Browsing by Author "Sikder, Md Safat"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
- A Framework for Estimating Global River Discharge From the Surface Water and Ocean Topography Satellite MissionDurand, Michael; Gleason, Colin J.; Pavelsky, Tamlin M.; Frasson, Renato Prata de Moraes D. M.; Turmon, Michael; David, Cedric H.; Altenau, Elizabeth H.; Tebaldi, Nikki; Larnier, Kevin; Monnier, Jerome; Malaterre, Pierre Olivier; Oubanas, Hind; Allen, George H.; Astifan, Brian; Brinkerhoff, Craig; Bates, Paul D.; Bjerklie, David; Coss, Stephen; Dudley, Robert; Fenoglio, Luciana; Garambois, Pierre-Andre; Getirana, Augusto; Lin, Peirong; Margulis, Steven A.; Matte, Pascal; Minear, J. Toby; Muhebwa, Aggrey; Pan, Ming; Peters, Daniel; Riggs, Ryan; Sikder, Md Safat; Simmons, Travis; Stuurman, Cassie; Taneja, Jay; Tarpanelli, Angelica; Schulze, Kerstin; Tourian, Mohammad J.; Wang, Jida (American Geophysical Union, 2023-04-06)The Surface Water and Ocean Topography (SWOT) mission will vastly expand measurements of global rivers, providing critical new data sets for both gaged and ungaged basins. SWOT discharge products (available approximately 1 year after launch) will provide discharge for all river that reaches wider than 100 m. In this paper, we describe how SWOT discharge produced and archived by the US and French space agencies will be computed from measurements of river water surface elevation, width, and slope and ancillary data, along with expected discharge accuracy. We present for the first time a complete estimate of the SWOT discharge uncertainty budget, with separate terms for random (standard error) and systematic (bias) uncertainty components in river discharge time series. We expect that discharge uncertainty will be less than 30% for two-thirds of global reaches and will be dominated by bias. Separate river discharge estimates will combine both SWOT and in situ data; these “gage-constrained” discharge estimates can be expected to have lower systematic uncertainty. Temporal variations in river discharge time series will be dominated by random error and are expected to be estimated within 15% for nearly all reaches, allowing accurate inference of event flow dynamics globally, including in ungaged basins. We believe this level of accuracy lays the groundwork for SWOT to enable breakthroughs in global hydrologic science.
- Lake-TopoCat: a global lake drainage topology and catchment databaseSikder, Md Safat; Wang, Jida; Allen, George H.; Sheng, Yongwei; Yamazaki, Dai; Song, Chunqiao; Ding, Meng; Cretaux, Jean-Francois; Pavelsky, Tamlin M. (Copernicus, 2023-08-08)Lakes and reservoirs are ubiquitous across global landscapes, functioning as the largest repository of liquid surface freshwater, hotspots of carbon cycling, and sentinels of climate change. Although typically considered lentic (hydrologically stationary) environments, lakes are an integral part of global drainage networks. Through perennial and intermittent hydrological connections, lakes often interact with each other, and these connections actively affect water mass, quality, and energy balances in both lacustrine and fluvial systems. Deciphering how global lakes are hydrologically interconnected (or the so-called "lake drainage topology") is not only important for lake change attribution but also increasingly critical for discharge, sediment, and carbon modeling. Despite the proliferation of river hydrography data, lakes remain poorly represented in routing models, partially because there has been no global-scale hydrography dataset tailored to lake drainage basins and networks. Here, we introduce the global Lake drainage Topology and Catchment database (Lake-TopoCat), which reveals detailed lake hydrography information with careful consideration of possible multifurcation. Lake-TopoCat contains the outlet(s) and catchment(s) of each lake; the interconnecting reaches among lakes; and a wide suite of attributes depicting lake drainage topology such as upstream and downstream relationship, drainage distance between lakes, and a priori drainage type and connectivity with river networks. Using the HydroLAKES v1.0 (Messager et al., 2016) global lake mask, Lake-TopoCat identifies ĝ1/4ĝ1.46 million outlets for ĝ1/4ĝ1.43 million lakes larger than 10ĝha and delineates 77.5×106ĝkm2 of lake catchments covering 57ĝ% of the Earth's landmass except Antarctica. The global lakes are interconnected by ĝ1/4ĝ3 million reaches, derived from MERIT Hydro v1.0.1 (Yamazaki et al., 2019), stretching a total distance of ĝ1/410×106ĝkm, of which ĝ1/4ĝ80ĝ% are shorter than 10ĝkm. With such unprecedented lake hydrography details, Lake-TopoCat contributes towards a globally coupled lake-river routing model. It may also facilitate a variety of limnological applications such as attributing water quality from lake scale to basin scale, tracing inter-lake fish migration due to changing climate, monitoring fluvial-lacustrine connectivity, and improving estimates of terrestrial carbon fluxes. Lake-TopoCat is freely accessible at 10.5281/zenodo.7916729 (Sikder et al., 2023).