Remote Sensing of Storage Fluctuations of Poorly Gauged Reservoirs and State Space Model (SSM)-Based Estimation

Alka Singh,Ujjwal Kumar,Florian Seitz

doi:10.3390/rs71215872

Abstract

To reduce hydrological uncertainties in the regular monitoring of poorly gauged lakes and reservoirs, multi-dimensional remote sensing data have emerged as an excellent alternative. In this paper, we propose three methods to delineate the volume of such equipotential water bodies through a combination of altimetry (1D), Landsat (2D) and bathymetry (2D) data, namely an altimetry-bathymetry-volume method (ABV), a Landsat-bathymetry-volume method (LBV) and an altimetry-Landsat-volume-variation method (ALVV). The first two data products are further merged by a Kalman-filter-based state space model (SSM) to obtain a combined estimate (CSSME) time series and near future prediction. To validate our methods, we tested them on the well-measured Lake Mead and further applied them on the poorly gauged Aral Sea, which has inaccurate bathymetry and very limited ground observation data. We updated the lake bathymetry of the Aral Sea, which was more than half a century old. The resultant remote sensing products have a very good long-term agreement among each other. The Lake Mead volume estimations are very highly coherent with the ground observations for all cases (R2 > 0.96 and NRMSE < 2.1%), except for the forecast (R2 = 0.75 and NRMSE = 3.7%). Due to lack of in situ data for the Aral Sea, the estimated volumes are compared, and the entire Aral Sea LBV and ABV have R2 = 0.91 and NRMSE = 5.5%, and the forecast compared to CSSME has R2 = 0.60 and NRMSE = 2.4%.

Highlights

Lakes and reservoirs are vital because they are a major source of water for domestic and industrial usage for human beings, and because of their riparian zones, where some of the most bio-diverse ecosystems exist
Water heights observed from the southern part of East Aral Sea are higher than the relatively stable part selected in the Landsat-selected region boundary (SRB)
For the East Aral Sea from 2008, only Landsat-SRB water heights are used, and meaningful comparisons of the models for the reservoir are restricted until December 2007

Summary

Introduction

Lakes and reservoirs are vital because they are a major source of water for domestic and industrial usage for human beings, and because of their riparian zones, where some of the most bio-diverse ecosystems exist. The rapidly changing water volume of lakes and reservoirs disturbs human settlements that are dependent on them, and whole ecosystems. In the last few decades, satellite remote sensing has evolved as a promising alternative for regular global monitoring of water resources [1,2,3]. Satellite altimetry is a well-established tool for inland water level estimation [4,5,6,7] and Landsat, with its long archive, free availability and relatively high-resolution database, delivers one of the most frequently used remote sensing data sets [8,9,10,11]

Objectives

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Conclusion