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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.

This paper aims to construct a simplified distributed hydrological model based on the surveyed watershed soil properties database.

The new established model requires fewer parameters to be adjusted than needed by former hydrological models. However, the achieved stream-flow simulation results are similar and comparable to the classic hydrological models, such as the Xinanjiang model and the TOPMODEL.

Good results show that the discharge and the top surface soil moisture can be simultaneously simulated, and that is the exclusive character of this new model. The stream-flow simulation results from two moderate hydrological watershed models show that the daily stream-flow simulation achieved the classic hydrological results shown in the TOPMODEL and Xinanjiang model. The soil moisture validation results show that the modeled watershed scale surface soil moisture has general agreement with the obtained measurements, with a root-mean-square error (RMSE) value of 0.04 (m³/m³) for one of the one-measurement sites and an averaged RMSE of 0.08 (m³/m³) over all measurements.

In this paper, a new simplified distributed hydrological model was constructed.

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.

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 book aims to examine how modeling can be applicable toward local adaptation to climate change, using the Hindu Kush-Himalayas (HKH) as a case study. This introductory chapter sets the stage by summarizing mountain systems and change in the context of the HKH, especially highlighting the importance of involving mountain peoples in any discussion and work. Then, each chapter is summarized. In the final section, limitations and extensions of the work here are reported, focused on developing, testing, and implementing solutions on the terms of the people most affected without losing sight of wider contexts. Modeling is one knowledge system among many that is needed for adaptation and other development work in the HKH and other mountain areas.

Bangladesh has a long history of dealing with seasonal changes resulting in droughts and floods. Three major rivers, the Ganges, Brahmaputra and Meghna (GBM) come to a confluence, forming the GBM floodplain. There is a specific time window (June to September) when most of the runoff occurs and over 90% of their combined flow is discharged into the Bay of Bengal. As a result, the seasonal monsoons result in wet and dry seasons, making Bangladesh vulnerable to both floods and droughts. Climate change will likely alter characteristics such as timing and intensity, therefore increasing the challenge of adaptation. Socioeconomic conditions and high-population density limit the country's ability to adapt to these hydro-meteorological extremes. Although climatic variability causes severe damage and loss of life in Bangladesh, examples of local adaptation to the annual rhythm of seasonal variation can be found in flood-prone areas. Scientific modeling has resulted in more robust and efficient early warning systems that have greatly decreased the loss of life from climate hazards in recent years. However, positive impacts from models are limited by complex social concerns that are pervasive across the country.

The purpose of this paper is to indicate the limitations of the studies that address the impact of climate change on groundwater resources and to suggest an improved approach.

A general review, both from a groundwater hydrological and a climatological viewpoint, is given, oriented on the impact of climate change on groundwater resources.

The impact of climate change on groundwater resources is not the subject of many studies in the scientific literature. Only rarely sophisticated downscaling techniques are applied to downscale estimated global circulation model (GCM) future precipitation series for a point or region of interest. Often it is not taken into account that different climate models calculate considerably different precipitation amounts (conceptual uncertainty). The joint downscaling of the meteorological variables that govern potential evapotranspiration (ET) is never done in the context of a study that assessed the impact of climate change on groundwater resources. It is desirable that actual ET is calculated in (groundwater) hydrological models on a physical basis, i.e. by coupling the energy and water balance at the Earth's surface.

This review signalises a number of problems with published studies on the impact of climate change on groundwater resources. In many studies the method to downscale meteorological variables from a climate model to a hydrological model is not adequate. ET is often calculated in a strongly simplified manner and not all hydrological processes are modelled in a fully coupled fashion. More sophisticated downscaling approaches, physically based schemes to calculate ET and well‐calibrated, integrative hydrological models are needed.

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.

Big data have rapidly developed as a viable solution to many problems faced in engineering industries. Specifically, in the industry of water resource engineering, where there is a tremendous amount of data, various big data techniques could be applied to achieve innovative and efficient solutions for the industry. This study reviewed the proposal of big data as potential approaches to solve various difficulties encountered in managing water resources and related applications in Malaysia. The advantages and disadvantages of big data applications have also been discussed along with a brief literature review and some examples of case studies.

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.