Flood vulnerability of the Karun River System and short-term mitigation measures

2013 ◽  
Vol 7 (1) ◽  
pp. 65-80 ◽  
Author(s):  
A. Heidari
Keyword(s):  
River System ◽  
Mitigation Measures ◽  
Short Term ◽  
Flood Vulnerability ◽  
Karun River

scholarly journals Structural mitigation measures for flood reduction in urban area: A case study of Ciliwung watershed

2020 ◽  
Vol 200 ◽  
pp. 01004
Author(s):  
Rizki Maulana Fadillah ◽  
Hafizh Tsaqib ◽  
Aryanti Karlina Nurendyastuti ◽  
Miftahul Jannah ◽  
Rian Mantasa Salve Prastica
Keyword(s):  
River System ◽  
Mitigation Measures ◽  
Ideal Condition ◽  
Water Infrastructure ◽  
Embankment Dam ◽  
The Earth ◽  
Earth Embankment ◽  
Infrastructure Maintenance ◽  
The Ideal

Flooding is an obstacle for water infrastructure which installed in a river system in Ciliwung, West Java, Indonesia. The climate change triggers unpredictable rainfall which occurs in the watershed, therefore the vulnerability of river and other infrastructures are alarming. The rehabilitation and maintenance strategies are needed to make water infrastructures in the river system obtain lower damage. The research aims to simulate the 2-D HEC-RAS modelling of river system and stability. The result produces the water level of the river even in 1000-year discharge flood. Also, the research proposes the earth embankment dam for flood reduction in the watershed. The dam is designed according to the ideal condition. The simulation of HEC-RAS shows that the river experiences flooding in a certain condition. Besides, the research concludes that designed dam could overcome the flooding problem and suitable strategy for water infrastructure maintenance towards flooding impacts. Further investigation towards soil data for designed dam should be further analyzed to obtain better and comprehensive understanding.

scholarly journals Modeling the Impact of Building-Level Flood Mitigation Measures Made Possible by Early Flood Warnings on Community-Level Flood Loss Reduction

Buildings ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 475
Author(s):  
Omar M. Nofal ◽  
John W. van de van de Lindt ◽  
Harvey Cutler ◽  
Martin Shields ◽  
Kevin Crofton
Keyword(s):  
Flood Risk ◽  
Risk Model ◽  
Flood Hazard ◽  
Community Level ◽  
Flood Mitigation ◽  
Precipitation Forecast ◽  
Mitigation Measures ◽  
Flood Vulnerability ◽  
The Impact ◽  
Flood Warnings

The growing number of flood disasters worldwide and the subsequent catastrophic consequences of these events have revealed the flood vulnerability of communities. Flood impact predictions are essential for better flood risk management which can result in an improvement of flood preparedness for vulnerable communities. Early flood warnings can provide households and business owners additional time to save certain possessions or products in their buildings. This can be accomplished by elevating some of the water-sensitive components (e.g., appliances, furniture, electronics, etc.) or installing a temporary flood barrier. Although many qualitative and quantitative flood risk models have been developed and highlighted in the literature, the resolution used in these models does not allow a detailed analysis of flood mitigation at the building- and community level. Therefore, in this article, a high-fidelity flood risk model was used to provide a linkage between the outputs from a high-resolution flood hazard model integrated with a component-based probabilistic flood vulnerability model to account for the damage for each building within the community. The developed model allowed to investigate the benefits of using a precipitation forecast system that allows a lead time for the community to protect its assets and thereby decreasing the amount of flood-induced losses.

scholarly journals Global Analysis of SARS-COV-2 Mitigation Impact Reveals an Arabian Peninsula Cluster with High Infection Rates and Shared Indicators

2020 ◽  
Author(s):  
Najeeb Halabi ◽  
Reem S. Chamseddine ◽  
Mayyasa Rammah ◽  
Quentin Griette ◽  
Rayaz Malik ◽  
...  
Keyword(s):  
Arabian Peninsula ◽  
Global Analysis ◽  
Statistical Testing ◽  
Mitigation Measures ◽  
Infection Rates ◽  
Short Term ◽  
Mechanistic Modelling ◽  
Pollution Levels ◽  
Early Adoption ◽  
The Impact

Abstract Background SARS-CoV-2 is a novel virus that appeared in China in November 2019 and spread rapidly. With no vaccine or effective treatment, countries have adopted different mitigation measures to reduce SARS-COV-2 spread with different efficacy.MethodsWe mapped the impact of mitigation measures across different countries. We compared regional SARS-COV-2 population burden via Kruskal-Wallis statistical testing. We analyzed time of adoption of mitigation measures and the impact of PCR testing on mitigation impact. We analyzed the association of climate, health, demographic and economic indicators with mitigation impact via non-parametric correlation tests. We performed mechanistic modelling of to predict short-term SARS-COV-2 case numbers in selected countries. ResultsMany countries showed a reduction of infection rates within one month of implementing mitigation measures. However, we identified a geographic cluster of countries centered on the Arabian Peninsula (AP) that show a high SARS-COV-2 population burden despite early adoption of mitigation measures. We find that higher air pollution levels (p=0.01), higher CO2 emissions (p=0.03) and younger population (p=0.02) were associated with reduced mitigation impact in AP countries. We also show that mechanistic modelling can closely predict confirmed case numbers in the short term.ConclusionsThe impact of mitigation measures varies greatly between countries. Countries with similar profiles as AP countries should adopt more stringent mitigation measures to more rapidly reduce SARS-CoV-2 spread. Specific interventions targeting young people may also be effective in reducing SARS-COV-2 spread.

scholarly journals Reverse flood routing in an open channel using a combined model of genetic algorithm and a numerical model

2021 ◽  
Vol 16 (4) ◽  
pp. 1465-1474
Author(s):  
Ali Azizipour ◽  
Seyed Mahmood Kashefipour ◽  
Ali Haghighi
Keyword(s):  
Genetic Algorithm ◽  
Numerical Model ◽  
Rural Areas ◽  
Fitness Function ◽  
River System ◽  
Flood Routing ◽  
Integrated Method ◽  
Karun River ◽  
The Status ◽  
Urban And Rural Areas

Abstract Flood impact assessment in a river system is done with the help of flood routing and this process helps to determine the status of sensitive points of the route in terms of flood entry and the resulting risks for urban and rural areas. For flood routing, a hydrodynamic numerical model should be implemented and this model needs upstream and downstream boundaries. In some cases, the upstream boundary, which is usually a hydrograph, is not available due to the lack of facilities and it is necessary to be generated for numerical model implementation. The purpose of this study is to present an integrated method comprising an optimization model and a hydrodynamic numerical model for flood modeling in order to determine the upstream hydrograph using the measured downstream hydrograph along a river. The routing procedure consists of three steps: (1) generating a hypothetical upstream hydrograph using the genetic algorithm method; (2) hydrodynamic modeling using a numerical simulation model for flood routing according to the hypothetical hydrograph, which is generated in the first step; (3) comparing the calculated and observed hydrograph in the downstream by using a fitness function. This recommended procedure was named the Reverse Flood Routing Method (RFRM) and was then applied to Karun River, the largest river in Iran. Comparison of the final generated upstream hydrograph by the RFRM model with the corresponding measured hydrograph at the upstream boundary (here Ahvaz hydrometric station was assumed as an ungauged river location) shows the high accuracy of the recommended model in this study.

scholarly journals Assessment of Flood Risk in the Eastern Part of Jamuna Floodplain

2018 ◽  
Vol 44 (2) ◽  
pp. 211-224
Author(s):  
Maruf Billah ◽  
Mehedi Ahmed Ansary
Keyword(s):  
Flood Hazard ◽  
Emergency Situation ◽  
Mitigation Measures ◽  
Hazard Map ◽  
Individual Factor ◽  
Flood Vulnerability ◽  
Risk Zone ◽  
Hazard Vulnerability ◽  
Floodplain Area ◽  
Very High

Risk assessment provides the scope to understand the vulnerability situation of any area based on different hazard context. The study has been conducted in the eastern part of Jamuna floodplain area to examine its flood vulnerability. To perform the analysis, the whole study area has been surveyed and examined applying Geographic Information System. The entire hazard, vulnerability as well as the capacity factors are assessed and have been classified into different categories from very low to very high. Individual factor analysis has been considered to realize the specific condition of different factors. Finally, flood hazard map has been prepared to examine the vulnerability of the proposed area. This type of work helps the planners and disaster managers to identify the most risk zone which should receive immediate hazard mitigation measures as well as help to take a decision in an emergency situation when a flood may occur in the study area. Asiat. Soc. Bangladesh, Sci. 44(2): 211-224, December 2018

scholarly journals Flood vulnerability and risk assessment of urban traditional buildings in a heritage district of Kuala Lumpur, Malaysia

2020 ◽  
Vol 20 (8) ◽  
pp. 2221-2241 ◽  
Author(s):  
Dina D'Ayala ◽  
Kai Wang ◽  
Yuan Yan ◽  
Helen Smith ◽  
Ashleigh Massam ◽  
...  
Keyword(s):  
Large Scale ◽  
Residential Buildings ◽  
Mitigation Measures ◽  
Economic Losses ◽  
Exceedance Probability ◽  
Kuala Lumpur ◽  
Flood Vulnerability ◽  
Management Actions ◽  
Vulnerability Model ◽  
Wide Range

Abstract. Flood hazard is increasing in frequency and magnitude in major South East Asian metropolitan areas due to fast urban development and changes in climate, threatening people's property and life. Typically, flood management actions are mostly focused on large-scale defences, such as river embankments or discharge channels or tunnels. However, these are difficult to implement in town centres without affecting the value of their heritage districts and might not provide sufficient mitigation. Therefore, urban heritage buildings may become vulnerable to flood events, even when they were originally designed and built with intrinsic resilient measures, based on the local knowledge of the natural environment and its threats at the time. Their aesthetic and cultural and economic values mean that they can represent a proportionally high contribution to losses in any event. Hence it is worth investigating more localized, tailored mitigation measures. Vulnerability assessment studies are essential to inform the feasibility and development of such strategies. In this study we propose a multilevel methodology to assess the flood vulnerability and risk of residential buildings in an area of Kuala Lumpur, Malaysia, characterized by traditional timber housing. The multiscale flood vulnerability model is based on a wide range of parameters, covering building-specific parameters, neighbourhood conditions and catchment area conditions. The obtained vulnerability index shows the ability to reflect different exposure by different building types and their relative locations. The vulnerability model is combined with high-resolution fluvial and pluvial flood maps providing scenario events with 0.1 % annual exceedance probability (AEP). A damage function of generic applicability is developed to compute the economic losses at individual building and sample levels. The study provides evidence that results obtained for a small district can be scaled up to the city level, to inform both generic and specific protection strategies.

scholarly journals Short-Term Firm-Level Energy-Consumption Forecasting for Energy-Intensive Manufacturing: A Comparison of Machine Learning and Deep Learning Models

Algorithms ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 274 ◽  
Author(s):  
Andrea Maria N. C. Ribeiro ◽  
Pedro Rafael X. do Carmo ◽  
Iago Richard Rodrigues ◽  
Djamel Sadok ◽  
Theo Lynn ◽  
...  
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Deep Learning ◽  
Energy Consumption ◽  
Mitigation Measures ◽  
Support Vector ◽  
Level Energy ◽  
Learning Models ◽  
Short Term ◽  
Case Site

To minimise environmental impact, to avoid regulatory penalties, and to improve competitiveness, energy-intensive manufacturing firms require accurate forecasts of their energy consumption so that precautionary and mitigation measures can be taken. Deep learning is widely touted as a superior analytical technique to traditional artificial neural networks, machine learning, and other classical time-series models due to its high dimensionality and problem-solving capabilities. Despite this, research on its application in demand-side energy forecasting is limited. We compare two benchmarks (Autoregressive Integrated Moving Average (ARIMA) and an existing manual technique used at the case site) against three deep-learning models (simple Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU)) and two machine-learning models (Support Vector Regression (SVR) and Random Forest) for short-term load forecasting (STLF) using data from a Brazilian thermoplastic resin manufacturing plant. We use the grid search method to identify the best configurations for each model and then use Diebold–Mariano testing to confirm the results. The results suggests that the legacy approach used at the case site is the worst performing and that the GRU model outperformed all other models tested.

scholarly journals Integrated Modelling of Runoff, Alkalinity, and pH on a Daily Basis

1985 ◽  
Vol 16 (2) ◽  
pp. 89-104 ◽  
Author(s):  
S. Bergström ◽  
B. Carlsson ◽  
G. Sandberg ◽  
L. Maxe
Keyword(s):  
River System ◽  
Daily Basis ◽  
Integrated Modelling ◽  
Running Waters ◽  
Short Term ◽  
Long Term Storage ◽  
Semi Empirical ◽  
Term Storage

Based on the experience from runoff and groundwater recharge simulation a model system has been developed for terrestrial, hydrochemical, and hydrological simulations. The system emphasizes the role of temporary or long term storage in the aquifers of a basin and, separately, accounts for each rainfall or snowmelt event from its entrance into the ground until mixing in the river system. The model is primarily intended for simulation of natural short term variations in alkalinity and pH in running waters. The hydrochemical processes are modelled in a semi-empirical way without assumption of complete hydrochemichal mass-balance. In the paper a brief hydrochemical background is given, and a model with two alternative hydrochemical sub-structures is described. Examples of daily simulations of runoff alkalinity and pH from three different basins are given.

scholarly journals Geomorphic Approaches to Estimate Short-Term Erosion Rates: An Example from Valmarecchia River System (Northern Apennines, Italy)

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2535
Author(s):  
Veronica Guerra ◽  
Maurizio Lazzari
Keyword(s):  
Drainage Basin ◽  
Regional Scale ◽  
River System ◽  
Northern Apennines ◽  
Short Term ◽  
Catchment Basin ◽  
Average Value ◽  
Erosion Rates ◽  
Fluvial Dynamics ◽  
Uplift Rates

Studying fluvial dynamics and environments, GIS-based analyses are of fundamental importance to evaluate the network geometry and possible anomalies, and can be particularly useful to estimate modifications in processes and erosion rates. The aim of this paper is to estimate short-term erosion rates attributable to fluvial processes in two sample catchment sub-basins of the Marecchia river valley, by conducting quantitative morphometric analyses in order to calculate various descriptive parameters of the hierarchisation of the river networks and the mean turbid transport of streams (Tu). Sediment yield transported by streams can in fact partially express the amount of erosional processes acting within the drainage basin. The study area includes two sub-basins of the Marecchia valley (Senatello river, 49 km2 and Mazzocco river, 47 km2), chosen because of their similar extent and of the different location in the major catchment basin. Starting from geomorphological maps of the two river basins, the Tu parameter has been calculated and converted in short-term rate (average value 0.21 mm/year). Moreover, the comparison of these short-term mean data with the uplift rates calculated on a regional scale (0.41 ± 0.26 mm/year) in the Marecchia valley confirms that the northern Apennines may represent a non-steady state system.

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