Urban floods pose significant challenges to cities worldwide, driven by the interplay between urbanization and climate change. This review examines recent studies of urban floods to understand their causes, impacts, and potential mitigation strategies. Urbanization, with its increase in impermeable surfaces and altered drainage patterns, disrupts natural water flow, exacerbating surface runoff during intense rainfall events. The impacts of urban floods are far-reaching, affecting lives, infrastructure, the economy, and the environment. Loss of life, property damage, disruptions to critical services, and environmental consequences underscore the urgency of effective urban flood management. To mitigate urban floods, integrated flood management strategies are crucial. Sustainable urban planning, green infrastructure, and improved drainage systems play pivotal roles in reducing flood vulnerabilities. Early warning systems, emergency response planning, and community engagement are essential components of flood preparedness and resilience. Looking to the future, climate change projections indicate increased flood risks, necessitating resilience and adaptation measures. Advances in research, data collection, and modeling techniques will enable more accurate flood predictions, thus guiding decision-making. In conclusion, urban flooding demands urgent attention and comprehensive strategies to protect lives, infrastructure, and the economy.
KSCE Journal of Civil and Environmental Engineering Research
/
v.30
no.5B
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pp.429-435
/
2010
This study proposed a methodology for evaluating the radar rainfall data, whose basic idea is similar to the analysis of variance in statistics. This method enables us to represent separately the error from the bias and that from the data variability. The proposed method was then applied to two storm events for its evaluation. As results, the error from the bias was found to comprises most of the raw radar data error, which becomes significantly decreased in the quality improved cases. On the other hand, the error from the data variability was rather increased due to the quality improvement procedure. The proposed methodology was found to be effective for evaluating the data quality of a storm event for steps of quality improvement, but has a limitation for comparing qualities of storm events. This limitation should be implemented for its general application.
Vahed Ghiasi;Nur Irfah Mohd Pauzi;Shahab Karimi;Mahyar Yousefi
Geomechanics and Engineering
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v.34
no.3
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pp.267-284
/
2023
Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.
Proceedings of the Korea Water Resources Association Conference
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2022.05a
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pp.334-334
/
2022
Improvement of old-fashioned rain gauge systems for automatic, timely, continuous, and accurate precipitation observation is highly essential for weather/climate prediction and natural hazards early warning, since the occurrence frequency and intensity of heavy and extreme precipitation events (especially floods) are recently getting more increase and severe worldwide due to climate change. Although rain gauge accuracy of 0.1 mm is recommended by the World Meteorological Organization (WMO), the traditional rain gauges in both weighting and tipping bucket types are often unable to meet that demand due to several existing technical limitations together with higher production and maintenance costs. Therefore, we aim to introduce a newly developed and cost-effective hybrid rain gauge system at 0.1 mm accuracy that combines advantages of weighting and tipping bucket types for continuous, automatic, and accurate precipitation observation, where the errors from long-term load cells and external environmental sources (e.g., winds) can be removed via an automatic drainage system and artificial intelligence-based data quality control procedure. Our rain gauge system consists of an instrument unit for measuring precipitation, a communication unit for transmitting and receiving measured precipitation signals, and a database unit for storing, processing, and analyzing precipitation data. This newly developed rain gauge was designed according to the weather instrument criteria, where precipitation amounts filled into the tipping bucket are measured considering the receiver's diameter, the maximum measurement of precipitation, drainage time, and the conductivity marking. Moreover, it is also designed to transmit the measured precipitation data stored in the PCB through RS232, RS485, and TCP/IP, together with connecting to the data logger to enable data collection and analysis based on user needs. Preliminary results from a comparison with an existing 1.0-mm tipping bucket rain gauge indicated that our developed rain gauge has an excellent performance in continuous precipitation observation with higher measurement accuracy, more correct precipitation days observed (120 days), and a lower error of roughly 27 mm occurred during the measurement period.
Kim, Song-Hyun;Nam, Won-Ho;Jeon, Min-Gi;Hong, Eun-Mi;Oh, Chansung
Journal of The Korean Society of Agricultural Engineers
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v.66
no.4
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pp.1-15
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2024
In recent years, climate change has been responsible for unusual weather patterns on a global scale. Droughts, natural disasters triggered by insufficient rainfall, can inflict significant social and economic consequences on the entire agricultural sector due to their widespread occurrence and the challenge in accurately predicting their onset. The frequency of drought occurrences in South Korea has been rapidly increasing since 2000, with notably severe droughts hitting regions such as Incheon, Gyeonggi, Gangwon, Chungbuk, and Gyeongbuk in 2015, resulting in significant agricultural and social damage. To prepare for future drought occurrences resulting from climate change, it is essential to develop long-term drought predictions and implement corresponding measures for areas prone to drought. The Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report outlines a climate change scenario under the Shared Socioeconomic Pathways (SSPs), which integrates projected future socio-economic changes and climate change mitigation efforts derived from the Coupled Model Intercomparison Project 6 (CMIP6). SSPs encompass a range of factors including demographics, economic development, ecosystems, institutions, technological advancements, and policy frameworks. In this study, various drought indices were calculated using SSP scenarios derived from 18 CMIP6 global climate models. The SSP5-8.5 scenario was employed as the climate change scenario, and meteorological drought indices such as the Standardized Precipitation Index (SPI), Self-Calibrating Effective Drought Index (scEDI), and Standardized Precipitation Evapotranspiration Index (SPEI) were utilized to analyze the prediction and variability of future drought occurrences in South Korea.
Although the dominant land use at the Imha-dam watershed is forest areas, soil erosion has been increasing because of intensive agricultural activities performed at the fields located along the stream for easy-access to water supply and relatively favorable topography. In addition, steep topography at the Imha-dam watershed is also contributing increased soil erosion and sediment loads. At the Imha-dam watershed, outflow has increased sharply by the typhoons Rusa and Maemi in 2002, 2003 respectively. In this study, the Soil and Water Assessment Tool (SWAT) model was evaluated for simulation of flow and sediment behaviors with long-term temporal and spatial conditions. The precipitation data from eight precipitation observatories, located at Ilwol, Subi and etc., were used. There was no significant difference in monthly rainfall for 8 locations. However, there was slight differences in rainfall amounts and patterns in 2003 and 2004. The topographical map at 1:5000 scale from the National Geographic Information Institute was used to define watershed boundaries, the detailed soil map at 1:25,000 scale from the National Institute of Highland Agriculture and the land cover data from the Korea Institute of Water and Environment were used to simulate the hydrologic response and soil erosion and sediment behaviors. To evaluate hydrologic component of the SWAT model, calibration was performed for the period from Jan. 2002 to Dec. 2003, and validation for Jan. 2004 to Apr. 2005. The $R^2$ value and El value were 0.93 and 0.90 respectively for calibration period, and the $R^2$ value and El value for validation were 0.73 and 0.68 respectively. The $R^2$ value and El value of sediment yield data with the calibrated parameters was 0.89 and 0.84 respectively. The comparisons with the measured data showed that the SWAT model is applicable to simulate hydrology and sediment behaviors at Imha dam watershed. With proper representation of the Best Management Practices (BM Ps) in the SWAT model, the SWAT can be used for pre-evaluation of the cost-effective and sustainable soil erosion BMPs to solve sediment issues at the Imha-dam watershed. In Korea, the Universal Soil Loss Equation (USLE) has been used to estimate the soil loss for over 30 years. However, there are limitations in the field scale mdel, USLE when applied for watershed. Also, the soil loss changes temporarily and spatially, for example, the Imha-dam watershed. Thus, the SW AT model, capable of simulating hydrologic and soil erosion/sediment behaviors temporarily and spatially at watershed scale, should be used to solve the muddy water issues at the Imha-dam watershed to establish more effective muddy water reduction countermeasure.
Proceedings of the Korea Water Resources Association Conference
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2005.05b
/
pp.1403-1407
/
2005
In order to analyze the water storage of the Daecheong dam after constructing the Yongdam dam situated in upstream, a daily cascaded simulation model for analyzing water storages in the Yongdam-Daecheong dams was developed. Operation scenarios of the Yongdam dam were selected to 8 cases with the combinations of downstream outflows and water supplies to the Jeonju region. Daily water storages in the Daecheong dam was analyzed daily by simulating from 1983 to 2004. The results are summarized as follows. Firstly, water supplies from the Daecheong dam were analyzed to amount $1,964.2Mm^3$ on a yearly average in case without the Yongdam dam. In case with the Yongdam dam, water supplies from the Daecheong dam were analyzed to amount $1,858.7\~1,927.3Mm^3$ in case with downstream outflow of $5\;m^3$ is, and were analyzed to amount $1,994.9\~2,017.8Mm^3$ in case with downstream outflow of $10\;m^3/s $. These values are compared to $1,649Mm^3$ applied in design. Secondly, reservoir use rate which was defined rate of water supply to effective water storage reached $241.3\% in case without the Yongdam dam. In case with the Yongdam dam, reservoir use rate reached $228.3\~236.8\% In case with downstream outflow of $5\;m^3/s$, and reached $245.1\~247.9\% in case with downstream outflow of $10\;m^3/s$. Thirdly, runoff rate which is defined rate of dam inflow to areal rainfall reached $57.3\% in case without the Yongdam dam. In case with the Yongdam dam, reservoir use rate reached $62.0\~68.4\% in case with downstream outflow of $5\;m^3/s$, and reached $64.1\~68.5\% in case with downstream outflow of $10\;m^3/s$. Fourth, in case with downstream outflow of $10\;m^3/s$ is from the Yongdam dam, appropriate water supply amounts to the Jeonju region were analyzed to only $0.50Mm^3/day$ from the daily simulation of water storages in the Yongdam dam. Comprehensively, water supply capacity of the Daecheong dam was analyzed to affect in small amounts in spite of the construction of the Yonsdam dam. It is effected to achieve the effective water management of the Yongdam dam and the Daecheong dam by using the developed cascaded model.
In this study, factors that influence water supply capacities of dams are extracted using factor analysis, and multiple regression equations for estimating water supply capacities of dams are developed using the analysis results. Twenty-one multi-purpose dams and twelve Municipal and Industrial (M&I) water supply dams are selected for case studies, and eight variables influencing water supply capacities of dams, namely: watershed area, inflow, effective reservoir storage, grade on amount of M&I water supply, grade on amount of agricultural water supply, grade on amount of in-stream flow supply, grade on river administration, and grade on average rainfall, are determined. Two case studies for multi-purpose dams and M&I water supply dams are performed, employing factor analysis, respectively. For the two cases, preliminary tests, such as reviewing matrix of correlation coefficient, Bartlett's test of sphericity, and Kaiser-Meyer-Olkin (KMO) test, are conducted to evaluate the suitability of the variables for factor analysis. In case of multi-purpose dams, variables are grouped into three factors; M&I water supply dams, two factors. The factors are rotated using Varimax method, and then factor loading of each variable is computed. The results show that the variables influencing water supply capacities of dams are reasonably selected and appropriately grouped into factors. In addition, multiple regression equations for predicting the amounts of annual water supply of dams are established using the factor scores as explanatory variables, it is identified that the models' accuracies are high, and their applications to determining effective storage capacity of a dam during dam planning and design steps are presented. Consequently, it is thought that the variables and factors are useful for dam planning and dam design.
Proceedings of the Korea Water Resources Association Conference
/
2008.05a
/
pp.495-499
/
2008
This study developed a determination method for a rainwater retention-pumping combination system for roof runoff control. The outflow and stored water volume in the rainwater system was simulated using a water balance equation. Its result is presented in the TPP (Tank capcity-Peak outflow-Pumping rate) curves for rainfall return periods. In a case study on reduction of the peak flow rate of 100-year return period to 5-year in Seoul, The range of pumping rate for $100m^2$ roof area is determined as $0{\sim}25{\ell}$/min. Additionally, retention volume of $8.5{\sim}10m^3$ can be combined with the pumping rate range. That is to say an effective combination of a retention-pumping system capacity can be determined from a system of $8.5m^3$ tank with $25{\ell}$/min to $10m^3$ tank without pump. Using the TPP curves, engineers can determine the effective combination range of retention & pumping system capacity. Furthermore, that can be helpful to decide a detail system capacity for field condition.
Kim, Chang-Gi;Choung, Yeon-Sook;Joo, Kwang-Yeong;Lee, Kyu-Song
Journal of Ecology and Environment
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v.29
no.3
/
pp.295-303
/
2006
Clear-cut followed by tree planting has been a conventional management practice in burned forests in Korea. Because this can considerably increase soil loss, hillslope treatments may be needed in order to improve soil stability at poorly regenerating areas. This paper reviews the effects of hillslope treatments, such as seeding, mulching and log erosion barriers, which have been applied to restore vegetation and conserve soil in burned forests in North America and Europe. Seeding has been the most common method for postfire restoration. However, the effects of seeding on vegetation cover and soil erosion are not clear and seeding with non-native species has been reported to inhibit regeneration of native vegetation. Mulching has been found to be effective at reducing soil erosion. However, this also can introduce non-native plant species and inhibit native plant regeration. Although studies on the effect of log erosion barriers are very few, it appears that log erosion barriers are effective in the period of little rainfall. Hillslope treatments for postfire restoration is not necessary for naturally regenerating areas and therefore, they should be restricted to the areas where regeneration potential is low and runoff and soil loss is considerable. Long-term monitoring is needed to assess the effectiveness of hillslope treatments on soil erosion, the introduction of non-native plant species and the inhibition of natural plant regeneration.
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