Volume Variations of Small Inland Water Bodies from a Combination of Satellite Altimetry and Optical Imagery

Christian Schwatke,Denise Dettmering,Florian Seitz

doi:10.3390/rs12101606

Abstract

In this study, a new approach for estimating volume variations of lakes and reservoirs using water levels from satellite altimetry and surface areas from optical imagery is presented. Both input data sets, namely water level time series and surface area time series, are provided by the Database of Hydrological Time Series of Inland Waters (DAHITI), developed and maintained by the Deutsches Geodätisches Forschungsinsitut der Technischen Universität München (DGFI-TUM). The approach is divided into three parts. In the first part, a hypsometry model based on the new modified Strahler approach is computed by combining water levels and surface areas. The hypsometry model describes the dependency between water levels and surface areas of lakes and reservoirs. In the second part, a bathymetry between minimum and maximum surface area is computed. For this purpose, DAHITI land-water masks are stacked using water levels derived from the hypsometry model. Finally, water levels and surface areas are intersected with the bathymetry to estimate a time series of volume variations in relation to the minimum observed surface area. The results are validated with volume time series derived from in-situ water levels in combination with bathymetric surveys. In this study, 28 lakes and reservoirs located in Texas are investigated. The absolute volumes of the investigated lakes and reservoirs vary between 0.062 km 3 and 6.041 km 3 . The correlation coefficients of the resulting volume variation time series with validation data vary between 0.80 and 0.99. Overall, the relative errors with respect to volume variations vary between 2.8% and 14.9% with an average of 8.3% for all 28 investigated lakes and reservoirs. When comparing the resulting RMSE with absolute volumes, the absolute errors vary between 1.5% and 6.4% with an average of 3.1%. This study shows that volume variations can be calculated with a high accuracy which depends essentially on the quality of the used water levels and surface areas. In addition, this study provides a hypsometry model, high-resolution bathymetry and water level time series derived from surface areas based on the hypsometry model. All data sets are publicly available on the Database of Hydrological Time Series of Inland Waters.

Highlights

In the last years, discussions about global climate change have been increasing in the media and society, especially in connection with originators of climate change
The water levels of the gauging station of Pilot Point (ID: 08051100) at Ray Roberts Lake provided by the Texas Water Development Board (TWDB)/United States Geological Survey (USGS) are used
A hypsometry model based on water levels and surface areas is calculated

Summary

Introduction

Discussions about global climate change have been increasing in the media and society, especially in connection with originators of climate change. Numerous climate studies are based on remote sensing data [1,2]. Since the 1970s, remote sensing has been providing valuable data for monitoring the global water cycle and its changes. Compared to the global water storage, only 0.013% [3] of the Earth‘s water is stored in lakes and reservoirs which are often affected by the impact of climate change. The impact of climate change on the availability of fresh water for human consumption is immense. In future, this will require sustainable water management by the countries [6]. Today, existing data gaps can be often filled by using remote sensing technology which has already provided valuable information about changes on Earth

Methods

Results

Conclusion