.

Hazard assessment on drought disaster is of great significance for improving drought risk management. Due to the complexity and uncertainty of the drought disaster, the index values have some grey multi-source heterogeneous characteristics. The purpose of this paper is to construct a grey projection incidence model (GPIM) to evaluate the hazard of the drought disaster characterised by the grey heterogeneity information.

First, the index system of the drought hazard risk is established based on the formation mechanism of the drought disaster. Then, the GPIM for the heterogeneous panel data is constructed to assess drought hazard of five cities in Henan Province. Subsequently, based on the assessment results, the grey clustering model is employed for the regional division.

The findings demonstrate that five cities in central Henan Province are divided into three categories, which correspond to three different risk grades, respectively. With respect to different drought risk areas, corresponding countermeasures and suggestions are proposed.

This paper provides a practical and effective new method for the hazard assessment on drought disaster. Meanwhile, these countermeasures and suggestions can help policy makers to improve the efficiency of drought resistance work and reduce the losses caused by drought disasters in Henan Province.

This paper proposes a new GPIM which resolves the assessment problems of the uncertain systems with grey heterogeneous information, such as real numbers, interval grey numbers and three-parameter interval grey numbers. It not only expands the application scope of the grey incidence model, but also enriches the research of panel data.

The present study aims to evaluate the effect of climate change on the flood hazard potential in the Kelantan River Basin using current and future scenarios.

The intensity-duration-frequency (IDF) was used to estimate the current 50- and 100-year return period 24-h design rainfall, and the climate change factor (CCF) was used to compute the future design rainfall. The CCF was calculated from the rainfall projections of two global climate models, CGCM1 and CCSM3, with different pre-processing steps applied to each. The IDF data were used in the rainfall-runoff-inundation model to simulate current and future flood inundation scenarios.

The estimated CCF values demonstrate a contrast, whereby each station had a CCF value greater than one for CGCM1, while some stations had a CCF value of less than one for CCSM3. Therefore, CGCM1 projected an aggravation and CCSM3 a reduction of flood hazard for future scenarios. The study reveals that topography plays an essential role in calculating the CCF.

To the best of the author’s knowledge, this is the first study to examine flood projections in the Kelantan River Basin. It is, therefore, hoped that these results could benefit local managers and authorities by enabling them to make informed decisions regarding flood risk mitigation in a climate change scenario.

The purpose of this paper is to assess the extent of climate change likely to be manifested in the MENA region using statistical tools as well as outputs from physics‐based General Circulation Models (GCMs).

Atmospheric temperature and precipitation primarily capture climate change features and are considered the drivers of other manifestations of climate change such as rises in sea‐level, tropical cyclone intensities, severe floods, prolonged droughts, and retreating ice. Data on atmospheric temperature and precipitation have been statistically analysed for trend, distribution and variability in this study. Long‐range prediction is then made using time series analysis. Long‐range projections have also been made by many investigators using physics‐based GCMs and the Fourth Assessment Report of IPCC provides a summary. IPCC projections are not indisputable because of some inherent limitations of GCMs. A comparative study is made between statistical predictions and IPCC projections, as well as forecasts from some GCMs specifically applied to the region, to develop a more reliable forecast scenario. Water resources projects are quite vulnerable to changes in atmospheric temperature and precipitation amounts. The various aspects of planning, design and management of water resources projects which are likely to be influenced by climate change are discussed.

There is considerable variability in atmospheric temperature and precipitation in recent observations but if the variability is filtered out and the underlying trend extrapolated it is found that there is in general an agreement between IPCC projections and statistical predictions. For rise in atmospheric temperature projections made from many GCMs applied to the region, as well as projections summarised in the Fourth Assessment Report of IPCC, appear to be good estimates to be included in design considerations. For precipitation, statistical predictions are perhaps a better choice because GCM projections are less reliable with precipitation since associated meteorological processes occur at a much smaller scale than the grid size of a GCM. For low‐lying coastal regions sea‐level rise and more frequent extreme climatic events such as tropical cyclones add to the dimensionality of design considerations especially for infrastructure design.

This paper presents a comparative study of possible climate change in the long‐term between physics‐based model projections and statistical predictions. This should provide greater insight into climate change that is expected in MENA and reduce uncertainty, thereby instilling greater confidence in water resources planners and practitioners to incorporate climate change aspects into decision making. This research is believed to be particularly helpful because of scant research work done on this part of the globe on climate change.

The Orange River is one of the largest river basins in southern Africa. Since it plays a crucial role in the region's ecology and economy, it is important to estimate future developments in its hydrology. A necessary means to this end are climate projections. This paper seeks to address this issue.

In this work the authors present projections obtained by two complementary methods; they use a Statistical Analogue Re‐sampling Scheme (STARS) and a dynamical regional climate model (CCLM – COSMO in Climate Mode). In order to determine the viability of these methods, the authors perform cross‐validations for the years 1976‐2000.

CCLM shows good performance regarding the 2 m temperature but the reproduction of precipitation is rather poor. STARS, on the other hand, produces very good results for both variables. The climate projections of both models show a considerable temperature increase for the future (2036‐2060, SRES A1B scenario), especially in the inland of the simulation area. However, while CCLM projects a general decrease in precipitation, STARS indicates a strong precipitation decrease in the already dry western part of the region and a moderate decrease resp. no change in the east during the rain season.

For the first time the statistical approach used gridded data as its input. Therefore, it was possible to apply complementary methods in order to generate the climate projections and to compare them.