Remote sensing estimation of water storage in the channel-type reservoirs under unknown underwater topographic data

Dynamic monitoring of reservoir water storage in arid areas is important for water resources assessment, hydroelectric
power generation and agricultural irrigation. However, existing reservoir water calculation methods
often rely on in-situ measurements, which limits their application in data scarce regionals and for regional scale
analyses. Hence, we propose a novel method to estimate the water storage of channel-type reservoirs in arid
areas with unknown underwater topography, with the Bosten Lake watershed serving as a case study site. The
method first divides reservoirs into three types based on their upstream and downstream topography: V-shape, Ushape,
and flat-shape reservoirs. For the V-shape and U-shape reservoirs, the underwater topography was produced
by fitting a linear fit and a polynomial based on the observed elevation above the water surface,
respectively. Meanwhile, extrapolation or splining techniques were used to derive the underwater topography for
the flat-shape reservoir. The proposed methods are able to measure the underwater topography of the Bosten
Lake watershed accurately, with the coefficient of determination (R2) values of 0.83, 0.75 and 0.61 for the Vshape,
U-shape, and flat-shape reservoirs, respectively. In addition, the fit of the in-situ water depths of unmanned
ships was matched to the simulated water depths for the Xiaoshankou and Bayi reservoirs, yielding R2
values of 0.91 and 0.83 as well as root mean square error (RMSE) of 1.27 m and 1.18 m, respectively. Our
approach may be applied in other areas where river underwater topography data is lacking or sparse, and
provide important basis for rational water resources management in these areas.