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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.

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 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.

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.

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.

The purpose of this paper is to examine the practicality of an application called the mobile geographic information system (GIS). The authors' purpose was to focus specifically on the mobile GIS application in a prototype, mobile‐based model that is utilized for detecting flood warnings and issuing forecasts. At the end of this research project, a usability study was carried out in a test‐lab environment.

In this paper, research is presented regarding the architecture of a structure that has been built on practicality. Readers will learn about a system that is applicable within a vast array of turning‐point situations where rainfall data are communicated to the system in real time.

It has been revealed that traditional GIS and remote sensing software packages are not as cost‐effective as GIS services that are mobile. Mobile GIS systems have the capability to combine GIS, global positioning system, and remote sensing abilities for retrieving geospatial data sets at costs that are not as pricey as the traditional systems. As time moves on, the need for reliable real‐time data sets is increasing. Additionally, flood management examination provides a valid debate for the combining of mobile GISs within the realm of hydrology. Empirical evidence insinuates and illustrates reliability of GIS and the enhancement in the utilization and creation of devices that are offer mobile capabilities. The usability study revealed that the slope, aspect, watershed, and flow direction functions were not easy to comprehend. It was also discovered during the usability study that the word arrangement, radio button arrangement, and dropdown list caused confusion amongst users. The issue that was deemed as most severe, that was discovered during the usability study, was the blurred comprehension that users experienced regarding the digital elevation model.

Before the wisest solution can be pinpointed, all of the associated constraints of mobile GIS mapping application need to be identified; however, enough constraints have already been identified to bring to a close that a basic mobile GIS mapping application could created and triumphantly used. There are many platforms to choose from in regards to providing a solution to a feasible incorporation of the mobile GISs into the playing field. It should be decided which browser‐based strategy would serve as the highest of benefit based on characteristics that are important to consumers, such as affordability, ease‐of‐use, user‐friendly coding, and acceptability by users.

This research is highly indicative that mobile GIS would be of great benefit for future studies within the realm of disaster monitoring management. The research presented in this paper can be deemed as original due to the fact that it is a study about the utilization of mobile technologically‐advanced gadgets that provide data analysis for flooding in real time. Moreover, these highly technologically‐advanced devices are cost‐effective compared to those in the past.

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.

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.

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.

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.