Flash Floods: Forecasting, Monitoring and Mitigation Strategies

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

Deadline for manuscript submissions: closed (20 November 2022) | Viewed by 30385

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors


E-Mail Website
Guest Editor
State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, China
Interests: hydraulics and river dynamics; water–sediment disaster; flash flood; forecasting and early warning; hydrological–hydrodynamic modeling
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Graduate School of Engineering, Université Côte d'Azur, Nice, France
Interests: urban water management; hydroinformatics; deterministic modeling; real-time simulation; DSS; resilience
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
China Institute of Water Resources and Hydropower Research, Beijing, China
Interests: flash flood prevention and control; hydrology and hydraulic modeling; remote science; flood risk management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent decades, flash floods have become one of the major natural disasters and show a continuously increasing trend at the worldwide scale. Flash flood disaster events often occur due to the complex influences of extreme-intensity rainfall events, special geological and topographical conditions, and obviously human activities. The magnitude of the damages associated with flash floods requires forecasting and monitoring strategies in order to understand the vulnerability factors, analyze the mechanisms of flash floods, and mitigate disasters. Research efforts are needed to improve early warning mechanisms, risk control, and hazard prevention that could obviously aim at a reduction in casualties, social impacts, and economic losses. New technical approaches such as surface monitoring and combined hydrologic–hydrodynamic models are coming up and are offering useful information for field managers.

Therefore, we kindly invite you to submit to this Special Issue your work results and contributions on flash flood events, new technologies, and novel approaches to better understand those extreme processes. The potential contributions could include but are not limited to:

  • Major flash flood disaster event analysis;
  • Key factors for flash floods and monitoring strategies;
  • Field observations for flash flood processes;
  • Modeling and forecasting of flash flood events;
  • Risk assessment for flash floods;
  • Prevention and mitigation measures for flash floods.

Submissions of both novel methodology and technological contributions as well as case studies for major flash flood regimes in different regions are strongly encouraged.

Prof. Dr. Xiekang Wang
Prof. Dr. Philippe Gourbesville
Prof. Dr. Changjun Liu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • hydrology
  • flash flood
  • monitoring techniques
  • modeling and forecasting
  • risk assessment
  • prevention and mitigation measures

Published Papers (13 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Editorial

Jump to: Research

5 pages, 187 KiB  
Editorial
Flash Floods: Forecasting, Monitoring and Mitigation Strategies
by Xiekang Wang, Philippe Gourbesville and Changjun Liu
Water 2023, 15(9), 1700; https://doi.org/10.3390/w15091700 - 27 Apr 2023
Cited by 3 | Viewed by 2801
Abstract
In recent decades, flash floods have become a major natural disaster and show a continuously increasing trend on a worldwide scale [...] Full article
(This article belongs to the Special Issue Flash Floods: Forecasting, Monitoring and Mitigation Strategies)

Research

Jump to: Editorial

17 pages, 4311 KiB  
Article
Research on Parameter Regionalization of Distributed Hydrological Model Based on Machine Learning
by Wenchuan Wang, Yanwei Zhao, Yong Tu, Rui Dong, Qiang Ma and Changjun Liu
Water 2023, 15(3), 518; https://doi.org/10.3390/w15030518 - 28 Jan 2023
Cited by 9 | Viewed by 2450
Abstract
In the past decade, more than 300 people have died per year on average due to mountain torrents in China. Mountain torrents mostly occur in ungauged small and medium-sized catchments, so it is difficult to maintain high accuracy of flood prediction. In order [...] Read more.
In the past decade, more than 300 people have died per year on average due to mountain torrents in China. Mountain torrents mostly occur in ungauged small and medium-sized catchments, so it is difficult to maintain high accuracy of flood prediction. In order to solve the problem of the low accuracy of flood simulation in the ungauged areas, this paper studies the influence of different methods on the parameter regionalization of distributed hydrological model parameters in hilly areas of Hunan Province. According to the terrain, landform, soil and land use characteristics of each catchment, we use Shortest Distance, Attribute Similarity, Support Vector Regression, Generative Adversarial Networks, Classification and Regression Tree and Random Forest methods to create parameter regionalization schemes. In total, 426 floods of 25 catchments are selected to calibrate the model parameters, and 136 floods of 8 catchments are used for verification. The results showed that the average values of the Nash–Sutcliffe coefficients of each scheme were 0.58, 0.64, 0.60, 0.66, 0.61 and 0.68, and the worst values were 0.27, 0.31, 0.25, 0.43, 0.35 and 0.59. The random forest model is the most stable solution and significantly outperforms other methods. Using the random forest model to regionalize parameters can improve the accuracy of flood simulation in ungauged areas, which is of great significance for flash flood forecasting and early warning. Full article
(This article belongs to the Special Issue Flash Floods: Forecasting, Monitoring and Mitigation Strategies)
Show Figures

Figure 1

26 pages, 2641 KiB  
Article
Prediction of the Periglacial Debris Flow in Southeast Tibet Based on Imbalanced Small Sample Data
by Jun Du, Hong-ya Zhang, Kai-heng Hu, Lin Wang and Lin-yao Dong
Water 2023, 15(2), 310; https://doi.org/10.3390/w15020310 - 11 Jan 2023
Cited by 4 | Viewed by 1624
Abstract
Using data sourced from 15 periglacial debris flow gullies in the Parlung Zangbo Basin of southeast Tibet, the importance of 26 potential indicators to the development of debris flows was analyzed quantitatively. Three machine learning approaches combined with the borderline resampling technique were [...] Read more.
Using data sourced from 15 periglacial debris flow gullies in the Parlung Zangbo Basin of southeast Tibet, the importance of 26 potential indicators to the development of debris flows was analyzed quantitatively. Three machine learning approaches combined with the borderline resampling technique were introduced for predicting debris flow occurrences, and several scenarios were tested and compared. The results indicated that temperature and precipitation, as well as vegetation coverage, were closely related to the development of periglacial debris flow in the study area. Based on seven selected indicators, the Random Forest-based model, with its weighted recall rate and Area Under the ROC Curve (AUC) greater than 0.76 and 0.77, respectively, performed the best in predicting debris flow events. Scenario tests indicated that the resampling was necessary to the improvement of model performance in the context of data scarcity. The new understandings obtained may enrich existing knowledge of the effects of main factors on periglacial debris flow development, and the modeling method could be promoted as a prediction scheme of regional precipitation-related debris flow for further research. Full article
(This article belongs to the Special Issue Flash Floods: Forecasting, Monitoring and Mitigation Strategies)
Show Figures

Figure 1

15 pages, 6520 KiB  
Article
Model-Based Mechanism Analysis of “7.20” Flash Flood Disaster in Wangzongdian River Basin
by Sijia Hao, Wenchuan Wang, Qiang Ma, Changzhi Li, Lei Wen, Jiyang Tian and Changjun Liu
Water 2023, 15(2), 304; https://doi.org/10.3390/w15020304 - 11 Jan 2023
Cited by 4 | Viewed by 1689
Abstract
With digital information technology based on limited data, disaster simulation review is an important guideline for analyzing disaster mechanisms, planning post-disaster reconstruction, and improving defense capability. Taking the “7.20” flash flood in the Wangzongdian river basin as a research area, a hydrological-hydrodynamic model [...] Read more.
With digital information technology based on limited data, disaster simulation review is an important guideline for analyzing disaster mechanisms, planning post-disaster reconstruction, and improving defense capability. Taking the “7.20” flash flood in the Wangzongdian river basin as a research area, a hydrological-hydrodynamic model was established using limited measured data. The results showed that the extreme rainstorm caused flooding in mountainous areas and the collapse of subgrade water damming, and the high-level flood quickly flowed into Wangzongdian Village in a short distance, which was the main cause of this serious disaster. Considering the collapse due to the congestion of the upstream bridge, the simulated flood flow in Wangzongdian Village reached 782 m3/s, which was basically consistent with the post-disaster survey results, with a relative error of only +8%. The modeling strategy proposed in this paper is applicable in the review of sudden heavy rainstorms and flash floods and can provide technical guidance for future flash flood simulation review analysis in other areas. Full article
(This article belongs to the Special Issue Flash Floods: Forecasting, Monitoring and Mitigation Strategies)
Show Figures

Figure 1

16 pages, 36285 KiB  
Article
Application of a Regionalization Method for Estimating Flash Floods: Cuautepec Basin, Mexico
by Maritza Arganis, Margarita Preciado, Faustino De Luna, Liliana Cruz, Ramón Domínguez and Olaf Santana
Water 2023, 15(2), 303; https://doi.org/10.3390/w15020303 - 11 Jan 2023
Cited by 1 | Viewed by 2129
Abstract
A rainfall regionalization method based on variation coefficient was applied with a variant in the construction of flash flood hyetographs with several return periods using the flash flood shape of the historical event that occurred in September 2021 in the Tlalnepantla River basin, [...] Read more.
A rainfall regionalization method based on variation coefficient was applied with a variant in the construction of flash flood hyetographs with several return periods using the flash flood shape of the historical event that occurred in September 2021 in the Tlalnepantla River basin, Mexico, that caused severe damage to population and its infrastructure in a few hours. The historical flash flood was simulated with a semi-distributed model in the free software HEC-HMS in order to obtain the outflow hydrograph, and the flood plains were obtained with Iber and Hec-Ras 2d software that simulate free surface flow with a two-dimensional analysis. With photographs of the site, it was possible to locate traces of water that were contrasted with they calculated depths; they were concordant. Synthetic design storms were then simulated to estimate their potential consequences on the site. Full article
(This article belongs to the Special Issue Flash Floods: Forecasting, Monitoring and Mitigation Strategies)
Show Figures

Figure 1

16 pages, 6699 KiB  
Article
Experimental Study on Gully Erosion Characteristics of Mountain Torrent Debris Flow in a Strong Earthquake Area
by Jiqin Zhang, Dengze Luo, Hongtao Li, Liang Pei and Qiang Yao
Water 2023, 15(2), 283; https://doi.org/10.3390/w15020283 - 9 Jan 2023
Cited by 2 | Viewed by 2027
Abstract
In recent years, as the frequency of debris flow outbreak in strong earthquake areas has increased and the scale has been expanding, in order to explore the erosion characteristics of debris flow, a lateral erosion flume model experimental device has been designed, and [...] Read more.
In recent years, as the frequency of debris flow outbreak in strong earthquake areas has increased and the scale has been expanding, in order to explore the erosion characteristics of debris flow, a lateral erosion flume model experimental device has been designed, and 18 groups of incomplete orthogonal experiments have been carried out, with a unit weight of debris flow of 1.6~2.0 g/cm3, a content of fine particles in the accumulation of 0~28.82%, and a longitudinal slope gradient of the gully of 8°~20° as variables. The results show that the erosion width, erosion depth, and erosion volume decrease with the increase in fluid bulk density and increase with the increase in gully slope. When the longitudinal slope of the gully was 16°, the sediment with 11.40% fine particles had the strongest erosion effect, indicating that more or less fine particles are not conducive to the occurrence of lateral erosion of the gully. Finally, through multi-factor variance analysis, it was found that the order of the three factors on the gully lateral erosion degree from strong to weak is: debris flow unit weight, gully slope, and accumulation grading. The analysis results further showed that the unit weight of debris flow has the greatest impact on the erosion degree of the side slope, which is consistent with the experimental results. The research results have important reference significance for revealing the mechanism of lateral erosion and improving the level of debris flow disaster prevention in strong earthquake areas. Full article
(This article belongs to the Special Issue Flash Floods: Forecasting, Monitoring and Mitigation Strategies)
Show Figures

Figure 1

14 pages, 1499 KiB  
Article
Impacts of Grass Coverage and Arrangement Patterns on Runoff and Sediment Yield in Slope-Gully System of the Loess Plateau, China
by Wenfeng Ding, Xiekang Wang, Guanhua Zhang, Xi Meng and Zhiwei Ye
Water 2023, 15(1), 133; https://doi.org/10.3390/w15010133 - 30 Dec 2022
Cited by 2 | Viewed by 2031
Abstract
Both vegetation coverage rates and arrangement patterns have important influences on erosion. Very little previous research focuses on the impacts of spatial vegetation distribution patterns on erosion. The slope-gully system was taken as the research object, which is composed of a 5.0 m [...] Read more.
Both vegetation coverage rates and arrangement patterns have important influences on erosion. Very little previous research focuses on the impacts of spatial vegetation distribution patterns on erosion. The slope-gully system was taken as the research object, which is composed of a 5.0 m long hillslope with a slope gradient of 20° and a 3.0 m long gully slope with a gradient of 50°. A series of scouring experiments with two inflow discharges (3.2 L min−1, 5.2 L min−1) was carried out. The effects of the flow discharges, spatial grass arrangement patterns (US, MS, and DS represent the presence of grass covering on up-hillslope, middle-hillslope, and down-hillslope, respectively) and grass coverage rates (0%, 30%, 50%, 70%, and 90%) on runoff and sediment were studied in this paper. The results indicated that either runoff or sediment yielding was significantly decreased with the grass coverage rates increasing and with the variation of grass arrangement patterns on a hillslope. While grass coverage had more effectiveness in controlling erosion compared with runoff reduction, and DS can control erosion more effectively than US and MS erosion controlling. For the gully slope, erosion significantly increased with the grass coverage rates increasing no matter how the grass arrangement patterns on the hillslope. Therefore, both different grass coverage and different grass arrangement patterns have an influence on erosion processes; any research that only takes care of the single factor mentioned above is not enough to reveal the effects of grass on erosion. In the process of erosion control in the Loess Plateau, taking effective measures both on the hillslope and gully slope will be effective methods of reducing soil erosion. Full article
(This article belongs to the Special Issue Flash Floods: Forecasting, Monitoring and Mitigation Strategies)
Show Figures

Figure 1

17 pages, 4452 KiB  
Article
Flash Flood Susceptibility Mapping in Sinai, Egypt Using Hydromorphic Data, Principal Component Analysis and Logistic Regression
by Mustafa El-Rawy, Wael M. Elsadek and Florimond De Smedt
Water 2022, 14(15), 2434; https://doi.org/10.3390/w14152434 - 6 Aug 2022
Cited by 19 | Viewed by 2695
Abstract
Flash floods in the Sinai often cause significant damage to infrastructure and even loss of life. In this study, the susceptibility to flash flooding is determined using hydro-morphometric characteristics of the catchments. Basins and their hydro-morphometric features are derived from a digital elevation [...] Read more.
Flash floods in the Sinai often cause significant damage to infrastructure and even loss of life. In this study, the susceptibility to flash flooding is determined using hydro-morphometric characteristics of the catchments. Basins and their hydro-morphometric features are derived from a digital elevation model from NASA Earthdata. Principal component analysis is used to identify principal components with a clear physical meaning that explains most of the variation in the data. The probability of flash flooding is estimated by logistic regression using the principal components as predictors and by fitting the model to flash flood observations. The model prediction results are cross validated. The logistic model is used to classify Sinai basins into four classes: low, moderate, high and very high susceptibility to flash flooding. The map indicating the susceptibility to flash flooding in Sinai shows that the large basins in the mountain ranges of the southern Sinai have a very high susceptibility for flash flooding, several basins in the southwest Sinai have a high or moderate susceptibility to flash flooding, some sub-basins of wadi El-Arish in the center have a high susceptibility to flash flooding, while smaller to medium-sized basins in flatter areas in the center and north usually have a moderate or low susceptibility to flash flooding. These results are consistent with observations of flash floods that occurred in different regions of the Sinai and with the findings or predictions of other studies. Full article
(This article belongs to the Special Issue Flash Floods: Forecasting, Monitoring and Mitigation Strategies)
Show Figures

Figure 1

15 pages, 10567 KiB  
Article
Driving Effects and Spatial-Temporal Variations in Economic Losses Due to Flood Disasters in China
by Zhixiong Zhang, Qing Li, Changjun Liu, Liuqian Ding, Qiang Ma and Yao Chen
Water 2022, 14(14), 2266; https://doi.org/10.3390/w14142266 - 20 Jul 2022
Cited by 3 | Viewed by 2122
Abstract
The economic loss caused by frequent flood disasters poses a great threat to China’s economic prosperity. This study analyzes the driving factors of flood-related economic losses in China. We used the extended Kaya identity to establish a factor decomposition model and the logarithmic [...] Read more.
The economic loss caused by frequent flood disasters poses a great threat to China’s economic prosperity. This study analyzes the driving factors of flood-related economic losses in China. We used the extended Kaya identity to establish a factor decomposition model and the logarithmic mean Divisia index decomposition method to identify five flood-related driving effects for economic loss: demographic effect, economic effect, flash flood disaster control effect, capital efficiency effect, and loss-rainfall effect. Among these factors, the flash flood disaster control effect most obviously reduced flood-related economic losses. Considering the weak foundation of flash flood disaster prevention and control in China, non-engineering measures for flash flood prevention and control have been implemented since 2010, achieving remarkable results. Influenced by these measures, the loss-rainfall effect also showed reduction output characteristics. The demographic, economic, and capital efficiency effects showed incremental effect characteristics. China’s current economic growth leads to an increase in flood control pressure, thus explaining the incremental effect of the economic effect. This study discusses the relationship between flood-related economic loss and flash flood disaster prevention and control in China, adding value for the adjustment and formulation of future flood disaster prevention policies. Full article
(This article belongs to the Special Issue Flash Floods: Forecasting, Monitoring and Mitigation Strategies)
Show Figures

Figure 1

12 pages, 5323 KiB  
Article
Analysis on the Disaster Mechanism of “8.12” Flash Flood in Liulin River Basin
by Sijia Hao, Wenchuan Wang, Qiang Ma, Changzhi Li, Lei Wen, Jiyang Tian and Changjun Liu
Water 2022, 14(13), 2017; https://doi.org/10.3390/w14132017 - 24 Jun 2022
Cited by 2 | Viewed by 1790
Abstract
Hubei province is located in the center of China with 56% total area characterized with mountainous area. Thus, flash flood caused by extreme rainfall has become one of the significant obstacles that highly affect the social and economic development of the province. In [...] Read more.
Hubei province is located in the center of China with 56% total area characterized with mountainous area. Thus, flash flood caused by extreme rainfall has become one of the significant obstacles that highly affect the social and economic development of the province. In order to scientifically understand the mechanism of flash flood disasters and provide technological support to the local flood prevention and control work, the IWHR designed and developed a new distributed hydrological model named China-FFMS that can simulate the evolution of natural disasters and make an assessment by setting the flood water sources in line with the flow discharge. The FFMS was further applied to simulate the 8.12 flash flood disaster that occurred in the Liulin county of Hubei province on 12 August (“8.12”) and fed by the data collected from the national flash flood disaster investigation and assessment. The calculated peak flow was 666.22 m3/s with an error of +13% compared with postdisaster investigation data (589 m3/s). The results showed that using a multisourced modelling approach, e.g., mixing spatiotemporal variables and sources, to simulate the flash flood process was able to accurately reproduce the flood process and the consistence of the flow discharge, thereby explaining the underlying reason of the disaster formation and evolution. Regarding the case of the Liulin county, the main factor leading to the disaster was the overlapped peak flow where the Dunne flood peak of three different tributaries from the upper reach met together at the same time. Moreover, the peak flow of the Lianhua river at the downstream of Liulin County also arrived at the same time as the upstream peak, which obstructed the flood progress and increased the damage of the disaster. According to the analysis, several suggestions and recommendations are proposed such as the improvement of the forecast and early warning system of the upstream areas, the optimization of the current flood defense plan, and the enhancement of the residents’ awareness of flash flood disasters. Full article
(This article belongs to the Special Issue Flash Floods: Forecasting, Monitoring and Mitigation Strategies)
Show Figures

Figure 1

23 pages, 13743 KiB  
Article
Numerical Investigation on a Flash Flood Disaster in Streams with Confluence and Bifurcation
by Qingyuan Yang, Xiekang Wang, Yi Sun, Wengang Duan and Shan Xie
Water 2022, 14(10), 1646; https://doi.org/10.3390/w14101646 - 21 May 2022
Cited by 4 | Viewed by 1658
Abstract
On 20 August 2019, a flash flood occurred in Sanjiang Town, Sichuan, China, and caused great damage to people living there. The town lies at the junction of five streams, with streams A, B, and C combining at the town and further dividing [...] Read more.
On 20 August 2019, a flash flood occurred in Sanjiang Town, Sichuan, China, and caused great damage to people living there. The town lies at the junction of five streams, with streams A, B, and C combining at the town and further dividing into streams D and E. The slope of streams A, B, and C is about 3~5%, while the slope of streams D and E is around 0.3%. The Sanjiang Town actually lies in the transition from supercritical slope to subcritical slope. During the flood, huge sediments were released to streams A, B, and C, and further transported to stream E. Due to the rapid change of velocity, only few sediments deposited at the supercritical slope parts of the stream, while plenty of them sedimented at the streams with subcritical slope. In order to simulate the flood with a hydrodynamic model, a field investigation was carried out to collect high DEM (digital elevation model) data, flood marks, sediment grading, etc., after the flood. The discharge curve of the flood was also obtained by the hydrometric station near Sanjiang Town. For the inlet sediment concentrations of streams A, B, and C, we made a series of assumptions and utilized the case which best fits the flood marks to set the inlet sediment concentration. Based on these data, we adopted a depth-averaged two-dimensional hydrodynamic model coupled with a sediment transport model to simulate the flash flood accident. The results revealed that the flash flood enlargement in confluence streams is mainly induced by the inflows, and the flash flood enlargement in bifurcation streams is largely affected by the sediment deposition. The bifurcation of flows can decrease the peak discharge of each branch, but may increase the flooded area near the streams. Flow in the supercritical slope runs at a very fast velocity, and seldom deposits sediment in the steep channel. Meanwhile, most sediment is transported to the streams with flat hydraulic slopes. Due to the functioning of the reservoir, the transition region from supercritical slope to subcritical slope has a much larger probability of being submerged during the flood. Full article
(This article belongs to the Special Issue Flash Floods: Forecasting, Monitoring and Mitigation Strategies)
Show Figures

Figure 1

22 pages, 3563 KiB  
Article
Assessment of an Alternative Climate Product for Hydrological Modeling: A Case Study of the Danjiang River Basin, China
by Yiwei Guo, Wenfeng Ding, Wentao Xu, Xiudi Zhu, Xiekang Wang and Wenjian Tang
Water 2022, 14(7), 1105; https://doi.org/10.3390/w14071105 - 30 Mar 2022
Cited by 5 | Viewed by 2308
Abstract
Precipitation has been recognized as the most critical meteorological parameter in hydrological studies. Recent developments in space technology provide cost-effective alternative ground-based observations to simulate the hydrological process. Here, this paper aims to evaluate the performance of satellite-based datasets in the hydrological modeling [...] Read more.
Precipitation has been recognized as the most critical meteorological parameter in hydrological studies. Recent developments in space technology provide cost-effective alternative ground-based observations to simulate the hydrological process. Here, this paper aims to evaluate the performance of satellite-based datasets in the hydrological modeling of a sensitive area in terms of water quality and safety watershed. Three precipitation products, i.e., rain gauge observations (RO), the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS), and Tropical Rainfall Measuring Mission Multi-satellite (TRMM) products, were used to develop the Soil and Water Assessment Tool (SWAT) model to simulate the streamflow in the Danjiang River Basin (DRB). The results show that: (1) these three precipitation products have a similar performance with regard to monthly time scale compared with the daily scale; (2) CMADS and TRMM performed better than RO in the runoff simulations. CMADS is a more accurate dataset when combined with satellite-based and ground-based data; (3) the results indicate that the CMADS dataset provides reliable results on both monthly and daily scales, and CMADS is a possible alternative climate product for developing a SWAT model for the DRB. This study is expected to serve as a reference for choosing the precipitation products for watersheds similar to DRB where the rain gauge data are limited. Full article
(This article belongs to the Special Issue Flash Floods: Forecasting, Monitoring and Mitigation Strategies)
Show Figures

Figure 1

19 pages, 6471 KiB  
Communication
An Impacts-Based Flood Decision Support System for a Tropical Pacific Island Catchment with Short Warnings Lead Time
by Shaun Williams, James Griffiths, Bernard Miville, Emarosa Romeo, Mafutaga Leiofi, Michael O’Driscoll, Malaki Iakopo, Silipa Mulitalo, Josephina Chan Ting, Ryan Paulik and Graham Elley
Water 2021, 13(23), 3371; https://doi.org/10.3390/w13233371 - 29 Nov 2021
Cited by 4 | Viewed by 2837
Abstract
Early warnings decision support systems are recognized as effective soft adaptation tools to prepare for the impacts of imminent flooding and minimize potential injuries and/or loss of life in flood-prone regions. This paper presents a case study of a pilot project that aimed [...] Read more.
Early warnings decision support systems are recognized as effective soft adaptation tools to prepare for the impacts of imminent flooding and minimize potential injuries and/or loss of life in flood-prone regions. This paper presents a case study of a pilot project that aimed to establish an impacts-based flood monitoring, early warnings, and decision support system for the Vaisigano River which flows through Apia, the capital of Samoa. This river is located in a characteristic short and steep catchment with rapid critical flood peak durations following periods of intense rainfall. The developed system integrates numerical weather prediction rainfall forecasts, real-time rainfall, river level and flow monitoring data, precomputed rainfall-runoff simulations, and flood inundation estimates of exposure levels and threat to human safety at buildings and on roads for different return period events. Information is ingested into a centralized real-time, web-based, flood decision support system portal that enables hydrometeorological officers to monitor, forecast and alert relevant emergency or humanitarian responders of imminent flooding with adequate lead time. This includes nowcasts and forecasts of estimated flood peak time, magnitude and likely impacts of inundation. The occurrence of three distinct extreme rainfall and flood events over the 2020/2021 tropical cyclone season provided a means to operationally test the system. In each case, the system proved adequate in alerting duty officers of imminent flooding in the Vaisigano catchment with up to 24 h warnings and response lead time. Gaps for improvement of system capabilities and performance are discussed, with recommendations for future work suggested. Full article
(This article belongs to the Special Issue Flash Floods: Forecasting, Monitoring and Mitigation Strategies)
Show Figures

Figure 1

Back to TopTop