Google Earth Engine as Multi-Sensor Open-Source Tool for Monitoring Stream Flow in the Transboundary River Basin: Doosti River Dam
Article
Article Title | Google Earth Engine as Multi-Sensor Open-Source Tool for Monitoring Stream Flow in the Transboundary River Basin: Doosti River Dam |
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ERA Journal ID | 200858 |
Article Category | Article |
Authors | Pakdel-Khasmakhi, Hadis, Vazifedoust, Majid, Paudyal, Dev Raj, Chadalavada, Sreeni and Alam, Md Jahangir |
Journal Title | ISPRS International Journal of Geo-Information |
Journal Citation | 11 (11), pp. 1-28 |
Article Number | 535 |
Number of Pages | 28 |
Year | 2022 |
Publisher | MDPI AG |
Place of Publication | Switzerland |
ISSN | 2220-9964 |
Digital Object Identifier (DOI) | https://doi.org/10.3390/ijgi11110535 |
Web Address (URL) | https://www.mdpi.com/2220-9964/11/11/535 |
Abstract | Understanding the effects of global change and human activities on water supplies depends greatly on surface water dynamics. A comprehensive examination of the hydroclimatic variations at the transboundary level is essential for the development of any adaptation or mitigation plans to deal with the negative effects of climate change. This research paper examines the hydroclimatic factors that contribute to the desiccation of the Doosti Dam’s basin in the transboundary area using multisensor satellite data from the Google Earth Engine (GEE) platform. The Mann–Kendall and Sens slope estimator test was applied to the satellite datasets to analyse the spatial and temporal variation of the hydroclimate variables and their trend over the transboundary area for 18 years from 2004 to 2021 (as the dam began operating in 2005). Statistical analysis results showed decreasing trends in temperature and an increase in rainfall with respect to station-observed available data. Evapotranspiration and irrigated area development followed the increasing pattern and a slight decrease in snow cover. The results confirmed a large expansion of the irrigated area, especially during the winter growing season. The increase in irrigated cultivated areas during both winter and summer seasons is possibly the main reason for the diversion of water to meet the irrigation requirements of the developed agriculture areas. The approach followed in this study could be applied to any location around the globe to evaluate the hydrological conditions and spatiotemporal changes in response to climate change, trend analysis and human activities. |
Keywords | Google Earth Engine; spatiotemporal analysis; cloud-computing platform; Doosti Dam; ungauged or sparsely gauged basin; Landsat; MODIS |
Related Output | |
Is part of | Extreme climate variability and impacts of future climate change on the streamflow in the southeast Queensland, Australia |
Article Publishing Charge (APC) Amount Paid | 2169.86 |
Article Publishing Charge (APC) Funding | Researcher |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 401302. Geospatial information systems and geospatial data modelling |
370704. Surface water hydrology | |
401304. Photogrammetry and remote sensing | |
Public Notes | This article is part of a UniSQ Thesis by publication. See Related Output. |
Byline Affiliations | School of Engineering |
School of Surveying and Built Environment | |
University of Guilan, Iran | |
Murray-Darling Basin Authority, Australia |
https://research.usq.edu.au/item/v8654/google-earth-engine-as-multi-sensor-open-source-tool-for-monitoring-stream-flow-in-the-transboundary-river-basin-doosti-river-dam
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