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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.

Global change results both from climatic and land practice evolution in response to anthropogenic needs for development and human safety. The purpose of this paper is to describe a method to assess the respective effect of both sources of change on the flood regimes.

The research takes place in the Western periurban part of Lyon (France), which is characterized by a rapidly expanding, scattered urban development since the 1970s. An increase in frequency of large floods is reported. At the same time, a long daily rainfall time series exhibits sensitive changes in rainfall durations and intensities. Independent analysis of global change components is performed using observed rainfall and land‐use data from two disconnected decades. A marked difference in natural climatic regime variability between decades is used as a surrogate to study effect of climate change.

Anthropogenic activity at the observed rate of land use change, in particular urban change, mainly influences the frequent flood distribution. The observed large flood increase results both of longer rainfall events and more heavy daily rainfall. From simulations, a 43 percent urban cover as planned from 2025 projection would have a very sensitive effect also on larger floods, giving the hand to a more anthropogenic‐based flood control.

Despite an expected increase in rainfall and flow variability regimes as a result of climate change and a projected growing of the world urban population, there is a lack of methodology to address combination of both processes on the flood regimes. A method is proposed to judge on the respective importance and interplay of these processes.

Malaysia experiences a major flood event every three years due to the adverse effects of two monsoon seasons a year. Floods have thus become the most significant natural disaster in the country in terms of the population affected, frequency, aerial extent, financial cost and the disruption to socio‐economic activities. Many previous flood control measures have had different levels of success but have generally had little effect in reducing the problem. However, it is now understood that it is neither possible nor desirable to control floods completely. Spatial information technology is thus being increasingly recognized as the most effective approach to flood disaster management. This paper reviews the spatial information technology in flood disaster management and its application in Malaysia. Some flood forecasting systems are discussed, along with their shortcomings. The paper discusses the framework of a proposed flood early warning system for the Langat river basin that operationally couples real‐time NOAA‐AVHRR data for quantitative precipitation forecasting with hydrologically oriented GIS and a MIKE11 hydrodynamic model.

The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail. The operating environment of the high-speed rail is complex, and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters, perimeter intrusion and external environmental hazards. The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.

In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments, the research status is elaborated, and the latest research progress and achievements of the team are introduced. This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological, perimeter and external environmental situation perception methods for high-speed rail operation.

Based on the technical route of “situational awareness evaluation warning active control,” a technical system for monitoring the safety of high-speed train operation environments has been formed. Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters, perimeter intrusion and the external environment on high-speed rail safety. These works strongly support the improvement of China’s railway environmental safety guarantee technology.

With the operation of CR450 high-speed trains with a speed of 400 km per hour and the application of high-speed train autonomous driving technology in the future, new and higher requirements have been put forward for the safety of high-speed rail operation environments. The following five aspects of work are urgently needed: (1) Research the single factor disaster mechanism of wind, rain, snow, lightning, etc. for high-speed railways with a speed of 400 kms per hour, and based on this, study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment, revealing the coupling disaster mechanism of multiple influencing factors; (2) Research covers multi-source data fusion methods and associated features such as disaster monitoring data, meteorological information, route characteristics and terrain and landforms, studying the spatio-temporal evolution laws of meteorological disasters, perimeter intrusions and external environmental hazards; (3) In terms of meteorological disaster situation awareness, research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines; (4) In terms of perimeter intrusion, research a multi-modal fusion perception method for typical scenarios of high-speed rail operation in all time, all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and (5) In terms of external environment, based on the existing general network framework for change detection, we will carry out research on change detection and algorithms in the surrounding environment of high-speed rail.

The purpose of this paper is to establish a two-stage grey cloud clustering model to assess the drought risk level of 18 prefecture-level cities in Henan Province.

The clustering process is divided into two stages. In the first stage, grey cloud clustering coefficient vectors are obtained by grey cloud clustering. In the second stage, with the help of the weight kernel clustering function, the general representation of the weight vector group of kernel clustering is given. And a new coefficient vector of kernel clustering that integrates the support factors of the adjacent components was obtained in this stage. The entropy resolution coefficient of grey cloud clustering coefficient vector is set as the demarcation line of the two stages, and a two-stage grey cloud clustering model, which combines grey and randomness, is proposed.

This paper demonstrates that 18 cities in Henan Province are divided into five categories, which are in accordance with five drought hazard levels. And the rationality and validity of this model is illustrated by comparing with other methods.

This paper provides a practical and effective new method for drought risk assessment and, then, provides theoretical support for the government and production departments to master drought information and formulate disaster prevention and mitigation measures.

The model in this paper not only solves the problem that the result and the rule of individual subjective judgment are always inconsistent owing to not fully considering the randomness of the possibility function, but also solves the problem that it’s difficult to ascertain the attribution of decision objects, when several components of grey clustering coefficient vector tend to be balanced. It provides a new idea for the development of the grey clustering model. The rationality and validity of the model are illustrated by taking 18 cities in Henan Province as examples.

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.

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.

The purpose of this study is to address a highly heterogeneous rift margin environment and exhibit considerable spatiotemporal hydro-climatic variations. In spite of limited, random and inaccurate data retrieved from rainfall gauging stations, the recent advancement of satellite rainfall estimate (SRE) has provided promising alternatives over such remote areas. The aim of this research is to take advantage of the technologies through performance evaluation of the SREs against ground-based-gauge rainfall data sets by incorporating its applicability in calibrating hydrological models.

Selected multi satellite-based rainfall estimates were primarily compared statistically with rain gauge observations using a point-to-pixel approach at different time scales (daily and seasonal). The continuous and categorical indices are used to evaluate the performance of SRE. The simple scaling time-variant bias correction method was further applied to remove the systematic error in satellite rainfall estimates before being used as input for a semi-distributed hydrologic engineering center's hydraulic modeling system (HEC-HMS). Runoff calibration and validation were conducted for consecutive periods ranging from 1999–2010 to 2011–2015, respectively.

The spatial patterns retrieved from climate hazards group infrared precipitation with stations (CHIRPS), multi-source weighted-ensemble precipitation (MSWEP) and tropical rainfall measuring mission (TRMM) rainfall estimates are more or less comparably underestimate the ground-based gauge observation at daily and seasonal scales. In comparison to the others, MSWEP has the best probability of detection followed by TRMM at all observation stations whereas CHIRPS performs the least in the study area. Accordingly, the relative calibration performance of the hydrological model (HEC-HMS) using ground-based gauge observation (Nash and Sutcliffe efficiency criteria [NSE] = 0.71; R² = 0.72) is better as compared to MSWEP (NSE = 0.69; R² = 0.7), TRMM (NSE = 0.67, R² = 0.68) and CHIRPS (NSE = 0.58 and R² = 0.62).

Calibration of hydrological model using the satellite rainfall estimate products have promising results. The results also suggest that products can be a potential alternative source of data sparse complex rift margin having heterogeneous characteristics for various water resource related applications in the study area.

This research is an original work that focuses on all three satellite rainfall estimates forced simulations displaying substantially improved performance after bias correction and recalibration.

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 prepare flood hazard map and show the extent of flood hazard under climate change scenarios in Woybo River catchment. The hydraulic model, Hydrologic Engineering Center - River Analysis System (HEC-RAS) was used to simulate the floods under future climate scenarios. The impact of climate changes on severity of flooding was evaluated for the mid-term (2041–2070) and long-term (2071–2100) with relative to a baseline period (1971–2000).

Future climate scenarios were constructed from the bias corrected outputs of five regional climate models and the inflow hydrographs for 10, 25, 50 and 100 years design floods were derived from the flow which generated from HEC-hydrological modeling system; that was an input for the HEC-RAS model to generate the flood hazard maps in the catchment.

The results of this research show that 25.68% of the study area can be classified as very high hazard class while 28.56% of the area is under high hazard. It was also found that 20.20% is under moderate hazard and about 25.56% is under low hazard class in future under high emission scenario. The projected area to be flooded in far future relative to the baseline period is 66.3 ha of land which accounts for 62.82% from the total area. This study suggested that agricultural/crop land located at the right side of the Woybo River near the flood plain would be affected more with the 25, 50 and 100 years design floods.

Multiple climate models were assessed properly and the ensemble mean was used to prepare flood hazard map using HEC-RAS modeling.