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Special Issue "Flood Modelling: Regional Flood Estimation and GIS Based Techniques"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: 31 December 2019.

Special Issue Editors

Guest Editor
Prof. Dr. Ataur Rahman

Civil and Environmental Engineering, School of Computing, Engineering and Mathematics, University of Western Sydney, Locked Bag 1797, Penrith, NSW 2751, Australia
Website | E-Mail
Interests: hydrology; rainfall runoff; rainwater harvesting; flood; water demand forecasting; water sensitive urban design; water quality
Guest Editor
Prof. Dr. Biswajeet Pradhan

Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Sydney, Australia
Website | E-Mail
Interests: remote sensing and GIS; natural hazards; technological disasters and environmental modelling; natural resources
Guest Editor
Prof. Dr. Taha B.M.J. Ouarda

Center Water Earth Environment, National Institute of Scientific Research, Quebec, Canada
Website | E-Mail
Interests: hydrology; climatology; statistics; environmental modeling

Special Issue Information

Dear Colleagues,

This Special Issue deals with flood estimation for ungauged catchments using regional flood frequency analysis and GIS-based methods.

Floods are severe and frequent forms of natural hazards that cost human lives and results in significant economic losses. They occur at different intervals with varying durations and severity. Although it is not possible to prevent flooding completely, it can be predicted and managed through proper analysis, estimation and forecasting. It is a challenging task to accurately estimate floods and to delineate flood prone areas. Combination of hydrological, hydrodynamic and Geographical Information Systems (GIS) provides state-of-the-art investigation in flood modelling.

Regional flood frequency analysis (RFFA) is widely used to estimate floods at locations with no, inadequate and poor quality flood data. Most commonly adopted RFFA methods include index flood method, regression based methods and artificial intelligence based methods. More recently, GIS integrated methods are being used in RFFA. Space borne satellite data such as Quickbird, Worldview 3, SPOT 5, Google Earth Engine, etc., with the aid of GIS tools, offer excellent platform for flood mentoring and assessment. Advanced artificial intelligence (AI) techniques based on data mining, machine learning, deep-learning and ensemble models can be used to identify and monitor these floods and forecast them.

The topics of interest include, but not limited to:

-      Index flood method for RFFA
-      Quantile regression technique for RFFA
-      Parameter regression technique for RFFA
-      Bayesian methods in RFFA
-      Artificial intelligence based techniques for RFFA
-      At-site/RFFA
-      GIS based RFFA methods
-      Flood detection and monitoring
-      Flood modelling using GIS
-      Multi-temporal high resolution satellite images in flood modelling
-      LiDAR data in flood assessment
-      Ensemble modelling for flood estimation
-      Deep-leaning in flood modelling
-      New machine learning techniques in flood detection

Prof. Dr. Ataur Rahman
Prof. Dr. Biswajeet Pradhan
Prof. Dr. Taha B.M.J. Ouarda
Guest Editors

Manuscript Submission Information

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Keywords

  • Regional flood frequency analysis
  • Index flood methods
  • Quantile regression technique
  • Parameter regression technique
  • At-site/regional flood frequency analysis
  • ANN
  • GIS
  • Bayesian methods
  • Homogeneous regions
  • Satellite images
  • LiDAR
  • Ensemble modelling

Published Papers (10 papers)

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Research

Open AccessArticle
GIS Applications to Investigate the Linkage between Geomorphological Catchment Characteristics and Response Time: A Case Study in Four Climatological Regions, South Africa
Water 2019, 11(5), 1072; https://doi.org/10.3390/w11051072
Received: 12 April 2019 / Revised: 29 April 2019 / Accepted: 30 April 2019 / Published: 23 May 2019
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Abstract
In flood hydrology, geomorphological catchment characteristics serve as fundamental input to inform decisions related to design flood estimation and regionalization. Typically, site-specific geomorphological catchment characteristics are used for regionalization, while flood statistics are used to test the homogeneity of the identified regions. This [...] Read more.
In flood hydrology, geomorphological catchment characteristics serve as fundamental input to inform decisions related to design flood estimation and regionalization. Typically, site-specific geomorphological catchment characteristics are used for regionalization, while flood statistics are used to test the homogeneity of the identified regions. This paper presents the application and comparison of Geographical Information Systems (GIS) modelling tools for the estimation of catchment characteristics to provide an enhanced understanding of the linkage between geomorphological catchment characteristics and response time. It was evident that catchment response variability is not exclusively related to catchment area, but rather associated with the increasing spatial–temporal heterogeneity of other catchment characteristics as the catchment scale increases. In general, catchment and channel geomorphology overruled the impact that catchment variables might have on the response time and resulting runoff. Shorter response times and higher peak flows were evident in similar-sized catchments characterized by lower shape factors, circularity ratios, and shorter centroid distances and associated higher elongation ratios, drainage densities and steeper slopes. The GIS applications not only enabled the inclusion of a more diverse selection of catchment characteristics as opposed to when manual methods are used, but the high degree of association between the different GIS-based methods also confirmed their preferential use. Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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Open AccessArticle
A Quantitative Flood-Related Building Damage Evaluation Method Using Airborne LiDAR Data and 2-D Hydraulic Model
Water 2019, 11(5), 987; https://doi.org/10.3390/w11050987
Received: 22 March 2019 / Revised: 21 April 2019 / Accepted: 26 April 2019 / Published: 10 May 2019
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Abstract
The evaluation of building damage is of great significance for flood management. Chinese floodplains usually contain small- and medium-sized towns with many other scattered buildings. Detailed building information is usually scarce, making it difficult to evaluate flood damage. We developed an evaluation method [...] Read more.
The evaluation of building damage is of great significance for flood management. Chinese floodplains usually contain small- and medium-sized towns with many other scattered buildings. Detailed building information is usually scarce, making it difficult to evaluate flood damage. We developed an evaluation method for building damage by using airborne LiDAR data to obtain large-area, high-precision building information and digital elevation models (DEMs) for potentially affected areas. These data were then used to develop a two-dimensional (2-D) flood routing model. Next, flood loss rate curves were generated by fitting historical damage data to allow rapid evaluation of single-building losses. Finally, we conducted an empirical study based on the Gongshuangcha detention basin in China’s Dongting Lake region. The results showed that the use of airborne LiDAR data for flood-related building damage evaluation can improve the assessment accuracy and efficiency; this approach is especially suitable for rural areas where building information is scarce. Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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Open AccessArticle
Development of a Large Flood Regionalisation Model Considering Spatial Dependence—Application to Ungauged Catchments in Australia
Water 2019, 11(4), 677; https://doi.org/10.3390/w11040677
Received: 12 February 2019 / Revised: 19 March 2019 / Accepted: 29 March 2019 / Published: 1 April 2019
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Abstract
Estimation of large floods is imperative in planning and designing large hydraulic structures. Due to the limited availability of observed flood data, estimating the frequencies of large floods requires significant extrapolation beyond the available data. This paper presents the development of a large [...] Read more.
Estimation of large floods is imperative in planning and designing large hydraulic structures. Due to the limited availability of observed flood data, estimating the frequencies of large floods requires significant extrapolation beyond the available data. This paper presents the development of a large flood regionalisation model (LFRM) based on observed flood data. The LFRM assumes that the maximum observed flood data over a large number of sites in a region can be pooled together by accounting for the at-site variations in the mean and coefficient of variation. The LFRM is enhanced by adding a spatial dependence model, which accounts for the net information available for regional analysis. It was found that the LFRM, which accounts for spatial dependence and that pools 1 or 3 maxima from a site, was able to estimate the 1 in 1000 annual exceedance probability flood quantile with consistency, showing a positive bias on average (5–7%) and modest median relative errors (30–33%). Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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Open AccessArticle
Flood Susceptibility Mapping Using GIS-Based Analytic Network Process: A Case Study of Perlis, Malaysia
Water 2019, 11(3), 615; https://doi.org/10.3390/w11030615
Received: 31 December 2018 / Revised: 6 March 2019 / Accepted: 11 March 2019 / Published: 25 March 2019
Cited by 1 | PDF Full-text (11836 KB) | HTML Full-text | XML Full-text
Abstract
Understanding factors associated with flood incidence could facilitate flood disaster control and management. This paper assesses flood susceptibility of Perlis, Malaysia for reducing and managing their impacts on people and the environment. The study used an integrated approach that combines geographic information system [...] Read more.
Understanding factors associated with flood incidence could facilitate flood disaster control and management. This paper assesses flood susceptibility of Perlis, Malaysia for reducing and managing their impacts on people and the environment. The study used an integrated approach that combines geographic information system (GIS), analytic network process (ANP), and remote sensing (RS) derived variables for flood susceptibility assessment and mapping. Based on experts’ opinion solicited via ANP survey questionnaire, the ANP mathematical model was used to calculate the relative weights of the various flood influencing factors. The ArcGIS spatial analyst tools were used in generating flood susceptible zones. The study found zones that are very highly susceptible to flood (VHSF) and those highly susceptible to flood (HSF) covering 38.4% (30,924.6 ha) and 19.0% (15,341.1 ha) of the study area, respectively. The results were subjected to one-at-a-time (OAT) sensitivity analysis to verify their stability, where 6 out of the 22 flood scenarios correlated with the simulated spatial assessment of flood susceptibility. The findings were further validated using real-life flood incidences in the study area obtained from satellite images, which confirmed that most of the flooded areas were distributed over the VHSF and HSF zones. This integrated approach enables network model structuring, and reflects the interdependences among real-life flood influencing factors. This accurate identification of flood prone areas could serve as an early warning mechanism. The approach can be replicated in cities facing flood incidences in identifying areas susceptible to flooding for more effective flood disaster control. Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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Open AccessArticle
A New Empirical Approach to Calculating Flood Frequency in Ungauged Catchments: A Case Study of the Upper Vistula Basin, Poland
Water 2019, 11(3), 601; https://doi.org/10.3390/w11030601
Received: 5 March 2019 / Revised: 18 March 2019 / Accepted: 19 March 2019 / Published: 22 March 2019
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Abstract
The aim of the work was to develop a new empirical model for calculating the peak annual flows of a given frequency of occurrence (QT) in the ungauged catchments of the upper Vistula basin in Poland. The approach to the [...] Read more.
The aim of the work was to develop a new empirical model for calculating the peak annual flows of a given frequency of occurrence (QT) in the ungauged catchments of the upper Vistula basin in Poland. The approach to the regionalization of the catchment and the selection of the optimal form of the empirical model are indicated as a novelty of the proposed research. The research was carried out on the basis of observation series of peak annual flows (Qmax) for 41 catchments. The analysis was performed in the following steps: statistical verification of data; estimation of Qmax flows using kernel density estimation; determination of physiographic and meteorological characteristics affecting the Qmax flow volume; determination of the value of dimensionless quantiles for QT flow calculation in the upper Vistula basin; verification of the determined correlation for the calculation of QT flows in the upper Vistula basin. Based on the research we conducted, we found that the following factors have the greatest impact on the formation of flood flows in the upper Vistula basin: the size of catchment area; the height difference in the catchment area; the density of the river network; the soil imperviousness index; and the volume of normal annual precipitation. The verification procedure that we performed made it possible to conclude that the developed empirical model functions correctly. Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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Open AccessArticle
Seasonal Surface Runoff Characteristics in the Semiarid Region of Western Heilongjiang Province in Northeast China—A Case of the Alun River Basin
Water 2019, 11(3), 557; https://doi.org/10.3390/w11030557
Received: 15 February 2019 / Revised: 14 March 2019 / Accepted: 14 March 2019 / Published: 18 March 2019
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Abstract
Water resource issues are a challenging area of research in semiarid regions of the world. The objective of the current study was to reveal the main characteristics of seasonal surface runoff for the semiarid western Heilongjiang Province of China. The Alun River Basin, [...] Read more.
Water resource issues are a challenging area of research in semiarid regions of the world. The objective of the current study was to reveal the main characteristics of seasonal surface runoff for the semiarid western Heilongjiang Province of China. The Alun River Basin, which has hydrological and meteorological characteristics of the local region, was adopted as the study location. A distributed rainfall-runoff combined with snowmelt hydrological model was used to carry out the runoff calculation for the six years (2011–2016). The results indicated that: The mean annual runoff coefficient was 0.34; snowmelt runoff accounted for 2.2% of annual total runoff in 2011–2016; the main part of annual rainfall and runoff was concentrated in the rainy season from June to September, the proportions of rainfall and runoff in this period were 78% and 86% to that of the annual means of 2011–2016; the peak flow represents a decreased trend since 2013, and evidently decreased in 2015 and 2016; less annual precipitation complex with paddy field retention of rainwater and runoff led to the peak flow and annual runoff coefficient in 2016 were obviously lower than that of annual means of 2011–2016. The results are expected to provide the basis for rational development and utilization of surface runoff, and further researches on surface runoff and water resources of the semiarid western Heilongjiang Province of China. Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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Open AccessArticle
Comparative Study of Regional Frequency Analysis and Traditional At-Site Hydrological Frequency Analysis
Water 2019, 11(3), 486; https://doi.org/10.3390/w11030486
Received: 1 February 2019 / Revised: 4 March 2019 / Accepted: 4 March 2019 / Published: 7 March 2019
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Abstract
Hydrological frequency analysis plays an indispensable role in the construction of national flood control projects. This study selects the stations with the smallest and largest discordances in the nine homogeneous regions of Sichuan Province as the representative stations, and results obtained by regional [...] Read more.
Hydrological frequency analysis plays an indispensable role in the construction of national flood control projects. This study selects the stations with the smallest and largest discordances in the nine homogeneous regions of Sichuan Province as the representative stations, and results obtained by regional frequency analysis are compared with those obtained by traditional at-site hydrological frequency analysis. The results showed that the optimal frequency distribution of each representative station obtained by traditional at-site hydrological frequency analysis and the ones of corresponding homogeneous regions obtained by regional frequency analysis were not necessarily consistent, which was related to the site and homogeneous regions. At the same time, there were also differences between the fitting of the theoretical rainstorm frequency curve obtained by the two methods and the observation. In general, in each homogeneous region, the results obtained by regional frequency analysis and traditional at-site hydrological frequency analysis at the stations with the largest frequency analysis were quite different. The design values obtained by the two methods were also increasingly different with the increase of the return period. The study has specific reflections on the differences between regional frequency analysis and traditional at-site hydrological frequency analysis. Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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Open AccessArticle
Inclusion of Modified Snow Melting and Flood Processes in the SWAT Model
Water 2018, 10(12), 1715; https://doi.org/10.3390/w10121715
Received: 8 November 2018 / Revised: 19 November 2018 / Accepted: 20 November 2018 / Published: 23 November 2018
Cited by 2 | PDF Full-text (5203 KB) | HTML Full-text | XML Full-text
Abstract
Flooding, one of the most serious natural disasters, poses a significant threat to people’s lives and property. At present, the forecasting method uses simple snowmelt accumulation and has certain regional restrictions that limit the accuracy and timeliness of flood simulation and prediction. In [...] Read more.
Flooding, one of the most serious natural disasters, poses a significant threat to people’s lives and property. At present, the forecasting method uses simple snowmelt accumulation and has certain regional restrictions that limit the accuracy and timeliness of flood simulation and prediction. In this paper, the influence of accumulated temperature (AT) and maximum temperature (MT) on snow melting was considered in order to (1) reclassify the precipitation categories of the watershed using a separation algorithm of rain and snow that incorporates AT and MT, and (2) develop a new snow-melting process utilizing the algorithm in the Soil and Water Assessment Tool Model (SWAT) by considering the effects of AT and MT. The SWAT model was used to simulate snowmelt and flooding in the Tizinafu River Basin (TRB). We found that the modified SWAT model increased the value of the average flood peak flow by 43%, the snowmelt amounts increased by 45%, and the contribution of snowmelt to runoff increased from 44.7% to 54.07%. In comparison, we concluded the snowmelt contribution to runoff, flood peak performance, flood process simulation, model accuracy, and time accuracy. The new method provides a more accurate simulation technique for snowmelt floods and flood simulation. Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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Open AccessArticle
Analysis of Flood Risk of Urban Agglomeration Polders Using Multivariate Copula
Water 2018, 10(10), 1470; https://doi.org/10.3390/w10101470
Received: 13 September 2018 / Revised: 3 October 2018 / Accepted: 16 October 2018 / Published: 18 October 2018
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Abstract
Urban agglomeration polders (UAPs) are often used to control flooding in eastern China. The impacts of UAPs on individual flood events have been extensively examined, but how flood risks are influenced by UAPs is much less examined. This study aimed to explore a [...] Read more.
Urban agglomeration polders (UAPs) are often used to control flooding in eastern China. The impacts of UAPs on individual flood events have been extensively examined, but how flood risks are influenced by UAPs is much less examined. This study aimed to explore a three-dimensional joint distribution of annual flood volume, peak flow and water level to examine UAPs’ impact on flood risks based on hydrological simulations. The dependence between pairwise hydrological characteristics are measured by rank correlation coefficients and graphs. An Archimedean Copula is applied to model the dependence structure. This approach is applied to the Qinhuai River Basin where UAPs are used proactively for flood control. The result shows that the Frank Copula can better represent the dependence structure in the Qinhuai River Basin. UAPs increase risks of individual flood characteristics and integrated risks. UAPs have a relatively greater impact on water level than the other two flood characteristics. It is noted that the impact on flood risk levels off for greater floods. Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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Open AccessArticle
Groundwater Augmentation through the Site Selection of Floodwater Spreading Using a Data Mining Approach (Case study: Mashhad Plain, Iran)
Water 2018, 10(10), 1405; https://doi.org/10.3390/w10101405
Received: 22 August 2018 / Revised: 2 October 2018 / Accepted: 2 October 2018 / Published: 10 October 2018
Cited by 4 | PDF Full-text (3709 KB) | HTML Full-text | XML Full-text
Abstract
It is a well-known fact that sustainable development goals are difficult to achieve without a proper water resources management strategy. This study tries to implement some state-of-the-art statistical and data mining models i.e., weights-of-evidence (WoE), boosted regression trees (BRT), and classification and regression [...] Read more.
It is a well-known fact that sustainable development goals are difficult to achieve without a proper water resources management strategy. This study tries to implement some state-of-the-art statistical and data mining models i.e., weights-of-evidence (WoE), boosted regression trees (BRT), and classification and regression tree (CART) to identify suitable areas for artificial recharge through floodwater spreading (FWS). At first, suitable areas for the FWS project were identified in a basin in north-eastern Iran based on the national guidelines and a literature survey. Using the same methodology, an identical number of FWS unsuitable areas were also determined. Afterward, a set of different FWS conditioning factors were selected for modeling FWS suitability. The models were applied using 70% of the suitable and unsuitable locations and validated with the rest of the input data (i.e., 30%). Finally, a receiver operating characteristics (ROC) curve was plotted to compare the produced FWS suitability maps. The findings depicted acceptable performance of the BRT, CART, and WoE for FWS suitability mapping with an area under the ROC curves of 92, 87.5, and 81.6%, respectively. Among the considered variables, transmissivity, distance from rivers, aquifer thickness, and electrical conductivity were determined as the most important contributors in the modeling. FWS suitability maps produced by the proposed method in this study could be used as a guideline for water resource managers to control flood damage and obtain new sources of groundwater. This methodology could be easily replicated to produce FWS suitability maps in other regions with similar hydrogeological conditions. Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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