An automated approach to establish relationship between total and effective impervious area for urban Indian catchments

IF 1.6 3区环境科学与生态学 Q3 WATER RESOURCES

Urban Water Journal Pub Date : 2023-09-19 DOI:10.1080/1573062x.2023.2255168

Sovan Sankalp, Sanat Nalini Sahoo

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引用次数: 0

Abstract

ABSTRACTDetermination of total impervious area (TIA) or effective impervious area (EIA) is mandatory for hydrological modelling of water quantity and quality in urban areas. In this study, a multilayer deep learning model Convolutional Neural Network (CNN) is implemented for estimating TIA. A more realistic automated method is suggested to determine EIA by integrating the remote sensing data, the digital format of the drainage network, and a digital elevation model (DEM). A graphical user interface (GUI) called EIA estimator is developed for automatic creation of EIA maps. An effort is made to derive a relationship between TIA and EIA. Several power relationships are obtained for easily measurable TIA and hydraulically relevant EIA in urban catchments of India. These relationships would aid planners and decision-makers with quick initial estimates for surface water quantity and quality problems.KEYWORDS: TIAEIARSGISurbanimperviousness Disclosure statementThe authors declare that they don’t have any conflict of interest.Availability of data and materialPart of data may be available on request.Additional informationFundingThe authors would like to acknowledge the Science and Engineering Research Board (SERB), India for providing the financial support for this research program, project no. [ECR/2016/000057].

查看原文本刊更多论文

建立印度城市集水区总不透水面积和有效不透水面积关系的自动化方法

摘要总不透水面积(TIA)或有效不透水面积(EIA)的确定是城市水量和水质水文模拟的必要条件。在本研究中，采用多层深度学习模型卷积神经网络(CNN)来估计TIA。提出了将遥感数据、流域网络数字格式和数字高程模型(DEM)相结合，实现环评的自动化方法。为实现环评地图的自动生成，开发了环评估计器图形用户界面。努力推导出TIA和EIA之间的关系。在印度城市集水区，获得了易于测量的TIA和水力相关的EIA的几个功率关系。这些关系将有助于规划者和决策者对地表水的数量和质量问题作出迅速的初步估计。公开声明作者声明无任何利益冲突。数据和材料的可用性部分数据可应要求提供。作者感谢印度科学与工程研究委员会(塞尔维亚)为本研究项目提供资金支持。(ECR / 2016/000057)。

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来源期刊

Urban Water Journal WATER RESOURCES-

CiteScore

4.40

自引率

11.10%

发文量

101

审稿时长

3 months

期刊介绍： Urban Water Journal provides a forum for the research and professional communities dealing with water systems in the urban environment, directly contributing to the furtherance of sustainable development. Particular emphasis is placed on the analysis of interrelationships and interactions between the individual water systems, urban water bodies and the wider environment. The Journal encourages the adoption of an integrated approach, and system''s thinking to solve the numerous problems associated with sustainable urban water management. Urban Water Journal focuses on the water-related infrastructure in the city: namely potable water supply, treatment and distribution; wastewater collection, treatment and management, and environmental return; storm drainage and urban flood management. Specific topics of interest include: network design, optimisation, management, operation and rehabilitation; novel treatment processes for water and wastewater, resource recovery, treatment plant design and optimisation as well as treatment plants as part of the integrated urban water system; demand management and water efficiency, water recycling and source control; stormwater management, urban flood risk quantification and management; monitoring, utilisation and management of urban water bodies including groundwater; water-sensitive planning and design (including analysis of interactions of the urban water cycle with city planning and green infrastructure); resilience of the urban water system, long term scenarios to manage uncertainty, system stress testing; data needs, smart metering and sensors, advanced data analytics for knowledge discovery, quantification and management of uncertainty, smart technologies for urban water systems; decision-support and informatic tools;...