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This chapter describes the scenario technique used for the integrative methodological approach (IMA) of the German global change project GLOWA Elbe. It is outlined how regional scenarios are systematically derived to analyze water use conflicts and their resolution in the context of global change for the German Elbe river basin. Through the combination of frameworks of development and policy strategies a consistent set of developmental scenarios can be generated that makes it possible to examine the regional impact of policy strategies under conditions of different future global change development paths. The scenario analysis of the framework of development starts on the global level with qualitative IPCC storylines, translates them to the regional level, and quantifies their regional effects by means of modeling and statistical estimation methods. The policy strategies are derived in close cooperation with regional stakeholders.

Climate data, including historical climate observations and climate model outputs, are often used in climate impact assessments, to explore potential climate futures. However, characteristics often associated with “islandness”, such as smallness, land boundedness and isolation, may mean that climate impact assessment methods applied at broader scales cannot simply be downscaled to island settings. This paper aims to discuss information needs and the limitations of climate models and datasets in the context of small islands and explores how such challenges might be addressed.

Reviewing existing literature, this paper explores challenges of islandness in top-down, model-led climate impact assessment and bottom-up, vulnerability-led approaches. It examines how alternative forms of knowledge production can play a role in validating models and in guiding adaptation actions at the local level and highlights decision-making techniques that can support adaptation even when data is uncertain.

Small island topography is often too detailed for global or even regional climate models to resolve, but equally, local meteorological station data may be absent or uncertain, particularly in island peripheries. However, rather than viewing the issue as decision-making with big data at the regional/global scale versus with little or no data at the small island scale, a more productive discourse can emerge by conceptualising strategies of decision-making with unconventional types of data.

This paper provides a critical overview and synthesis of issues relating to climate models, data sets and impact assessment methods as they pertain to islands, which can benefit decision makers and other end-users of climate data in island communities.

The purpose of the paper is to present a scenario‐based approach to river basin planning, and demonstrate how land‐use planning can be utilised as a strong measure in meeting the climate change challenges with new precipitation patterns during the current century.

The current research takes a scenario‐based approach to river basin planning. A modelling framework is defined to assess the effects of active spatial planning to mitigate the negative consequences of climate change in river basin management. In total, three models are included in the framework: a land‐use model, a runoff model, and a flooding screening model.

The research has demonstrated the advantages of using models and scenarios to assess the effects of climate change in river basin management, and how active spatial planning – in the current example afforestation – can mitigate negative consequences of climate change.

The current research demonstrates how to combine models from different fields into one integrated model for impact assessment.

The developed methodology will assist river basin managers to assess the effects of river basin management plans.

The consequences of climate change are mainstream topics discussed by most citizens and results from the models can facilitate a qualified debate.

The paper analyses the feasibility of using active spatial planning to mitigate the negative consequences of climate change, such as flooding along rivers. This work is original, as no such analysis has been carried out before.

The paper aims to investigate the possible changes in mean temperature in the Mongolian Plateau associated with the 1.5 and 2°C global warming targets and how snow changes in the Mongolian Plateau when the mean global warming is well below 2°C or limited to 1.5°C.

In total, 30 model simulations of consecutive temperature and precipitation days from Coupled Model Inter-comparison Project Phase 5 (CMIP5) are assessed in comparison with the 111 meteorological monitoring stations from 1961–2005. Multi-model ensemble and model relative error were used to evaluate the performance of CMIP5 models. Slope and the Mann–Kendall test were used to analyze the magnitude of the trends and evaluate the significance of trends of snow depth (SD) from 1981 to 2014 in the Mongolian Plateau.

Some models perform well, even better than the majority (80%) of the models over the Mongolian Plateau, particularly HadGEM2-CC, CMCC-CM, BNU-ESM and GFDL-ESM2M, which simulate best in consecutive dry days (CDD), consecutive wet days (CWD), cold spell duration indicator (CSDI) and warm spell duration indicator (WSDI), respectively. Emphasis zones of WSDI on SD were deeply analysed in the 1.5 and 2 °C global warming period above pre-industrial conditions, because it alone has a significant negative relation with SD among the four indices. It is warmer than before in the Mongolian Plateau, particularly in the southern part of the Mongolian Plateau, indicating less SD.

Providing climate extremes and SD data sets with different spatial-temporal scales over the Mongolian Plateau. Zoning SD potential risk areas and proposing adaptations to promote regional sustainable development.

The observed increase in the atmospheric concentration of greenhouse gases since the industrial period, due to human activities, is very likely causing the warming of the climate system. Anthropogenic warming and rising sea levels will continue for centuries due to the time scales associated with climate processes and feedbacks. Even if greenhouse gas concentrations were to be stabilized, different types of adaptation measures are needed to cope with the inevitable change. At the same time mitigation measures aiming at decreasing greenhouse gas emissions and enhancing carbon sinks must be taken in order to reduce the potential extent of global warming. This chapter covers the main aspects of the current understanding of the physical basis of climate change, including the directly measured observations and estimated projections for the 21st century. Causes and effects of climate change are also addressed. Finally, the main uncertainties of climate projections and a few general considerations on the different ways to respond to the climate change issue are discussed.

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 paper aims to assess the economic effects of climate change on the Mediterranean’s irrigated agriculture and how the adoption of alternative crop varieties adapted to the expected length of the growing season can be an effective adaptation measure.

A case study of two irrigation areas in Southern Portugal is used to assess the response to climate change impacts on crop yields and irrigation requirements, and an agricultural supply model is calibrated using a positive mathematical programming (PMP) approach was developed.

Climate change reduces crop yields and causes a slight decrease in irrigation requirements, which could allow an increase in the irrigated area. However, positive impacts on rural areas regarding employment and investment are not expected. The adoption of adaptation measures based on alternative crop varieties, which could maintain crop yields at current levels, increases dramatically the economic value of water and mitigates losses in farm income.

The impacts on output and input market prices, as well as other biophysical impacts (for instance, CO₂ and water availability), are important in understanding the effects of climate change on irrigated agriculture, but they were not considered in this study. While this may be a limitation, it can also be a stimulus for further research.

This is an empirical paper, whose results contribute to improving knowledge about the effects of climate change on irrigated agriculture in Mediterranean areas, namely, its economic impacts on returns and the use of agricultural resources (land, water, labour and capital). Other practical implications of the paper are associated with the methodological approach, which provides a framework able to deal with the complexity and multidimensional effects of climate change.

The results of the paper provide important information for scientists, politicians and other stakeholders about the design of more effective adaptation measures able to mitigate the effects of climate change.

Crop yields and irrigation requirements were previously calculated based on data generated by the regional climate models. This is the first time that an application is developed for Portugal. Two distinct profiles of irrigation areas were studied and a large set of crops was considered, which is not common in the existing studies. To specify the PMP approach used to calibrate the agricultural supply model, exogenous crop-specific supply elasticities were estimated through a least square model, which is not common in previous studies.

Climate change will affect tourism at several temporal and spatial levels. This chapter focuses on the quantification of effects and the development of strategies to reduce extremes and frequencies as well as thresholds in tourism areas. Knowledge about possibilities for mitigation and adaptation of current and expected climate conditions requires interdisciplinary approaches and solutions. Several examples are presented, including the effects of trees against climate change and extreme events (heat waves), behavior adaptations, urban and regional planning measures, bioclimatic conditions in the Mediterranean and human–biometeorological conditions under climate change conditions, and user-friendly computer tools for the quantification of urban bioclimate conditions.

Climate change data and predictions for the Himalayas are very sparse and uncertain, characterized by a “Himalayan data gap” and difficulties in predicting changes due to topographic complexity. A few reliable studies and climate change models for Nepal predict considerable changes: shorter monsoon seasons, more intensive rainfall patterns, higher temperatures, and drought. These predictions are confirmed by farmers who claim that temperatures have been increasing for the past decade and wonder why the rains have “gone mad.” The number of hazard events, notably droughts, floods, and landslides are increasing and now account for approximately 100 deaths in Nepal annually. Other effects are drinking water shortages and shifting agricultural patterns, with many communities struggling to meet basic food security before climatic conditions started changing.

The aim of this paper is to examine existing gaps between current climate models and the realities of local development planning through a case study on flood risk and drinking water management for the Municipality of Dharan in Eastern Nepal. This example highlights current challenges facing local-level governments, namely, flood and landslide mitigation, providing basic amenities – especially an urgent lack of drinking water during the dry season – poor local planning capacities, and limited resources. In this context, the challenge for Nepal will be to simultaneously address increasing risks caused by hazard events alongside the omnipresent food security and drinking water issues in both urban and rural areas. Local planning is needed that integrates rural development and disaster risk reduction (DRR) with knowledge about climate change considerations. The paper concludes with a critical analysis of climate change modeling and the gap between scientific data and low-tech and low capacities of local planners to access or implement adequate adaptation measures. Recommendations include the need to bridge gaps between scientific models, the local political reality and local information needs.

Novel micro‐insurance schemes are emerging to help the poor better deal with droughts and other disasters. Climate change is projected to increase the intensity and frequency of disasters and is already adding stress to actual and potential clients of these schemes. As well, insurers and reinsurers are increasingly getting worried about increasing claim burdens and the robustness of their pricing given changing risks. The purpose of this paper is to review and suggest ways to methodologically tackle the challenges regarding the assessment of drought risk and the viability of index‐based insurance arrangements in the light of changing risks and climate change.

Based on novel modeling approaches, the authors take supply as well as demand side perspectives by combining risk analysis with regional climate projections and linking this to household livelihood modeling and insurance pricing. Two important examples in Malawi and India are discussed, where such schemes have been or are about to be implemented.

The authors find that indeed micro‐insurance instruments may help low‐income farming households better manage drought risk by smoothing livelihoods and reducing debt, thus avoiding poverty traps. Yet, also many obstacles to optimal design, viability and affordability of these schemes, are encountered. One of those is climate change and the authors find that changing drought risk under climate change would pose a threat to the viability of micro‐insurance, as well as the livelihoods of people requesting such contracts.

The findings and suggestions may corroborate the case for donor support for existing or emerging insurance arrangements helping the poor better cope with climate variability and change. Furthermore, a closer linkage between climate and global change models with insurance and risk management models should be established in the future, which could be beneficial for both sides.