Summary

The proposed activity aims to investigate the new SWOT data to study the ocean processes at different scales from regional (North Sea and Baltic Sea) to coastal/estuarine/tidal inlets (German Bight, Ems, Weser, Elbe estuaries, Stanev et al., 2017, Fig. 1) and along the German coasts (Fig.2) In the 1-day phase data calibration will be attempted and the high temporal and space variability investigated over ocean and in-land water. The synergy between SWOT observations and in-situ, model simulation and SAR altimeter data (Fenoglio-Marc et al., 2015, Dinardo et al., 2017, Wiese et al., 2018) will be further used in the following science phase to improve the actual understanding of physical phenomena. The modelling tool will be based on the high spatial and temporal-resolution integrated coupled (ocean, wave, sediment transport and hydrology) model system GCOAST for river-to-ocean continuum scales (Staneva et al., 2017).

Because of its mapping resolution and of the novelty of its measurements, SWOT will present new challenges for data retrieval and interpretation, especially at the smallest length scales, which are not captured from both along-track altimetry and gridded products. Surface waves, tides, and internal waves are the physical processes which govern oceanic behavior at these small scales. For research towards application in operation we will consider the four scientific challenges listed below:

1. Coastal ocean dynamics
2. Coastal tides and internal tides
3. Extremes
4. Track coastal evolution

The approach will consist in:

1. Simulating the SWOT observations
2. Assessing the quality of real observations and L2 products during the cal/val 1-day phase in the limited strife covered by the 1-day repeat (Fig. 2 and river Rhine)
3. Assess the quality of real observations and L2 products during the scientific phase with repeat 21 days and 2-4 observations per pass in the enlarged region (Figs. 1, 2)
4. Investigate the 1-4 scientific challenges during the scientific phase in the full region (Figs. 1, 2)

Current Progress and Future Steps

References

Dinardo S., Fenoglio-Marc L., Buchhaupt C., Becker M., Scharro R., Fernandez J. Benveniste J. (2017). CryoSat-2 performance along the german coasts, AdSR special Issue CryoSat-2, https://doi.org/10.1016/j.asr.2017.12.018, https://authors.elsevier.com/c/ 1XXGm~ 6OiXQOF.

Fenoglio-Marc, L., Dinardo, S., Scharroo, R., Roland, A., Dutour, M., Lucas, B., Becker, M., Benveniste, J., Weiss, R. (2015). The German Bight: a validation of CryoSat-2 altimeter data in SAR mode, Advances in Space Research, doi: http://dx.doi.org/10.1016/j.asr.2015.02.014.

Stanev E., Schulz-Stellenfleth J., Staneva J., Grayek S., Grashorn S., Behrens A., Koch W., Pein J. (2016): Ocean forecasting for the German Bight: from regional to coastal scales, Ocean Sci., 12, 1105–1136, 2016.

Staneva J., Alari V., Breivik O, Bidlot J.-R. and Mogensen K. (2017): Effects of wave-induced forcing on a circulation model of the North Sea. Ocean Dynamics, Vol. 67, Issue 1, pp 81-191.

Wiese A., J. Staneva, J. Schultz-Stellenfleth, A. Behrens, L. Fenoglio-Marc and J.R. Bidlot (2018): Synergy between satellite observations and model simulations during extreme events. Ocean Science. doi.org/10.5194/os-2018-87.

Figures

Summary

The new capabilities and performance offered by the SWOT mission demonstrate the need to progress and innovate in science, but also to lead the specific methodological developments (new methods of treatment, adaptation existing methods, …), in close collaboration with scientists and end users. Integrated into complex information systems, data provided by the SWOT mission will maintain and improve the quality of ocean forecasts and hydrological diagnostics whose economic value is recognized. These analyzes will only be possible if the quality of the SWOT measurements is demonstrated. This mission therefore requires the development of accurate Calibration and Validation tools adapted to the very high precision of the expected measurements.

Concerning the routine monitoring of inland water bodies, the vorteX.io light altimeter is a complementary space-derived remote sensing solution for bridging data gaps and comparing data time series with other instruments. Indeed, this solution relies on the complementarity between flying UAVs and an autonomous light altimeter payload with a centimeter accuracy water surface height assessment over rivers and lakes. Taking the advantage of UAV versatility and fast deployment capabilities, the solution is based on an innovative instrument capable of performing high resolution and real-time measurements of hydrological areas. Thus, on-demand fast data acquisition is possible, as well as offline long-term monitoring. We propose the vorteX.io solution to be considered by the SWOT mission team and early adopters to perform in-situ measurements campaigns over hydrological systems and provide relevant information collocated in space and time with the SWOT mission in order to assess its performance over hydrology.

Summary

The USGS has used operational monitoring of river discharge using Jason-2/3 altimetry for river stage (and slope as available) and Landsat dynamic surface-water extent for river surface geometry. These data are used with a modified flow-law equation to compute streamflow (discharge). Ancillary data include ground-based streamflow measurements collected by USGS for calibration and validation. Workflow culminates in dissemination of satellite-derived discharges via USGS National Water Information System (NWIS). We plan to use the river reach SWOT products as they become available for operational computation of streamflow at remotely sensed gaging sites. From the river reach data we will need to obtain river-reach elevation, slope, and width at locations of interest; these data are the required inputs to our existing satellite-based remote sensing of discharge workflow. We are currently developing our remote stream gauging techniques at several river reaches in Alaska. SWOT data simulated for these study reaches would be ideal for integrating into our operational stream gauging workflow. The sites have either ongoing ground-gage information or field measurements that can be used for validation. We plan to compare SWOT-derived discharge to USGS ground-based gaging station data for validation.

The USGS Water Mission Area is investing in development of the operational capability to measure river discharge from satellite data. Post launch, the ongoing R&D project expects to ingest SWOT data, when they become available, into its operational river monitoring system. We are also working with the SWOT Discharge Algorithm Working Group and plan to continue collaboration with that group to inform our stream gauging work post launch.

Summary

LIS (Kumar et al., 2006) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. LIS is used in operational and routine environments at numerous U.S. agencies, supporting model runs for the North America Land Data Assimilation System (NLDAS), the Global Land Data Assimilation System (GLDAS; Rodell et al., 2004), among others. The current version of LIS includes a separate data preprocessing environment known as the Land surface Data Toolkit (LDT; Arsenault et al., 2018) and a post-processing data analytics environment known as the Land surface Verification Toolkit (LVT; Kumar et al., 2012). LDT and LVT are open source and available through GitHub.

he utility of remote-sensed data for hydrological applications is of utmost importance to the U.S. Air Force. The current lack of sufficient data-driven information available at the critical time horizons for informing transboundary water decision-making for the intelligence, defense, and foreign policy communities is a key gap in 557th Weather Wing’s operational Land Information System (LIS). Implementation of a multivariate DA scheme accounting for the simultaneous assimilation of SWOT data and terrestrial water storage (TWS) anomalies derived from the Gravity Recovery and Climate Experiment (GRACE) mission into the LIS Framework will provide the much-needed observation-based constraints on modeled estimates via the USAF’s LIS-based Global Hydro-Modeling Intelligence System, particularly over data poor regions of the world (Kumar et al., 2016; Getirana et al., 2014). The resultant hydrologic products and services will be synthesized into information required by decision makers (e.g., the Interagency Water Working Group) to address transboundary water security threats including potential for migration, economic losses and conflict, and disruptions to military navigation. Thus, the proposed infrastructure will promote societal applications for sustainable water resource management, humanitarian assistance and disaster response, economic development, and regional stability. Completion of this project and sustainment of the operational capability by Air Force Weather will empower our federal agencies and partners (e.g., Department of State) to fulfill the strategic objectives of the U.S. Global Water Strategy while helping them bring to light transboundary water issues for the stakeholder community at-large.

Summary

Of the over 7,000+ dams (lakes/reservoirs) in Texas, only 119 are gauged for water level monitoring. Evaporative loss from reservoirs is significant (especially during summer) and it often exceeds the water usage from reservoir. Being able to monitor evaporative water loss from all unmonitored reservoirs would lead to improved assessments of surface water availability in the state. The quantitative estimate of evaporative water loss requires accurate information on reservoir surface area. The volumetric water loss can be computed by multiplying the lake area with the reservoir evaporation rate that the TWDB compiles at monthly timescale for 1˚x 1˚grids. Currently, we can only estimate the evaporation loss for the monitored reservoir through reservoir specific elevation-area rating curves. SWOT’s ability to track water elevation and area/extent over global inland water bodies will equip TWDB with a monitoring capability that covers all other unmonitored water bodies that are greater than 250 m × 250 m. SWOT’s storage change data will also help TWDB with a more accurate inventory of water gained through precipitation or depleted through evaporation/water use, leading to improved forecasts of water availability.

The TWDB plans to use SWOT lake surface elevation and area datasets, along with TWDB’s gridded lake evaporation rate dataset to compute the volumetric lake evaporation loss for all lakes that are detected by SWOT on a monthly basis.

Summary

Stantec is engaged in a multitude of coastal resiliency, climate change vulnerability, coastal restoration, coastal engineering, and community development projects throughout the world. Planning, permitting, and executing such studies requires detailed baseline information and subsequent monitoring of environmental drivers and dynamics at sub-mesoscale both from rivers and the ocean. We will use this new SWOT high resolution data to parameterize and validate hydrographic and hydrodynamic model outputs, evaluate the effectiveness of water quality and sediment management related projects, and improve coastal hazard identification for habitats, communities, and infrastructure during planning, design, and impact assessments.

Summary

This project will use SWOT-relevant data products to enhance the quality of flow monitoring, river flux over gates of trans-boundary reservoirs for anticipating floods in the Jhelum basin. This will allow for observation of unanticipated flood events from unregulated tributaries of river Jhelum (such as the Poonch River).

For determining the variations in wetlands, fresh simulations will be created for southern Pakistan, Sindh Province. For this aspect of study, ground data will be used for undertaking calibration/validation of the simulation. Once a simulation is created, SWOT-like products will be connected whenever available to gain monthly/cross seasonal variations in the wetlands developed on waterlogged soil.

Summary

This project will apply the CNES Hydrology data simulator over river reaches where JPL SWOT SLC simulator has already been applied and make comparisons. Example river reaches will be from the Sacramento, Po, and Platte Rivers. Error characteristics over these rivers will be compared to understand the circumstances under which a large scale hydrology simulator such as CNES SWOT simulator is acceptable for hydrologic investigations. Comparisons will be made available over test cases for SWOT Early Adopters to understand the limit to which CNES hydrology simulator can be applied. After the launch of SWOT in 2022, the OSU team may compare SWOT simulations from the two types (JPL and CNES) actual error statistics from Cal/Val sites.

Summary

Four potential uses of SWOT data products within the National Water Model (NWM) will be the focus for this EA activity. These include: Evaluating the SWOT raster data product within the Analysis mode of the NWM as an indicator of available water storage. This is a running calculation within the NWM and is not well constrained at present. Assessing the temporal stack of SWOT raster data products as an historical evaluation of relative level and extent of flooding for given discharges (a high priority of the NWM). Using SWOT river vector products (RiverSP, RiverAVG) to test current channel slope estimates in the NWM, as well as channel routing. Using SWOT RiverAVG vector to evaluate channel geometry estimates within NWM.

CLS will integrate SWOT data in the Hydroweb database and plans to use SWOT data for validation and calibration of numerical models.

Summary

This project will explore the transition of NASA satellite capabilities to operational forecasters and operational models. This project will develop a methodology to assimilate SWOT water surface elevation (WSE) into the National Water Model (NWM) to expand the spatial coverage of observations to regions of the world without adequate in situ streamflow information. In order to use SWOT data to initialize the NWM, case studies will be examined within Alaska related to rain-generated flooding events. In addition, an AirSWOT dataset collected along the Tanana River in June 2015 will be included. Synthetic SWOT WSE simulations will be generated (following Biancamaria et al., 2016), and will be assimilated into a low resolution model (WRF-Hydro).

When complete, this project will inform the user on ways to allow real-time SWOT data to be ingested into the operational National Water Model.

Summary

In routine or in real time, on a global or regional scale, both on the surface and beneath it, Mercator Ocean describes, analyses and forecasts the state of the ocean by developing the “Mercator System” for ocean analysis and forecasting and maintaining it in an operational condition. Mercator Ocean is the entrusted entity to implement the Copernicus Marine Environment Monitoring Service.

Mercator Ocean prepares the assimilation of SWOT data in the Mercator Ocean analysis and forecasting systems. It plans to combine SWOT, nadir altimeter, other satellite data (SST, Ocean Color, …) and in-situ data with high resolution global models to allow a dynamical interpolation of SWOT data and to describe and forecast the ocean state worldwide.

Summary

This project will evaluate solutions to extract the (near) real-time continuous information on: Surface water extent or width, Water level, and Slope

from satellite data of the river reaches by developing suitable machine learning algorithms. They propose to adopt an exercise involving multi-source satellite data (optical, SAR and altimeter satellites), error identification and correction, coupled with in-situ dense data procurement, hydro-dynamic models, and meteorological information of the river basin. A pilot study over the Godavari basin, the second largest basin in India after the Ganga basin, will be conducted in association with officials from Central Water Commission (CWC), Govt. of India. For more information, visit HydroX.

Summary

In order to derive weekly/monthly estimates of river discharge, this project will use data assimilation to generate continuous fields of SWOT-relevant observables by merging them with model predictions. This will provide hydrologic information in areas where SWOT data gaps will prevent direct observation. The research objectives of this project are: Evaluate various data assimilation (DA) techniques on synthetic SWOT measurements to generate improved SWOT observables Uncertainty quantification of SWOT orbital data products Using SWOT measurements for the creation of a data inventory towards flood forecasting for different hydro-climatic scenarios

Current Progress and Future Steps

Summary

FM Global will perform incremental assessments of synthetic SWOT data products to: (i) ensure they meet suggested accuracy and uncertainty expectations, (ii) fully understand the unique space-time sampling impacts, (iii) quantify how they may add value to local/regional hydrologic and hydraulic understanding, and (iii) integrate relevant data products into the flood mapping workflow if needed. Case studies will be explored in collaboration with SWOT Science Team and Applications Working Group member, Ed Beighley-Northeastern University, to address the above. For example, the Ohio River Basin may be one of the initial experimental basins.

Current Progress and Future Steps

Summary

This project will focus on the Redberry Lake (area about 120 km2), located in the North Saskatchewan River Basin. This lake is an UNESCO research and education facility, and has long-term water level data since 1966. This lake is also a key SWOT research sites in Canada; it is under the SWOT orbit and is one of the AirSWOT flight lines for the 2017 AirSWOT campaign.

The main goals for this site/project are: a) to integrate SWOT data/products in regional lake hydrometric database; and b) to test/apply SWOT data (including AirSWOT data) for lake water balance analysis and modeling. This project will support SWOT lake calibration and validation activities in Canada, link SWOT mission with research and operational programs of the Environment and Climate Change Canada (ECCC), and c) to establish/enhance research collaborations with other organizations in Canada.

Summary

Key components to CUAHSI’s mission are the HydroClient and HydroShare portals that support the water science community in accessing available datasets and hosting user-developed data and applications. CUAHSI’s HydroClient currently provides the water science community with access to nearly 7 million time-series data sources (e.g., NASA’s NLDAS). The inclusion of select SWOT data products, development of tools to assess the space-time sampling of SWOT, and hosting of user data/findings related to SWOT are well-aligned with CUAHSI’s efforts to provide unprecedented access to water data at a global level and to support rapid advances in coupled water-climate-terrestrial modeling.

Building on CUAHSI’s Water Data Services, CUAHSI, in collaboration with the SWOT Science Team (ST), Applications Working Group (SAWG) members and NASA PO.DAAC representatives, will explore optimal methods for; (i) hosting of available synthetic SWOT data products, and (ii) enabling web services for exploring available synthetic SWOT data products and subsetting non-SWOT datasets (e.g., in-situ or simulated water surface elevations, water extents, and river discharges for lakes and rivers) to reflect the space/time sampling characteristics of SWOT. Corresponding SWOT data product uncertainties will also be included based on findings and simulator developments from the SWOT ST. The subsetting web services are primarily intended to help users explore SWOT’s space/time sampling within their river basin(s) prior to launch.

Summary

Since 1933, based on the concession received by French Government, CNR has been developing the Rhone River according to three core missions: hydropower generation, inland navigation and irrigation. Designer and operator of 19 run-of-river projects with 85 years of experience, CNR also supports other stakeholders in the fields of hydropower and river engineering to sustainably develop basins and rivers.

CNR is part of the French working group on space hydrology led by CNES, AFD – the French Development Agency – and the International Office for Water. This group aims at promoting the use of space data in hydrology and to prepare the use of SWOT data (SWOT satellite to be launched in 2021). CNR is particularly interested in ungauged basin/river and long time series of water level that could be made available to end users thanks to SWOT. CNR already uses altimetry data to develop operational applications in the field of water resources management, hydropower potential assessment and navigation forecasting.

Summary

CLS collects, analyses and disseminates satellite hydrological parameters to provide databases and services monitoring surface water and natural resources based today on remote sensing observations and in situ data. CLS works also on numerical modelling data. It develops also management tools and databases for hydrological parameters, hydrological monitoring and in the future plans to include forecasting services.

CLS will integrate SWOT data in the Hydroweb database and plans to use SWOT data for validation and calibration of numerical models.

Summary

This project will monitor lake storage change through a Citizen Science project over the Pookode Lake, Wayanad, Kerala, India. The project will serve as a case study for a larger India Citizen Science lake study initiative. The research objectives include assessing the performance of SWOT to establish limitations on the lake storage variation due to KaRIN instrument limitations. A secondary objective is to estimate lake water volume using existing satellite missions/repositories such as those on Hydroweb, as well as for SWOT after launch.

PI Dr. J. Indu, from the IIT Bombay, has expertise in working with satellite altimetry datasets and is presently involved in projects on SWOT. Her research team shall focus on the processing of satellite altimetry data. The collaborators, Mr. Vivek B and Mr. Jainet P J, are working as Scientists-B with the Centre for Water Resources Development and Management (CWRDM), Kerala, India. Their team shall focus on the establishment of the in-situ site at the Pookode Lake case study area.

Summary

BRLi is a consulting firm specialising in areas related to water, the environment and regional planning, providing design and construction engineering, management services and technical assistance on integrated water resource management, hydraulic, port and navigation infrastructures, protection of the environment and coastal areas and natural risk management. BRLi is an expert in hydrology and hydraulics and has integrated satellite data in its projects since years. As designer and provider of downstream services, BRLi has developed the solution WIMES, a software and services platform, for building water information and management systems and aid decision tools. BRLi is part of the French working group on Space Hydrology lead by CNES, AFD – the French development agency and IOWater. This groups aims to promote the use of space data in hydrology and to prepare the use of SWOT data.

BRL is particularly interested in ungauged basin/river to help basin’s holder to have a better water resources management. It also has applications on navigations and flooding maps and forecast.

Summary

This project will establish virtual stream gauges (VSG) in the Lower Mekong Region (LMR) region of southeast Asia using pre-SWOT or SWOT-relevant data. Data products at these VSG locations will be used to generate water level elevations. These VSGs will be located over many streams (including small and larger streams). These multi-scale data will help explore SWOT’s advance technical capabilities to improve temporal water level analysis, reservoir/lake outflow estimations, and water level forecasting for major rivers by taking the advantage of water discharge output with the Variable Infiltration Capacity (VIC) model.

One of the existing challenges is to forecast the water levels in the streams of Mekong delta due to ocean tidal effect. This project will, therefore, closely monitor water levels deriving from SWOT VSGs over Mekong delta and would improve existing VIC and ocean tidal model’s setup to forecast the water levels in Mekong delta utilizing up streams discharges and water levels.