Understanding Volumetric Water Storage in Monsoonal Wetlands of Northeastern Bangladesh

Abstract

The volume of water stored in seasonal wetlands is a fundamental but difficult to measure variable for developing a physical understanding of wetland behavior. For seasonal wetlands that are a major source of water for rice and fish production, this physical understanding is key to planning for water-food security and ecosystem services. This study quantified variations in volumetric storage for the numerous seasonal wetlands of northeastern Bangladesh, locally known as "haors." These haors receive transboundary runoff from densely vegetated and mountainous terrain in India and face persistent monsoonal cloud cover as they become full. We estimated volumetric storage for 13 haors by using extensive remote sensing data on water surface extent and elevation that was complemented with citizen-contributed gauge data. Assuming a trapezoidal bathymetry, an area-volume relationship was developed for selected haors. This relationship was assumed to be valid for extrapolating volumetric estimations over all the haors in the region. Results suggested that as haors get filled with the onset of monsoon rains, total estimated storage relative to the lowest observable level varied from 6.5 (±0.4) km 3 in May to 30.9 (±2.0) km 3 in July (peak of monsoon). Choosing a rectangular bathymetry can lead to 47% higher estimates compared to trapezoidal cross section. Estimating this intra-annual/interannual increase in storage is important for the region to plan water management policies that balance the human and ecosystem needs. Our analytical approach has potential for application to wetlands worldwide in light of the upcoming Surface Water and Ocean Topography (SWOT) mission.

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

“…Incidence angle also plays an important role in the image pre-processing; for the water surface classification, and we considered look angles from 31.7⁰ to 45.4⁰. More details on this choice are described by Ahmad et al [29]. With the pre-processed image, a backscatter threshold of -13db was selected to identify the water body, as suggested by Liu [45].…”

“…To estimate the volume variation, we linearly interpolated the water surface area data, so that the timestamps of both water elevation and interpolated water surface area were the same, which makes it easier to calculate the volume change. The information of the exact bathymetry of the water bodies was not available, so we estimated the volume stored with respect to the lowest observed water surface elevation in the time series, similar to Ahmad et al [29] who had earlier applied citizen scientist height data for northeastern wetlands of Bangladesh. The lowest water elevation observation was obtained from the LOCSS website over the period of the study.…”

“…The lowest water elevation observation was obtained from the LOCSS website over the period of the study. For simplicity, many studies in the past have assumed trapezoidal bathymetry [29], [30], so we also assumed trapezoidal bathymetry. Pyramidal bathymetry of lakes can also be assumed as proposed in Cretaux et al [26] but internal comparison done between both hypotheses have usually yielded very similar results.…”

“…To overcome the combined challenges of the current fleet of satellite sensors and the limitations of existing in-situ gauge networks, one possible solution to monitoring lake water level is the application of citizen science in monitoring waterbodies [29]- [31]. Citizen science is an emerging science where the public participates and collaborates in scientific research to increase knowledge.…”

Long-Term Hydrological Regime Monitoring of a Mediterranean Agro-Ecological Wetland Using Landsat Imagery: Correlation with the Water Renewal Rate of a Shallow Lake

“…Several studies have been reported in recent years, in which different methodologies have been used for the volumetric study of water storage in wetlands. One of the reported procedures has been the combination of SAR imagery, which provides continuous surface data without cloud interference [40], with elevation data provided by altimetric radars such us ENVISAT RA-2 GDR, PALSAR-2, Jason-3 and Sentinel-3, among others [34,[41][42][43]. These studies were able to estimate variations in the volumetric storage of wetlands of different hydrological characteristics.…”