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25 pages, 5323 KiB

Open AccessArticle

Creating a Nationwide Composite Hazard Index Using Empirically Based Threat Assessment Approaches Applied to Open Geospatial Data

by Christopher T. Emrich, Yao Zhou, Sanam K. Aksha and Herbert E. Longenecker

Sustainability 2022, 14(5), 2685; https://doi.org/10.3390/su14052685 - 25 Feb 2022

Cited by 2 | Viewed by 3446

Abstract

The US is exposed to myriad natural hazards causing USD billions in damages and thousands of fatalities each year. Significant population and economic growth during the last several decades have resulted in more people residing in hazardous places. However, consistent national-scale hazard threat [...] Read more.

The US is exposed to myriad natural hazards causing USD billions in damages and thousands of fatalities each year. Significant population and economic growth during the last several decades have resulted in more people residing in hazardous places. However, consistent national-scale hazard threat assessment techniques reflecting the state of hazard knowledge are not readily available for application in risk and vulnerability assessments. Mapping natural hazard threats is the crucial first step in identifying and implementing threat reduction or mitigation strategies. In this study, we demonstrate applied GIS approaches for creating and synthesizing US hazard threat extents using publicly available data for 15 natural hazards. Individually mapping each threat enables empirically supported intervention development and the building of a Composite Hazard Index (CHI). Summarizing the hazard frequencies provides a novel representation of US hazardousness. Implementing cluster analysis to regionalize US counties based on their underlying hazard characteristics offers insight into hazard threats’ spatial (non-political) natures. The results indicate that the southeast, central plains, and coastal regions of the northeast had high hazard occurrence scores, whereas more moderate hazard scores were observed west of the continental divide. Furthermore, while no place is safe from hazard occurrence, identifying each region’s distinct “hazardousness” can support individualized risk assessments and mitigation intervention development. Full article

(This article belongs to the Special Issue Hydrometeorological Hazards and Disasters)

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22 pages, 8224 KiB

Open AccessArticle

Flood-Prone Area Delineation in Urban Subbasins Based on Stream Ordering: Culiacan Urban Basin as a Study Case

by Antonio J. Sanhouse-García, Jesús Gabriel Rangel-Peraza, Sergio A. Rentería-Guevara, Yaneth A. Bustos-Terrones, Zuriel D. Mora-Félix, Wenseslao Plata-Rocha and Sergio Alberto Monjardin-Armenta

Sustainability 2021, 13(24), 13513; https://doi.org/10.3390/su132413513 - 7 Dec 2021

Cited by 2 | Viewed by 3256

Abstract

Urban development decreases infiltration, increases the runoff velocity, and reduces the concentration times. This situation increases the flood risk in urban watersheds, which represent a management challenge for urban communities and authorities. To increase the resilience of communities due to modifications of the [...] Read more.

Urban development decreases infiltration, increases the runoff velocity, and reduces the concentration times. This situation increases the flood risk in urban watersheds, which represent a management challenge for urban communities and authorities. To increase the resilience of communities due to modifications of the hydrological cycle produced by climate change and urban development, a methodology is proposed to delineate flood-prone areas in urban basins. This methodology is implemented in an urban subbasin of Culiacan, Mexico, and is based on stream order. A high-resolution digital elevation model was used, which was validated independently through a photogrammetric flight with an unmanned aerial vehicle and ground control points obtained with GNSS (global navigation satellite systems) receivers. Morphometric parameters related to geometry, shape, relief, and drainage network aspects of the subbasin were determined and analyzed. Then, flood-prone area zonation was carried out based on stream-order classification and flow direction. Fieldwork was also carried out for the inspection of the sewage network conditions. This methodology simplifies the identification of the flood-prone areas in urban subbasins without carrying out complex hydraulic calculations. Full article

(This article belongs to the Special Issue Hydrometeorological Hazards and Disasters)

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10 pages, 2559 KiB

Open AccessArticle

A Model for Calculating the Spatial Coverage of Audible Disaster Warnings Using GTFS Realtime Data

by Akihiko Nishino, Akira Kodaka, Madoka Nakajima and Naohiko Kohtake

Sustainability 2021, 13(23), 13471; https://doi.org/10.3390/su132313471 - 6 Dec 2021

Cited by 5 | Viewed by 2183

Abstract

In the event of a large-scale disaster, the dissemination of audible disaster warning information via sirens is effective in ensuring a rapid response. Sirens can be installed not only on fixed towers, but also on public transport and other vehicles passing through residential [...] Read more.

In the event of a large-scale disaster, the dissemination of audible disaster warning information via sirens is effective in ensuring a rapid response. Sirens can be installed not only on fixed towers, but also on public transport and other vehicles passing through residential areas, and at spots where residents congregate, to increase area coverage. Although models to calculate the spatial coverage of audible information delivered from fixed sirens have been constructed, no general-purpose model has been developed to assess the delivery from vehicles. In this study, we focused on the General Transit Feed Specification (GTFS), which is an open format for geospatial information on public transport. We conducted a spatial analysis using a geographic information system (GIS) on the basis of the acquired bus location information. We developed a model to calculate the spatial coverage of the audible information delivery for overlapping hazard maps and population. Assuming a flood occurred in the vicinity of Brisbane Central Station, Queensland, Australia, we confirmed that the developed model was capable of characterizing the time-series changes in the exposed population in the target area. Since the GTFS format is currently distributed across various countries, this assessment model is considered to be highly versatile and widely applicable. Full article

(This article belongs to the Special Issue Hydrometeorological Hazards and Disasters)

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31 pages, 37782 KiB

Open AccessArticle

Detailed Analysis of Spatial–Temporal Variability of Rainfall Erosivity and Erosivity Density in the Central and Southern Pannonian Basin

by Tanja Micić Ponjiger, Tin Lukić, Biljana Basarin, Maja Jokić, Robert L. Wilby, Dragoslav Pavić, Minučer Mesaroš, Aleksandar Valjarević, Miško M. Milanović and Cezar Morar

Sustainability 2021, 13(23), 13355; https://doi.org/10.3390/su132313355 - 2 Dec 2021

Cited by 20 | Viewed by 3435

Abstract

Estimation of rainfall erosivity (RE) and erosivity density (ED) is essential for understanding the complex relationships between hydrological and soil erosion processes. The main objective of this study is to assess the spatial–temporal trends and variability of the RE [...] Read more.

Estimation of rainfall erosivity (RE) and erosivity density (ED) is essential for understanding the complex relationships between hydrological and soil erosion processes. The main objective of this study is to assess the spatial–temporal trends and variability of the RE and ED in the central and southern Pannonian Basin by using station observations and gridded datasets. To assess RE and ED, precipitation data for 14 meteorological stations, 225 grid points. and an erosion model consisting of daily, monthly, seasonal, and annual rainfall for the period of 1961–2014 were used. Annual RE and ED based on station data match spatially variable patterns of precipitation, with higher values in the southwest (2100 MJ·mm·ha⁻¹·h⁻¹) and southeast (1650 MJ·mm·ha⁻¹·h⁻¹) of the study area, but minimal values in the northern part (700 MJ·mm·ha⁻¹·h⁻¹). On the other hand, gridded datasets display more detailed RE and ED spatial–temporal variability, with the values ranging from 250 to 2800 MJ·mm·ha⁻¹·h⁻¹. The identified trends are showing increasing values of RE (ranging between 0.20 and 21.17 MJ·mm·ha⁻¹·h⁻¹) and ED (ranging between 0.01 and 0.03 MJ·ha⁻¹·h⁻¹) at the annual level. This tendency is also observed for autumn RE (from 5.55 to 0.37 MJ·mm·ha⁻¹·h⁻¹) and ED (from 0.05 to 0.01 MJ·ha⁻¹·h⁻¹), as for spring RE (from 1.00 to 0.01 MJ·mm·ha⁻¹·h⁻¹) and ED (from 0.04 to 0.01 MJ·ha⁻¹·h⁻¹), due to the influence of the large-scale processes of climate variability, with North Atlantic Oscillation (NAO) being the most prominent. These increases may cause a transition to a higher erosive class in the future, thus raising concerns about this type of hydro-meteorological hazard in this part of the Pannonian Basin. The present analysis identifies seasons and places of greatest erosion risk, which is the starting point for implementing suitable mitigation measures at local to regional scales. Full article

(This article belongs to the Special Issue Hydrometeorological Hazards and Disasters)

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21 pages, 4162 KiB

Open AccessArticle

Prediction of Potential Evapotranspiration Using Temperature-Based Heuristic Approaches

by Rana Muhammad Adnan, Salim Heddam, Zaher Mundher Yaseen, Shamsuddin Shahid, Ozgur Kisi and Binquan Li

Sustainability 2021, 13(1), 297; https://doi.org/10.3390/su13010297 - 31 Dec 2020

Cited by 17 | Viewed by 3263

Abstract

The potential or reference evapotranspiration (ET₀) is considered as one of the fundamental variables for irrigation management, agricultural planning, and modeling different hydrological pr°Cesses, and therefore, its accurate prediction is highly essential. The study validates the feasibility of new temperature [...] Read more.

The potential or reference evapotranspiration (ET₀) is considered as one of the fundamental variables for irrigation management, agricultural planning, and modeling different hydrological pr°Cesses, and therefore, its accurate prediction is highly essential. The study validates the feasibility of new temperature based heuristic models (i.e., group method of data handling neural network (GMDHNN), multivariate adaptive regression spline (MARS), and M5 model tree (M5Tree)) for estimating monthly ET₀. The outcomes of the newly developed models are compared with empirical formulations including Hargreaves-Samani (HS), calibrated HS, and Stephens-Stewart (SS) models based on mean absolute error (MAE), root mean square error (RMSE), and Nash-Sutcliffe efficiency. Monthly maximum and minimum temperatures (T_max and T_min) observed at two stations in Turkey are utilized as inputs for model development. In the applications, three data division scenarios are utilized and the effect of periodicity component (PC) on models’ accuracies are also examined. By importing PC into the model inputs, the RMSE accuracy of GMDHNN, MARS, and M5Tree models increased by 1.4%, 8%, and 6% in one station, respectively. The GMDHNN model with periodic input provides a superior performance to the other alternatives in both stations. The recommended model reduced the average error of MARS, M5Tree, HS, CHS, and SS models with respect to RMSE by 3.7–6.4%, 10.7–3.9%, 76–75%, 10–35%, and 0.8–17% in estimating monthly ET₀, respectively. The HS model provides the worst accuracy while the calibrated version significantly improves its accuracy. The GMDHNN, MARS, M5Tree, SS, and CHS models are also compared in estimating monthly mean ET₀. The GMDHNN generally gave the best accuracy while the CHS provides considerably over/under-estimations. The study indicated that the only one data splitting scenario may mislead the modeler and for better validation of the heuristic methods, more data splitting scenarios should be applied. Full article

(This article belongs to the Special Issue Hydrometeorological Hazards and Disasters)

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25 pages, 316 KiB

Open AccessArticle

Using Logistic Regression to Identify Leading Factors to Prepare for an Earthquake Emergency during Daytime and Nighttime: The Case of Mass Earthquake Drills

by Jaime Santos-Reyes

Sustainability 2020, 12(23), 10009; https://doi.org/10.3390/su122310009 - 30 Nov 2020

Cited by 7 | Viewed by 3050

Abstract

Historical data have demonstrated that earthquakes can happen any time of the day and night. Drills may help communities to better prepare for such emergencies. A cross-sectional survey was conducted from 4 October to 20 November 2017, in Mexico City. The sample size [...] Read more.

Historical data have demonstrated that earthquakes can happen any time of the day and night. Drills may help communities to better prepare for such emergencies. A cross-sectional survey was conducted from 4 October to 20 November 2017, in Mexico City. The sample size was 2400. The addressed research questions were “what factors predict the likelihood that respondents would report that they agree on conducting mass evacuation drills: (a) any time of the day and (b) any time at night?” The logistic regression technique was employed to identify the factors leading to the outcome. In relation to (a), five variables were significantly associated with the outcome, i.e., age, frequency of drills, warning time, knowledge on what to do, and “perception vulnerability city”. Regarding (b), five variables were also significantly associated with the outcome variable, i.e., age, level of education, frequency of drills, negative emotions, and fear of house/building collapsing. More generally, several drills should be conducted any time of the day and night; further, 50% of them should be announced and 50% unannounced. Furthermore, the time of earthquake drills should be randomly selected. In this way, we may just match the spatial–temporal dimension of an earthquake emergency. It is hoped that the findings will lead to better preparedness of the residents of the capital city during an earthquake occurrence. Full article

(This article belongs to the Special Issue Hydrometeorological Hazards and Disasters)

16 pages, 4178 KiB

Open AccessArticle

On the Operational Flood Forecasting Practices Using Low-Quality Data Input of a Distributed Hydrological Model

by Binquan Li, Zhongmin Liang, Qingrui Chang, Wei Zhou, Huan Wang, Jun Wang and Yiming Hu

Sustainability 2020, 12(19), 8268; https://doi.org/10.3390/su12198268 - 8 Oct 2020

Cited by 10 | Viewed by 2569

Abstract

Low-quality input data (such as sparse rainfall gauges, low spatial resolution soil type and land use maps) have limited the application of physically-based distributed hydrological models in operational practices in many data-sparse regions. It is necessary to quantify the uncertainty in the deterministic [...] Read more.

Low-quality input data (such as sparse rainfall gauges, low spatial resolution soil type and land use maps) have limited the application of physically-based distributed hydrological models in operational practices in many data-sparse regions. It is necessary to quantify the uncertainty in the deterministic forecast results of distributed models. In this paper, the TOPographic Kinematic Approximation and Integration (TOPKAPI) distributed model was used for deterministic forecasts with low-quality input data, and then the Hydrologic Uncertainty Processor (HUP) was used to provide the probabilistic forecast results for operational practices. Results showed that the deterministic forecasts by TOPKAPI performed poorly in some flood seasons, such as the years 1997, 2001 and 2008, despite which the overall accuracy of the whole study period 1996–2008 could be acceptable and generally reproduced the hydrological behaviors of the catchment (Lushi basin, China). The HUP model can not only provide probabilistic forecasts (e.g., 90% predictive uncertainty bounds), but also provides deterministic forecasts in terms of 50% percentiles. The 50% percentiles obviously improved the forecast accuracy of selected flood events at the leading time of one hour. Besides, the HUP performance decayed with the leading time increasing (6, 12 h). This work revealed that deterministic model outputs had large uncertainties in flood forecasts, and the HUP model may provide an alternative for operational flood forecasting practices in those areas with low-quality data. Full article

(This article belongs to the Special Issue Hydrometeorological Hazards and Disasters)

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19 pages, 9474 KiB

Open AccessArticle

Investigation of the Relationship between Rainfall and Fatal Crashes in Texas, 1994–2018

by Zhongyu Han and Hatim O. Sharif

Sustainability 2020, 12(19), 7976; https://doi.org/10.3390/su12197976 - 26 Sep 2020

Cited by 9 | Viewed by 2786

Abstract

Understanding how crash factors are impacted by rain is critical to road safety planning and management. This study assesses the impact of rain on traffic safety by conducting an analysis of the fatal crashes related to rain in Texas from 1994 to 2018. [...] Read more.

Understanding how crash factors are impacted by rain is critical to road safety planning and management. This study assesses the impact of rain on traffic safety by conducting an analysis of the fatal crashes related to rain in Texas from 1994 to 2018. The fatal crash data was gathered from the Fatality Analysis Reporting System (FARS) database maintained by the National Highway Traffic Safety Administration (NHTSA). Environmental variables used in the analysis include month of the year, time of the day, temperature, and weather condition. The roadway-related factors identified include the posted speed limit, the number of lanes, route sign, and Vehicle Miles Traveled (VMT). The driver-related factors identified include age, gender, and the number of licensed drivers in total. Relative risk analysis was performed to statistically quantify the impact of rainy conditions at the hourly and monthly time scales. On average, rain-related fatal crashes represented about 6.8% of the total fatal crashes. However, the proportion shows higher variability at the annual, monthly, and hourly time scales and seems to be influenced by other factors such as the age and gender of the driver, type of the road, and posted roadway speed limit. Total and rain-related crashes show statistically significant decreasing trends when normalized by the total number of licensed drivers or vehicle miles travelled. The relative risk of a fatal crash during rainy conditions was always greater than 1.0 at hourly, monthly, and annual time scales. However, it shows significant variability at the monthly (1.07 to 2.78) and hourly scales (1.35 to 2.57). The relative risk is higher in less urbanized and drier counties, in general. Gender and age analysis reveals that male and young drivers are more likely to be involved in a fatal crash but less likely to be killed in the crash. Full article

(This article belongs to the Special Issue Hydrometeorological Hazards and Disasters)

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24 pages, 4160 KiB

Open AccessArticle

Intense Cyclones in the Black Sea Region: Change, Variability, Predictability and Manifestations in the Storm Activity

by Veronika N. Maslova, Elena N. Voskresenskaya, Andrey S. Lubkov, Aleksandr V. Yurovsky, Viktor Y. Zhuravskiy and Vladislav P. Evstigneev

Sustainability 2020, 12(11), 4468; https://doi.org/10.3390/su12114468 - 1 Jun 2020

Cited by 10 | Viewed by 3056

Abstract

Cyclonic activity in the midlatitudes is a form of general atmospheric circulation, and the most intense cyclones are the cause of hydrometeorological anomalies that lead to economic damage, casualties and human losses. This paper examines the features of variability of intense cyclonic activity [...] Read more.

Cyclonic activity in the midlatitudes is a form of general atmospheric circulation, and the most intense cyclones are the cause of hydrometeorological anomalies that lead to economic damage, casualties and human losses. This paper examines the features of variability of intense cyclonic activity in the Black Sea region and the examples of their regional manifestations in the storm types. Based on 6-hourly NCEP/NCAR reanalysis data on 1000 hPa geopotential height fields with 2° × 2° spatial resolution and using the methodology by M.Yu. Bardin, objective data were obtained for the identification and estimation of the frequency of deep cyclones (reaching 0.75 and 0.95 quantiles by intensity and depth—intense and extreme cyclones, respectively) for the Black Sea region during the period 1951–2017. Additionally, a specific methodology of more precise cyclone identification based on spherical spline interpolation was successfully applied, and then the two methodologies were compared. The key point of the study is the following: In the background of negative significant linear trends and interdecadal variability (period of about 35 years), typical scales of their interannual variability on the periods of about 2.5–3.5 and 6–8 years were identified. These periods coincide with the time scales of the North Atlantic Oscillation and El Nino–Southern Oscillation, providing an outlook for further study of the patterns of their connection. Besides, seasonal forecasts of frequency of intense cyclones in the Black Sea region were successfully modeled using an artificial neural network technique. Finally, the case studies of regional manifestations of deep cyclones in the types of storms in the northern Black Sea coast revealed substantial differences in the location of deep centers of cyclones and storm tracks associated with the large-scale pressure fields. Full article

(This article belongs to the Special Issue Hydrometeorological Hazards and Disasters)

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13 pages, 2624 KiB

Open AccessArticle

Perception of Natural Hazards in Rural Areas: A Case Study Examination of the Influence of Seasonal Weather

by Rodrigo Rudge Ramos Ribeiro, Samia Nascimento Sulaiman, Michelle Bonatti, Stefan Sieber and Marcos Alberto Lana

Sustainability 2020, 12(6), 2251; https://doi.org/10.3390/su12062251 - 13 Mar 2020

Cited by 4 | Viewed by 3192

Abstract

A series of factors affect the social perception of hazards in a rural context. This article analyzes how weather conditions influence farmers’ perceptions of natural hazards. In order to understand the relationship between time of year/season and farmers’ concerns about hazards, this study [...] Read more.

A series of factors affect the social perception of hazards in a rural context. This article analyzes how weather conditions influence farmers’ perceptions of natural hazards. In order to understand the relationship between time of year/season and farmers’ concerns about hazards, this study was undertaken. The methodology was based on surveys done to obtain a base-collection of primary data, as well as a meteorological and production analysis using secondary data. A case study of small coffee farms was carried out in a Brazilian municipality with questionnaires applied during the dry season in 2016 and the rainy season in 2017. The results indicate that drought is the main hazard identified by farmers in both weather seasons. Although there were some changes in perceptions observed, the ranking order of the main hazards did not change over the dry and rainy weather seasons. Full article

(This article belongs to the Special Issue Hydrometeorological Hazards and Disasters)

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19 pages, 10913 KiB

Open AccessArticle

Spatial and Temporal Variations in Extreme Precipitation and Temperature Events in the Beijing–Tianjin–Hebei Region of China over the Past Six Decades

by Runze Tong, Wenchao Sun, Quan Han, Jingshan Yu and Zaifeng Tian

Sustainability 2020, 12(4), 1415; https://doi.org/10.3390/su12041415 - 14 Feb 2020

Cited by 15 | Viewed by 2881

Abstract

Extreme weather events can cause a lot of damage in highly populated regions, such as in the Beijing–Tianjin–Hebei Region (BTHR) in northern China. To understand where and how extreme precipitation and temperature events are changing within the BTHR, data for 1959–2018 from 25 [...] Read more.

Extreme weather events can cause a lot of damage in highly populated regions, such as in the Beijing–Tianjin–Hebei Region (BTHR) in northern China. To understand where and how extreme precipitation and temperature events are changing within the BTHR, data for 1959–2018 from 25 mereological stations were used to detect trends in the intensity, frequency, and duration of these events. The results showed that intensity, accumulated amount, the duration of extreme precipitation events, and the annual number of days with precipitation greater than 50 mm decreased on a regional scale over this 60-year period. Changes in extreme precipitation events at most stations were not statistically significant, although a few stations had a significant downward trend. The combined effects of the East Asian summer monsoon and rapid urbanization are possible reasons for these trends. Both the annual maximum and minimum temperature increased on a regional and local scale. The frequency of extreme hot and cold weather also, respectively, increased and decreased, with consistent patterns on a regional and local scale. However, the spatial changes of these trends were different, reflecting the effects of irrigation and urbanization on the regional surface energy balance. These findings are valuable to decisionmakers involved in disaster prevention in the BTHR and in other highly populated regions worldwide. Full article

(This article belongs to the Special Issue Hydrometeorological Hazards and Disasters)

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19 pages, 5456 KiB

Open AccessArticle

Coastal Runoff in the United Arab Emirates—The Hazard and Opportunity

by Khameis Al Abdouli, Khalid Hussein, Dawit Ghebreyesus and Hatim O. Sharif

Sustainability 2019, 11(19), 5406; https://doi.org/10.3390/su11195406 - 29 Sep 2019

Cited by 21 | Viewed by 5955

Abstract

Properly quantifying the potential exposure of hyper-arid regions to climate extremes is fundamental to developing frameworks that can be used to manage these extremes. In the United Arab Emirates (UAE), rapid growth may exacerbate the impacts of climate extremes through urbanization (increased runoff), [...] Read more.

Properly quantifying the potential exposure of hyper-arid regions to climate extremes is fundamental to developing frameworks that can be used to manage these extremes. In the United Arab Emirates (UAE), rapid growth may exacerbate the impacts of climate extremes through urbanization (increased runoff), population and industrial development (more water demand). Water resources management approaches such as Managed Aquifer Recharge (MAR) application may help mitigate both extremes by storing more water from wet periods for use during droughts. In this study, we quantified the volumes of runoff from coastal watersheds discharging to the Gulf of Oman and the Arabian Gulf that could potentially be captured to replenish depleted aquifers along the coast and help reduce the adverse impacts of urban flooding. To this aim, we first downloaded and processed the Integrated Multi-satellite Retrievals for Global Precipitation Measurement Mission (IMERG) rainfall data for a recent wide-spread storm event. The rainfall product was then used as input to hydrologic models of coastal watersheds for estimating the resulting runoff. A multi-criteria decision analysis technique was used to identify areas most prone to runoff accumulation. Lastly, we quantified the volumes of runoff that could potentially be captured from frequency storms of different return periods and how rapid urbanization in the region may increase these runoff volumes creating more opportunities for the replenishment of depleted aquifers. Our results indicate that the average runoff from watersheds discharging to the ocean ranges between 0.11 km³ and 0.48 km³ for the 5-year and 100-year storms, respectively. We also found that these amounts will substantially increase due to rapid urbanization in the coastal regions of the UAE. In addition to water supply augmentation during droughts, potential benefits of application of MAR techniques in the UAE coastal regions may include flood control, mitigation against sea-level rise through subsidence control, reduction of aquifer salinity, rehabilitation of ecosystems, cleansing polluted runoff and preventing excessive runoff into the Gulf that can contribute to red tide events. Full article

(This article belongs to the Special Issue Hydrometeorological Hazards and Disasters)

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19 pages, 4511 KiB

Open AccessArticle

The Influence of River Channel Occupation on Urban Inundation and Sedimentation Induced by Floodwater in Mountainous Areas: A Case Study in the Loess Plateau, China

by Zhihui Wang, Wenyi Yao, Ming Wang, Peiqing Xiao, Jishan Yang, Pan Zhang, Qiuhong Tang, Xiangbing Kong and Jie Wu

Sustainability 2019, 11(3), 761; https://doi.org/10.3390/su11030761 - 1 Feb 2019

Cited by 4 | Viewed by 3335

Abstract

River channel occupation has made cities in the mountainous areas more vulnerable to floodwater out of river channels during rapid global urbanization. A better understanding of the influence of river channel occupation on urban flood disasters can serve as a reference in planning [...] Read more.

River channel occupation has made cities in the mountainous areas more vulnerable to floodwater out of river channels during rapid global urbanization. A better understanding of the influence of river channel occupation on urban flood disasters can serve as a reference in planning effective urban flood control strategies. In this study, taking a flood event that occurred on July 26th, 2017 in a city on the Loess Plateau as an example, field surveys, dynamics detection of the river channel using remote sensing technology, and scenario simulations with a two-dimensional flow and sediment model were utilized to quantitatively analyze the impacts of river channel occupation on urban inundation and sedimentation. The results show that river channel dynamics reduced by construction can be successfully detected using the combination of high-resolution images and Landsat time-series images. The variation of the water level–discharge relationship caused by the narrowing of the river channel and the increase of the flood-water level caused by water-blocking bridges/houses result in a significant reduction of the flood discharge capacity. The contribution of the narrowing of the river channel was 72.3% for the total area inundated by floodwater, whereas 57.2% of urban sedimentation was caused by the construction of bridges/houses within the river channel. Sustainable flood mitigation measures were also recommended according to the investigations and research findings in this study in order to reduce the social, environmental and economic damages caused by floods. Full article

(This article belongs to the Special Issue Hydrometeorological Hazards and Disasters)

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32 pages, 2585 KiB

Open AccessReview

Earthquake Prediction Using Expert Systems: A Systematic Mapping Study

by Rabia Tehseen, Muhammad Shoaib Farooq and Adnan Abid

Sustainability 2020, 12(6), 2420; https://doi.org/10.3390/su12062420 - 19 Mar 2020

Cited by 45 | Viewed by 10630

Abstract

Earthquake is one of the most hazardous natural calamity. Many algorithms have been proposed for earthquake prediction using expert systems (ES). We aim to identify and compare methods, models, frameworks, and tools used to forecast earthquakes using different parameters. We have conducted a [...] Read more.

Earthquake is one of the most hazardous natural calamity. Many algorithms have been proposed for earthquake prediction using expert systems (ES). We aim to identify and compare methods, models, frameworks, and tools used to forecast earthquakes using different parameters. We have conducted a systematic mapping study based upon 70 systematically selected high quality peer reviewed research articles involving ES for earthquake prediction, published between January 2010 and January 2020.To the best of our knowledge, there is no recent study that provides a comprehensive survey of this research area. The analysis shows that most of the proposed models have attempted long term predictions about time, intensity, and location of future earthquakes. The article discusses different variants of rule-based, fuzzy, and machine learning based expert systems for earthquake prediction. Moreover, the discussion covers regional and global seismic data sets used, tools employed, to predict earth quake for different geographical regions. Bibliometric and meta-information based analysis has been performed by classifying the articles according to research type, empirical type, approach, target area, and system specific parameters. Lastly, it also presents a taxonomy of earthquake prediction approaches, and research evolution during the last decade. Full article

(This article belongs to the Special Issue Hydrometeorological Hazards and Disasters)

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