Editorial Board Members’ Collection Series: The Flood Estimation and Forecasting Chain: Meteorological–Hydrological–Hydraulic Forecasts and Predictive Uncertainty towards Operational Decisions

A special issue of Hydrology (ISSN 2306-5338). This special issue belongs to the section "Hydrological and Hydrodynamic Processes and Modelling".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 6963

Special Issue Editors


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Guest Editor
Department of Economics, Engineering, Society and Business Organization (DEIM), Tuscia University, 01100 Viterbo, Italy
Interests: rainfall-runoff modeling; flood prone area estimation; surface hydrology; GIS terrain analysis for hydrogeomorphic applications; hydrological processes monitoring and modelling
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Water and Environment, Chang’an University, Xi'an 710054, China
Interests: urban flood; flood management; hydrological modeling; water quality analysis; statistical analysis; sustainable water resource management; ecohydrology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Modeling and monitoring approaches are pivotal in the comprehension of the flood estimation and forecasting chains. Meteorological, hydrological and hydraulic forecasts and estimations, together with the associated predictive uncertainty, are needed in order to support operational decisions, not only for research but also for water institutions and professional communities.

Indeed, the understanding, simulation and mitigation of flooding scenarios represent ongoing challenges for both researchers and floodplain managers for large basins in watersheds characterized by limited contributing areas, where, often, the modeler is forced to apply simplified models. Recent advancements in remote sensing technologies and computer capabilities have provided a new generation of scenarios to solve the problem, from the use of artificial neural networks to the use of synthetic rainfall generation models and continuous rainfall–runoff modeling.

In this Topical Collection, we welcome the submission of original and innovative research papers focusing on modeling and monitoring aspects related to the whole flood estimation and forecasting chain, in order to address water resource management issues and use the available information to reduce the uncertainty in the estimations as much as possible. Additionally, opportunities arising from new sources of remotely sensed information, which can also be linked to informal unstructured data (e.g., social networks), citizen science approaches and low-cost sensors, among others, are welcomed.

We expect that this Topical Collection will reduce the uncertainty in the determination of design variables linked to water cycle processes and features considered in different meteorological, hydrological and hydraulic processes related to the whole flood estimation and forecasting chain.

Dr. Andrea Petroselli
Prof. Dr. Pingping Luo
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. Hydrology is an international peer-reviewed open access monthly 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 1800 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

  • hydrological processes
  • hydraulic processes
  • flood estimation
  • flood forecasting
  • modeling and monitoring
  • water resources management
  • wet and arid areas

Published Papers (3 papers)

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Research

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19 pages, 7581 KiB  
Article
A Spatiotemporal Assessment of the Precipitation Variability and Pattern and an Evaluation of the Predictive Reliability of Global Climate Models over Bihar
by Ahmad Rashiq, Vishwajeet Kumar and Om Prakash
Hydrology 2024, 11(4), 50; https://doi.org/10.3390/hydrology11040050 - 8 Apr 2024
Viewed by 1115
Abstract
Climate change is significantly altering precipitation patterns, leading to spatiotemporal changes throughout the world. In particular, the increased frequency and intensity of extreme weather events, leading to heavy rainfall, floods, and droughts, have been a cause of concern. A comprehensive understanding of these [...] Read more.
Climate change is significantly altering precipitation patterns, leading to spatiotemporal changes throughout the world. In particular, the increased frequency and intensity of extreme weather events, leading to heavy rainfall, floods, and droughts, have been a cause of concern. A comprehensive understanding of these changes in precipitation patterns on a regional scale is essential to enhance resilience against the adverse effects of climate change. The present study, focused on the state of Bihar in India, uses a long-term (1901–2020) gridded precipitation dataset to analyze the effect of climate change. Change point detection tests divide the time series into two epochs: 1901–1960 and 1961–2020, with 1960 as the change point year. Modified Mann–Kendall (MMK) and Sen’s slope estimator tests are used to identify trends in seasonal and annual time scales, while Centroidal Day (CD) analysis is performed to determine changes in temporal patterns of rainfall. The results show significant variability in seasonal rainfall, with the nature of pre-monsoon and post-monsoon observed to have flipped in second epoch. The daily rainfall intensity during the monsoon season has increased considerably, particularly in north Bihar, while the extreme rainfall has increased by 60.6 mm/day in the second epoch. The surface runoff increased by approximately 13.43% from 2001 to 2020. Further, 13 Global Climate Models (GCMs) evaluate future scenarios based on Shared Socioeconomic Pathways (SSP) 370 and SSP585. The suitability analysis of these GCMs, based on probability density function (PDF), monthly mean absolute error (MAE), root mean square error (RMSE) and percentage bias (P-Bias), suggests that EC-Earth3-Veg-LR, MIROC6, and MPI-ESM1-2-LR are the three best GCMs representative of rainfall in Bihar. A Bayesian model-averaged (BMA) multi-model ensemble reflects the variability expected in the future with the least uncertainty. The present study’s findings clarify the current state of variability, patterns and trends in precipitation, while suggesting the most appropriate GCMs for better decision-making and preparedness. Full article
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16 pages, 1409 KiB  
Article
Development of Green Disaster Management Toolkit to Achieve Carbon Neutrality Goals in Flood Risk Management
by Tae Sung Cheong and Sangman Jeong
Hydrology 2024, 11(4), 44; https://doi.org/10.3390/hydrology11040044 - 26 Mar 2024
Viewed by 1141
Abstract
Current flood risk management projects have been criticized for their high carbon emissions, raising the need for carbon emission reduction and carbon absorption efforts to mitigate environmental impacts and achieve carbon neutrality goals. The research develops a comprehensive green disaster risk management toolkit [...] Read more.
Current flood risk management projects have been criticized for their high carbon emissions, raising the need for carbon emission reduction and carbon absorption efforts to mitigate environmental impacts and achieve carbon neutrality goals. The research develops a comprehensive green disaster risk management toolkit to calculate the carbon emissions and absorption quantitatively based on the unit volume of materials and processes employed in a flood risk management project. As a result of applying the developed toolkit to a about 22,300 small stream restoration projects in Korea, the total carbon emissions were estimated to be 1,158,840.7 tons of CO2, of which 89.4% of the total carbon emissions originated from concrete-related construction activities, such as cement and ready-mixed concrete pouring. As a result of evaluating the nationwide carbon absorption results of all small stream restoration projects, total absorption by 2030 is expected to be 3.0 to 10.2 times higher than carbon emissions. The comprehensive toolkits are expected to support the selection of customized processes, materials, and methods by providing a systematic approach to calculate and minimize carbon emissions, ultimately contributing to the achievement of carbon neutrality goals in flood risk management projects. Full article
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Review

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16 pages, 991 KiB  
Review
Comprehensive Flood Risk Assessment: State of the Practice
by Neil S. Grigg
Hydrology 2023, 10(2), 46; https://doi.org/10.3390/hydrology10020046 - 10 Feb 2023
Cited by 3 | Viewed by 3901
Abstract
A comprehensive assessment of flood hazards will necessitate a step-by-step analysis, starting with hydrometeorological examinations of runoff and flow, followed by an assessment of the vulnerability of those at risk. Although bodies of knowledge about these topics are large, flood risk assessments face [...] Read more.
A comprehensive assessment of flood hazards will necessitate a step-by-step analysis, starting with hydrometeorological examinations of runoff and flow, followed by an assessment of the vulnerability of those at risk. Although bodies of knowledge about these topics are large, flood risk assessments face data challenges such as climate change, population growth, and shifting land uses. Recent studies have provided comprehensive reviews of advances in the water sciences arena, and in a complementary way, this paper reviews the state of the practice of assessing flood risk, include flood scenarios, hydrometeorology, inundation modeling, flood frequency analysis, interrelationships with water infrastructure, and vulnerability of people and places. The research base for each of these topics is extensive. Some of the tools in these areas, such as hydrologic modeling, have research advances that extend back decades, whereas others, such as numerical weather prediction, have more room to evolve. It’s clear from all studies that data is crucial along the progression from atmospheric conditions to the impact on flood victims. How data are provided and shared and how they are used by stakeholders in flood risk reduction continue to evolve. Improved availability of data and uses of emerging tools of data science and machine learning are needed to assess and mitigate flood risks. Continued the development of key tools is also required, especially to improve the capability to assemble them effectively on user platforms. Full article
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