Special Issue "Hydrological Hazard: Analysis and Prevention"

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Natural Hazards".

Deadline for manuscript submissions: closed (31 March 2018)

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Special Issue Editor

Guest Editor
Dr. Tommaso Caloiero

National Research Council of Italy, Research Institute for Agricultural and Forest Systems in the Mediterranean (CNR-ISAFOM), Rende (CS), Italy
Website | E-Mail
Interests: hydrology; climatology; climate change; natural hazards

Special Issue Information

Dear Colleagues,

Due to the considerable impacts of hydrological hazard on water resources, on natural environments and human activities, as well as on human health and safety, climate variability and climate change have become key issues for the research community. In fact, a warmer climate, with its heightened climate variability, will increase the risk of hydrological extremes phenomena, such as droughts and floods. The overall goal of this Special Issue of Geosciences is to consider innovative approaches to the analysis, prediction, prevention, and mitigation of hydrological extremes. With this aim, interdisciplinary original research articles highlighting new ideas, approaches and innovations in the analysis of various types of droughts (e.g., meteorological, agricultural and hydrological drought) and various types of flood (e.g., fluvial, coastal and pluvial) are welcomed.

Potential topics of this Special Issue of Geosciences include, but are not limited to:

  • Regional flood and drought analysis
  • Case studies and comparative studies in different parts of the world
  • Analyses of regional/global patterns and trends
  • Effects of land-use or land-cover change on hydrological extremes
  • Prediction and prevention of hydrological extremes
  • Use of satellite and climate data for drought analysis
  • Innovative modelling methods for flood hazards
  • Strategies for reducing the vulnerability to hydrological extremes
  • Climate change and hydrogeologicl risk
Dr. Tommaso Caloiero
Guest Editor

Manuscript Submission Information

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Published Papers (14 papers)

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Editorial

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Open AccessEditorial Hydrological Hazard: Analysis and Prevention
Geosciences 2018, 8(11), 389; https://doi.org/10.3390/geosciences8110389
Received: 22 October 2018 / Accepted: 25 October 2018 / Published: 26 October 2018
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Abstract
As a result of the considerable impacts of hydrological hazard on water resources, on natural environments and human activities, as well as on human health and safety, climate variability and climate change have become key issues for the research community. In fact, a [...] Read more.
As a result of the considerable impacts of hydrological hazard on water resources, on natural environments and human activities, as well as on human health and safety, climate variability and climate change have become key issues for the research community. In fact, a warmer climate, with its heightened climate variability, will increase the risk of hydrological extreme phenomena, such as droughts and floods. The Special Issue “Hydrological Hazard: Analysis and Prevention” presents a collection of scientific contributions that provides a sample of the state-of-the-art and forefront research in this field. In particular, innovative modelling methods for flood hazards, regional flood and drought analysis, and the use of satellite and climate data for drought analysis were the main topics and practice targets that the papers published in this Special Issue aimed to address. Full article
(This article belongs to the Special Issue Hydrological Hazard: Analysis and Prevention) Printed Edition available
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Research

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Open AccessArticle Analysis of Damage Caused by Hydrometeorological Disasters in Texas, 1960–2016
Geosciences 2018, 8(10), 384; https://doi.org/10.3390/geosciences8100384
Received: 20 September 2018 / Revised: 16 October 2018 / Accepted: 18 October 2018 / Published: 20 October 2018
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Abstract
Property damages caused by hydrometeorological disasters in Texas during the period 1960–2016 totaled $54.2 billion with hurricanes, tropical storms, and hail accounting for 56%, followed by flooding and severe thunderstorms responsible for 24% of the total damages. The current study provides normalized trends [...] Read more.
Property damages caused by hydrometeorological disasters in Texas during the period 1960–2016 totaled $54.2 billion with hurricanes, tropical storms, and hail accounting for 56%, followed by flooding and severe thunderstorms responsible for 24% of the total damages. The current study provides normalized trends to support the assertion that the increase in property damage is a combined contribution of stronger disasters as predicted by climate change models and increases in urban development in risk prone regions such as the Texas Gulf Coast. A comparison of the temporal distribution of damages normalized by population and GDP resulted in a less statistically significant increasing trend per capita. Seasonal distribution highlights spring as the costliest season (March, April and May) while the hurricane season (June through November) is well aligned with the months of highest property damage. Normalization of property damage by GDP during 2001–2016 showed Dallas as the only metropolitan statistical area (MSA) with a significant increasing trend of the 25 MSAs in Texas. Spatial analysis of property damage per capita highlighted the regions that are at greater risk during and after a major disaster given their limited economic resources compared to more urbanized regions. Variation in the causes of damage (wind or water) and types of damage that a “Hurricane” can produce was investigated using Hazus model simulation. A comparison of published damage estimates at time of occurrence with simulation outputs for Hurricanes Carla, 1961; Alicia, 1983; and Ike, 2008 based on 2010 building exposure highlighted the impact of economic growth, susceptibility of wood building types, and the predominant cause of damage. Carla and Ike simulation models captured less than 50% of their respective estimates reported by other sources suggesting a broad geographical zone of damage with flood damage making a significant contribution. Conversely, the model damage estimates for Alicia are 50% higher than total damage estimates that were reported at the time of occurrence suggesting a substantial increase in building exposure susceptible to wind damage in the modeled region from 1983 – 2010. Full article
(This article belongs to the Special Issue Hydrological Hazard: Analysis and Prevention) Printed Edition available
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Open AccessArticle An Attempt to Use Non-Linear Regression Modelling Technique in Long-Term Seasonal Rainfall Forecasting for Australian Capital Territory
Geosciences 2018, 8(8), 282; https://doi.org/10.3390/geosciences8080282
Received: 9 June 2018 / Revised: 24 July 2018 / Accepted: 26 July 2018 / Published: 28 July 2018
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Abstract
The objective of this research is the assessment of the efficiency of a non-linear regression technique in predicting long-term seasonal rainfall. The non-linear models were developed using the lagged (past) values of the climate drivers, which have a significant correlation with rainfall. More [...] Read more.
The objective of this research is the assessment of the efficiency of a non-linear regression technique in predicting long-term seasonal rainfall. The non-linear models were developed using the lagged (past) values of the climate drivers, which have a significant correlation with rainfall. More specifically, the capabilities of SEIO (South-eastern Indian Ocean) and ENSO (El Nino Southern Oscillation) were assessed in reproducing the rainfall characteristics using the non-linear regression approach. The non-linear models developed were tested using the individual data sets, which were not used during the calibration of the models. The models were assessed using the commonly used statistical parameters, such as Pearson correlations (R), root mean square error (RMSE), mean absolute error (MAE) and index of agreement (d). Three rainfall stations located in the Australian Capital Territory (ACT) were selected as a case study. The analysis suggests that the predictors which has the highest correlation with the predictands do not necessarily produce the least errors in rainfall forecasting. The non-linear regression was able to predict seasonal rainfall with correlation coefficients varying from 0.71 to 0.91. The outcomes of the analysis will help the watershed management authorities to adopt efficient modelling technique by predicting long-term seasonal rainfall. Full article
(This article belongs to the Special Issue Hydrological Hazard: Analysis and Prevention) Printed Edition available
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Open AccessArticle Modelling the Present and Future Water Level and Discharge of the Tidal Betna River
Geosciences 2018, 8(8), 271; https://doi.org/10.3390/geosciences8080271
Received: 14 June 2018 / Revised: 3 July 2018 / Accepted: 23 July 2018 / Published: 24 July 2018
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Abstract
Climate change, comprising of changes in precipitation patterns, higher temperatures and sea level rises, increases the likelihood of future flooding in the Betna River basin, Bangladesh. Hydrodynamic modelling was performed to simulate the present and future water level and discharge for different scenarios [...] Read more.
Climate change, comprising of changes in precipitation patterns, higher temperatures and sea level rises, increases the likelihood of future flooding in the Betna River basin, Bangladesh. Hydrodynamic modelling was performed to simulate the present and future water level and discharge for different scenarios using bias-corrected, downscaled data from two general circulation models. The modelling results indicated that, compared to the baseline year (2014–2015), the water level is expected to increase by 11–16% by the 2040s and 14–23% by the 2090s, and the monsoon daily maximum discharge is expected to increase by up to 13% by the 2040s and 21% by the 2090s. Sea level rise is mostly responsible for the increase in water level. The duration of water level exceedance of the established danger threshold and extreme discharge events can increase by up to half a month by the 2040s and above one month by the 2090s. The combined influence of the increased water level and discharge has the potential to cause major floods in the Betna River basin. The results of our study increase the knowledge base on climate change influence on water level and discharge at a local scale. This is valuable for water managers in flood-risk mitigation and water management. Full article
(This article belongs to the Special Issue Hydrological Hazard: Analysis and Prevention) Printed Edition available
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Open AccessArticle Assessment of the Performance of Satellite-Based Precipitation Products for Flood Events across Diverse Spatial Scales Using GSSHA Modeling System
Geosciences 2018, 8(6), 191; https://doi.org/10.3390/geosciences8060191
Received: 21 April 2018 / Revised: 24 May 2018 / Accepted: 24 May 2018 / Published: 28 May 2018
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Abstract
Accurate precipitation measurements for high magnitude rainfall events are of great importance in hydrometeorology and climatology research. The focus of the study is to assess the performance of satellite-based precipitation products against a gauge adjusted Next-Generation Radar (NEXRAD) Stage IV product during high [...] Read more.
Accurate precipitation measurements for high magnitude rainfall events are of great importance in hydrometeorology and climatology research. The focus of the study is to assess the performance of satellite-based precipitation products against a gauge adjusted Next-Generation Radar (NEXRAD) Stage IV product during high magnitude rainfall events. The assessment was categorized across three spatial scales using watershed ranging from ~200–10,000 km2. The propagation of the errors from rainfall estimates to runoff estimates was analyzed by forcing a hydrologic-model with the satellite-based precipitation products for nine storm events from 2004 to 2015. The National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) Morphing Technique (CMORPH) products showed high correlation to the NEXRAD estimates in all spatial domains, and had an average Nash-Sutcliffe coefficient of 0.81. The Global Precipitation Measurement (GPM) Early product was inconsistent with a very high variance of Nash-Sutcliffe coefficient in all spatial domains (from −0.46 to 0.38), however, the variance decreased as the watershed size increased. Surprisingly, Tropical Rainfall Measuring Mission (TRMM) also showed a very high variance in all the performance statics. In contrast, the un-corrected product of the TRMM showed a relatively better performance. The errors of the precipitation estimates were amplified in the simulated hydrographs. Even though the products provide evenly distributed near-global spatiotemporal estimates, they significantly underestimate strong storm events in all spatial scales. Full article
(This article belongs to the Special Issue Hydrological Hazard: Analysis and Prevention) Printed Edition available
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Open AccessArticle Fatalities Caused by Hydrometeorological Disasters in Texas
Geosciences 2018, 8(5), 186; https://doi.org/10.3390/geosciences8050186
Received: 20 April 2018 / Revised: 6 May 2018 / Accepted: 15 May 2018 / Published: 18 May 2018
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Abstract
Texas ranks first in the U.S in number of fatalities due to natural disasters. Based on data culled from the National Oceanic and Atmospheric Administration (NOAA) from 1959 to 2016, the number of hydrometeorological fatalities in Texas have increased over the 58-year study [...] Read more.
Texas ranks first in the U.S in number of fatalities due to natural disasters. Based on data culled from the National Oceanic and Atmospheric Administration (NOAA) from 1959 to 2016, the number of hydrometeorological fatalities in Texas have increased over the 58-year study period, but the per capita fatalities have significantly decreased. Spatial review found that non-coastal flooding is the predominant hydrometeorological disaster in a majority of the Texas counties located in “Flash Flood Alley” and accounts for 43% of all hydrometeorological fatalities in the state. Flooding fatalities occur most frequently on “Transportation Routes” followed by heat fatalities in “Permanent Residences”. Seasonal and monthly stratification identifies Spring and Summer as the deadliest seasons, with the month of May registering the highest number of total fatalities dominated by flooding and tornado fatalities. Demographic trends of hydrometeorological disaster fatalities indicated that approximately twice as many male fatalities occurred from 1959-2016 than female fatalities, but with decreasing gender disparity over time. Adults are the highest fatality risk group overall, children are most at risk to die in flooding, and the elderly at greatest risk of heat-related death. Full article
(This article belongs to the Special Issue Hydrological Hazard: Analysis and Prevention) Printed Edition available
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Open AccessArticle From Deterministic to Probabilistic Forecasts: The ‘Shift-Target’ Approach in the Milan Urban Area (Northern Italy)
Geosciences 2018, 8(5), 181; https://doi.org/10.3390/geosciences8050181
Received: 6 April 2018 / Revised: 8 May 2018 / Accepted: 10 May 2018 / Published: 15 May 2018
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Abstract
The number of natural catastrophes that affect people worldwide is increasing; among these, the hydro-meteorological events represent the worst scenario due to the thousands of deaths and huge damages to private and state ownership they can cause. To prevent this, besides various structural [...] Read more.
The number of natural catastrophes that affect people worldwide is increasing; among these, the hydro-meteorological events represent the worst scenario due to the thousands of deaths and huge damages to private and state ownership they can cause. To prevent this, besides various structural measures, many non-structural solutions, such as the implementation of flood warning systems, have been proposed in recent years. In this study, we suggest a low computational cost method to produce a probabilistic flood prediction system using a single forecast precipitation scenario perturbed via a spatial shift. In fact, it is well-known that accurate forecasts of heavy precipitation, especially associated with deep moist convection, are challenging due to uncertainties arising from the numerical weather prediction (NWP), and high sensitivity to misrepresentation of the initial atmospheric state. Inaccuracies in precipitation forecasts are partially due to spatial misplacing. To produce hydro-meteorological simulations and forecasts, we use a flood forecasting system which comprises the physically-based rainfall-runoff hydrological model FEST-WB developed by the Politecnico di Milano, and the MOLOCH meteorological model provided by the Institute of Atmospheric Sciences and Climate (CNR-ISAC). The areas of study are the hydrological basins of the rivers Seveso, Olona, and Lambro located in the northern part of Milan city (northern Italy) where this system works every day in real-time. In this paper, we show the performance of reforecasts carried out between the years 2012 and 2015: in particular, we explore the ‘Shift-Target’ (ST) approach in order to obtain 40 ensemble members, which we assume equally likely, derived from the available deterministic precipitation forecast. Performances are shown through statistical indexes based on exceeding the threshold for different gauge stations over the three hydrological basins. Results highlight how the Shift-Target approach complements the deterministic MOLOCH-based flood forecast for warning purposes. Full article
(This article belongs to the Special Issue Hydrological Hazard: Analysis and Prevention) Printed Edition available
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Open AccessArticle Correlation Analysis of Seasonal Temperature and Precipitation in a Region of Southern Italy
Geosciences 2018, 8(5), 160; https://doi.org/10.3390/geosciences8050160
Received: 27 March 2018 / Revised: 27 April 2018 / Accepted: 28 April 2018 / Published: 2 May 2018
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Abstract
The investigation of the statistical links between changes in temperature and rainfall, though not widely achieved in the past, is an interesting issue because their physical interdependence is difficult to point out. Aiming at detecting possible trends with a pooled approach, a correlative [...] Read more.
The investigation of the statistical links between changes in temperature and rainfall, though not widely achieved in the past, is an interesting issue because their physical interdependence is difficult to point out. Aiming at detecting possible trends with a pooled approach, a correlative analysis of temperature and rainfall has been carried out by comparing changes in their standardized anomalies from two different 30-year time periods. The procedure has been applied to the time series of seasonal mean temperature and cumulative rainfall observed in four sites of the Calabria region (Southern Italy), with reference to the series which verify the normality hypothesis. Specifically, the displacements of the ellipses, representing the probability density functions of the bivariate normal distribution assumed for the climatic variables, have been quantified and tested for each season, passing from the first subperiod to the following one. The main results concern a decreasing trend of both the temperature and the rainfall anomalies, predominantly in the winter and autumn seasons. Full article
(This article belongs to the Special Issue Hydrological Hazard: Analysis and Prevention) Printed Edition available
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Open AccessArticle Comparison of SCS and Green-Ampt Distributed Models for Flood Modelling in a Small Cultivated Catchment in Senegal
Geosciences 2018, 8(4), 122; https://doi.org/10.3390/geosciences8040122
Received: 29 January 2018 / Revised: 27 March 2018 / Accepted: 29 March 2018 / Published: 4 April 2018
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Abstract
The vulnerability to floods in Africa has increased over the last decades, together with a modification of land cover as urbanized areas are increasing, agricultural practices are changing, and deforestation is increasing. Rainfall-runoff models that properly represent land use change and hydrologic response [...] Read more.
The vulnerability to floods in Africa has increased over the last decades, together with a modification of land cover as urbanized areas are increasing, agricultural practices are changing, and deforestation is increasing. Rainfall-runoff models that properly represent land use change and hydrologic response should be useful for the development of water management and mitigation plans. Although some studies have applied rainfall-runoff models in West Africa for flood modelling, there is still a need to develop such models, while many data are available and have not still been used for modelling improvement. The Ndiba catchment (16.2 km2), which is located in an agricultural area in south Senegal, is such catchment, where a lot of hydro-climatic data has been collected between 1983 and 1992. Twenty-eight flood events have been extracted and modelled by two event-based rainfall-runoff models that are based on the Soil Conservation Service (SCS) or the Green-Ampt (GA) models for runoff, both coupled with the distributed Lag and Route (LR) for routing. Both models were able to reproduce the flood events after calibration, but they had to account for that the infiltration processes are highly dependent on the tillage of the soils and the growing of the crops during the rainy season, which made the initialization of the event-based models difficult. The most influent parameters for both models (the maximal water storage capacity for SCS, the hydraulic conductivity at saturation for Green-Ampt) were mostly related to the development stage of the vegetation, described by a Normalized Difference Vegetation Index (NDVI) anomaly. The SCS model performed finally better than the Green-Ampt model, because Green-Ampt was very sensitive to the variability of the hydraulic conductivity at saturation. The variability of the parameters of the models highlights the complexity of this kind of cultivated catchment, with highly non stationary conditions. The models could be improved by a better knowledge of the tillage practices, and a better integration of these practices in the parameters predictors. Full article
(This article belongs to the Special Issue Hydrological Hazard: Analysis and Prevention) Printed Edition available
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Open AccessArticle SPI Trend Analysis of New Zealand Applying the ITA Technique
Geosciences 2018, 8(3), 101; https://doi.org/10.3390/geosciences8030101
Received: 28 February 2018 / Revised: 8 March 2018 / Accepted: 13 March 2018 / Published: 15 March 2018
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Abstract
A natural temporary imbalance of water availability, consisting of persistent lower-than-average or higher-than-average precipitation, can cause extreme dry and wet conditions that adversely impact agricultural yields, water resources, infrastructure, and human systems. In this study, dry and wet periods in New Zealand were [...] Read more.
A natural temporary imbalance of water availability, consisting of persistent lower-than-average or higher-than-average precipitation, can cause extreme dry and wet conditions that adversely impact agricultural yields, water resources, infrastructure, and human systems. In this study, dry and wet periods in New Zealand were expressed using the Standardized Precipitation Index (SPI). First, both the short term (3 and 6 months) and the long term (12 and 24 months) SPI were estimated, and then, possible trends in the SPI values were detected by means of a new graphical technique, the Innovative Trend Analysis (ITA), which allows the trend identification of the low, medium, and high values of a series. Results show that, in every area currently subject to drought, an increase in this phenomenon can be expected. Specifically, the results of this paper highlight that agricultural regions on the eastern side of the South Island, as well as the north-eastern regions of the North Island, are the most consistently vulnerable areas. In fact, in these regions, the trend analysis mainly showed a general reduction in all the values of the SPI: that is, a tendency toward heavier droughts and weaker wet periods. Full article
(This article belongs to the Special Issue Hydrological Hazard: Analysis and Prevention) Printed Edition available
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Open AccessArticle Simulating the Influence of Buildings on Flood Inundation in Urban Areas
Geosciences 2018, 8(2), 77; https://doi.org/10.3390/geosciences8020077
Received: 19 January 2018 / Revised: 19 February 2018 / Accepted: 19 February 2018 / Published: 24 February 2018
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Abstract
Two-dimensional hydraulic modeling is fundamental to simulate flood events in urban area. Key factors to reach optimal results are detailed information about domain geometry and utility of hydrodynamic models to integrate the full or simplified Saint Venant equations in complex geometry. However, in [...] Read more.
Two-dimensional hydraulic modeling is fundamental to simulate flood events in urban area. Key factors to reach optimal results are detailed information about domain geometry and utility of hydrodynamic models to integrate the full or simplified Saint Venant equations in complex geometry. However, in some cases, detailed topographic datasets that represent the domain geometry are not available, so approximations—such as diffusive wave equation—is introduced whilst representing urban area with an adjusted roughness coefficient. In the present paper, different methods to represent buildings and approximation of the Saint Venant equations are tested by performing experiments on a scale physical model of urban district in laboratory. Simplified methods are tested for simulation of a real flood event which occurred in 2013 in the city of Olbia, Italy. Results show that accuracy of simulating flow depth with a detailed geometry is comparable to the one achieved with an adjusted roughness coefficient. Full article
(This article belongs to the Special Issue Hydrological Hazard: Analysis and Prevention) Printed Edition available
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Open AccessArticle Impact of the Rainfall Duration and Temporal Rainfall Distribution Defined Using the Huff Curves on the Hydraulic Flood Modelling Results
Geosciences 2018, 8(2), 69; https://doi.org/10.3390/geosciences8020069
Received: 15 January 2018 / Revised: 7 February 2018 / Accepted: 10 February 2018 / Published: 11 February 2018
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Abstract
In the case of ungauged catchments, different procedures can be used to derive the design hydrograph and design peak discharge, which are crucial input data for the design of different hydrotechnical engineering structures, or the production of flood hazard maps. One of the [...] Read more.
In the case of ungauged catchments, different procedures can be used to derive the design hydrograph and design peak discharge, which are crucial input data for the design of different hydrotechnical engineering structures, or the production of flood hazard maps. One of the possible approaches involves using a hydrological model where one can calculate the design hydrograph through the design of a rainfall event. This study investigates the impact of the design rainfall on the combined one-dimensional/two-dimensional (1D/2D) hydraulic modelling results. The Glinščica Stream catchment located in Slovenia (central Europe) is used as a case study. Ten different design rainfall events were compared for 10 and 100-year return periods, where we used Huff curves for the design rainfall event definition. The results indicate that the selection of the design rainfall event should be regarded as an important step, since the hydraulic modelling results for different scenarios differ significantly. In the presented experimental case study, the maximum flooded area extent was twice as large as the minimum one, and the maximum water velocity over flooded areas was more than 10 times larger than the minimum one. This can lead to the production of very different flood hazard maps, and consequently planning very different flood protection schemes. Full article
(This article belongs to the Special Issue Hydrological Hazard: Analysis and Prevention) Printed Edition available
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Other

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Open AccessCase Report A Novel Method for Evaluation of Flood Risk Reduction Strategies: Explanation of ICPR FloRiAn GIS-Tool and Its First Application to the Rhine River Basin
Geosciences 2018, 8(10), 371; https://doi.org/10.3390/geosciences8100371
Received: 17 August 2018 / Revised: 28 September 2018 / Accepted: 3 October 2018 / Published: 6 October 2018
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Abstract
To determine the effects of measures on flood risk, the International Commission for the Protection of the Rhine (ICPR), supported by the engineering consultant HKV has developed a method and a GIS-tool named “ICPR FloRiAn (Flood Risk Analysis)”, which enables the broad-scale assessment [...] Read more.
To determine the effects of measures on flood risk, the International Commission for the Protection of the Rhine (ICPR), supported by the engineering consultant HKV has developed a method and a GIS-tool named “ICPR FloRiAn (Flood Risk Analysis)”, which enables the broad-scale assessment of the effectiveness of flood risk management measures on the Rhine, but could be also applied to other rivers. The tool uses flood hazard maps and associated recurrence periods for an overall damage and risk assessment for four receptors: human health, environment, culture heritage, and economic activity. For each receptor, a method is designed to calculate the impact of flooding and the effect of measures. The tool consists of three interacting modules: damage assessment, risk assessment, and measures. Calculations using this tool show that the flood risk reduction target defined in the Action Plan on Floods of the ICPR in 1998 could be achieved with the measures already taken and those planned until 2030. Upon request, the ICPR will provide this tool and the method to other river basin organizations, national authorities, or scientific institutions. This article presents the method and GIS-tool developed by the ICPR as well as first calculation results. Full article
(This article belongs to the Special Issue Hydrological Hazard: Analysis and Prevention) Printed Edition available
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Open AccessTechnical Note Examples of Application of GASAKe for Predicting the Occurrence of Rainfall-Induced Landslides in Southern Italy
Geosciences 2018, 8(2), 78; https://doi.org/10.3390/geosciences8020078
Received: 12 January 2018 / Revised: 16 February 2018 / Accepted: 22 February 2018 / Published: 24 February 2018
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Abstract
GASAKe is an empirical-hydrological model aimed at forecasting the time of occurrence of landslides. Activations can be predicted of either single landslides or sets of slope movements of the same type in a homogeneous environment. The model requires a rainfall series and [...] Read more.
GASAKe is an empirical-hydrological model aimed at forecasting the time of occurrence of landslides. Activations can be predicted of either single landslides or sets of slope movements of the same type in a homogeneous environment. The model requires a rainfall series and a set of dates of landslide activation as input data. Calibration is performed through genetic algorithms, and allows for determining a family of optimal kernels to weight antecedent rainfall properly. As output, the mobility function highlights critical conditions of slope stability. Based on suitable calibration and validation samples of activation dates, the model represents a useful tool to be integrated in early-warning systems for geo-hydrological risk mitigation purposes. In the present paper, examples of application to three rock slides in Calabria and to cases of soil slips in Campania are discussed. Calibration and validation are discussed, based on independent datasets. Obtained results are either excellent for two of the Calabrian rock slides or just promising for the remaining case studies. The best performances of the model take advantage of an accurate knowledge of the activation history of the landslides, and a proper hydrological characterization of the sites. For such cases, GASAKe could be usefully employed within early-warning systems for geo-hydrological risk mitigation and Civil Protection purposes. Finally, a new release of the model is presently under test: its innovative features are briefly presented. Full article
(This article belongs to the Special Issue Hydrological Hazard: Analysis and Prevention) Printed Edition available
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