Special Issue "Hydrometeorological Extremes and Its Local Impacts on Human-Environmental Systems"

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Biosphere/Hydrosphere/Land–Atmosphere Interactions".

Deadline for manuscript submissions: closed (15 September 2021) | Viewed by 9636

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Special Issue Editors

Prof. Dr. Jong-Suk Kim
E-Mail Website
Guest Editor
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
Interests: hydroclimatology; hydrosystem modeling; flood/drought frequency analysis; climate variability and change; tropical meteorology; environmental assessment; risk management
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Nirajan Dhakal
E-Mail Website
Guest Editor
Environmental and Health Sciences, Spelman College, 350 Spelman Lane, Atlanta, GA 30314, USA
Interests: hydrological and hydraulic analysis and modeling; hydroclimatology; sustainable water resources management; coupled human–environment system; GIS and remote sensing; risk analysis and decision making
Dr. Changhyun Jun
E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, Chung-Ang University, Seoul 06974, Korea
Interests: hydrological modeling; climate change; disaster and risk management
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Taesam Lee
E-Mail Website
Guest Editor
Department of Civil Engineering, Gyeongsang National University, 501 Jinju-daero, Jinju-si 52828, Gyeongsangnam-do, Korea
Interests: climate change; probability; remote sensing; statistics; stochastic processes; hydrology; water resources

Special Issue Information

Dear Colleagues,

Extreme events of tropical typhoons in summer cause a number of casualties as well as a tremendous amount of social and financial loss. Such climate changes are expected to continue in the 21st century, and the intensity and frequency of typhoons over the Pacific Northwest region will increase. As a result, serious damage over East Asia is expected, and thus, quantitative evaluation of the possible influence and establishment of a disaster-preventive system is urgent. Extreme hydrometeorological events are critically important not only for their episodic impacts, such as floods or droughts, but also for their significant contribution to seasonal freshwater supplies that maintain the integrity of the human and natural system. This Special Issue of Atmosphere focuses on hydrometeorological extremes and their local impacts on human–environment systems. Particularly, we welcome the topics of observational and model-based studies that could provide useful information for infrastructure design, decision making, and policy to achieve our goals of enhancing the resilience of human–environment systems to climate change and increased variability.

Prof. Dr. Jong-Suk Kim
Prof. Dr. Nirajan Dhakal
Prof. Dr. Changhyun Jun
Prof. Dr. Taesam Lee
Guest Editors

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Keywords

  • hydrometeorological extremes
  • tropical typhoons
  • prediction of extreme events
  • climate variability and change
  • vulnerability analysis
  • nonstationary frequency analysis
  • environmental assessment and risk management

Published Papers (9 papers)

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Research

Article
Copula-Based Drought Monitoring and Assessment According to Zonal and Meridional Temperature Gradients
Atmosphere 2021, 12(8), 1066; https://doi.org/10.3390/atmos12081066 - 20 Aug 2021
Cited by 1 | Viewed by 526
Abstract
Drought is one of the most severe natural disasters. However, many of its characteristic variables have complex nonlinear relationships. Therefore, it is difficult to construct effective drought assessment models. In this study, we analyzed regional drought characteristics in China to identify their relationship [...] Read more.
Drought is one of the most severe natural disasters. However, many of its characteristic variables have complex nonlinear relationships. Therefore, it is difficult to construct effective drought assessment models. In this study, we analyzed regional drought characteristics in China to identify their relationship with changes in meridional and zonal temperature gradients. Drought duration and severity were extracted according to standardized precipitation evapotranspiration index (SPEI) drought grades. Trends in drought duration and severity were detected by the Mann-Kendall test for the period of 1979–2019; they showed that both parameters had been steadily increasing during that time. Nevertheless, the increasing trend in drought severity was particularly significant for northwest and southwest China. A composite analysis confirmed the relationships between drought characteristics and temperature gradients. The northwest areas were relatively less affected by temperature gradients, as they are landlocked, remote from the ocean, and only slightly influenced by the land–ocean thermal contrast (LOC) and the meridional temperature gradient (MTG). The impacts of LOC and MTG on drought duration and severity were positive in the southwest region of China but negative in the northeast. As there was a strong correlation between drought duration and severity, we constructed a 2D copula function model of these parameters. The Gaussian, HuslerReiss, and Frank copula functions were the most appropriate distributions for the northeast, northwest, and southwest regions, respectively. As drought processes are highly complex, the present study explored the internal connections between drought duration and severity and their responses to meteorological conditions. In this manner, an accurate method of predicting future drought events was developed. Full article
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Article
Climate Variability, Dengue Vector Abundance and Dengue Fever Cases in Dhaka, Bangladesh: A Time-Series Study
Atmosphere 2021, 12(7), 905; https://doi.org/10.3390/atmos12070905 - 14 Jul 2021
Cited by 1 | Viewed by 1058
Abstract
Numerous studies on climate change and variability have revealed that these phenomena have noticeable influence on the epidemiology of dengue fever, and such relationships are complex due to the role of the vector—the Aedes mosquitoes. By undertaking a step-by-step approach, the present study [...] Read more.
Numerous studies on climate change and variability have revealed that these phenomena have noticeable influence on the epidemiology of dengue fever, and such relationships are complex due to the role of the vector—the Aedes mosquitoes. By undertaking a step-by-step approach, the present study examined the effects of climatic factors on vector abundance and subsequent effects on dengue cases of Dhaka city, Bangladesh. Here, we first analyzed the time-series of Stegomyia indices for Aedes mosquitoes in relation to temperature, rainfall and relative humidity for 2002–2013, and then in relation to reported dengue cases in Dhaka. These data were analyzed at three sequential stages using the generalized linear model (GLM) and generalized additive model (GAM). Results revealed strong evidence that an increase in Aedes abundance is associated with the rise in temperature, relative humidity, and rainfall during the monsoon months, that turns into subsequent increases in dengue incidence. Further we found that (i) the mean rainfall and the lag mean rainfall were significantly related to Container Index, and (ii) the Breteau Index was significantly related to the mean relative humidity and mean rainfall. The relationships of dengue cases with Stegomyia indices and with the mean relative humidity, and the lag mean rainfall were highly significant. In examining longitudinal (2001–2013) data, we found significant evidence of time lag between mean rainfall and dengue cases. Full article
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Article
Decision-Tree-Based Classification of Lifetime Maximum Intensity of Tropical Cyclones in the Tropical Western North Pacific
Atmosphere 2021, 12(7), 802; https://doi.org/10.3390/atmos12070802 - 22 Jun 2021
Cited by 3 | Viewed by 622
Abstract
The National Typhoon Center of the Korea Meteorological Administration developed a statistical–dynamical typhoon intensity prediction model for the western North Pacific, the CSTIPS-DAT, using a track-pattern clustering technique. The model led to significant improvements in the prediction of the intensity of tropical cyclones [...] Read more.
The National Typhoon Center of the Korea Meteorological Administration developed a statistical–dynamical typhoon intensity prediction model for the western North Pacific, the CSTIPS-DAT, using a track-pattern clustering technique. The model led to significant improvements in the prediction of the intensity of tropical cyclones (TCs). However, relatively large errors have been found in a cluster located in the tropical western North Pacific (TWNP), mainly because of the large predictand variance. In this study, a decision-tree algorithm was employed to reduce the predictand variance for TCs in the TWNP. The tree predicts the likelihood of a TC reaching a maximum lifetime intensity greater than 70 knots at its genesis. The developed four rules suggest that the pre-existing ocean thermal structures along the track and the latitude of a TC’s position play significant roles in the determination of its intensity. The developed decision-tree classification exhibited 90.0% and 80.5% accuracy in the training and test periods, respectively. These results suggest that intensity prediction with the CSTIPS-DAT can be further improved by developing independent statistical models for TC groups classified by the present algorithm. Full article
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Article
Spatial Recognition of Regional Maximum Floods in Ungauged Watersheds and Investigations of the Influence of Rainfall
Atmosphere 2021, 12(7), 800; https://doi.org/10.3390/atmos12070800 - 22 Jun 2021
Cited by 1 | Viewed by 616
Abstract
This study primarily aims to develop a method for estimating the range of flood sizes in small and medium ungauged watersheds in local river streams. In practice, several water control projects have insufficient streamflow information. To compensate for the lack of data, the [...] Read more.
This study primarily aims to develop a method for estimating the range of flood sizes in small and medium ungauged watersheds in local river streams. In practice, several water control projects have insufficient streamflow information. To compensate for the lack of data, the streamflow propagation method (SPM) provides streamflow information for ungauged watersheds. The ranges of flood sizes for ungauged watersheds were generated using a specific flood distribution analysis based on the obtained streamflow data. Furthermore, the influence of rainfall information was analyzed to characterize the patterns of specific flood distributions. Rainfall location, intensity, and duration highly affected the shape of the specific flood distribution. Concentrated rainfall locations affected the patterns of the maximum specific flood distribution. The shape and size of the minimum specific flood distribution were dependent on the rainfall intensity and duration. The Creager envelope curve was used to generate equations for the maximum/minimum specific flood distribution for the study site. The ranges of the specific flood distributions were produced for each watershed size. Full article
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Article
Reanalysis Product-Based Nonstationary Frequency Analysis for Estimating Extreme Design Rainfall
Atmosphere 2021, 12(2), 191; https://doi.org/10.3390/atmos12020191 - 31 Jan 2021
Cited by 3 | Viewed by 750
Abstract
Nonstationarity is one major issue in hydrological models, especially in design rainfall analysis. Design rainfalls are typically estimated by annual maximum rainfalls (AMRs) of observations below 50 years in many parts of the world, including South Korea. However, due to the lack of [...] Read more.
Nonstationarity is one major issue in hydrological models, especially in design rainfall analysis. Design rainfalls are typically estimated by annual maximum rainfalls (AMRs) of observations below 50 years in many parts of the world, including South Korea. However, due to the lack of data, the time-dependent nature may not be sufficiently identified by this classic approach. Here, this study aims to explore design rainfall with nonstationary condition using century-long reanalysis products that help one to go back to the early 20th century. Despite its useful representation of the past climate, the reanalysis products via observational data assimilation schemes and models have never been tested in representing the nonstationary behavior in extreme rainfall events. We used daily precipitations of two century-long reanalysis datasets as the ERA-20c by the European Centre for Medium-Range Weather Forecasts (ECMWF) and the 20th century reanalysis (20CR) by the National Oceanic and Atmospheric Administration (NOAA). The AMRs from 1900 to 2010 were derived from the grids over South Korea. The systematic errors were downgraded through quantile delta mapping (QDM), as well as conventional stationary quantile mapping (SQM). The evaluation result of the bias-corrected AMRs indicated the significant reduction of the errors. Furthermore, the AMRs present obvious increasing trends from 1900 to 2010. With the bias-corrected values, we carried out nonstationary frequency analysis based on the time-varying location parameters of generalized extreme value (GEV) distribution. Design rainfalls with certain return periods were estimated based on the expected number of exceedance (ENE) interpretation. Although there is a significant range of uncertainty, the design quantiles by the median parameters showed the significant relative difference, from −30.8% to 42.8% for QDM, compared with the quantiles by the multi-decadal observations. Even though the AMRs from the reanalysis products are challenged by various errors such as quantile mapping (QM) and systematic errors, the results from the current study imply that the proposed scheme with employing the reanalysis product might be beneficial to predict the future evolution of extreme precipitation and to estimate the design rainfall accordingly. Full article
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Article
Changes in Intensity and Variability of Tropical Cyclones over the Western North Pacific and Their Local Impacts under Different Types of El Niños
Atmosphere 2021, 12(1), 59; https://doi.org/10.3390/atmos12010059 - 31 Dec 2020
Cited by 2 | Viewed by 979
Abstract
This study investigated the effects of El Niño events on tropical cyclone (TC) characteristics over the western North Pacific (WNP) region. First, TC characteristics associated with large-scale atmospheric phenomena (i.e., genesis position, frequency, track, intensity, and duration) were investigated in the WNP in [...] Read more.
This study investigated the effects of El Niño events on tropical cyclone (TC) characteristics over the western North Pacific (WNP) region. First, TC characteristics associated with large-scale atmospheric phenomena (i.e., genesis position, frequency, track, intensity, and duration) were investigated in the WNP in relation to various types of El Niño events—moderate central Pacific (MCP), moderate eastern Pacific (MEP), and strong basin-wide (SBW). Subsequently, the seasonal and regional variability of TC-induced rainfall across China was analyzed to compare precipitation patterns under the three El Niño types. When extreme El Niño events of varying degrees occurred, the local rainfall varied during the developmental and decaying years. The development of MEP and SBW was associated with a distinct change in TC-induced rainfall. During MEP development, TC-induced rainfall occurred in eastern and northeastern China, whereas in SBW, TC-induced heavy rainfall occurred in southwest China. During SBW development, the southwestern region was affected by TCs over a long period, with the eastern and northeastern regions being affected significantly fewer days. During El Niño decay, coastal areas were relatively more affected by TCs during MCP events, and the Pearl River basin was more affected during SBW events. This study’s results could help mitigate TC-related disasters and improve water-supply management. Full article
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Article
Complexity of Forces Driving Trend of Reference Evapotranspiration and Signals of Climate Change
Atmosphere 2020, 11(10), 1081; https://doi.org/10.3390/atmos11101081 - 10 Oct 2020
Cited by 38 | Viewed by 1639
Abstract
Understanding the trends of reference evapotranspiration (ETo) and its influential meteorological variables due to climate change is required for studying the hydrological cycle, vegetation restoration, and regional agricultural production. Although several studies have evaluated these trends, they suffer from a [...] Read more.
Understanding the trends of reference evapotranspiration (ETo) and its influential meteorological variables due to climate change is required for studying the hydrological cycle, vegetation restoration, and regional agricultural production. Although several studies have evaluated these trends, they suffer from a number of drawbacks: (1) they used data series of less than 50 years; (2) they evaluated the individual impact of a few climatic variables on ETo, and thus could not represent the interactive effects of all forces driving trends of ETo; (3) they mostly studied trends of ETo and meteorological variables in similar climate regions; (4) they often did not eliminate the impact of serial correlations on the trends of ETo and meteorological variables; and finally (5) they did not study the extremum values of meteorological variables and ETo. This study overcame the abovementioned shortcomings by (1) analyzing the 50-year (1961–2010) annual trends of ETo and 12 meteorological variables from 18 study sites in contrasting climate types in Iran, (2) removing the effect of serial correlations on the trends analysis via the trend-free pre-whitening approach, (3) determining the most important meteorological variables that control the variations of ETo, and (4) evaluating the coincidence of annual extremum values of meteorological variables and ETo. The results showed that ETo and several meteorological variables (namely wind speed, vapor pressure deficit, cloudy days, minimum relative humidity, and mean, maximum and minimum air temperature) had significant trends at the confidence level of 95% in more than 50% of the study sites. These significant trends were indicative of climate change in many regions of Iran. It was also found that the wind speed (WS) had the most significant influence on the trend of ETo in most of the study sites, especially in the years with extremum values of ETo. In 83.3% of the study sites (i.e., all arid, Mediterranean and humid regions and 66.7% of semiarid regions), both ETo and WS reached their extremum values in the same year. The significant changes in ETo due to WS and other meteorological variables have made it necessary to optimize cropping patterns in Iran. Full article
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Article
Increasing Neurons or Deepening Layers in Forecasting Maximum Temperature Time Series?
Atmosphere 2020, 11(10), 1072; https://doi.org/10.3390/atmos11101072 - 09 Oct 2020
Cited by 9 | Viewed by 1061
Abstract
Weather forecasting, especially that of extreme climatic events, has gained considerable attention among researchers due to their impacts on natural ecosystems and human life. The applicability of artificial neural networks (ANNs) in non-linear process forecasting has significantly contributed to hydro-climatology. The efficiency of [...] Read more.
Weather forecasting, especially that of extreme climatic events, has gained considerable attention among researchers due to their impacts on natural ecosystems and human life. The applicability of artificial neural networks (ANNs) in non-linear process forecasting has significantly contributed to hydro-climatology. The efficiency of neural network functions depends on the network structure and parameters. This study proposed a new approach to forecasting a one-day-ahead maximum temperature time series for South Korea to discuss the relationship between network specifications and performance by employing various scenarios for the number of parameters and hidden layers in the ANN model. Specifically, a different number of trainable parameters (i.e., the total number of weights and bias) and distinctive numbers of hidden layers were compared for system-performance effects. If the parameter sizes were too large, the root mean square error (RMSE) would be generally increased, and the model’s ability was impaired. Besides, too many hidden layers would reduce the system prediction if the number of parameters was high. The number of parameters and hidden layers affected the performance of ANN models for time series forecasting competitively. The result showed that the five-hidden layer model with 49 parameters produced the smallest RMSE at most South Korean stations. Full article
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Article
Integrated Flood Forecasting and Warning System against Flash Rainfall in the Small-Scaled Urban Stream
Atmosphere 2020, 11(9), 971; https://doi.org/10.3390/atmos11090971 - 11 Sep 2020
Cited by 5 | Viewed by 1114
Abstract
The flood forecasting and warning system enable an advanced warning of flash floods and inundation depths for disseminating alarms in urban areas. Therefore, in this study, we developed an integrated flood forecasting and warning system combined inland-river that systematized technology to quantify flood [...] Read more.
The flood forecasting and warning system enable an advanced warning of flash floods and inundation depths for disseminating alarms in urban areas. Therefore, in this study, we developed an integrated flood forecasting and warning system combined inland-river that systematized technology to quantify flood risk and flood forecasting in urban areas. LSTM was used to predict the stream depth in the short-term inundation prediction. Moreover, rainfall prediction by radar data, a rainfall-runoff model combined inland-river by coupled SWMM and HEC-RAS, automatic simplification module of drainage networks, automatic calibration module of SWMM parameter by Dynamically Dimensioned Search (DDS) algorithm, and 2-dimension inundation database were used in very short-term inundation prediction to warn and convey the flood-related data and information to communities. The proposed system presented better forecasting results compared to the Seoul integrated disaster prevention system. It can provide an accurate water level for 30 min to 90 min lead times in the short-term inundation prediction module. And the very short-term inundation prediction module can provide water level across a stream for 10 min to 60 min lead times using forecasting rainfall by radar as well as inundation risk areas. In conclusion, the proposed modules were expected to be useful to support inundation forecasting and warning systems. Full article
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