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Floods and Landslide Prediction

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A special issue of Hydrology (ISSN 2306-5338).

Deadline for manuscript submissions: closed (31 October 2016) | Viewed by 59789

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Dr. Angelica Tarpanelli

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Research Institute for Geo-Hydrological Protection, National Research Council, Via della Madonna Alta 126, 06128 Perugia, Italy
Interests: remote sensing of rivers; hydrological and hydraulic processes; flooded area estimation; analysis of climate change effects on flood frequency
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Dr. Luca Brocca

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Research Institute for Geo-Hydrological Protection, National Research Council, Via della Madonna Alta, 126, 06128 Perugia, Italy
Interests: soil moisture; flood; drought; irrigation; remote sensing
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Dr. Mauro Rossi

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Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Via della Madonna Alta 126, 06128 Perugia, Italia
Interests: landslide; erosion; hazard; susceptibility; early-warning systems; landslide & erosion forecast; societal risk; geo-hydrological modelling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Floods and landslides are among the most dangerous and costly of all natural disasters, with expectations to worsen in the future as a result to global temperatures increase and environmental changes. In developing countries, the situation is exacerbated to the lack of monitoring and warning systems and an effort is required to set up flood and landslide prediction systems to limit the vulnerability of certain regions and to mitigate the damage. The goal of many studies is to assist scientists, forecasters, practitioners and stakeholders in forecasting of these complex phenomena in order to protect individual and collective resources. Several qualitative and quantitative methods and techniques have been proposed covering different geographical environment and spatial scales. New algorithms and approaches have been developed to explore the use of ground data along with satellite sensors. Based on possible future scenarios of meteorological and hydrological variables such predictions may be used for operational use including uncertainty.

This Special Issue intends to collect studies addressing the prediction, in space and in time, of floods and landslides in order to improve the dissemination of advanced research. Of interest are contributions investigating theoretical aspects of floods and landslide prediction, including conceptual, mathematical, physical, statistical, numerical and computational problems. Additionally, applicative contributions are encouraged (early warning system) that demonstrate the potential to predict floods and landslides through new models, methodologies, and observations (e.g., remote sensing). Contributions will cover, but are not restricted to, the following topics:

Development of tools for the identification, management and prediction of floods and/or landslides in gauged and ungauged basins;
monitoring and modelling of the physical processes leading to floods and /or landslides occurrence;
use of new observations (e.g. remote sensing, UAV) for floods and/or landslides prediction;
improving floods and/or landslides prediction through data assimilation

Dr. Angelica Tarpanelli
Dr. Luca Brocca
Dr. Mauro Rossi
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Hydrology is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

floods
landslides
process understanding
early warning system
remote sensing
data assimilation

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Published Papers (8 papers)

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4517 KiB

Open AccessArticle

Evaluation of Variations in Frequency of Landslide Events Affecting Pyroclastic Covers in Campania Region under the Effect of Climate Changes

by Guido Rianna, Alfredo Reder, Paola Mercogliano and Luca Pagano

Hydrology 2017, 4(3), 34; https://doi.org/10.3390/hydrology4030034 - 28 Jun 2017

Cited by 22 | Viewed by 4417

Abstract

In recent years, pyroclastic covers mantling slopes in the Campania region of southern Italy have frequently been affected by flowslides. Due to high exposure and demographic pressure in these areas, assessment of the potential effects of climate change on the frequency of such events has become a crucial issue. In this regard, our paper proposes a simulation chain comprising three main elements: (i) climate simulation at the highest horizontal resolution available for Italy (8 km); (ii) a bias correction procedure in an attempt to remove systematic errors in the entire weather forcing probability distribution; (iii) the data obtained used as input for an interpretative tool estimating the evolution of soil pore water pressure and water storage (bulk water content) by means of a well-calibrated coupled thermo-hydraulic approach able to adequately take into account soil-atmosphere interaction dynamics. The predictive ability of the geotechnical model to reproduce failure conditions was tested by forcing it with temperature and precipitation observations. Subsequently, the performance of the entire modeling chain was evaluated for a period from 1981 to 2010. Lastly, variations in landslide occurrence were assessed up to 2100 under two concentration scenarios. An increase with different features was estimated under both scenarios depending on the time horizon and the severity of the concentration scenario. Full article

(This article belongs to the Special Issue Floods and Landslide Prediction)

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8821 KiB

Open AccessArticle

A Multi-Faceted Debris-Flood Hazard Assessment for Cougar Creek, Alberta, Canada

by Matthias Jakob, Hamish Weatherly, Stephanie Bale, Ashley Perkins and Brent MacDonald

Hydrology 2017, 4(1), 7; https://doi.org/10.3390/hydrology4010007 - 25 Jan 2017

Cited by 18 | Viewed by 9195

Abstract

A destructive debris flood occurred between 19 and 21 June 2013 on Cougar Creek, located in Canmore, Alberta. Cougar Creek fan is likely the most densely developed alluvial fan in Canada. While no lives were lost, the event resulted in approximately $40 M of damage and closed both the Trans-Canada Highway (Highway 1) and the Canadian Pacific Railway line for a period of several days. The debris flood triggered a comprehensive hazard assessment which is the focus of this paper. Debris-flood frequencies and magnitudes are determined by combining several quantitative methods including photogrammetry, dendrochronology, radiometric dating, test pit logging, empirical relationships between rainfall volumes and sediment volumes, and landslide dam outburst flood modeling. The data analysis suggests that three distinct process types act in the watershed. The most frequent process is normal or “clearwater” floods. Less frequent but more damaging are debris floods during which excessive amounts of bedload are transported on the fan, typically associated with rapid and extensive bank erosion and channel infilling and widening. The third and most destructive process is interpreted to be landslide dam outbreak floods. This event type is estimated to occur at return periods exceeding 300 years. Using a cumulative magnitude frequency technique, the data for conventional debris floods were plotted up to the 100–300s year return period. A peak-over-threshold approach was used for landslide dam outbreak floods occurring at return periods exceeding 300 years, as not all such events were identified during test trenching. Hydrographs for 6 return period classes were approximated by using the estimated peak discharges and fitting the hydrograph shape to integrate to the debris flood volumes as determined from the frequency-magnitude relationship. The fan volume was calculated and compared with the integrated frequency-magnitude curve to check of the validity of the latter. A reasonable match was accomplished, verifying the overall relationship. The findings from this work were later used as input to a risk assessment seeking to quantify risk to loss of life and economic losses. The risk assessment then formed the basis for design of debris-flood mitigation structures. Full article

(This article belongs to the Special Issue Floods and Landslide Prediction)

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2708 KiB

Open AccessArticle

Hydrodynamic Modeling of Nokoué Lake in Benin

by Josué Zandagba, Mahmoud Moussa, Ezéchiel Obada and Abel Afouda

Hydrology 2016, 3(4), 44; https://doi.org/10.3390/hydrology3040044 - 15 Dec 2016

Cited by 15 | Viewed by 6811

Abstract

Nokoué Lake is a complex ecosystem, the understanding of which requires control of physical processes that have occurred. For this, the Surface Water Modeling System (SMS) hydrodynamic model was calibrated and validated on the water depth data. The results of these simulations show a good match between the simulated and observed data for bottom roughness and turbulent exchange coefficients, of 0.02 m^−1/3·s and 20 m²/s respectively. Once the ability of the model to simulate the hydrodynamics of the lake is testified, the model is used to simulate water surface elevation, exchanged flows and velocities. The simulation shows that the tidal amplitude is maximum at the inlet of the channel and decreases gradually from the inlet towards the lagoon’s main body. The propagation of the tidal wave is characterized by the dephasing and the flattening of the amplitude tide, which increases as we move away from the channel. This dephasing is characterized by a high and low tides delay of about 1 or 4 h and also depends on the tide amplitude and location. The velocities inside the lake are very low and do not exceed 0.03 m/s. The highest are obtained at the entrance of the channel. In a flood period, in contrast with the low-water period, incoming flows are higher than outflows, reinforced by the amplitude of the tide. An average renewal time of the lake has been estimated and corresponds during a flood period to 30 days for an average amplitude tide and 26.3 days on a high amplitude tide. In a low water period it is 40.2 days for an average amplitude tide and 30 days for a high amplitude tide. From the results obtained, several measures must be taken into account for the rational management of the lake water resources. These include a dam construction at the lake upstream, to control the river flows, and the dredging of the channel to facilitate exchanges with the sea. Full article

(This article belongs to the Special Issue Floods and Landslide Prediction)

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4771 KiB

Open AccessArticle

2015 Disastrous Floods in Louisiana, USA, and Assam, India: Groundwater Impact on the Water Balance Estimation

by Tatiana Trifonova, Dmitriy Trifonov and Sergey Arakelian

Hydrology 2016, 3(4), 41; https://doi.org/10.3390/hydrology3040041 - 21 Nov 2016

Cited by 3 | Viewed by 4542

Abstract

Traditionally torrential rains are considered as the main factor of flood emergence. With the examples of two disastrous floods in 2015 in absolutely different parts of the world, the authors roughly estimate the water balance and suggest an alternative hypothesis. The simplest model, taking into account precipitation, evaporation and soil permeability, clearly points out the significant discrepancy between potentially accumulated and observed water masses. This observation pushes the idea that precipitation is necessary but not sufficient for disastrous flood emergence, so the only other available water source—groundwater—cannot be ignored. Full article

(This article belongs to the Special Issue Floods and Landslide Prediction)

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3519 KiB

Open AccessArticle

Seasonal Changes in the Inundation Area and Water Volume of the Tonle Sap River and Its Floodplain

by Sokly Siev, Enrico C. Paringit, Chihiro Yoshimura and Seingheng Hul

Hydrology 2016, 3(4), 33; https://doi.org/10.3390/hydrology3040033 - 21 Oct 2016

Cited by 26 | Viewed by 7473

Abstract

Flood pulses occur annually along the Tonle Sap River (TSR) due to the large volume of water flowing from Tonle Sap Lake (TSL), its tributaries, and the Mekong River (MR). This study describes the seasonal changes in inundation area and water volume in the floodplain along the TSR over three years. The method employed time series remote sensing images of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data, the digital elevation model (DEM) of the Shuttle Radar Topography Mission (SRTM), bathymetric data, and observed water level data. Adding normalized difference vegetation index (NDVI) as a “third band” in the maximum likelihood classification (MLC) provided higher accuracy compared to thresholding NDVI and pure MLC (two bands) only. The results showed that the inundation area ranged from 123.8 to 3251.2 km² (mean: 1028.5 km²) with overall accuracy of 96.9%. The estimated water volume ranged from 418.3 to 2223.9 million m³ (mean: 917.3 million m³) from the dry to wet season, respectively. Seasonally, the TSR floodplain accounted for up to 5.3% and 3.2% of the mean annual inflow and outflow of the TSR, respectively. In addition to the TSL water reservoir, the TSR and its floodplain exchanged and stabilized the flow of the MR and its downstream delta, respectively. Overall, the obtained results have enhanced our understanding of the TSR, supporting further studies on river connectivity and reversal flow in this study area. Full article

(This article belongs to the Special Issue Floods and Landslide Prediction)

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13528 KiB

Open AccessArticle

Combined Modelling of Coastal Barrier Breaching and Induced Flood Propagation Using XBeach

by Saber M. Elsayed and Hocine Oumeraci

Hydrology 2016, 3(4), 32; https://doi.org/10.3390/hydrology3040032 - 30 Sep 2016

Cited by 19 | Viewed by 8651

Abstract

Breaching of coastal barriers is a three-dimensional process induced by complex interactions between hydrodynamics, sediment transport and soil avalanching processes. Although numerous coastal barriers are breached every year in many coastal countries, causing dramatic inundations of the nearshore areas, the understanding of the processes and interactions associated with both breaching and subsequent flood propagation is still poor. This might explain why their combined modelling and prediction has not yet been sufficiently addressed. Consequently, barrier breaching and subsequent inundation are still often modelled separately, thus ignoring the strong interaction between breaching and flooding. However, the combined modelling of such strongly coupled processes is crucial. Since the open-source model system “XBeach” consists, among others, of a nonlinear shallow water solver coupled with a morphodynamic model, also including a soil avalanching module, it has the potential to simulate both breaching and subsequent flood propagation together. Indeed, the mutual interactions between hydrodynamics and morphodynamics (including soil avalanching) are properly accounted for. This paper, therefore, aims to examine the applicability of XBeach for modelling coastal barrier breaching and inundation modelling in combination, instead of the current approaches, which address the modelling of each of these two processes separately. The performance of XBeach, in terms of inundation modelling, is assessed through comparisons of the results from this model system (i) with the results from common 1D and 2D flood propagation models and (ii) with observations for barrier breaching and subsequent inundation from a real case study. Besides providing an improved understanding of the breaching process, the results of this study demonstrate a new promising application of XBeach and its potential for calculating time-varying inland discharges, as well as for combined modelling of both dune breaching and subsequent flood propagation in coastal zones. Full article

(This article belongs to the Special Issue Floods and Landslide Prediction)

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5840 KiB

Open AccessCase Report

Flood Response System—A Case Study

by Yogesh Kumar Singh, Upasana Dutta, T. S. Murugesh Prabhu, I. Prabu, Jitendra Mhatre, Manoj Khare, Sandeep Srivastava and Subasisha Dutta

Hydrology 2017, 4(2), 30; https://doi.org/10.3390/hydrology4020030 - 7 Jun 2017

Cited by 10 | Viewed by 7664

Abstract

Flood Response System (FRS) is a network-enabled solution developed using open-source software. The system has query based flood damage assessment modules with outputs in the form of spatial maps and statistical databases. FRS effectively facilitates the management of post-disaster activities caused due to flood, like displaying spatial maps of area affected, inundated roads, etc., and maintains a steady flow of information at all levels with different access rights depending upon the criticality of the information. It is designed to facilitate users in managing information related to flooding during critical flood seasons and analyzing the extent of damage. The inputs to FRS are provided using two components: (1) a semi-automated application developed indigenously, to delineate inundated areas for Near-Real Time Flood Monitoring using Active Microwave Remote Sensing data and (2) a two-dimensional (2D) hydrodynamic river model generated outputs for water depth and velocity in flooded areas for an embankment breach scenario. The 2D Hydrodynamic model, CCHE2D (Center for Computational Hydroscience and Engineering Two-Dimensional model), was used to simulate an area of 600 km² in the flood-prone zone of the Brahmaputra basin. The resultant inundated area from the model was found to be 85% accurate when validated with post-flood optical satellite data. Full article

(This article belongs to the Special Issue Floods and Landslide Prediction)

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3156 KiB

Open AccessFeature PaperCase Report

Development of Flood Warning System and Flood Inundation Mapping Using Field Survey and LiDAR Data for the Grand River near the City of Painesville, Ohio

by Niraj Lamichhane and Suresh Sharma

Hydrology 2017, 4(2), 24; https://doi.org/10.3390/hydrology4020024 - 14 Apr 2017

Cited by 30 | Viewed by 8299

Abstract

Abstract: Flooding is one of the most frequent natural disasters across the world, which damages properties and may take the lives of people. Flood warning systems can play a significant role in minimizing those effects by helping to evacuate people from the probable affected areas during peak flash flood times. Therefore, a conceptual approach of an automated flood warning system is presented in this research to protect several houses, roads, and infrastructures along the Grand River, which are vulnerable to flooding during a 500 year return period flash flood. The Grand River is a tributary of Lake Erie, which lies in the Grand River watershed in the northeastern region of the United States and has a humid continental climate and receives lake-effect precipitation. The flood warning system for the Grand River was developed specifically during high flow conditions by calculating flood travel time and generating the inundation mapping for 12 different selected flood stages, which were approximately 2 to 500 years in recurrence interval, ranging from 10 ft. to 21 ft. at gage station 04212100, near the City of Painesville, OH. A Hydraulic Engineering Center-River Analysis System (HEC-RAS) was utilized for hydraulic modeling. Geospatial data required for HEC-RAS was obtained using a Digital Elevation Model (DEM) derived from Light Detection and Ranging (LiDAR) datasets, which were pre-processed and post-processed in HEC-GeoRAS to produce flood inundation maps. The flood travel time and flood inundation maps were generated by integrating LiDAR data with field verified survey results in order to provide the evacuation lead time needed for the people of probable affected areas, which is different from earlier studies. The generated inundation maps estimate the aerial extent of flooding along the Grand River corresponding to the various flood stages at the gage station near the City of Painesville and Harpersfield. The inundation maps were overlaid on digital orthographic maps to visualize its aerial extents, which can be uploaded online to provide a real-time inundation warning to the public when the flood occurs in the river. Full article

(This article belongs to the Special Issue Floods and Landslide Prediction)

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