Volumetric analysis of reservoirs in drought-prone areas using remote sensing products

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-termmonitoring of reservoir water volume variations. In this study, we used freely available remote sensing products to assess volume variations for LakeMead, 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 SurfaceWater (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 LakeMead 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 atmediumtime scales (12-18-24-36months). Ourwork demonstrates the potential of processed, open source remote sensing products for reservoirwater volume variations and provides insights on usability of these variations in hydrological droughtmonitoring. Furthermore, the spatial coverage and long-termtemporal availability of our data presents an opportunity to transfer thesemethods for volumetric analyses on a global scale.