Abstract
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.
Highlights
The global fresh water reservoirs constitute as important sources of fresh water storage, transportation and provision [1]
While our work presents a novel approach for reservoir water volume variation monitoring, our methodology consists of some limitations and assumptions which are discussed
Using globally available and validated digital elevation models, we provided a methodology that is capable of utilizing the complete coverage of the Global Surface Water (GSW) product
Summary
The global fresh water reservoirs constitute as important sources of fresh water storage, transportation and provision [1]. In addition to the fresh water supply, they are major water providers for the industry, hydropower plants and agriculture sector [2]. While China, Brazil, Russia, Canada and the USA are the world’s top five hydroelectricity producers [4], most of the global dam projects and reservoirs are located in North America and Asia [5,6]. With such rapid growth in the number of reservoirs, there is a need for a globally consistent, reliable and openly accessible reservoir water storage information system that could be used to monitor water volume patterns. The global dispersal and availability of fresh water is highly irregular and often does not correlate with human population distributions or socio-economic requirements [2]
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