scholarly journals Study on the Classification of Urban Waterlogging Rainstorms and Rainfall Thresholds in Cities Lacking Actual Data

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3328
Author(s):  
Bingyan Ma ◽  
Zening Wu ◽  
Huiliang Wang ◽  
Yuan Guo
Keyword(s):  
Return Period ◽  
Flood Control ◽  
Rainfall Intensity ◽  
Influencing Factor ◽  
Extreme Rainfall ◽  
Observation Data ◽  
Urban Flood ◽  
Storm Water Management Model ◽  
Different Characteristics

Extreme rainfall is the main influencing factor of urban waterlogging. Different types of rainfall often have different characteristics of waterlogging. In order to establish a more accurate urban flood control system, it is necessary to classify waterlogging rainstorms and divide their thresholds. This study proposes a method for applying web crawlers to identify waterlogging rainfall in cities lacking waterlogging observation data and classifying them using the rainfall intensity–duration curves. By selecting appropriate duration thresholds and return period, waterlogging rainstorms are divided into rainfall intensity waterlogging (IW), rainfall amount of waterlogging (AW), combined waterlogging (CW) and no waterlogging (NW). In the application of Zhengzhou City, China, the urban flood control standard and the rainfall time distribution characteristics are used as the basis for the selection of the return period and duration thresholds, and the storm water management model (SWMM) is constructed to simulate the 4 kinds of rainfall characteristics of waterlogging, which is similar to actual situations. It proves that the method is suitable for the classification and thresholds division of different waterlogging rainfall in cities. The results show that the best duration thresholds in Zhengzhou are 20 min (M20) and 60 min (M60), and the best return period standard is 2 a. The thresholds for the 4 types of waterlogging rainstorm are: M20 ≥ 26.47 mm, M60 ≥ 43.80 mm, CW; M20 ≥ 26.47 mm, M60 < 43.80 mm, IW; M20 < 26.47 mm, M60 ≥ 43.80 mm, AW; M20 < 26.47 mm and M60 < 43.80 mm, No waterlogging.

Sewer System for Improving Flood Control in Tokyo: A Step towards a Return Period of 70 Years

1994 ◽  
Vol 29 (1-2) ◽  
pp. 303-310 ◽  
Author(s):  
Kazuyuki Higuchi ◽  
Masahiro Maeda ◽  
Yasuyuki Shintani
Keyword(s):  
Return Period ◽  
Flood Control ◽  
Rainfall Intensity ◽  
Runoff Coefficient ◽  
Large Drop ◽  
Construction Costs ◽  
Sewer System ◽  
Construction Period ◽  
Metropolitan Government ◽  
Under Construction

The Tokyo Metropolitan Government has planned future flood control for a rainfall intensity of 100 mm/hr, which corresponds to a return period of 70 years, and a runoff coefficient of 0.8. Considering that the realization of this plan requires a long construction period and high construction costs, the decision was made to proceed by stages. In the first stage, the improvement of the facilities will be based on a rainfall intensity of 75 mm/hr (presently 50 mm/hr), corresponding to a return period of 17 years, and a runoff coefficient of 0.8. In the next stage the facilities will be improved to accommodate a rainfall intensity of 100 mm/hr. In the Nakano and Suginami regions, which suffer frequently from flooding, the plan of improvement based on a rainfall intensity of 75 mm/hr is being implemented before other areas. This facility will be used as a storage sewer for the time being. The Wada-Yayoi Trunk Sewer, as a project of this plan, will have a diameter of 8 m and a 50 m earth cover. This trunk sewer will be constructed considering several constraints. To resolve these problems, hydraulic experiments as well as an inventory study have been carried out. A large drop shaft for the trunk sewer is under construction.

scholarly journals Modelling and assessment of urban flood hazards based on rainfall intensity-duration-frequency curves reformation

2016 ◽  
Author(s):  
Reza Ghazavi ◽  
Ali Moafi Rabori ◽  
Mohsen Ahadnejad Reveshty
Keyword(s):  
Return Period ◽  
Urban Areas ◽  
Rainfall Intensity ◽  
Flood Hazards ◽  
Return Periods ◽  
Urban Flood ◽  
Design Storm ◽  
Hourly Rainfall ◽  
Idf Curves ◽  
Intensity Duration Frequency

Abstract. Estimate design storm based on rainfall intensity–duration–frequency (IDF) curves is an important parameter for hydrologic planning of urban areas. The main aim of this study was to estimate rainfall intensities of Zanjan city watershed based on overall relationship of rainfall IDF curves and appropriate model of hourly rainfall estimation (Sherman method, Ghahreman and Abkhezr method). Hydrologic and hydraulic impacts of rainfall IDF curves change in flood properties was evaluated via Stormwater Management Model (SWMM). The accuracy of model simulations was confirmed based on the results of calibration. Design hyetographs in different return periods show that estimated rainfall depth via Sherman method are greater than other method except for 2-year return period. According to Ghahreman and Abkhezr method, decrease of runoff peak was 30, 39, 41 and 42 percent for 5-10-20 and 50-year return periods respectively, while runoff peak for 2-year return period was increased by 20 percent.

scholarly journals Predictive Performance Analysis of PDF – IDF Model Types Using Rainfall Observations from Fourteen Gauged Stations

2021 ◽  
pp. 125-143
Author(s):  
Ify L. Nwaogazie ◽  
M. G. Sam ◽  
A. O. David
Keyword(s):  
Return Period ◽  
Flood Control ◽  
Goodness Of Fit ◽  
Rainfall Intensity ◽  
Model Development ◽  
Predictive Performance ◽  
Specific Model ◽  
Data Set ◽  
Pearson Type ◽  
Significant Difference

The design of structures for flood mitigation depends on the adequate estimation of rainfall intensity over a given catchment which is achieved by the rainfall intensity duration frequency modelling. In this study, an extensive comparative analyses were carried out on the predictive performance of three PDF – IDF model types, namely: Gumbel Extreme Value Type 1 (GEVT – 1), Log-Pearson Type 3 (LPT – 3) and Normal Distribution (ND) in 14 selected cities in Southern Nigeria. This is to rank the order of best performance. The principle of general model development was adopted in which rainfall intensities at different durations and specified return periods were used as input data set. This is not same as return period specific model that involves rainfall intensities for various durations and a given return period. The predicted rainfall intensity values with the PDF – IDF model types indicate high goodness of fit (R2) and Mean Squared Errors (MSE) ranging from: (a) R2 = 0.875 – 0.992; MSE = 33.17 – 224.6 for GEVT – 1; (b) R2 = 0.849 – 0.990; MSE = 65.34 – 405.5 for LPT – 3 and (c) R2 = 0.839 – 0.992; MSE = 29.23 – 200.2 for ND. The comparative analysis of all the 42 general models (14 locations versus 3 model types) considered showed that the order of best performance is LPT – 3 1st, GEVT - 1 2nd and ND 3rd for each return period (10, 50 and 100 years). The Kruskal Wallis test of significance indicates that no significant difference exists in the predictive performance of the three General models across the board. This may be due to the fact that the fourteen locations of the study area are bordering with the Atlantic Ocean and seems to have similar climatology. These developed General models are recommended for the computation of intensities in the fourteen locations for the design of flood control structures; and the order of preference should be LPT – 3 > GEVT – 1 > ND.

scholarly journals Case Study of Urban Flood Inundation—Impact of Temporal Variability in Rainfall Events

Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3438
Author(s):  
Ting Li ◽  
Gyuwon Lee ◽  
Gwangseob Kim
Keyword(s):  
Drainage Basin ◽  
Temporal Distribution ◽  
Extreme Rainfall ◽  
Exceedance Probability ◽  
Distribution Characteristics ◽  
Drainage Basins ◽  
Urban Flood ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Storm Water Management Model

This study aimed to calculate and analyze total overflows that accumulate in urban manholes in the target drainage basin of Samsung-dong, Seoul in heavy rainfall events with different temporal distribution characteristics, using the EPA’s Storm Water Management Model (EPA-SWMM model). Inundation behaviors were analyzed using the two-dimensional flood model (FLO-2D). The extreme rainfall events were produced using different exceedance probability Huff distributions for different durations and return periods, such as from 1 to 3 h and 10 years, 50 years, 80 years, 100 years, respectively. The inundation model was validated using the actual flood observations on 21 September 2010 in the Samsung-dong drainage basin. The total overflow amount showed considerable differences according to the different time distribution characteristics, such as the temporal location of the storm peak and the concentration level of the storm. Furthermore, the inundation behaviors were also related to the temporal characteristics of storms. The results illustrated that the consideration of the temporal distribution characteristics of extreme rainfall events is essential for an accurate understanding of the rainfall–runoff response and inundation behavior in urban drainage basins.

scholarly journals Hydrology model establishment of pit lake: Extreme event rainfall data analysis

2021 ◽  
Vol 882 (1) ◽  
pp. 012048
Author(s):  
M A Danasla ◽  
G J Kusuma ◽  
E J Tuheteru ◽  
R S Gautama
Keyword(s):  
Return Period ◽  
Rainfall Intensity ◽  
Extreme Event ◽  
Extreme Rainfall ◽  
Lake Management ◽  
Extreme Conditions ◽  
Pit Lake ◽  
Concentration Time ◽  
Hydrology Model ◽  
Water Filling

Abstract Analysis of water management in the pit lake is divided into two conditions, namely Continuous Events and Extreme Events. The former is an analysis of pit lake management related to the water filling in a pit lake that takes place continuously. Meanwhile, the later is the analysis of pit lake management related to the possibility of extreme conditions that will occur, including extreme rainfall. This study is focused only on the Extreme Event conditions. The Gumbel method is used to calculate the planned return period rainfall T concerning the prediction of extreme rainfall. Meanwhile, for a certain return period, rainfall intensity can be predicted using the Mononobe formula. Based on the result of calculation the Gumbel method, it shows that the planned rainfall for a return period of 10 years is 132.9 mm / day. Then based on the results of the calculation of rainfall intensity using the Mononobe formula, it is obtained that the intensity of rainfall for a return period of 10 years with a concentration-time of 5 minutes is 241.5 mm/hour, while the amount of rainfall intensity with a concentration-time of 300 minutes or 5 hours is 15.8 mm/hour.

scholarly journals Evaluation of Real-Time Water Level Prediction Technology Using Statistical Models for Reducing Urban Flood Risk

2021 ◽  
Vol 16 (3) ◽  
pp. 387-394
Author(s):  
Mitsuhiro Nakashima ◽  
Shoichi Sameshima ◽  
Yuki Kimura ◽  
Midori Yoshimoto ◽  
◽  
...  
Keyword(s):  
Statistical Model ◽  
Water Level ◽  
Real Time ◽  
Flood Control ◽  
Prediction Models ◽  
Prediction Method ◽  
Observation Data ◽  
Urban Flood ◽  
Inland Flooding ◽  
Water Level Prediction

The frequency of localized short-term torrential rains that exceed the planned rainfall is increasing along with inundation damage due to inland flooding. Stepwise inundation measures utilizing existing stock and disaster prevention/mitigation for excessive rainfall are required. In this study, we describe the results of empirical research using a statistical model constructed based on rainfall and water level observation data as a highly accurate water level prediction method suitable for real-time prediction. This is aimed at application in flood control activities and operation support of pump facilities. By comparing and verifying the prediction accuracy between the water level prediction model and the statistical model by Convolutional Neural Network (CNN), which is generally used as an image recognition technology, the usefulness of the statistical model was confirmed. Further improvement in accuracy and widespread use of these water level prediction models are expected.

scholarly journals Urban Flood Control in Sringin Catchment, Semarang City, Central Java Province, Indonesia

2018 ◽  
Vol 4 (2) ◽  
pp. 191
Author(s):  
Ngo Pheaktra ◽  
Istiarto Istiarto ◽  
Rachmad Jayadi
Keyword(s):  
Return Period ◽  
Flood Control ◽  
Flow Analysis ◽  
Drainage System ◽  
Urban Flood ◽  
Central Java ◽  
Design Rainfall ◽  
Prone Area ◽  
Lowland Area ◽  
Flood Prone Area

Sringin is the lowland area located in Semarang city which has been vulnerable to rob flooding from the Java Sea along with flood triggered by the intense amount of rainfall. The case study will further discuss the hydrological analysis, transformation of rational method into flow hydrograph with the design rainfall of 25-year return period, and unsteady flow analysis by HEC-RAS 5.0.3 under existing condition and design condition. The result shows that the design rainfall of 25-year return period measures 173 mm in vertical length and data collected from the office of public work, Semarang city can be used to implement the design scenario with normalization of drainage system and the increase of levee with the freeboard up to 0.75 m is proved to be the solution to the flood inundation in that flood-prone area while the flood under existing condition has caused excessive discharge at downstream up to 9 hours.

scholarly journals Numerical Investigation on Infiltration and Runoff in Unsaturated Soils with Unsteady Rainfall Intensity

Water ◽  
2018 ◽  
Vol 10 (7) ◽  
pp. 914 ◽  
Author(s):  
Jinqiang Tan ◽  
Hongqing Song ◽  
Hailong Zhang ◽  
Qinghui Zhu ◽  
Yi Xing ◽  
...  
Keyword(s):  
Unsaturated Soils ◽  
Flood Control ◽  
Rainfall Intensity ◽  
Flow Model ◽  
Theoretical Foundation ◽  
Urban Flood ◽  
Initial Stage ◽  
Cumulative Infiltration ◽  
Project Construction ◽  
Numerical Approaches

Modeling infiltration into soil and runoff quantitative evaluations is very significant for hydrological applications. In this paper, a flow model of unsaturated soils was established. A computational process of soil water content and runoff prediction was presented that combines an analytical solution with numerical approaches. The solutions have good agreements with the experimental results and other infiltration solutions (Richards numerical solution and classical Green–Ampt solution). We analyzed the effects on cumulative infiltration and runoff under three conditions of rainfall intensity with same average magnitude. These rainfall conditions were (Case 1) decreasing rainfall, (Case 2) steady rainfall, and (Case 3) increasing rainfall, respectively. The results show that the cumulative infiltration in Case 1 is the highest among the three cases. The cumulative runoff under condition of Case 3 is smaller than that of decreasing rainfall at the initial stage, which then becomes larger at the later stage. The time of runoff under the conditions of Case 1 is earliest among the three rainfall conditions, which is about 50% earlier than Case 3. Therefore, project construction for urban flood control should pay more attention to urban flood defense in increasing rainfall weather than other rainfall intensities under the same average magnitude. The approaches presented can be utilized to easily and effectively evaluate infiltration and runoff as a theoretical foundation.

Analysis of the impact of low impact development on runoff from a new district in Korea

2013 ◽  
Vol 68 (6) ◽  
pp. 1315-1321 ◽  
Author(s):  
Jung-min Lee ◽  
Kyoung-hak Hyun ◽  
Jong-soo Choi
Keyword(s):  
Flood Control ◽  
Low Impact Development ◽  
Urban Flood ◽  
Management Planning ◽  
Storm Water Management Model ◽  
Continuous Simulation ◽  
Runoff Volume ◽  
Urban Stormwater Runoff ◽  
Peak Runoff ◽  
The Impact

An analysis of the impact of a low impact development (LID) on runoff was performed using a Storm Water Management Model 5 (SWMM5)–LID model. The SWMM5 package has been developed to facilitate the analysis of the hydrologic impacts of LID facilities. Continuous simulation of urban stormwater runoff from the district which included the LID design was conducted. In order to examine the impact of runoff in the LID district the first, second and third highest ranked flood events over the past 38 years were analyzed. The assessment estimated that a LID system under historical storm conditions would reduce peak runoff by approximately 55–66% and runoff volume by approximately 25–121% in comparison with that before the LID design. The impact on runoff was also simulated under 50, 80 and 100 year return period conditions. Under these conditions, the runoff reductions within the district were estimated to be about 6–16% (peak runoff) and 33–37% (runoff volume) in comparison with conditions prior to the LID. It is concluded from these results that LID is worthy of consideration for urban flood control in future development and as part of sewer and stormwater management planning.

Classification of Observations through Combination of the Dimension Reduction and the Cluster Analysis

2017 ◽  
Vol 7 (8) ◽  
pp. 30
Author(s):  
Hyeuk Kim
Keyword(s):  
Machine Learning ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Unsupervised Learning ◽  
Principal Component ◽  
Component Analysis ◽  
Baseball Players ◽  
Partitioning Around Medoids ◽  
Different Characteristics

Unsupervised learning in machine learning divides data into several groups. The observations in the same group have similar characteristics and the observations in the different groups have the different characteristics. In the paper, we classify data by partitioning around medoids which have some advantages over the k-means clustering. We apply it to baseball players in Korea Baseball League. We also apply the principal component analysis to data and draw the graph using two components for axis. We interpret the meaning of the clustering graphically through the procedure. The combination of the partitioning around medoids and the principal component analysis can be used to any other data and the approach makes us to figure out the characteristics easily.

Sign in / Sign up

Export Citation Format

Share Document