Volume 10, Issue 19 (5-2019)
J Watershed Manage Res 2019, 10(19): 46-57 |
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Habibi Khaveh H, GHolami Sefidkouhi M A, Emadi A R. (2019). Bathymetry and Volume Estimation of Reservoirs using OLI Imagary. J Watershed Manage Res. 10(19), 46-57. doi:10.29252/jwmr.10.19.46
URL: http://jwmr.sanru.ac.ir/article-1-680-en.html
URL: http://jwmr.sanru.ac.ir/article-1-680-en.html
1- Sari Agricultural Sciences and Natural Resources University
Abstract: (3098 Views)
Nowadays using field depth measurement to estimate capacity of water reservoirs is a costly and time consuming method. In this regard, different multiple techniques of remote sensing method has been adopted. In this study, a radiation and reflection based model was introduced to estimating the bathymetry and water capacity of reservoir by images of OLI sensor. For this, at May 17, 2015 water depth was measured each 50 meters in Mahdasht, Sorbon and Dasht-e-naz water reservoirs using Sonar system. All water reservoirs located in Miandoroud plain between latitude of and longitude of in north east of Sari city, Mazandaran province, Iran. Then, the measurement continued for five more times; on May 26, Aug 5 of 2015 and again on May 28, June 29 and August 23 of 2016 to record depth and precise determination of water capacity. In order to estimate the reservoir capacity image values for blue, green and red band two times more than maximum depth, were classified equally (any given class represents 0.5 meter depth). Subsequently, total volume of reservoir was extracted by a sum of product of number of cells, cell depth index and cell area. Finally, the average relative error and estimated correlation coefficients of volume estimation for 3 mentioned reservoirs in 6 times in blue, green and red bands were 11.19, 4.95, 5.5 and 96, 97 and 98 percent, respectively. Consequently, the use of this method is proposed to measure the volume of reservoirs.
Type of Study: Research |
Subject:
سنجش از دور و سامانه های اطلاعات جغرافيايی
Received: 2016/07/20 | Accepted: 2017/12/31
Received: 2016/07/20 | Accepted: 2017/12/31
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