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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.

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.

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.

Climate change is expected to alter the major components of hydrological regime such as streamflow and water availability. The magnitude and their impacts are still uncertain. Therefore, it is highly required to study streamflow and flood vulnerability in tropical river basins particularly urbanised basin such as Langat River Basin. This study aims to model the future streamflow of Langat River Basin due to climate change using Rainfall-Runoff Inundation (RRI) model. Daily rainfall data obtained from Department of Irrigation and Drainage Malaysia and topographic data from HydroSHEDS at 15-second resolution were used. The projected future rainfall (2075–2099) is extracted from MRI-AGCM3.2s under the worst carbon emission scenario, RCP8.5. The annual maximum series of 1-day rainfall is selected for statistical bias correction using Quantile Mapping. The General Circulation Model data were found to be greatly corrected with reasonable Nash–Sutcliffe efficiency, Percent bias and Root Mean Square Error values. The mean of maximum 1-day future rainfall in Langat River Basin is found to be inconsistent where parts of the upstream will experience an increment at about 7% while other parts decrease at 8%. Meanwhile, the rainfall at downstream area are expected to decrease at 40%. Based on RRI simulation, the future streamflow can achieve up to 92% increment.

Climate change is one of the major challenges confronting human society in the 21st century (Ericksen & O’Brein, 2007; Adger, Lorenzoni, & O’Brien, 2009). Mounting evidence attests that climate change is now happening in many parts of the world as evidenced by increasing mean temperature, changing precipitation patterns, rising sea level, and increasing frequency and growing intensity of extreme weather events (Intergovernmental Panel on Climate Change [IPCC], 2007). In many parts of Asia, these climatic changes have led to massive flooding, landslides, and droughts, resulting in extensive damage to properties, assets, and human life (Cruz et al., 2007). Climate change is also exacerbating water shortages in many areas, constraining agricultural production, and threatening food security and energy supply from hydroelectric source. It is likewise causing forest fires and degradation, damaging coastal and marine resources, and increasing the risk of outbreaks of infectious diseases. Regional climate studies indicate that the worse is yet to come as far as weather-related disaster risks are concerned. If not addressed effectively, climate change could seriously frustrate the region's sustainable development and poverty-reduction efforts (ADB, 2009).

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.

A variety of stressors have been identified that threaten the sustainability of water resources. The availability and predictability of water resources are at the core of considering the role of climate for humans and natural ecosystems. The hydrological cycle defines available water resources in a river basin, but to ensure sustainability, it is important to examine other factors within river basin borders influencing the quality and quantity of water. Preparing for pressures and building adaptive capacity require a holistic assessment of the current status and possible future impacts on the freshwater resources.

This chapter describes a case study focusing on the Irrawaddy and Salween Rivers that form a major part of Myanmar's water resources. Despite their importance, these basins have been little studied. The basins were divided according to ecological zones and terrain slope into subareas, and a vulnerability assessment based on 22 indicators was conducted. Indicators represent publicly available global spatial data on temperature, precipitation, hydrology, glaciers, state of wetlands, population distribution, land cover, nitrogen load, and water use. Indicators were based either on model outputs or on land cover and land-use information, representing variably current situations or future projections.

Besides describing the case study, this chapter discusses the challenges and opportunities of linking large-scale spatial modeling results to local-level management and adaptation planning. Challenges arise first from the process of modeling and input data characteristics that manifest as questions of scale and uncertainty. Secondly, the process of distributing the results for the relevant stakeholders (if identified and reached) can turn out to be tricky. Opportunities exist if attention is given to impact of scale and unit of analysis in (especially spatial) data ensuring best applicability in local-scale management. Also improving information management with a systematic approach in identifying knowledge gaps and synthesizing existing information is crucial for improving linkages between researchers, policy-makers, and local decision-makers. Finally, modeling should be developed toward acknowledging the value of the process of modeling rather than the actual results. This would provide possibilities for translating the increasing amounts of information into understanding among the relevant stakeholders.

The Intergovernmental Panel on Climate Change (IPCC) IPCC (2007) projects that greater precipitation intensity and variability will increase the risks of flooding in many areas because of climate change. With climate change already happening, societies worldwide face the parallel challenge of having to adapt to its impacts as a certain degree of climate change is inevitable throughout this century and beyond, even if global mitigation efforts over the next decades prove successful (European Commission, 2007).