Deriving Global Baseflows
NASA GRACE-FO Science Team
GRACE/GRACE-FO Total Water Storage Anomalies (TWSA) will be used to derived global river discharges (Q) based on new Q-TWSA relationships. Research OBJECTIVES are: (1) develop a global river network based on MERIT Hydro and integrate spatial-temporal datasets for relevant climate and watershed characteristics; (2) derived Q-TWSA relationships using in-situ streamflow; (3) generalize relationship coefficients from gauged sites to estimate coefficients for ungauged river reaches based on remotely sensed (via TRMM/GPM, MODIS, SMAP) quantities that capture relevant climate and watershed characteristics (precip., land surface temp., land cover, veg. indices, soil moisture, topography); (4) produce a global river discharge product consisting of GRACE/GRACE-FO derived monthly discharges and associated uncertainties for individual river reaches for the period 2002-2022; (5) assess derived discharges using in-situ gauges and discharges derived from two models (VIC and CLM) within NASA’s NLDAS/GLDAS; and (6) assess the value of GRACE/GRACE-FO derived discharges in a hydrologic modeling application on the Mississippi River Basin. We will evaluate research hypotheses and science questions related to: (A) understanding how the magnitude and rate of change in discharge is controlled by changes in total water storage; (B) understanding how climate and watershed characteristics and watershed drainage area influence the relationship between monthly river discharge and TWSA’s, (C) assessing GRACE/GRACE-FO derived discharges with in-situ and hydrologic model derived discharges, and (D) quantifying the value added (i.e., improved model performance) by using GRACE/GRACE-FO derived discharges in hydrologic modeling applications with limited in-situ streamflow.
SWOT data products for hydrologic science
Consortium of Universities for the Advancement of Hydrologic Science, Inc (CUAHSI)
Providing the hydrologic sciences community with value-added SWOT data products (Beighley, PI)
Oversee the collection of synthetic SWOT data products (pre-launch data) in collaboration with SWOT Applications Working Group and NASA’s data service group for integration into CUAHSI’s hydroshare system. Initiate process using recently published synthetic SWOT data for the Mississippi River Basin based on USGS streamflow data; Develop web services to analyze/subset synthetic SWOT data products within CUAHSI’s hydroshare system. Build Jupiter Notebooks to visualize synthetic SWOT data along rivers in the Mississippi River Basin. Explore developing additional APPs to visualize, analyze and subset synthetic SWOT data products; Work with NASA’s data services group for integration of post-launch data products into CUAHSI’s hydroshare system. Develop web services to analyze/subset SWOT data products within CUAHSI’s hydroshare system.
https://www.cuahsi.org/ & https://swot.jpl.nasa.gov/
Assessing precipitation-based risk for well water contamination
NASA Precipitation Measurement Mission Science Team
In the U.S., nearly 50 million residents are reliant on unregulated private wells, which do not have the same level of protection from drinking water hazards as regulated municipal water. This is a significant problem because up to 60% of wells exceed at least one health-based drinking water standard. Building on our recent efforts, we hypothesize that well water contamination is impacted by precipitation-induce processes and pathways with initial hydrologic conditions, land cover, household (income, race), and well system (well depth, well type) characteristics amplifying contamination rates. Here, we propose to develop a precipitation-based risk index that utilizes NASA satellite observations, specifically GPM’s IMERG precipitation product(s), U.S. Census data, and the North Carolina Department of Health and Human Services (NC-DHHS) well sampling database to better identify and characterize private wells susceptibility to rainfall-induced contamination. Along with GPM precipitation, remotely sensed observations will be used to integrate additional contributions to well water contamination rates and variabilities such as hydrologic conditions derived from NASA’s SMAP, GRACE-FO, and future SWOT missions, proximity to flood prone areas derived from LANDSAT, and land cover characteristics derived from LANDSAT and MODIS. The GOAL of the proposed project is to develop a GPM precipitation-based risk index to provide NC-DHHS the capability to rapidly detect and respond to well water problems resulting from rainfall driven contamination. The index will provide time-history and near real-time insights on precipitation induced impacts on drinking water supplied by wells.
NASA Global Precipitation Measurement
Eutrophication
Sensor-based Bloom Classification
In-vivo sensors can provide near real-time monitoring of water quality. However, difficulty relating fluorometric measurements to relevant algal water quality parameters (e.g. cyanobacterial cell density or chlorophyll concentration), has limited the implementation of probe-based monitoring strategies. Ongoing research combines high rate cyanobacteria sampling with data collected from the EPA Charles River Buoy in order to create a model capable of estimating cyanobacterial cell density and tracking important bloom parameters.
Charles Floating Wetland
This project proposes the temporary installation of a ~700 square foot floating wetland in the waters near North Point Park in Cambridge, MA. The goals of this project are to: (1) research the impact of improved habitat on zooplankton species distribution and mean body size, (2) create a visually impactful wetland installation that will enliven the parkland, and (3) engage and educate the public about the relationship between river ecology, pollution and water quality.
Stormwater Nutrient Management
A collaborative study between the City of Cambridge Department of Public Works, Stantec, and Northeastern University is conducting stormwater sampling to understand the variability in phosphorus export from different urban landscapes. The goal of the project is to develop an optimized diversion and treatment strategy that will help to meet the Total Maximum Daily Load (TMDL) allocations of a dense urban watershed like Cambridge, MA.