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 and Hydrogeology".

Deadline for manuscript submissions: closed (31 December 2019).

Special Issue Editors

Prof. Dr. Ataur Rahman
Website
Guest Editor
Civil and Environmental Engineering, School of Computing, Engineering and Mathematics, University of Western Sydney, Locked Bag 1797, Penrith, NSW 2751, Australia
Interests: hydrology; rainfall runoff; rainwater harvesting; flood; water demand forecasting; water sensitive urban design; water quality
Special Issues and Collections in MDPI journals
Prof. Dr. Taha B.M.J. Ouarda
Website
Guest Editor
Center Water Earth Environment, National Institute of Scientific Research, Quebec, Canada
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 (17 papers)

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Research

Open AccessArticle
Flood Prediction and Uncertainty Estimation Using Deep Learning
Water 2020, 12(3), 884; https://doi.org/10.3390/w12030884 - 21 Mar 2020
Cited by 1
Abstract
Floods are a complex phenomenon that are difficult to predict because of their non-linear and dynamic nature. Therefore, flood prediction has been a key research topic in the field of hydrology. Various researchers have approached this problem using different techniques ranging from physical [...] Read more.
Floods are a complex phenomenon that are difficult to predict because of their non-linear and dynamic nature. Therefore, flood prediction has been a key research topic in the field of hydrology. Various researchers have approached this problem using different techniques ranging from physical models to image processing, but the accuracy and time steps are not sufficient for all applications. This study explores deep learning techniques for predicting gauge height and evaluating the associated uncertainty. Gauge height data for the Meramec River in Valley Park, Missouri was used to develop and validate the model. It was found that the deep learning model was more accurate than the physical and statistical models currently in use while providing information in 15 minute increments rather than six hour increments. It was also found that the use of data sub-selection for regularization in deep learning is preferred to dropout. These results make it possible to provide more accurate and timely flood prediction for a wide variety of applications, including transportation systems. Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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Open AccessArticle
Forecasting of Landslides Using Rainfall Severity and Soil Wetness: A Probabilistic Approach for Darjeeling Himalayas
Water 2020, 12(3), 804; https://doi.org/10.3390/w12030804 - 13 Mar 2020
Cited by 6
Abstract
Rainfall induced landslides are creating havoc in hilly areas and have become an important concern for the stakeholders and public. Many approaches have been proposed to derive rainfall thresholds to identify the critical conditions that can initiate landslides. Most of the empirical methods [...] Read more.
Rainfall induced landslides are creating havoc in hilly areas and have become an important concern for the stakeholders and public. Many approaches have been proposed to derive rainfall thresholds to identify the critical conditions that can initiate landslides. Most of the empirical methods are defined in such a way that it does not depend upon any of the in situ conditions. Soil moisture plays a key role in the initiation of landslides as the pore pressure increase and loss in shear strength of soil result in sliding of soil mass, which in turn are termed as landslides. Hence this study focuses on a Bayesian analysis, to calculate the probability of occurrence of landslides, based on different combinations of severity of rainfall and antecedent soil moisture content. A hydrological model, called Système Hydrologique Européen Transport (SHETRAN) is used for the simulation of soil moisture during the study period and event rainfall-duration (ED) thresholds of various exceedance probabilities were used to characterize the severity of a rainfall event. The approach was used to define two-dimensional Bayesian probabilities for occurrence of landslides in Kalimpong (India), which is a highly landslide susceptible zone in the Darjeeling Himalayas. The study proves the applicability of SHETRAN model for simulating moisture conditions for the study area and delivers an effective approach to enhance the prediction capability of empirical thresholds defined for the region. Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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Open AccessArticle
Application of Principal Component Analysis and Cluster Analysis in Regional Flood Frequency Analysis: A Case Study in New South Wales, Australia
Water 2020, 12(3), 781; https://doi.org/10.3390/w12030781 - 12 Mar 2020
Cited by 1
Abstract
This paper examines the applicability of principal component analysis (PCA) and cluster analysis in regional flood frequency analysis. A total of 88 sites in New South Wales, Australia are adopted. Quantile regression technique (QRT) is integrated with the PCA to estimate the flood [...] Read more.
This paper examines the applicability of principal component analysis (PCA) and cluster analysis in regional flood frequency analysis. A total of 88 sites in New South Wales, Australia are adopted. Quantile regression technique (QRT) is integrated with the PCA to estimate the flood quantiles. A total of eight catchment characteristics are selected as predictor variables. A leave-one-out validation is applied to determine the efficiency of the developed statistical models using an ensemble of evaluation diagnostics. It is found that the PCA with QRT model does not perform well, whereas cluster/group formed with smaller sized catchments performs better (with a median relative error values ranging from 22% to 37%) than other clusters/groups. No linkage is found between the degree of heterogeneity in the clusters/groups and precision of flood quantile prediction by the multiple linear regression technique. Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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Open AccessFeature PaperArticle
Geospatial Modelling of Watershed Peak Flood Discharge in Selangor, Malaysia
Water 2019, 11(12), 2490; https://doi.org/10.3390/w11122490 - 26 Nov 2019
Cited by 2
Abstract
Conservative peak flood discharge estimation methods such as the rational method do not take into account the soil infiltration of the precipitation, thus leading to inaccurate estimations of peak discharges during storm events. The accuracy of estimated peak flood discharge is crucial in [...] Read more.
Conservative peak flood discharge estimation methods such as the rational method do not take into account the soil infiltration of the precipitation, thus leading to inaccurate estimations of peak discharges during storm events. The accuracy of estimated peak flood discharge is crucial in designing a drainage system that has the capacity to channel runoffs during a storm event, especially cloudbursts and in the analysis of flood prevention and mitigation. The aim of this study was to model the peak flood discharges of each sub-watershed in Selangor using a geographic information system (GIS). The geospatial modelling integrated the watershed terrain model, the developed Soil Conservation Service Curve Cumber (SCS-CN) and precipitation to develop an equation for estimation of peak flood discharge. Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS) was used again to simulate the rainfall-runoff based on the Clark-unit hydrograph to validate the modelled estimation of peak flood discharge. The estimated peak flood discharge showed a coefficient of determination, r2 of 0.9445, when compared with the runoff simulation of the Clark-unit hydrograph. Both the results of the geospatial modelling and the developed equation suggest that the peak flood discharge of a sub-watershed during a storm event has a positive relationship with the watershed area, precipitation and Curve Number (CN), which takes into account the soil bulk density and land-use of the studied area, Selangor in Malaysia. The findings of the study present a comparable and holistic approach to the estimation of peak flood discharge in a watershed which can be in the absence of a hydrodynamic simulation model. 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-Prone Area Assessment Using GIS-Based Multi-Criteria Analysis: A Case Study in Davao Oriental, Philippines
Water 2019, 11(11), 2203; https://doi.org/10.3390/w11112203 - 23 Oct 2019
Cited by 7
Abstract
Flooding is one of the major destructive natural disasters in Davao Oriental, Philippines, and results primarily from a high incidence of typhoons and heavy rainfalls. The main objective of this study was to identify flood-prone risk areas by mapping them based on the [...] Read more.
Flooding is one of the major destructive natural disasters in Davao Oriental, Philippines, and results primarily from a high incidence of typhoons and heavy rainfalls. The main objective of this study was to identify flood-prone risk areas by mapping them based on the integration of multiple indicators, including rainfall, slope, elevation, drainage density, soil type, distance to the main channel and population density. For this purpose, a GIS-based flood risk spatial assessment was conducted by using analytic hierarchy process (AHP), weights by rank (WR) and ratio weighting (RW) frameworks to determine the relative importance of each indicator against another in the province of Davao Oriental. The resulting flood-prone areas by the three methods are validated by comparing with the estimated flood map based on ground truthing points from a field survey. The comparison results show that AHP is the most appropriate method among them to assess flood hazard. The result of the AHP flood risk map shows that 95.99% (5451.27 km2) of Davao Oriental is under low and moderate flood risk. The high and very high flood risk area covers approximately 3.39% (192.52 km2) of the province, primarily in the coastal areas. Thirty-one out of the one hundred eighty-three (31/183) barangays (towns) are at a high to very high risk of flooding at current climate, calling for the immediate attention of decision-makers to develop mitigation strategies for the future occurrence of flooding in Davao Oriental. Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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Open AccessArticle
Hydrodynamic-Based Numerical Assessment of Flood Risk of Tamuín City, Mexico, by Tampaón River: A Forecast Considering Climate Change
Water 2019, 11(9), 1867; https://doi.org/10.3390/w11091867 - 08 Sep 2019
Abstract
Climate change has unchained several natural extreme phenomena, including a major frequency and intensity of flooding episodes. From these, the ones of greatest importance are those which endanger human settlements as well as socioeconomic activities. This is the case of Tamuín city, settled [...] Read more.
Climate change has unchained several natural extreme phenomena, including a major frequency and intensity of flooding episodes. From these, the ones of greatest importance are those which endanger human settlements as well as socioeconomic activities. This is the case of Tamuín city, settled in the shore of Tampaón River, in Mexico. In this work, we performed a detailed numerical modelling of the hydrodynamics of the zone, considering in situ topographic and bathymetric data as well as hydrodynamic parameters. Severe rainfall scenarios were simulated in order to determine the zones which are prone to flooding, as well as the potential periods of time between the beginning of the rainfall up to the flooding, considering the potential effects of climate change in the precipitation rate. The outcome of this research will help local governments undertake preventive actions to reinforce the identified risky zones, thus providing an adequate protection of rural and urban zones, as well as their inhabitants and their economical activities from current and future floods, considering potential climate change effects. Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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Open AccessArticle
Examination of Changes in Flood Data in Australia
Water 2019, 11(8), 1734; https://doi.org/10.3390/w11081734 - 20 Aug 2019
Cited by 3
Abstract
This study performs a simultaneous evaluation of gradual and abrupt changes in Australian annual maximum (AM) flood data using a modified Mann–Kendall and Pettitt change-point detection test. The results show that AM flood data in eastern Australia is dominated by downward trends. Depending [...] Read more.
This study performs a simultaneous evaluation of gradual and abrupt changes in Australian annual maximum (AM) flood data using a modified Mann–Kendall and Pettitt change-point detection test. The results show that AM flood data in eastern Australia is dominated by downward trends. Depending on the significance level and study period under consideration, about 8% to 33% of stations are characterised by significant trends, where over 85% of detected significant trends are downward. Furthermore, the change-point analysis shows that the percentages of stations experiencing one abrupt change in the mean or in the direction of the trend are in the range of 8% to 33%, of which over 50% occurred in 1991, with a mode in 1995. Prominent resemblance between the monotonic trend and change-point analysis results is also noticed, in which a negative shift in the mean is observed at catchments that exhibited downward trends, and a positive shift in the mean is observed in the case of upward trends. Trend analysis of the segmented AM flood series based on their corresponding date indicates an absence of a significant trend, which may be attributed to the false detection of trends when the AM flood data are characterised by a shift in its mean. Full article
(This article belongs to the Special Issue Flood Modelling: Regional Flood Estimation and GIS Based Techniques)
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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 - 23 May 2019
Cited by 1
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 - 10 May 2019
Cited by 5
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 - 01 Apr 2019
Cited by 2
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 - 25 Mar 2019
Cited by 25
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 - 22 Mar 2019
Cited by 7
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 - 18 Mar 2019
Cited by 1
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 - 07 Mar 2019
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 - 23 Nov 2018
Cited by 6
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 - 18 Oct 2018
Cited by 2
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 - 10 Oct 2018
Cited by 13
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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