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Book part
Publication date: 21 November 2018

Lloyd Ling and Zulkifli Yusop

The US Department of Agriculture (USDA), Soil Conservation Services (SCS) rainfall-runoff model has been applied worldwide since 1954 and adopted by Malaysian government agencies…

Abstract

The US Department of Agriculture (USDA), Soil Conservation Services (SCS) rainfall-runoff model has been applied worldwide since 1954 and adopted by Malaysian government agencies. Malaysia does not have regional specific curve numbers (CN) available for the use in rainfall-runoff modelling, and therefore a SCS-CN practitioner has no option but to adopt its guideline and handbook values which are specific to the US region. The selection of CN to represent a watershed becomes subjective and even inconsistent to represent similar land cover area. In recent decades, hydrologists argue about the accuracy of the predicted runoff results from the model and challenge the validity of the key parameter, initial abstraction ratio coefficient (λ) and the use of CN. Unlike the conventional SCS-CN technique, the proposed calibration methodology in this chapter discarded the use of CN as input to the SCS model and derived statistically significant CN value of a specific region through rainfall-runoff events directly under the guide of inferential statistics. Between July and October of 2004, the derived λ was 0.015, while λ = 0.20 was rejected at alpha = 0.01 level at Melana watershed in Johor, Malaysia. Optimum CN of 88.9 was derived from the 99% confidence interval range from 87.4 to 96.6 at Melana watershed. Residual sum of square (RSS) was reduced by 79% while the runoff model of Nash–Sutcliffe was improved by 233%. The SCS rainfall-runoff model can be calibrated quickly to address urban runoff prediction challenge under rapid land use and land cover changes.

Details

Improving Flood Management, Prediction and Monitoring
Type: Book
ISBN: 978-1-78756-552-4

Keywords

Article
Publication date: 5 September 2016

Chunlu Liu and Yan Li

The rapid and ongoing expansion of urbanised impervious areas could lead to more frequent flood inundation in urban flood-prone regions. Nowadays, urban flood inundation induced…

Abstract

Purpose

The rapid and ongoing expansion of urbanised impervious areas could lead to more frequent flood inundation in urban flood-prone regions. Nowadays, urban flood inundation induced by rainstorm is an expensive natural disaster in many countries. In order to reduce the flooding risk, eco-roof systems (or green roof systems) could be considered as an effective mechanism of mitigating flooding disasters through their rainwater retention capability. However, there is still a lack of examining the stormwater management tool. The purpose of this paper is to evaluate the effects on flooding disaster from extensive green roofs.

Design/methodology/approach

Based on geographical information system (GIS) simulation, this research presents a frame of assessing eco-roof impacts on urban flash floods. The approach addresses both urban rainfall-runoff and underground hydrologic models for traditional impervious and green roofs. Deakin University’s Geelong Waurn Ponds campus is chosen as a study case. GIS technologies are then utilised to visualise and analyse the effects on flood inundation from surface properties of building roofs.

Findings

The results reveal that the eco-roof systems generate varying degrees of mitigation of urban flood inundation with different return period storms.

Originality/value

Although the eco-roof technology is considered as an effective stormwater management tool, it is not commonly adopted and examined in urban floods. This study will bring benefits to urban planners for raising awareness of hazard impacts and to construction technicians for considering disaster mitigation via roof technologies. The approach proposed here could be used for the disaster mitigation in future urban planning.

Article
Publication date: 6 August 2018

Sayed-Farhad Mousavi, Hojat Karami, Saeed Farzin and Ehsan Teymouri

This study aims to use porous concrete and mineral adsorbents (additives) for reducing the quantity and improving the quality of urban runoff.

Abstract

Purpose

This study aims to use porous concrete and mineral adsorbents (additives) for reducing the quantity and improving the quality of urban runoff.

Design/methodology/approach

The effects of adding mineral adsorbents and fine grains to porous concrete is tested for increasing its performance in improving the quality of urban runoff. Two levels of sand (10 and 20 per cent) and 5, 10 and 15 per cent of zeolite, perlite, LECA and pumice were added to the porous concrete. Unconfined compressive strength, hydraulic conductivity (permeability) and porosity of the porous concrete specimens were measured. Some of the best specimens were selected for testing the improvement of runoff quality. A rainfall simulator was designed and the quality of the runoff was investigated for changes in electrical conductivity (EC), total suspended solids (TSS), total dissolved solids (TDS) and chemical oxygen demand (COD).

Findings

The results of this study showed that compressive strength of the porous concrete was increased by adding fine grains to the concrete mixture. Fine grains decreased the permeability and porosity of the samples. Zeolite had the highest compressive strength. Samples having pumice own maximum permeability. Samples which had perlite, had the least compressive strength and permeability. Because of the fast flow of runoff water in the porous slab and its low thickness, sufficient time was not provided for effective functioning of the additives, and the removal percentage of the pollution parameters was low.

Originality/value

Porous concrete can ameliorate both quantity and quality of the urban runoff.

Details

World Journal of Engineering, vol. 15 no. 4
Type: Research Article
ISSN: 1708-5284

Keywords

Abstract

Details

Urban Resilience: Lessons on Urban Environmental Planning from Turkey
Type: Book
ISBN: 978-1-83549-617-6

Book part
Publication date: 6 July 2012

Karen Sudmeier-Rieux, Jean-Christophe Gaillard, Sundar Sharma, Jérôme Dubois and Michel Jaboyedoff

Climate change data and predictions for the Himalayas are very sparse and uncertain, characterized by a “Himalayan data gap” and difficulties in predicting changes due to…

Abstract

Climate change data and predictions for the Himalayas are very sparse and uncertain, characterized by a “Himalayan data gap” and difficulties in predicting changes due to topographic complexity. A few reliable studies and climate change models for Nepal predict considerable changes: shorter monsoon seasons, more intensive rainfall patterns, higher temperatures, and drought. These predictions are confirmed by farmers who claim that temperatures have been increasing for the past decade and wonder why the rains have “gone mad.” The number of hazard events, notably droughts, floods, and landslides are increasing and now account for approximately 100 deaths in Nepal annually. Other effects are drinking water shortages and shifting agricultural patterns, with many communities struggling to meet basic food security before climatic conditions started changing.

The aim of this paper is to examine existing gaps between current climate models and the realities of local development planning through a case study on flood risk and drinking water management for the Municipality of Dharan in Eastern Nepal. This example highlights current challenges facing local-level governments, namely, flood and landslide mitigation, providing basic amenities – especially an urgent lack of drinking water during the dry season – poor local planning capacities, and limited resources. In this context, the challenge for Nepal will be to simultaneously address increasing risks caused by hazard events alongside the omnipresent food security and drinking water issues in both urban and rural areas. Local planning is needed that integrates rural development and disaster risk reduction (DRR) with knowledge about climate change considerations. The paper concludes with a critical analysis of climate change modeling and the gap between scientific data and low-tech and low capacities of local planners to access or implement adequate adaptation measures. Recommendations include the need to bridge gaps between scientific models, the local political reality and local information needs.

Details

Climate Change Modeling For Local Adaptation In The Hindu Kush-Himalayan Region
Type: Book
ISBN: 978-1-78052-487-0

Keywords

Article
Publication date: 23 November 2023

Sayed Arash Hosseini Sabzevari, Haleh Mehdipour and Fereshteh Aslani

Golestan province in the northern part of Iran has been affected by devastating floods. There has been a significant change in the pattern of rainfall in Golestan province based…

Abstract

Purpose

Golestan province in the northern part of Iran has been affected by devastating floods. There has been a significant change in the pattern of rainfall in Golestan province based on an analysis of the seven heaviest rainfall events in recent decades. Climate change appears to be a significant contributing factor to destructive floods. Thus, this paper aims to assess the susceptibility of this area to flash floods in case of heavy downpours.

Design/methodology/approach

This paper uses a variety of computational approaches. Following the collection of data, spatial analyses have been conducted and validated. The layers of information are then weighted, and a final risk map is created. Fuzzy analytical hierarchy process, geographic information system and frequency ratio have been used for data analysis. In the final step, a flood risk map is prepared and discussed.

Findings

Due to the complex interaction between thermal fluctuations and precipitation, the situation in the area is further complicated by climate change and the variations in its patterns and intensities. According to the study results, coastal areas of the Caspian Sea, the Gorganrood Basin and the southern regions of the province are predicted to experience flash floods in the future. The research criteria are generalizable and can be used for decision-making in areas exposed to flash flood risk.

Originality/value

The unique feature of this paper is that it evaluates flash flood risks and predicts flood-prone areas in the northern part of Iran. Furthermore, some interventions (e.g. remapping land use and urban zoning) are provided based on the socioeconomic characteristics of the region to reduce flood risk. Based on the generated risk map, a practical suggestion would be to install and operate an integrated rapid flood warning system in high-risk zones.

Details

International Journal of Disaster Resilience in the Built Environment, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1759-5908

Keywords

Book part
Publication date: 6 July 2012

Alia Lauren Khan

Bangladesh has a long history of dealing with seasonal changes resulting in droughts and floods. Three major rivers, the Ganges, Brahmaputra and Meghna (GBM) come to a confluence…

Abstract

Bangladesh has a long history of dealing with seasonal changes resulting in droughts and floods. Three major rivers, the Ganges, Brahmaputra and Meghna (GBM) come to a confluence, forming the GBM floodplain. There is a specific time window (June to September) when most of the runoff occurs and over 90% of their combined flow is discharged into the Bay of Bengal. As a result, the seasonal monsoons result in wet and dry seasons, making Bangladesh vulnerable to both floods and droughts. Climate change will likely alter characteristics such as timing and intensity, therefore increasing the challenge of adaptation. Socioeconomic conditions and high-population density limit the country's ability to adapt to these hydro-meteorological extremes. Although climatic variability causes severe damage and loss of life in Bangladesh, examples of local adaptation to the annual rhythm of seasonal variation can be found in flood-prone areas. Scientific modeling has resulted in more robust and efficient early warning systems that have greatly decreased the loss of life from climate hazards in recent years. However, positive impacts from models are limited by complex social concerns that are pervasive across the country.

Details

Climate Change Modeling For Local Adaptation In The Hindu Kush-Himalayan Region
Type: Book
ISBN: 978-1-78052-487-0

Keywords

Article
Publication date: 25 September 2019

Pollyana C.V. Morais, Marcielly F.B. Lima, Davi A. Martins, Lysandra G. Fontenele, Joyce L.R. Lima, Ícaro Breno da Silva, Lidriana S. Pinheiro, Ronaldo F. Nascimento, Rivelino M. Cavalcante and Elissandra V. Marques

An efficient and adequate environmental monitoring plan is essential to any integrated coastal zone management (ICZM) program. The purpose of this paper is to apply an…

Abstract

Purpose

An efficient and adequate environmental monitoring plan is essential to any integrated coastal zone management (ICZM) program. The purpose of this paper is to apply an environmental diagnostic study to a coastal lagoon using anthropogenic markers as a decision support tool to aid the development of coastal environmental management policies.

Design/methodology/approach

Specifically, environmental status and anthropogenic sources were determined as part of a coastal environmental management plan; a study of human occupation and use was conducted to determine the predominant human activities around the lagoon; an environmental diagnostic study was conducted to determine the occurrence, levels and distribution of markers; and the results of the environmental diagnostic study were compared to indicators stipulated in Brazilian legislation.

Findings

Land use study revealed both urban and rural activities around the lagoon, as evidenced by the existence of residences, restaurants as well as poultry and livestock activities. The environmental diagnostic study revealed the input of human sewage (treated and raw) and runoff from animal husbandry activities.

Practical implications

The information produced using anthropogenic markers showed the influence of less studied rural activities, such as livestock and poultry farming, thereby providing a more reliable environmental status compared to the use of classic indicators employed in laws issued by international and Brazilian agencies.

Originality/value

The present results show that classic indicators used by environmental agencies are insufficient for an accurate diagnosis of coastal zones with multiple anthropogenic activities. Thus, the modernization of the environmental monitoring plan of the ICZM program is urgently needed for a more accurate assessment of coastal environments.

Details

Management of Environmental Quality: An International Journal, vol. 31 no. 1
Type: Research Article
ISSN: 1477-7835

Keywords

Book part
Publication date: 31 December 2010

Mikio Ishiwatari

The Intergovernmental Panel on Climate Change (IPCC) IPCC (2007) projects that greater precipitation intensity and variability will increase the risks of flooding in many areas…

Abstract

The Intergovernmental Panel on Climate Change (IPCC) IPCC (2007) projects that greater precipitation intensity and variability will increase the risks of flooding in many areas because of climate change. With climate change already happening, societies worldwide face the parallel challenge of having to adapt to its impacts as a certain degree of climate change is inevitable throughout this century and beyond, even if global mitigation efforts over the next decades prove successful (European Commission, 2007).

Details

Climate Change Adaptation and Disaster Risk Reduction: Issues and Challenges
Type: Book
ISBN: 978-0-85724-487-1

Article
Publication date: 1 March 2006

Guang Jin and A.J. Englande

The primary objective of this study is to develop a predictive model that will predict the swimmability of certain areas of a brackish water body (Lake Pontchartrain) based on…

Abstract

Purpose

The primary objective of this study is to develop a predictive model that will predict the swimmability of certain areas of a brackish water body (Lake Pontchartrain) based on physicochemical and meteorological conditions.

Design/methodology/approach

Samples were collected and analyzed for bacteria indicator organisms at 13 sites along and adjacent to Lincoln Beach for four years. Physicochemical parameters and meteorological data were also recorded. A logistic regression model and an artificial neural networks (ANNs) model were both used to predict whether a lake condition is “safe to swim” or “not safe to swim”, given only physicochemical and meteorological parameters.

Findings

Both models predicted very well the results observed when lake conditions were “safe to swim” (97.7 percent of time the statistical model predicted correctly and an average >99.5 percent of the time for the ANNs model). However, for conditions under which the lake water quality was “not safe to swim”, the statistical model predicted correctly only 5.6 percent of the time. The ANNs model successfully predicted the “not safe to swim” conditions for an average 98.5 percent of the time. However, this percentage decreases to 53.9 percent when ANNs is used for forecasting “not safe to swim” conditions.

Research limitations/implications

The poorer performance of both models for “not safe to swim” conditions is probably due to the fact that most data (84.5 percent) were collected during “safe to swim” conditions. The limited database for “not safe to swim” conditions resulted in a poorer forecasting success rate.

Originality/value

The ANNs model might serve as a useful tool for public beach management with increased data on “not safe to swim” conditions.

Details

Management of Environmental Quality: An International Journal, vol. 17 no. 2
Type: Research Article
ISSN: 1477-7835

Keywords

1 – 10 of 151