Joy Bhattacharjee, Mehedi Rabbil, Nasim Fazel, Hamid Darabi, Bahram Choubin, Md. Motiur Rahman Khan, Hannu Marttila, Ali Torabi Haghighi, Accuracy assessment of remotely sensed data to analyze lake water balance in semi-arid region, Science of The Total Environment, Volume 797, 2021, 149034, ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2021.149034
Accuracy assessment of remotely sensed data to analyze lake water balance in semi-arid region
|Author:||Bhattacharjee, Joy1; Rabbil, Mehedi1; Fazel, Nasim1,2;|
1Water, Energy and Environmental Engineering Research Unit, PO Box 4300, FI-90014, University of Oulu, Finland
2Freshwater Centre, Finnish Environment Institute (SYKE), Helsinki, Finland
3Soil Conservation and Watershed Management Research Department, West Azarbaijan Agricultural and Natural Resources Research and Education Center, AREEO, Urmia, Iran
|Online Access:||PDF Full Text (PDF, 4 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2021110854260
|Publish Date:|| 2021-11-08
Lake water level fluctuation is a function of hydro-meteorological components, namely input, and output to the system. The combination of these components from in-situ and remote sensing sources has been used in this study to define multiple scenarios, which are the major explanatory pathways to assess lake water levels. The goal is to analyze each scenario through the application of the water balance equation to simulate lake water levels. The largest lake in Iran, Lake Urmia, has been selected in this study as it needs a great deal of attention in terms of water management issues. We ran a monthly water balance simulation of nineteen scenarios for Lake Urmia from 2003 to 2007 by applying different combinations of data, including observed and remotely sensed water level, flow, evaporation, and rainfall. We used readily available water level data from Hydrosat, Hydroweb, and DAHITI platforms; evapotranspiration from MODIS and rainfall from TRMM. The analysis suggests that the consideration of field data in the algorithm as the initial water level can reproduce the fluctuation of Lake Urmia water level in the best way. The scenario that combines in-situ meteorological components is the closest match to the observed water level of Lake Urmia. Almost all scenarios showed good dynamics with the field water level, but we found that nine out of nineteen scenarios did not vary significantly in terms of dynamics. The results also reveal that, even without any field data, the proposed scenario, which consists entirely of remote sensing components, is capable of estimating water level fluctuation in a lake. The analysis also explains the necessity of using proper data sources to act on water regulations and managerial decisions to understand the temporal phenomenon not only for Lake Urmia but also for other lakes in semi-arid regions.
Science of the total environment
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
218 Environmental engineering
This work was partially funded by Maj and Tor Nessling Foundation.
© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).