Understanding Volume Estimation Uncertainty of Lakes and Wetlands Using Satellites and Citizen Science

Abstract

We studied variations in the volume of water stored in small lakes and wetlands using satellite remote sensing and lake water height data contributed by citizen scientists. A total of 94 water bodies across the globe were studied using satellite data in the optical and microwave wavelengths from Landsat 8, Sentinel-1 and Sentinel-2. The uncertainty in volume estimation as a function of geography and geophysical factors such as cloud cover, precipitation and water surface temperature, was studied. The key finding that emerged from this global study is that uncertainty is highest in regions with a distinct precipitation season such as in the monsoon dominated South Asia or the Pacific Northwestern region of the US. This uncertainty is further compounded when small lakes and wetlands are seasonal with alternating land use as a water body and agricultural land, such as the wetlands of Northeastern Bangladesh. On an average, 45% of studied lakes could be estimated of

Necessary storage for managing early flash flood to save crops in the north-eastern region of Bangladesh

“…This study estimates necessary storage at three stations using Flood duration curve (FDC) method (Takeuchi and Masood, 2017;. The study also es-timates water storage capacity of 6 haors by using satellitebased citizen science haor volume estimation technique (Ahmad et al, 2020;Khan et al, 2023). Finally, the study investigates the viability of the strategy of deliberately allowing a haor to be inundated as a means of safeguarding other haors.…”

“…Code availability. The python code to estimate reservoir volume of haor from remote sensing data is available from Khan et al (2023).…”