Submit to Sustainability Review for Sustainability Propose a Special Issue

Journal Menu

Journal Browser

Geo-computation and Spatial Big Data Application for Sustainable Management of Hydrometeorological Hazards: Methodological Innovations, Mitigation Strategies; Case Studies and Best Practices

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Benefits of Publishing in a Special Issue
Published Papers

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Hazards and Sustainability".

Deadline for manuscript submissions: closed (30 March 2022) | Viewed by 26772

Share This Special Issue

Special Issue Editors

Dr. Basu Bidroha

E-Mail Website
Guest Editor

Civil Structural and Environmental Engineering, Munster Technological University, Rossa Ave, Bishopstown, T12 P928 Cork, Ireland
Interests: nonlinear dynamics; hydrology; remote sensing and gis; computational fluid dynamics; statistical analysis; water and air quality analysis

Prof. Dr. Laurence Gill

E-Mail Website
Guest Editor

Department of Civil, Structural and Environmental Engineering, Trinity College Dublin, Dublin D02, Ireland
Interests: coastal and ocean engineering; earth science and hydrology; energy and climate change; environmental engineering; water pollution; groundwater; hydraulics; renewable energy; waste management
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Francesco Pilla

E-Mail Website
Guest Editor

School of Architecture, Planning and Environmental Policy, University College Dublin, Dublin D04, Ireland
Interests: smart cities; geospatial analysis and GIS; urban dynamics modeling; air quality modeling; pervasive sensing; nature-based solutions

Dr. Srikanta Sannigrahi

E-Mail Website
Guest Editor

School of Architecture, Planning and Environmental Policy, University College Dublin, Dublin D04, Ireland
Interests: ecosystem services; ecosystem service valuation; natural capital accounting; environmental remote sensing; spatial analysis; geospatial data analysis

Special Issue Information

Dear Colleagues,

Focus:

The increasing interdependencies and coexistence among humans, nature, and society often make the complex socioecological system fragile and susceptible to external extremities, including natural and human-induced hazards. There has been ample evidence of an increasing trend of occurrence and intensity of hydrometeorological hazards that includes both meteorological and hydrological extremes across small to large spatial scales. Given the cascading impacts of various hydrometeorological hazards (HMZs), ranging from tropical and extratropical cyclonic storms, pluvial and fluvial flooding, coastal storm surges, drought, heatwaves, landslides, wildfires, cold waves, local climatic storms, etc., the requirement of a detailed analysis of those hazards and generation of cost-effective preventive solutions of HMZs are of paramount importance. The recent progress in advanced data-driven technologies exacerbates the practical application of monitoring and modeling approaches to mitigate HMZs, making HMZ decision support systems more achievable and trustworthy. Considering the existing state-of-the-art methods for managing HMZs, the present Special Issue aims to explore cross-disciplinary knowledge and scientific discourses that can collectively advance the current practices by providing more scalable solutions embedded with realistic and achievable outcomes.

Scope:

The sole objective and scope of the Special Issue is to offer a novel, more sustainable, and cost-effective solutions to mitigate the risk of HMZs by providing a clear and detailed roadmap for practical implementation of the suggested solutions. The inclusion of cross-disciplinary ideas and approaches in the solution strategies can effectively reduce the augmented impact of HMZs in the long run. Hence, the Special Issue invites innovative contributions in terms of both original and review studies supported by either thorough monitoring or descriptive/analytical modeling and covering any of the following topics:

Fluvial Floods in both natural and urban areas;
Pluvial floods in both natural and urban areas;
Flash floods in mountainous areas;
Cloud burst and associated consequences;
Coastal storm surges in coastal periphery areas;
Innovations and sustainable solutions for urban flood risk;
Practical strategies for urban stormwater management;
Draught impact and control across the ecosystems;
Desertification and effective management strategies;
Tropical cyclonic storms from micro- to mesoscale and development of resilient community support system;
Temperate storms from local to regional scale and effective management strategies;
Local climatic storms;
Dust storm in arid regions and management strategies;
Soil loss and resulting consequences on ecosystem productivity;
Urban heatwave and management strategies;
Cold wave;
Landslide and slope failure and effective mitigation strategies;
Wildfires/forest fires/bush fires.

Purpose:

The present Special Issue expects to collect scientific discussion, innovative ideas, best practices, and cost-effective solutions that are embedded in both ecosystem/data-driven approaches and achievable management alternatives to provide a fresh overview of the state-of-the-art methods, techniques, and strategies for sustainably managing the risk of HMZs. This Special Issue also expects to receive articles that offer scalable and actionable multidisciplinary perspectives and have the potentiality to be applied in solving real-life problems. Additionally, studies that provide a critical discussion on the existing policies and decision support systems for managing HMZs effectively are also welcome.

Dr. Basu Bidroha
Prof. Dr. Laurence Gill
Prof. Dr. Francesco Pilla
Dr. Srikanta Sannigrahi
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. Sustainability 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 2400 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

hydrometeorological hazards
meteorological data analysis
hydro-meteorological modeling
sustainable management system

Benefits of Publishing in a Special Issue

Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

22 pages, 6694 KiB

Open AccessEditor’s ChoiceArticle

Google Earth Engine for Large-Scale Flood Mapping Using SAR Data and Impact Assessment on Agriculture and Population of Ganga-Brahmaputra Basin

by Arvind Chandra Pandey, Kavita Kaushik and Bikash Ranjan Parida

Sustainability 2022, 14(7), 4210; https://doi.org/10.3390/su14074210 - 1 Apr 2022

Cited by 43 | Viewed by 9098

Abstract

The Ganga-Brahmaputra basin is highly sensitive to the impacts of climate change and experiences recurrent flooding, which affects large agricultural areas and poses a high risk to the population. The present study is focused on the recent flood disaster in the Ganga-Brahmaputra basin, which mainly affected the regions of Bihar, West Bengal, and Assam in India and neighboring Bangladesh during July, August, and September 2020. Using the Sentinel-1A Synthetic Aperture Radar (SAR) data, the flood extent was derived in the Google Earth Engine (GEE) platform. The composite area under flood inundation for July–September was estimated to be 25,889.1 km² for Bangladesh, followed by Bihar (20,837 km²), West Bengal (17,307.1 km²), and Assam (13,460.1 km²). The Copernicus Global Land Cover dataset was used to extract the affected agricultural area and flood-affected settlement. Floods have caused adverse impacts on agricultural lands and settlements, affecting 23.68–28.47% and 5.66–9.15% of these areas, respectively. The Gridded Population of the World (GPW) population density and Global Human Settlement Layer (GHSL) population dataset were also employed to evaluate flood impacts, which revealed that 23.29 million of the population was affected by floods in the Ganga-Brahmaputra basin. The highest impacts of floods can be seen from the Bihar state, as people reside in the lower valley and near to the riverbank due to their dependency on river water. Similarly, the highest impact was from Bangladesh because of the high population density as well as the settlement density. The study provided a holistic spatial assessment of flood inundation in the region due to the combined impact of the Ganga-Brahmaputra River basin. The identification of highly flood-prone areas with an estimated impact on cropland and build-up will provide necessary information to decision-makers for flood risk reduction, mitigation activities, and management. Full article

(This article belongs to the Special Issue Geo-computation and Spatial Big Data Application for Sustainable Management of Hydrometeorological Hazards: Methodological Innovations, Mitigation Strategies; Case Studies and Best Practices)

► Show Figures

Figure 1

26 pages, 10708 KiB

Open AccessArticle

Flood Hazard and Risk Zonation in North Bihar Using Satellite-Derived Historical Flood Events and Socio-Economic Data

by Gaurav Tripathi, Arvind Chandra Pandey and Bikash Ranjan Parida

Sustainability 2022, 14(3), 1472; https://doi.org/10.3390/su14031472 - 27 Jan 2022

Cited by 23 | Viewed by 8136

Abstract

North Bihar is one of the most flood-affected regions of India. Frequent flooding caused significant loss of life and severe economic damages. In this study, hydroclimatic conditions and historical flood events during the period of 2001 to 2020 were coupled over different basins in North Bihar. The main objective of this study is to assess the severity of floods by estimating flood hazards, vulnerability and risk in North Bihar. The uniqueness of this study is to assess flood risk at the village level as no such study was performed earlier. Other thematic data, namely, land-use and drainage networks, were also utilised with flood maps to validate the severity of the event. MOD09A1 satellite data (during 2001–2020) derived indices were used to derive inundation extents and flood frequency. Socio-economic vulnerability (SEV) was derived based on seven census parameters (i.e., population density, house-hold density, literacy rate, agricultural labour, and cultivator, total male, and female) and coupled with flood hazard to derive flood risk over the study region. The study exhibited that a total ~34% of the geographical area of North Bihar was inundated in the last 20 years and the maximum flood extent was seen in 2020. Flood risk map exhibited that ~7%, ~8%, ~13%, ~4%, and ~2% of the geographical area was mapped under Very High, High, Moderate, Low, and Very Low categories, respectively. The 2770 and 3535 number of villages was categorized under Very High and High flood risk zone which are located in north-central and central-western regions. These findings can be applied to distinguish and classify areas of various risk zones to assist in flood mitigation and management activities. Full article

► Show Figures

Figure 1

22 pages, 7058 KiB

Open AccessArticle

Assessment of Variations in Runoff Due to Landcover Changes Using the SWAT Model in an Urban River in Dublin, Ireland

by Arunima Sarkar Basu, Laurence William Gill, Francesco Pilla and Bidroha Basu

Sustainability 2022, 14(1), 534; https://doi.org/10.3390/su14010534 - 4 Jan 2022

Cited by 11 | Viewed by 2848

Abstract

Investigating the impact of land cover change in hydrological modelling is essential for water resources management. This paper investigates the importance of landcover change in the development of a physically-based hydrological model called SWAT. The study area considered is the Dodder River basin located in southern Dublin, Ireland. Runoff at the basin outlet was simulated using SWAT for 1993–2019 using five landcover maps obtained for 1990, 2000, 2006, 2012 and 2018. Results indicate that, in general, the SWAT model-simulated runoff for a chosen time-period are closer to the real-world observations when the landcover data used for simulation was collated as close to the time-period for which the simulations were performed. For 23 (20) years (from 27 years period) the monthly mean (maximum) runoff for the Dodder River generated by the SWAT model had the least error when the nearby landcover data were used. This study indicates the necessity of considering dynamic and time-varying landcover data during the development of hydrological modelling for runoff simulation. Furthermore, two composite quantile functions were generated by using a kappa distribution for monthly mean runoff and GEV distribution for monthly maximum runoff, based on model simulations obtained using different landcover data corresponding to different time-period. Modelling landcover change patterns and development of projected landcover in the future for river basins in Ireland needs to be integrated with SWAT to simulate future runoff. Full article

► Show Figures

Figure 1

34 pages, 6883 KiB

Open AccessEditor’s ChoiceArticle

Theoretical Framework to Assess Green Roof Performance in Mitigating Urban Flooding as a Potential Nature-Based Solution

by Arunima Sarkar Basu, Francesco Pilla, Srikanta Sannigrahi, Rémi Gengembre, Antoine Guilland and Bidroha Basu

Sustainability 2021, 13(23), 13231; https://doi.org/10.3390/su132313231 - 29 Nov 2021

Cited by 11 | Viewed by 5413

Abstract

Increases in extreme hydro-meteorological events due to climate change and decreases in soil permeability and infiltration due to urbanization have increased the risk of flooding, particularly in cities. The limitation of the expansion of conventional drainage systems to manage excess stormwater leads to the application of nature-based solutions (NBS) to control flooding. This study explores potential of green roof NBS for rainfall-fed flood reduction, which can utilize existing roof space for deployment. A detailed literature survey using systematic literature-search procedures was conducted to investigate the performance of extensive/intensive green roofs in runoff reduction using monitoring/modeling approaches. Since limited studies have explored the use of semi-intensive green roofs for flood management, a new simulation study has been developed to compare the effectiveness of semi-intensive green roofs. The performance of different types of vegetation used on green roofs in runoff reduction was investigated using a simulation study, which was validated using a real-world green roof deployed in Dublin. Full article

► Show Figures

Journal Menu

Journal Browser

Geo-computation and Spatial Big Data Application for Sustainable Management of Hydrometeorological Hazards: Methodological Innovations, Mitigation Strategies; Case Studies and Best Practices

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (4 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI