Engineering topics

Arsenault, Kristi

Publications and source records attributed to Arsenault, Kristi.

6 records

NASA NTRS2020

Data Assimilation Enhancements to Air Force Weather’s Land Information System

The United States Air Force (USAF) has a proud and storied tradition of enabling significant advancements in the area of characterizing and modeling land state information. 557th Weather Wing (557 WW; DoD’s Executive Agent for Land Information) provides routine geospatial intelligence information to warfighters, planners, and decision makers at all echelons and services of the U.S. military, government and intelligence community. 557 WW and its predecessors have been home to the DoD’s only operational regional and global land data analysis systems since January 1958. As a trusted partner since 2005, Air Force Weather (AFW) has relied on the Hydrological Sciences Laboratory at NASA/GSFC to lead the interagency scientific collaboration known as the Land Information System (LIS). LIS is an advanced software framework for high performance land surface modeling and data assimilation of geospatial intelligence (GEOINT) information.

Wegiel, Jerry↗

NASA NTRS2014

Water Balance in the Amazon Basin from a Land Surface Model Ensemble

Despite recent advances in land surfacemodeling and remote sensing, estimates of the global water budget are still fairly uncertain. This study aims to evaluate the water budget of the Amazon basin based on several state-ofthe- art land surface model (LSM) outputs. Water budget variables (terrestrial water storage TWS, evapotranspiration ET, surface runoff R, and base flow B) are evaluated at the basin scale using both remote sensing and in situ data. Meteorological forcings at a 3-hourly time step and 18 spatial resolution were used to run 14 LSMs. Precipitation datasets that have been rescaled to matchmonthly Global Precipitation Climatology Project (GPCP) andGlobal Precipitation Climatology Centre (GPCC) datasets and the daily Hydrologie du Bassin de l'Amazone (HYBAM) dataset were used to perform three experiments. The Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme was forced with R and B and simulated discharges are compared against observations at 165 gauges. Simulated ET and TWS are compared against FLUXNET and MOD16A2 evapotranspiration datasets andGravity Recovery and ClimateExperiment (GRACE)TWSestimates in two subcatchments of main tributaries (Madeira and Negro Rivers).At the basin scale, simulated ET ranges from 2.39 to 3.26 mm day(exp -1) and a low spatial correlation between ET and precipitation indicates that evapotranspiration does not depend on water availability over most of the basin. Results also show that other simulated water budget components vary significantly as a function of both the LSM and precipitation dataset, but simulated TWS generally agrees with GRACE estimates at the basin scale. The best water budget simulations resulted from experiments using HYBAM, mostly explained by a denser rainfall gauge network and the rescaling at a finer temporal scale.

GPCP↗

NASA NTRS2014

Drought Prediction for Socio-Cultural Stability Project

The primary objective of this project is to answer the question: "Can existing, linked infrastructures be used to predict the onset of drought months in advance?" Based on our work, the answer to this question is "yes" with the qualifiers that skill depends on both lead-time and location, and especially with the associated teleconnections (e.g., ENSO, Indian Ocean Dipole) active in a given region season. As part of this work, we successfully developed a prototype drought early warning system based on existing/mature NASA Earth science components including the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5) forecasting model, the Land Information System (LIS) land data assimilation software framework, the Catchment Land Surface Model (CLSM), remotely sensed terrestrial water storage from the Gravity Recovery and Climate Experiment (GRACE) and remotely sensed soil moisture products from the Aqua/Advanced Microwave Scanning Radiometer - EOS (AMSR-E). We focused on a single drought year - 2011 - during which major agricultural droughts occurred with devastating impacts in the Texas-Mexico region of North America (TEXMEX) and the Horn of Africa (HOA). Our results demonstrate that GEOS-5 precipitation forecasts show skill globally at 1-month lead, and can show up to 3 months skill regionally in the TEXMEX and HOA areas. Our results also demonstrate that the CLSM soil moisture percentiles are a goof indicator of drought, as compared to the North American Drought Monitor of TEXMEX and a combination of Famine Early Warning Systems Network (FEWS NET) data and Moderate Resolution Imaging Spectrometer (MODIS)'s Normalizing Difference Vegetation Index (NDVI) anomalies over HOA. The data assimilation experiments produced mixed results. GRACE terrestrial water storage (TWS) assimilation was found to significantly improve soil moisture and evapotransportation, as well as drought monitoring via soil moisture percentiles, while AMSR-E soil moisture assimilation produced marginal benefits. We carried out 1-3 month lead-time forecast experiments using GEOS-5 forecasts as input to LIS/CLSM. Based on these forecast experiments, we find that the expected skill in GEOS-5 forecasts from 1-3 months is present in the soil moisture percentiles used to indicate drought. In the case of the HOA drought, the failure of the long rains in April appears in the February 1, March 1 and April 1 initialized forecasts, suggesting that for this case, drought forecasting would have provided some advance warning about the drought conditions observed in 2011. Three key recommendations for follow-up work include: (1) carry out a comprehensive analysis of droughts observed over the entire period of record for GEOS-5 forecasts; (2) continue to analyze the GEOS-5 forecasts in HOA stratifying by anomalies in long and short rains; and (3) continue to include GRACE TWS, Soil Moisture/Ocean Salinity (SMOS) and the upcoming NASA Soil Moisture Active/Passive (SMAP) soil moisture products in a routine activity building on this prototype to further quantify the benefits for drought assessment and prediction.

Peters-Lidard, Christa↗

NASA NTRS2010

NASA-Modified Precipitation Products to Improve EPA Nonpoint Source Water Quality Modeling for the Chesapeake Bay

The Environmental Protection Agency (EPA) has estimated that over 20,000 water bodies within the United States do not meet water quality standards. Ninety percent of the impairments are typically caused by nonpoint sources. One of the regulations in the Clean Water Act of 1972 requires States to monitor the Total Maximum Daily Load (TMDL), or the amount of pollution that can be carried by a water body before it is determined to be "polluted", for any watershed in the U.S.. In response to this mandate, the EPA developed Better Assessment Science Integrating Nonpoint Sources (BASINS) as a Decision Support Tool (DST) for assessing pollution and to guide the decision making process for improving water quality. One of the models in BASINS, the Hydrological Simulation Program -- Fortran (HSPF), computes daily stream flow rates and pollutant concentration at each basin outlet. By design, precipitation and other meteorological data from weather stations serve as standard model input. In practice, these stations may be unable to capture the spatial heterogeneity of precipitation events especially if they are few and far between. An attempt was made to resolve this issue by substituting station data with NASA modified/NOAA precipitation data. Using these data within HSPF, stream flow was calculated for seven watersheds in the Chesapeake Bay Basin during low flow periods, convective storm periods, and annual flows. In almost every case, the modeling performance of HSPF increased when using the NASA-modified precipitation data, resulting in better stream flow statistics and, ultimately, in improved water quality assessment.

Nigro, Joseph↗

NASA NTRS2005

NASA Land Information System (LIS) Water Availability to Support Reclamation ET Estimation

The U.S. Bureau of Reclamation identified the remote sensing of evapotranspiration (ET) as an important water flux for study and designated a test site in the Lower Colorado River basin. A consortium of groups will work together with the goal to develop more accurate and cost effective techniques using the enhanced spatial and temporal coverage afforded by remote sensing. ET is a critical water loss flux where improved estimation should lead to better management of Reclamation responsibilities. There are several areas where NASA satellite and modeling data may be useful to meet Reclamation's objectives for improved ET estimation. In this paper we outline one possible contribution to use NASA's data integration capability of the Land Information System (LIS) to provide a merger of observational (in situ and satellite) with physical process models to provide estimates of ET and other water availability outputs (e.g., runoff, soil moisture) retrospectively, in near real-time, and also providing short-term predictions.

Toll, David↗

NASA NTRS2004

NASA Data for Water Resources Applications

Water Management Applications is one of twelve elements in the Earth Science Enterprise National Applications Program. NASA Goddard Space Flight Center is supporting the Applications Program through partnering with other organizations to use NASA project results, such as from satellite instruments and Earth system models to enhance the organizations critical needs. The focus thus far has been: 1) estimating water storage including snowpack and soil moisture, 2) modeling and predicting water fluxes such as evapotranspiration (ET), precipitation and river runoff, and 3) remote sensing of water quality, including both point source (e.g., turbidity and productivity) and non-point source (e.g., land cover conversion such as forest to agriculture yielding higher nutrient runoff). The objectives of the partnering cover three steps of: 1) Evaluation, 2) Verification and Validation, and 3) Benchmark Report. We are working with the U.S. federal agencies including the Environmental Protection Agency (EPA), the Bureau of Reclamation (USBR) and the Department of Agriculture (USDA). We are using several of their Decision Support Systems (DSS) tools. This includes the DSS support tools BASINS used by EPA, Riverware and AWARDS ET ToolBox by USBR and SWAT by USDA and EPA. Regional application sites using NASA data across the US. are currently being eliminated for the DSS tools. The current NASA data emphasized thus far are from the Land Data Assimilation Systems WAS) and MODIS satellite products. We are currently in the first two steps of evaluation and verification validation. Water Management Applications is one of twelve elements in the Earth Science Enterprise s National Applications Program. NASA Goddard Space Flight Center is supporting the Applications Program through partnering with other organizations to use NASA project results, such as from satellite instruments and Earth system models to enhance the organizations critical needs. The focus thus far has been: 1) estimating water storage including snowpack and soil moisture, 2) modeling and predicting water fluxes such as evapotranspiration (ET), precipitation and river runoff, and 3) remote sensing of water quality, including both point source (e.g., turbidity and productivity) and non-point source (e.g., land cover conversion such as forest to agriculture yielding higher nutrient runoff). The objectives of the partnering cover three steps of 1) Evaluation, 2) Verification and Validation, and 3) Benchmark Report. We are working with the U.S. federal agencies the Environmental Protection Agency (EPA), the Bureau of Reclamation (USBR) and the Department of Agriculture (USDA). We are using several of their Decision Support Systems (DSS) tools. T us includes the DSS support tools BASINS used by EPA, Riverware and AWARDS ET ToolBox by USBR and SWAT by USDA and EPA. Regional application sites using NASA data across the US. are currently being evaluated for the DSS tools. The current NASA data emphasized thus far are from the Land Data Assimilation Systems (LDAS) and MODIS satellite products. We are currently in the first two steps of evaluation and verification and validation.

Toll, David↗