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Volumetric Analysis of Reservoirs in Drought-Prone Areas Using Remote Sensing Products

Bhagwat, Tejas and Klein, Igor and Huth, Juliane and Leinenkugel, Patrick (2019) Volumetric Analysis of Reservoirs in Drought-Prone Areas Using Remote Sensing Products. Remote Sensing, 11 (17), pp. 1-20. Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/rs11171974 ISSN 2072-4292

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Official URL: https://www.mdpi.com/2072-4292/11/17/1974


Globally, the number of dams increased dramatically during the 20th century. As a result, monitoring water levels and storage volume of dam-reservoirs has become essential in order to understand water resource availability amid changing climate and drought patterns. Recent advancements in remote sensing data show great potential for studies pertaining to long-term monitoring of reservoir water volume variations. In this study, we used freely available remote sensing products to assess volume variations for Lake Mead, Lake Powell and reservoirs in California between 1984 and 2015. Additionally, we provided insights on reservoir water volume fluctuations and hydrological drought patterns in the region. We based our volumetric estimations on the area–elevation hypsometry relationship, by combining water areas from the Global Surface Water (GSW) monthly water history (MWH) product with corresponding water surface median elevation values from three different digital elevation models (DEM) into a regression analysis. Using Lake Mead and Lake Powell as our validation reservoirs, we calculated a volumetric time series for the GSWMWH–DEMmedian elevation combinations that showed a strong linear ‘area (WA) – elevation (WH)’ (R2 > 0.75) hypsometry. Based on ‘WA-WH’ linearity and correlation analysis between the estimated and in situ volumetric time series, the methodology was expanded to reservoirs in California. Our volumetric results detected four distinct periods of water volume declines: 1987–1992, 2000–2004, 2007–2009 and 2012–2015 for Lake Mead, Lake Powell and in 40 reservoirs in California. We also used multiscalar Standardized Precipitation Evapotranspiration Index (SPEI) for San Joaquin drainage in California to assess regional links between the drought indicators and reservoir volume fluctuations. We found highest correlations between reservoir volume variations and the SPEI at medium time scales (12–18–24–36 months). Our work demonstrates the potential of processed, open source remote sensing products for reservoir water volume variations and provides insights on usability of these variations in hydrological drought monitoring. Furthermore, the spatial coverage and long-term temporal availability of our data presents an opportunity to transfer these methods for volumetric analyses on a global scale.

Item URL in elib:https://elib.dlr.de/128868/
Document Type:Article
Title:Volumetric Analysis of Reservoirs in Drought-Prone Areas Using Remote Sensing Products
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Bhagwat, Tejastejas.bhagwat (at) dlr.deUNSPECIFIED
Klein, IgorIgor.Klein (at) dlr.deUNSPECIFIED
Huth, JulianeJuliane.Huth (at) dlr.deUNSPECIFIED
Leinenkugel, PatrickPatrick.Leinenkugel (at) dlr.deUNSPECIFIED
Date:22 August 2019
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
DOI :10.3390/rs11171974
Page Range:pp. 1-20
Crétaux, Jean-Franciosjean-francois.cretaux@legos.obs-mip.fr
Del Rio, Rodrigo Abarcarabarcadelrio.univ@gmail.com
Duguay, Claudecrduguay@uwaterloo.ca
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Series Name:Lake Remote Sensing
Keywords:reservoirs; droughts; water volume; global surface water product; Lake Mead; Lake Powell; California; standardized precipitation evapotraspiration index; digital elevation models; San Joaquin drainage
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Remote sensing and geoscience
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface Dynamics
Deposited By: Bhagwat, Tejas
Deposited On:03 Sep 2019 15:12
Last Modified:14 Dec 2019 04:27

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