scholarly journals Using Tabu Search Adjusted with Urban Sewer Flood Simulation to Improve Pluvial Flood Warning via Rainfall Thresholds

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 348 ◽  
Author(s):  
Hao-Yu Liao ◽  
Tsung-Yi Pan ◽  
Hsiang-Kuan Chang ◽  
Chi-Tai Hsieh ◽  
Jihn-Sung Lai ◽  
...  
Keyword(s):  
Tabu Search ◽  
Overland Flow ◽  
Search Algorithm ◽  
Warning System ◽  
Extreme Rainfall ◽  
Initial Boundary ◽  
Rainfall Threshold ◽  
Hydrodynamic Modeling ◽  
Rainfall Thresholds ◽  
Flood Warning

Pluvial floods are the most frequent natural hazard impacting urban cities because of extreme rainfall intensity within short duration. Owing to the complex interaction between rainfall, drainage systems and overland flow, pluvial flood warning poses a challenge for many metropolises. Although physical-based flood inundation models could identify inundated locations, hydrodynamic modeling is limited in terms of computational costs and sophisticated calibration. Thus, herein, a quick pluvial flood warning system using rainfall thresholds for central Taipei is developed. A tabu search algorithm is implemented with hydrological-analysis-based initial boundary conditions to optimize rainfall thresholds. Furthermore, a cross test is adopted to evaluate the effect of each rainfall event on rainfall threshold optimization. Urban sewer flood is simulated via hydrodynamic modeling with calibration using crowdsourced data. The locations and time of occurrence of pluvial floods can be obtained to increase the quality of observed data that dominate the accuracy of pluvial flood warning when using rainfall thresholds. The optimization process is a tabu search based on flood reports and observed data for six flood-prone districts in central Taipei. The results show that optimum rainfall thresholds can be efficiently determined through tabu search and the accuracy of the issued flood warnings can be significantly improved.

scholarly journals Rainfall Threshold Estimation and Landslide Forecasting for Kalimpong, India Using SIGMA Model

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1195 ◽  
Author(s):  
Minu Treesa Abraham ◽  
Neelima Satyam ◽  
Sai Kushal ◽  
Ascanio Rosi ◽  
Biswajeet Pradhan ◽  
...  
Keyword(s):  
Early Warning ◽  
Sigma Model ◽  
Warning System ◽  
Daily Rainfall ◽  
Early Warning Systems ◽  
Rainfall Threshold ◽  
Integrated System ◽  
Warning Systems ◽  
Rainfall Forecasting ◽  
Rainfall Thresholds

Rainfall-induced landslides are among the most devastating natural disasters in hilly terrains and the reduction of the related risk has become paramount for public authorities. Between the several possible approaches, one of the most used is the development of early warning systems, so as the population can be rapidly warned, and the loss related to landslide can be reduced. Early warning systems which can forecast such disasters must hence be developed for zones which are susceptible to landslides, and have to be based on reliable scientific bases such as the SIGMA (sistema integrato gestione monitoraggio allerta—integrated system for management, monitoring and alerting) model, which is used in the regional landslide warning system developed for Emilia Romagna in Italy. The model uses statistical distribution of cumulative rainfall values as input and rainfall thresholds are defined as multiples of standard deviation. In this paper, the SIGMA model has been applied to the Kalimpong town in the Darjeeling Himalayas, which is among the regions most affected by landslides. The objectives of the study is twofold: (i) the definition of local rainfall thresholds for landslide occurrences in the Kalimpong region; (ii) testing the applicability of the SIGMA model in a physical setting completely different from one of the areas where it was first conceived and developed. To achieve these purposes, a calibration dataset of daily rainfall and landslides from 2010 to 2015 has been used; the results have then been validated using 2016 and 2017 data, which represent an independent dataset from the calibration one. The validation showed that the model correctly predicted all the reported landslide events in the region. Statistically, the SIGMA model for Kalimpong town is found to have 92% efficiency with a likelihood ratio of 11.28. This performance was deemed satisfactory, thus SIGMA can be integrated with rainfall forecasting and can be used to develop a landslide early warning system.

scholarly journals Rainfall Event–Duration Thresholds for Landslide Occurrences in China

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 494 ◽  
Author(s):  
Shuangshuang He ◽  
Jun Wang ◽  
Songnan Liu
Keyword(s):  
Rainy Season ◽  
Regression Line ◽  
Warning System ◽  
Rainfall Threshold ◽  
Rainfall Event ◽  
Mean Annual Precipitation ◽  
National Scale ◽  
Rainfall Thresholds ◽  
Event Duration ◽  
Landslide Occurrence

A rainfall threshold for landslide occurrence at a national scale in China has rarely been developed in the early warning system for landslides. Based on 771 landslide events that occurred in China during 1998–2017, four groups of rainfall thresholds at different quantile levels of the quantile regression for landslide occurrences in China are defined, which include the original rainfall event–duration (E–D) thresholds and normalized (the accumulated rainfall is normalized by mean annual precipitation) (EMAP–D) rainfall thresholds based on the merged rainfall and the Climate Prediction Center Morphing technique (CMORPH) rainfall products, respectively. Each group consists of four sub-thresholds in rainy season and non-rainy season, and both are divided into short duration (<48 h) and long duration (≥48 h). The results show that the slope of the regression line for the thresholds in the events with long durations is larger than that with short durations. In addition, the rainfall thresholds in the non-rainy season are generally lower than those in the rainy season. The E–D thresholds defined in this paper are generally lower than other thresholds in previous studies on a global scale, and a regional or national scale in China. This might be due to there being more landslide events used in this paper, as well as the combined effects of special geological environment, climate condition and human activities in China. Compared with the previous landslide model, the positive rates of the rainfall thresholds for landslides have increased by 16%–20%, 10%–17% and 20%–38% in the whole year, rainy season and non-rainy season, respectively.

scholarly journals Assessing Dual-Polarization Radar Estimates of Extreme Rainfall during Hurricane Harvey

2019 ◽  
Vol 36 (12) ◽  
pp. 2501-2520 ◽  
Author(s):  
David B. Wolff ◽  
Walter A. Petersen ◽  
Ali Tokay ◽  
David A. Marks ◽  
Jason L. Pippitt
Keyword(s):  
Gulf Coast ◽  
Warning System ◽  
Extreme Rainfall ◽  
Radar Data ◽  
Rain Gauge ◽  
Harris County ◽  
Flood Warning ◽  
Precipitation Estimates ◽  
Flood Warning System ◽  
Automated Technique

Abstract Hurricane Harvey hit the Texas Gulf Coast as a major hurricane on 25 August 2017 before exiting the state as a tropical storm on 29 August 2017. Left in its wake was historic flooding, with some locations measuring more than 60 in. (150 cm) of rain over a 5-day period. The WSR-88D radar (KHGX) maintained operations for the entirety of the event. Rain gauge data from the Harris County Flood Warning System (HCFWS) was used for validation with the full radar dataset to retrieve daily and event-total precipitation estimates for the period 25–29 August 2017. The KHGX precipitation estimates were then compared with the HCFWS gauges. Three different hybrid polarimetric rainfall retrievals were used, along with attenuation-based retrieval that employs the radar-observed differential propagation. An advantage of using a attenuation-based retrieval is its immunity to partial beam blockage and calibration errors in reflectivity and differential reflectivity. All of the retrievals are susceptible to changes in the observed drop size distribution (DSD). No in situ DSD data were available over the study area, so changes in the DSD were interpreted by examining the observed radar data. We examined the parameter space of two key values in the attenuation retrieval to test the sensitivity of the rain retrieval. Selecting a value of α = 0.015 and β = 0.600 provided the best overall results, relative to the gauges, but more work needs to be done to develop an automated technique to account for changes in the ambient DSD.

scholarly journals Estimation of Rainfall Threshold for Flood Warning for Small Urban Watersheds Based on the 1D-2D Drainage Model Simulation

2021 ◽  
Author(s):  
Duc Anh Dao ◽  
Dongkyun Kim ◽  
Dang Hai Ha Tran
Keyword(s):  
Temporal Variability ◽  
Model Simulation ◽  
Warning System ◽  
Curve Number ◽  
Rainfall Threshold ◽  
Urban Watersheds ◽  
Storm Events ◽  
Rainfall Events ◽  
Flood Warning ◽  
Flood Warning System

Abstract This study proposed an equation for Rainfall Threshold for Flood Warning (RTFW) for small urban watersheds based on computer simulations. First, a coupled 1D-2D dual-drainage model was developed for nine watersheds in Seoul, Korea. Next, the model simulation was repeated for a total of 540 combinations of the synthetic rainfall events and watershed imperviousness (9 watersheds x 4 NRCS Curve Number (CN) values x 15 rainfall events). Then, the results of the 101 simulations that caused the critical flooded depth (0.25m-0.35m) were used to develop the equation that relates the value of RTFW to the rainfall event temporal variability (represented as coefficient of variation or CV) and the watershed Curve Number. The results suggest that (1) RTFW exponentially decreases as the rainfall CV increases; (2) RTFW linearly decreases as the watershed CV increases; and that (3) RTFW is dominated by CV when the rainfall has low temporal variability (e.g., CV<0.2) while RTFW is dominated by CN when the rainfall has high temporal variability (e.g., CV>0.4). For validation, the proposed equation was applied for the flood warning system with two storm events occurred in 2010 and 2011 over 239 watersheds in Seoul. The system showed the the hit, false and missed alarm rates at 69% (48%), 31% (52%) and 6.7% (4.5%), respectively for the 2010 (2011) event.

scholarly journals Rainfall thresholds and flood warning: an operative case study

2009 ◽  
Vol 9 (1) ◽  
pp. 135-144 ◽  
Author(s):  
V. Montesarchio ◽  
F. Lombardo ◽  
F. Napolitano
Keyword(s):  
Precipitation Amount ◽  
Rainfall Threshold ◽  
False Alarms ◽  
Rainfall Thresholds ◽  
Flood Warning ◽  
Operative Case ◽  
Critical Discharge ◽  
Definition Of ◽  
Moisture Conditions

Abstract. An operative methodology for rainfall thresholds definition is illustrated, in order to provide at critical river section optimal flood warnings. Threshold overcoming could produce a critical situation in river sites exposed to alluvial risk and trigger the prevention and emergency system alert. The procedure for the definition of critical rainfall threshold values is based both on the quantitative precipitation observed and the hydrological response of the basin. Thresholds values specify the precipitation amount for a given duration that generates a critical discharge in a given cross section and are estimated by hydrological modelling for several scenarios (e.g.: modifying the soil moisture conditions). Some preliminary results, in terms of reliability analysis (presence of false alarms and missed alarms, evaluated using indicators like hit rate and false alarm rate) for the case study of Mignone River are presented.

scholarly journals Natural risk warning: comparison of two methodologies

2006 ◽  
Vol 2 ◽  
pp. 335-338
Author(s):  
A. Cavallo ◽  
F. Giannoni
Keyword(s):  
Back Analysis ◽  
Extreme Rainfall ◽  
Rainfall Thresholds ◽  
Natural Risk ◽  
Flood Warning ◽  
Risk Warning ◽  
Risk Forecasting ◽  
One Year ◽  
The One ◽  
Definition Of

Abstract. The Italian network of "Centri Funzionali" is now reaching operational status both in hydro-meteorological risk forecasting and support to the decision making of administrations that issue natural risk warning. Each centre operates for its district of influence. In order to have a nationwide common standard the National Civil Protection Department proposed a quantitative warning methodology based on the definition of rainfall thresholds correlated to historical damages. In the first phase the thresholds have been defined using two studies that cover all Italy: the VAPI (statistics of extreme rainfall and discharges, see reference) and the AVI (database of historical flood and landslide events and reported damages, see reference). This work presents one year back analysis that compares the new methodology and the one that has been usied since 2000 by the Liguria Region Meteorological Centre with regard to flood warning, pinpointing the performance differences in terms of false and missed alerts.

Determination of Optimal Public Transportation Routes Using Firefly and Tabu Search Algorithms

2020 ◽  
Vol 4 (5) ◽  
pp. 884-891
Author(s):  
Salwa Salsabila Mansur ◽  
Sri Widowati ◽  
Mahmud Imrona
Keyword(s):  
Tabu Search ◽  
Public Transportation ◽  
Traffic Congestion ◽  
Search Algorithm ◽  
Urban Transportation ◽  
The Public ◽  
Comparison Results ◽  
Congestion Problems ◽  
Transportation Routes

Traffic congestion problems generally caused by the increasing use of private vehicles and public transportations. In order to overcome the situation, the optimization of public transportation’s route is required particularly the urban transportation. In this research, the performance analysis of Firefly and Tabu Search algorithm is conducted to optimize eleven public transportation’s routes in Bandung. This optimization aims to increase the dispersion of public transportation’s route by expanding the scope of route that are crossed by public transportation so that it can reach the entire Bandung city and increase the driver’s income by providing the passengers easier access to public transportations in order to get to their destinations. The optimal route is represented by the route with most roads and highest number of incomes. In this research, the comparison results between the reference route and the public transportation’s optimized route increasing the dispersion of public transportation’s route to 60,58% and increasing the driver’s income to 20,03%.

Feedback structure and EFAS flood warning verification for the rivers in the northwestern Russian Federation

2020 ◽  
Vol 4 ◽  
pp. 96-109
Author(s):  
A.V. Romanov ◽  
◽  
M.V. Yachmenova ◽  
Keyword(s):  
Russian Federation ◽  
Forecast Accuracy ◽  
Warning System ◽  
General Description ◽  
System Quality ◽  
Flood Warning ◽  
Forecast Lead Time ◽  
Feedback Structure ◽  
The Russian Federation ◽  
Flood Warning System

Based on the example of flood warning data provided by EFAS for the territory of Northwestern Administration for Hydrometeorology and Environmental Monitoring in 2018-2020, the structure of the systematized issues of the EFAS portal is analyzed. The issues determine a feedback for the year-round monitoring of the accuracy of flood forecasting using the LISFLOOD base model, as well as its calibration. Several most important feedback sections are highlighted, that allow improving significantly a procedure for the quantitative and qualitative differentiated assessment of short- and medium-range flood forecasts. Using the results of the numerical analysis, a general description of the EFAS flood warning system quality and the prospects for the participation of the Russian Federation in it are given. Keywords: flooding, hydrological forecasts, forecast lead time, feedback, forecast accuracy

scholarly journals A susceptibility-based rainfall threshold approach for landslide occurrence

2019 ◽  
Vol 19 (4) ◽  
pp. 775-789 ◽  
Author(s):  
Elise Monsieurs ◽  
Olivier Dewitte ◽  
Alain Demoulin
Keyword(s):  
Landslide Susceptibility ◽  
Rainfall Threshold ◽  
Exceedance Probability ◽  
Equal Weight ◽  
Antecedent Rainfall ◽  
Rainfall Thresholds ◽  
Landslide Occurrence ◽  
Continental Scale ◽  
Satellite Rainfall ◽  
Rainfall Estimates

Abstract. Rainfall threshold determination is a pressing issue in the landslide scientific community. While major improvements have been made towards more reproducible techniques for the identification of triggering conditions for landsliding, the now well-established rainfall intensity or event-duration thresholds for landsliding suffer from several limitations. Here, we propose a new approach of the frequentist method for threshold definition based on satellite-derived antecedent rainfall estimates directly coupled with landslide susceptibility data. Adopting a bootstrap statistical technique for the identification of threshold uncertainties at different exceedance probability levels, it results in thresholds expressed as AR = (α±Δα)⋅S(β±Δβ), where AR is antecedent rainfall (mm), S is landslide susceptibility, α and β are scaling parameters, and Δα and Δβ are their uncertainties. The main improvements of this approach consist in (1) using spatially continuous satellite rainfall data, (2) giving equal weight to rainfall characteristics and ground susceptibility factors in the definition of spatially varying rainfall thresholds, (3) proposing an exponential antecedent rainfall function that involves past daily rainfall in the exponent to account for the different lasting effect of large versus small rainfall, (4) quantitatively exploiting the lower parts of the cloud of data points, most meaningful for threshold estimation, and (5) merging the uncertainty on landslide date with the fit uncertainty in a single error estimation. We apply our approach in the western branch of the East African Rift based on landslides that occurred between 2001 and 2018, satellite rainfall estimates from the Tropical Rainfall Measurement Mission Multi-satellite Precipitation Analysis (TMPA 3B42 RT), and the continental-scale map of landslide susceptibility of Broeckx et al. (2018) and provide the first regional rainfall thresholds for landsliding in tropical Africa.

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