Geo-Hydrological Risks Management, Volume II

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Natural Hazards".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 7449

Special Issue Editors


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Guest Editor
Geohazard Monitoring Group, Research Institute for Hydrogeological Prevention and Protection, National Research Council, 10135 Turin, Italy
Interests: natural hazards; monitoring; geomatics; remote sensing; glaciers; cryosphere
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Water Technology and Management, CSIR-National Environmental Engineering Research Institute, Nagpur 440020, India
Interests: ecosystem based approaches; disaster risk reduction; slope stabilisation; restoration; impact assessment; nature based solutions

Special Issue Information

Dear Colleagues,

This Special Issue of Geosciences aims to gather high-quality original research articles and technical notes on the use of geosciences applied to geo-hydrological risk management. The Special Issue will highlight case studies, best practices, and applied research. The use of geoscience tools is an undeniable added value when coping with natural disasters and their risk management. Survey devices, both close-range (e.g., Global Navigation Satellite System or GNSS) and remote (e.g., Unmanned Aerial Vehicles or UAVs, remote sensing) mapping tools, such as Geographic Information System (GIS), as well as geophysical tools such as Ground Penetrating Radar, contribute to improving the knowledge of investigated phenomena and, consequently, their risk management. Thanks to the accuracy and richness of geometric and thematic data, risk management is facilitated by and contributes to, among others, risk mitigation and the development of sustainable adaptation and mitigation strategies. Therefore, I would like to invite you to submit recent work, in the form of an article under different categories invited by the journal, concerning the above-mentioned topics. The use of open source approaches is highly appreciated. The preliminary submission of a short abstract outlining the aims of the research and its main results is encouraged in order to check, at an early stage, if the contribution fits the scope of the Special Issue.

Dr. Danilo Godone
Dr. Shalini Dhyani
Guest Editors

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Published Papers (3 papers)

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Research

13 pages, 3363 KiB  
Article
Sensitivity Analysis of Modelled Flood Inundation Extents over Hawkesbury–Nepean Catchment
by S. L. Kesav Unnithan, Basudev Biswal, Wendy Sharples, Christoph Rüdiger, Katayoon Bahramian and Jiawei Hou
Geosciences 2023, 13(3), 67; https://doi.org/10.3390/geosciences13030067 - 27 Feb 2023
Cited by 1 | Viewed by 2231
Abstract
Rainfall runoff and topography are among the major factors controlling the accuracy of modelled riverine inundation extents. We have evaluated the sensitivity of both these variables on a novel 1-D conceptual flood inundation model employing Height Above Nearest Drainage (HAND) thresholds within sub-catchment [...] Read more.
Rainfall runoff and topography are among the major factors controlling the accuracy of modelled riverine inundation extents. We have evaluated the sensitivity of both these variables on a novel 1-D conceptual flood inundation model employing Height Above Nearest Drainage (HAND) thresholds within sub-catchment units called Reach Contributing Area (RCA). We examined the March 2021 flood extent over the Hawkesbury–Nepean Valley (HNV) with 0.05′ gridded runoff derived from the Australian Water Resources Assessment (AWRA) modelling framework. HAND thresholds were enforced within each RCA using rating curve relationships generated by a modelled river geometry dataset obtained from Jet Propulsion Laboratory (JPL) and by modelling Manning’s roughness coefficient as a function of channel slope. We found that the step-like topographic nature of HNV significantly influences the back-water effect within the floodplain. At the same time, the improved accuracy of the GeoFabric Digital Elevation Model (DEM) outperforms SRTM DEM-derived flood output. The precision of HAND thresholds does not add significant value to the analysis. With enhanced access to river bathymetry and an ensemble point-based runoff modelling approach, we can generate an ensemble runoff-based probabilistic extent of inundation. Full article
(This article belongs to the Special Issue Geo-Hydrological Risks Management, Volume II)
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14 pages, 10024 KiB  
Article
Low-Cost Real-Time Water Level Monitoring Network for Falling Water River Watershed: A Case Study
by Alfred Kalyanapu, Collins Owusu, Tyler Wright and Tania Datta
Geosciences 2023, 13(3), 65; https://doi.org/10.3390/geosciences13030065 - 26 Feb 2023
Cited by 3 | Viewed by 2186
Abstract
Streamflow monitoring for flood warning and watershed management applications in the United States is a cost-intensive venture, and usually performed by government agencies such as the US Geological Survey (USGS). With reduced resources across the federal agencies towards environmental monitoring, agencies and stakeholders [...] Read more.
Streamflow monitoring for flood warning and watershed management applications in the United States is a cost-intensive venture, and usually performed by government agencies such as the US Geological Survey (USGS). With reduced resources across the federal agencies towards environmental monitoring, agencies and stakeholders are challenged to respond with cross-cutting, collaborative, and low-cost alternatives for streamflow monitoring. One such alternative is using low-cost environmental sensors and developing a real-time gage/sensor network using IoT (Internet of Things) devices. With this technology, smaller watersheds (e.g., HUC-8 and HUC-10 level) can be equipped with low-cost gages at many locations and a clear picture of the hydrological response can be obtained. This paper presents the development and implementation of a low-cost real-time water monitoring network for the Falling Water River (FWR) watershed in the middle Tennessee region in the US. To develop and implement this gage network, the following three tasks were performed: (i) assemble a low-cost, real-time internet enabled water level gage, (ii) field-test the sensor prototype and, (iii) deploy the sensors and build a network. A collaborative partnership was developed with stakeholders including the Tennessee Department of Environment and Conservation, Tennessee Department of Transportation, Burgess Falls State Park, City of Cookeville, and Friends of Burgess Falls. The performance of the gages in water level estimation was compared with the water levels measured with a nearby USGS streamgage. The comparison was performed for the 2020–2022 time period and at two levels: event-based comparison and a long-term comparison. Nine storm events were selected for the comparison, which showed “Very Good” agreement in terms of Coefficient of Determination (R2), Nash–Suttcliffe Efficiency (NSE), and percent bias (PBIAS) (except for four events). The mean squared error (MSE) ranged between 0.07 and 1.06 while the root mean squared error (RMSE) ranged between 3 inches and 12 inches. A long-term comparison was performed using Wilcoxon Signed-Rank test and Loess Seasonal Decomposition analysis, which showed that the differences between the two datasets is not significant and that they trended well across the two year period. The gages are currently installed along the main channel and tributaries of the Falling Water River, which also include portions of the Window Cliffs State Natural Area. With continued support from the stakeholders, the number of sensors are projected to increase, resulting in a dense sensor network across the watershed. This will over time enable the stakeholders to have a spatially variable hydrological response of the Falling Water River Watershed. Full article
(This article belongs to the Special Issue Geo-Hydrological Risks Management, Volume II)
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15 pages, 1585 KiB  
Article
Geoelectrical Measurements to Monitor a Hydrocarbon Leakage in the Aquifer: Simulation Experiment in the Lab
by Luigi Capozzoli, Valeria Giampaolo, Gregory De Martino, Mohamed M. Gomaa and Enzo Rizzo
Geosciences 2022, 12(10), 360; https://doi.org/10.3390/geosciences12100360 - 29 Sep 2022
Cited by 6 | Viewed by 2220
Abstract
Hydrocarbons represent one of the most dangerous sources of contamination for environmental resources. Petroleum contaminants released from leaking fuel storage tanks or accidental spillages represent serious worldwide problems. Knowledge of the contaminant distribution in the subsoil is very complex, and direct measurements, such [...] Read more.
Hydrocarbons represent one of the most dangerous sources of contamination for environmental resources. Petroleum contaminants released from leaking fuel storage tanks or accidental spillages represent serious worldwide problems. Knowledge of the contaminant distribution in the subsoil is very complex, and direct measurements, such as boreholes or drillings, are strongly required. Even if the direct measurements define accurate information, on the contrary, they have low spatial coverage. Geophysics can effectively support conventional methods of subsoil sampling by expanding the information obtainable, providing to analyze, with higher resolution, larger areas of investigation. Consequently, different geophysical techniques have been used to detect the presence and distribution of hydrocarbons in the subsurface. Electrical resistivity tomography is an efficient geophysical methodology for studying hydrocarbon contamination. Indeed, this methodology allows for the reduction of the number of drillings or soil samples, and several papers described its success. One of the advantages is the possibility to successfully perform analyses in time-lapse to identify the degradation of the contaminants. Indeed, natural attenuation of hydrocarbon contaminants is observed under aerobic conditions due to biodegradation, which should be the principal phenomenon of physical variations of the subsoil. Therefore, a laboratory experiment was conducted in a sandbox to simulate a spillage of common diesel occurring in the vadose zone. The sandbox was monitored for a long period (1 year, approximately) using time-lapse cross borehole electrical resistivity tomographies. Results highlight the usefulness of in-hole electrical tomography for characterizing underground hydrocarbon leakage and the variability of the subsurface physical behavior due to contaminant degradation. Therefore, the experiment demonstrates how the electrical method can monitor the biodegradation processes occurring in the subsoil, defining the possibility of using the methodology during remediation activities. Full article
(This article belongs to the Special Issue Geo-Hydrological Risks Management, Volume II)
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