{"title":"基于数字图像处理的居住区径流估算","authors":"Pramod Soni, Hemanta Medhi, Anitya Sagar, Pulkit Garg, Abhay Singh, Umesh Karna","doi":"10.2166/aqua.2022.070","DOIUrl":null,"url":null,"abstract":"\n With the burgeoning population worldwide, the demand for freshwater supply is increasing, mostly in urban areas, due to the influx of people for better livelihood. To mitigate this burden of freshwater demand and build a sustainable water management system, harvesting rainwater during the rainfall season is a viable option. Runoff estimation studies in the past are time-intensive as parameter estimation for an area is complex by the conventional method. In this study, the Motilal Nehru National Institute of Technology (MNNIT), Allahabad campus was selected as a pilot project to assess a methodology that uses Google Earth images for obtaining the runoff coefficients. This method is easy and consumes less time in runoff estimation. This was compared with the conventional method. Using the conventional method (Arc-GIS), the equivalent runoff coefficients for these catchments were found to be 0.2780, 0.3553, and 0.4111, respectively. The range of error (compared to the traditional method) in runoff obtained from the proposed method with a default k value (0.8) was found to be 8.16–13.55%, with an average value of 9.91%. However, with a slightly modified value of k (0.9), the errors were significantly reduced to 1.94–3.32%, with an average of 2.15%.","PeriodicalId":17666,"journal":{"name":"Journal of Water Supply: Research and Technology-Aqua","volume":"2 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Runoff estimation using digital image processing for residential areas\",\"authors\":\"Pramod Soni, Hemanta Medhi, Anitya Sagar, Pulkit Garg, Abhay Singh, Umesh Karna\",\"doi\":\"10.2166/aqua.2022.070\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n With the burgeoning population worldwide, the demand for freshwater supply is increasing, mostly in urban areas, due to the influx of people for better livelihood. To mitigate this burden of freshwater demand and build a sustainable water management system, harvesting rainwater during the rainfall season is a viable option. Runoff estimation studies in the past are time-intensive as parameter estimation for an area is complex by the conventional method. In this study, the Motilal Nehru National Institute of Technology (MNNIT), Allahabad campus was selected as a pilot project to assess a methodology that uses Google Earth images for obtaining the runoff coefficients. This method is easy and consumes less time in runoff estimation. This was compared with the conventional method. Using the conventional method (Arc-GIS), the equivalent runoff coefficients for these catchments were found to be 0.2780, 0.3553, and 0.4111, respectively. The range of error (compared to the traditional method) in runoff obtained from the proposed method with a default k value (0.8) was found to be 8.16–13.55%, with an average value of 9.91%. However, with a slightly modified value of k (0.9), the errors were significantly reduced to 1.94–3.32%, with an average of 2.15%.\",\"PeriodicalId\":17666,\"journal\":{\"name\":\"Journal of Water Supply: Research and Technology-Aqua\",\"volume\":\"2 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Water Supply: Research and Technology-Aqua\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2166/aqua.2022.070\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Water Supply: Research and Technology-Aqua","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/aqua.2022.070","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Runoff estimation using digital image processing for residential areas
With the burgeoning population worldwide, the demand for freshwater supply is increasing, mostly in urban areas, due to the influx of people for better livelihood. To mitigate this burden of freshwater demand and build a sustainable water management system, harvesting rainwater during the rainfall season is a viable option. Runoff estimation studies in the past are time-intensive as parameter estimation for an area is complex by the conventional method. In this study, the Motilal Nehru National Institute of Technology (MNNIT), Allahabad campus was selected as a pilot project to assess a methodology that uses Google Earth images for obtaining the runoff coefficients. This method is easy and consumes less time in runoff estimation. This was compared with the conventional method. Using the conventional method (Arc-GIS), the equivalent runoff coefficients for these catchments were found to be 0.2780, 0.3553, and 0.4111, respectively. The range of error (compared to the traditional method) in runoff obtained from the proposed method with a default k value (0.8) was found to be 8.16–13.55%, with an average value of 9.91%. However, with a slightly modified value of k (0.9), the errors were significantly reduced to 1.94–3.32%, with an average of 2.15%.