Evaluation of an urban drainage system and its resilience using remote sensing and GIS

Guptha, Guru Chythanya; Swain, Sarat Chandra; Al‐Ansari, Nadhir; Taloor, Ajay Kumar; Dayal, Deen

doi:10.1016/j.rsase.2021.100601

Cited by 44 publications

(24 citation statements)

References 73 publications

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“…Resilience is the probability of a system recovering from a failed state (Diao 2021;Guptha et al 2021). In this study, the widely used resilience concept proposed by Hashimoto et al (1982) and used by Khatavkar & Mays (2019) is adopted for both normal and abnormal conditions of the WDN.…”

Section: Resilience Indexmentioning

confidence: 99%

Fuzzy logic-based integrated performance evaluation of a water distribution network

Beker

Kansal

2022

Journal of Water Supply: Research and Technology-Aqua

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A water distribution network (WDN) is an essential component of an urban water supply scheme to deliver safe and adequate water to consumers under various operational conditions. This study focuses on the performance evaluation of an urban WDN using fuzzy logic-based aggregation of reliability, resilience, and vulnerability indices. To assess the individual performance indicators, this study advocates the pressure-dependent analysis (PDA) for the hydraulic simulation. Furthermore, it advocates a fuzzy rule-based aggregated performance index (API) that will deliver the outcome in linguistic form and help the decision-maker to prioritize the maintenance of the WDN. The proposed method is illustrated with the help of a real-time WDN for part of Dire Dawa city in Ethiopia. It has been found that the API values for this network are 0.721 and 0.624, respectively, under normal and abnormal conditions, which are just satisfactory. It has been noticed that nodes J4, J44, J47, and J49 are critical from the overall low API. Efforts should be made to improve the hydraulic and residual chlorine conditions at these nodes to increase the API. It is felt that such a methodology will help the decision-makers in improving the performance of an existing urban WDN.

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Section: Resilience Indexmentioning

confidence: 99%

Fuzzy logic-based integrated performance evaluation of a water distribution network

Beker

Kansal

2022

Journal of Water Supply: Research and Technology-Aqua

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“…In urban flood risk assessment, hydrometeorological risk assessment (HMR) and other different methods, including open data [ 52 ], multi-source remote-sensing precipitation products [ 53 ], and GIS and other software, can be used. In addition, principal component analysis [ 54 ], the extremum theorem, functional data analysis and other computational [ 55 ], mathematical and statistical methods [ 24 ], along with the Ornstein–Uhlenbeck process and meta-analyses [ 56 ], can be used to study urban flood resilience. In 2014, Revi A et al considered the adaptation capacity of cities in the world to climate change and discussed the risk level of factors driving short-term and long-term climate impacts [ 57 ].…”

Section: Systematic Analysismentioning

confidence: 99%

Review of Urban Flood Resilience: Insights from Scientometric and Systematic Analysis

Gao

Wang

Yang

2022

IJERPH

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In recent decades, climate change is exacerbating meteorological disasters around the world, causing more serious urban flood disaster losses. Many solutions in related research have been proposed to enhance urban adaptation to climate change, including urban flooding simulations, risk reduction and urban flood-resistance capacity. In this paper we provide a thorough review of urban flood-resilience using scientometric and systematic analysis. Using Cite Space and VOS viewer, we conducted a scientometric analysis to quantitively analyze related papers from the Web of Science Core Collection from 1999 to 2021 with urban flood resilience as the keyword. We systematically summarize the relationship of urban flood resilience, including co-citation analysis of keywords, authors, research institutions, countries, and research trends. The scientometric results show that four stages can be distinguished to indicate the evolution of different keywords in urban flood management from 1999, and urban flood resilience has become a research hotspot with a significant increase globally since 2015. The research methods and progress of urban flood resilience in these four related fields are systematically analyzed, including climate change, urban planning, urban system adaptation and urban flood-simulation models. Climate change has been of high interest in urban flood-resilience research. Urban planning and the adaptation of urban systems differ in terms of human involvement and local policies, while more dynamic factors need to be jointly described. Models are mostly evaluated with indicators, and comprehensive resilience studies based on traditional models are needed for multi-level and higher performance models. Consequently, more studies about urban flood resilience based on local policies and dynamics within global urban areas combined with fine simulation are needed in the future, improving the concept of resilience as applied to urban flood-risk-management and assessment.

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“…The Gurgaon and Faridabad districts of Haryana, located in the periphery of New Delhi, have witnessed rapid urbanization and industrialization in last few years (Guptha et al 2021(Guptha et al , 2022Rai and Saha 2015). This might have affected the groundwater quality of these two districts.…”

Section: Introductionmentioning

confidence: 99%

Groundwater quality assessment using geospatial and statistical approaches over Faridabad and Gurgaon districts of National Capital Region, India

2022

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This study presents an assessment of groundwater quality over the two constituent districts (Faridabad and Gurgaon) of the National Capital Region (NCR), India, using geospatial and statistical approaches. These districts have been subjected to rapid urbanization and industrialization in recent years. The groundwater quality parameters viz., pH, electrical conductivity (EC), carbonate (CO32−), bicarbonate (HCO3−), chloride (Cl−), sulphate (SO42−), nitrate (NO3−), fluoride (F−), calcium (Ca2+), magnesium (Mg2+), sodium (Na+), potassium (K+), silica (SiO2), and total hardness (TH) are obtained for the year of 2017 from 28 sites over the study area. The suitability for human drinking purposes is assessed by comparing the concentration of parameters at each site with respect to their permissible limits recommended by the Bureau of Indian Standards (IS 10500: 2012). The geospatial mapping of the water quality parameters is carried out to visualize their variations, whereas their risk assessment is accomplished by the statistical approaches viz., water quality index (WQI), correlation, and principal component analysis (PCA). The number of sites exceeding the permissible limits of pH, EC, Cl−, SO42−, NO3−, F−, Ca2+, Mg2+, Na+, K+, and TH is obtained to be 7, 15, 5, 6, 8, 3, 5, 7, 18, 3, and 8, respectively. The WQI analysis revealed 10 out of the 28 sites to be unsuitable for drinking purposes. The parameters mostly exhibited positive correlations except for pH that showed a negative correlation with other parameters. The results of PCA revealed the first principal component (PC1) to explain more than 95% of the total variance, thereby significantly reducing the dimensionality. The deteriorated water quality may be mainly attributed to anthropogenic activities, i.e., reckless industrial growth, population explosion, and rapid urbanization. This study emphasizes the need for regular water quality monitoring, and the information reported will certainly help for water resources planning and management, especially over the industrial regions of NCR, India.

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Evaluation of an urban drainage system and its resilience using remote sensing and GIS

Cited by 44 publications

References 73 publications

Fuzzy logic-based integrated performance evaluation of a water distribution network

Fuzzy logic-based integrated performance evaluation of a water distribution network

Review of Urban Flood Resilience: Insights from Scientometric and Systematic Analysis

Groundwater quality assessment using geospatial and statistical approaches over Faridabad and Gurgaon districts of National Capital Region, India

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