Downscaling Surface Water Inundation from Coarse Data to Fine-Scale Resolution: Methodology and Accuracy Assessment

Abstract. A set of complex processes contribute to generate river runoff, which in the hydrological sciences are typically divided into two major categories: surface runoff, sometimes called Hortonian flow, and baseflow-driven runoff or Dunne flow. In this study, we examine the covariance of global satellite-based surface water inundation (SWI) observations with two remotely sensed hydrological variables, precipitation, and terrestrial water storage, to better understand how apparent runoff generation responds to these two dominant forcing mechanisms in different regions of the world. Terrestrial water storage observations come from NASA’s Gravity Recovery and Climate Experiment (GRACE) mission, while precipitation comes from the Global Precipitation Climatology Project (GPCP) combined product, and surface inundation levels from the NASA Surface WAter Microwave Product Series (SWAMPS) product. We evaluate the statistical relationship between surface water inundation, total water storage anomalies (TWS; TWSAs), and precipitation values under different time lag and quality control adjustments between the data products. We find that the global estimation of surface inundation improves when considering a quality control threshold of 50 % reliability for the SWAMPS data and after applying time lags ranging from 1 to 5 months. Precipitation and total water storage equally control the majority of surface inundation developments across the globe. The model tends to underestimate and overestimate at locations with high interannual variability and with low inundation measurements, respectively.

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Preparing for fine-scale ocean surface topography observations with the Surface Water and Ocean Topography (SWOT) Mission

10.5194/egusphere-egu2020-7535 ◽

2020 ◽

Author(s):

Rosemary Morrow ◽

Lee-Lueng Fu

Keyword(s):

Surface Water ◽

High Frequency ◽

Sea Surface Height ◽

Internal Tides ◽

Ocean Dynamics ◽

Sea Surface ◽

Fine Scale ◽

In Situ Data ◽

Ocean Topography

The future international Surface Water and Ocean Topography (SWOT) Mission, planned for launch in late 2021, will make high-resolution 2D observations of sea-surface height using SAR radar interferometric techniques. SWOT will map the global and coastal oceans up to 77.6&#176; latitude every 21 days over a swath of 120 km (20 km nadir gap). Today&#8217;s 2D mapped altimeter data can resolve ocean scales of 150 km wavelength whereas the SWOT measurement will extend our 2D observations down to 15-30 km, depending on sea state. SWOT will offer new opportunities to observe the oceanic dynamic processes at these smaller scales, that are important in the generation and dissipation of ocean kinetic energy, and are one of the main gateways connecting the surface to the ocean interior. Active vertical exchanges linked to these scales have impacts on the local and global budgets of heat and carbon, and on nutrients for biogeochemical cycles.SWOT&#8217;s unprecedented 2D ocean SSH observations include &#8220;balanced&#8221; geostrophic eddy motions and high-frequency internal tides and internal waves. SWOT will provide global observations of the 2D structure of these phenomena, enabling us to learn more about their interactions, and helping us to interpret what is currently observed in 1D with conventional altimetry. Yet this mix of balanced and unbalanced motions is a challenge for calculating geostrophic currents directly from SSH or for reconstructing the 4D upper ocean circulation. At these small scales, the ocean dynamics evolve rapidly, and even with SWOT&#8217;s 2D SSH images, one satellite cannot observe the temporal evolution of these processes. SWOT data will need to be combined with other satellite and in-situ data and models to better understand the upper ocean 4D circulation (x,y,z,t) over the next decade. SWOT&#8217;s new technology will be a forerunner for the future altimetric observing system.We will present recent progress in understanding the ocean dynamics contributing to fine-scale sea-surface height, including high-frequency processes such as internal tides, from 1D alongtrack altimetry, SAR data, in-situ data and models. We will also discuss the specific problems of validating the SWOT 2D small, rapid dynamics with in-situ data and other satellite data.&#160;

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Review of available data for a South African Inventory of Inland Aquatic Ecosystems (SAIIAE)

Water SA ◽

10.4314/wsa.v44i2.05 ◽

2018 ◽

Vol 44 (2 April) ◽

Cited By ~ 1

Author(s):

Heidi Van Deventer ◽

Lindie Smith-Adao ◽

Chantel Petersen ◽

Namhla Mbona ◽

Andrew Skowno ◽

...

Keyword(s):

South Africa ◽

South African ◽

Aquatic Ecosystems ◽

Accuracy Assessment ◽

Conservation Status ◽

Freshwater Ecosystems ◽

Biodiversity Assessment ◽

Fine Scale ◽

Wetland Ecosystem ◽

Inland Wetlands

The National Biodiversity Assessment of 2011 found freshwater ecosystems to be highly threatened and poorly protected. However, a number of studies have shown that the National Wetland Map (NWM) Version 4 represents less than 54% of wetlands mapped at a fine scale. A more comprehensive South African Inventory of Inland Aquatic Ecosystems (SAIIAE) would greatly improve the assessment of wetland ecosystem types and their condition and conservation status, and is crucial for monitoring trends to inform decision making and planning. In preparation for the third National Biodiversity Assessment of 2018, a review was undertaken to identify possible data sources that could contribute to the SAIIAE. The objectives of the study were to (i) assess which type of information is available for developing a SAIIAE; and (ii) list and understand the availability of fine-scale wetland data for updating the NWM. A variety of data related to species occurrence and distribution, extent and type of inland wetlands and rivers, as well as datasets which describe regional settings of inland aquatic ecosystems, were found across a number of institutions. Fine-scale spatial data amounted to more than double the extent of inland wetlands mapped by remote sensing at a country-wide scale. Nearly 5 million ha of fine-scale data were collected from a diverse number of institutions, with the majority (73%) of these data mapped by Government (3 681 503 ha or 3% of South Africa). It is estimated that < 8% of the sub-quaternary catchments of South Africa had complete wetland data sets, primarily in the Gauteng, Mpumalanga and Western Cape Provinces. Accuracy assessment reports and confidence ratings were however not consistently available for the wetland datasets. Inland wetlands in the majority of South Africa (84%) therefore remain poorly represented. We recommend future steps to improve the SAIIAE, including improving the representation of inland wetland ecosystem types and focusing on accuracy assessment.

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