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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Dissemination of Global Flood Information Through Nasa Disasters Program Global Initiative for Flood Forecasting and Alerting (GIFFT)

The Global Initiative for Flood Forecasting and Alerting (GIFFT) is an initiative to disseminate flood products from different sensors to global stakeholders via the Pacific Disaster Center’s (PDC) DisasterAWARE®, the NASA Disasters Mapping Portal and potentially other mechanisms. GIFFT will also generate an integrated product(s) using ensembled hydrologic models and Earth observation derived flood outputs to stakeholders globally. This initiative combines the results of several Disasters Program funded projects that focus on flood forecasting, flood severity estimation, post-event flood mapping, flooddepth estimation and resulting flood severity using remote sensing-based flood information derived from SAR and optical imagery. PDC’s DisasterAWARE platform is a global multi-hazard alerting platform that currently incorporatesModel of Models (MoM) outputs as flood “incidents,” visually depicting potential floods in the context ofpopulation and infrastructure that may become affected. Automated procedures are being developed tocategorize MoM outputs as DisasterAWARE “hazards,” allowing for their dissemination to users alongwith other flood products that assess potential impacts. PDC’s stakeholders include UN, DoD, FEMA andtheir equivalents around the world. Additionally, the DisasterALERT mobile platform has 2 million usersworldwide and is a fully functional and sustained platform used to disseminate alerts and analyticalproducts for 18 different hazard types. GIFFT has incorporated HydroSAR products that will bedistributed via DisasterAWARE.

remote sensing↗
NASA NTRSDate not supplied

Warm-Based Glacial Landforms and Past Climate Signals: Icelandic Eskers as Proxies for Small Sinuous Ridges on Mars

The surface of Mars exhibits plentiful geomorphic evidence for glacial processes, but the history of the cryosphere on Mars remains debated [e.g., 1, 2]. Recent hydrological modeling predicts that warm-based ice sheets on Mars may have resulted in subglacial incised channels (e.g., valley networks) and eskers [3]. Evidence on Mars for warm-based glaciation includes candidate moraines, bedrock channels, and candidate eskers [e.g., 4-6]. Eskers are sinuous ridges comprising glaciofluvial sediments deposited by meltwater flowing through tunnels at the bed of warm-based large glaciers [e.g., 7, 8]. They provide direct evidence of basal melting of ice and preserve glaciofluvial sediments. Warm-based glacial transport is primarily driven by meltwater and can chemically weather the underlying bedrock. An alternative signature of past climate on Mars may thus be the geochemical record, due to alteration by interactions with glacial meltwater, preserved in esker sediments and strata. At present, the sedimentology and stratigraphy of terrestrial eskers is poorly understood. This study will combine sedimentology, geochemistry, and geomorphology to better constrain the unique properties of eskers resulting from warm-based glaciation on Mars-like substrates by leveraging a natural laboratory in Iceland.

A. M. Rutledge↗
NASA NTRS2020

Assessment of Extremes in Global Precipitation Products: How Reliable Are They?

Global gridded precipitation products have proven essential for many applications ranging from hydrological modeling and climate model validation to natural hazard risk assessment. They provide a global picture of how precipitation varies across time and space, specifically in regions where ground-based observations are scarce. While the application of global precipitation products has become widespread, there is limited knowledge on how well these products represent the magnitude and frequency of extreme precipitation—the key features in triggering flood hazards. Here, five global precipitation datasets (MSWEP, CFSR, CPC, PERSIANN-CDR, and WFDEI) are compared to each other and to surface observations. The spatial variability of relatively high precipitation events (tail heaviness) and the resulting discrepancy among datasets in the predicted precipitation return levels were evaluated for the time period 1979–2017. The analysis shows that 1) these products do not provide a consistent representation of the behavior of extremes as quantified by the tail heaviness, 2) there is strong spatial variability in the tail index, 3) the spatial patterns of the tail heaviness generally match the Köppen–Geiger climate classification, and 4) the predicted return levels for 100 and 1000 years differ significantly among the gridded products. More generally, our findings reveal shortcomings of global precipitation products in representing extremes and highlight that there is no single global product that performs best for all regions and climates.

Risk assessment↗
NASA NTRS2022

Reservoir Assessment Tool 2.0: Stakeholder driven improvements to satellite remote sensing based reservoir monitoring

In light of the rapidly increasing regulation of rivers due to planned and constructed reservoirs, monitoring reservoir operations has become very crucial. The Reservoir Assessment Tool (RAT) framework was developed to monitor reservoir operations globally, using hydrological modeling and satellite observations. With feedback from stakeholders, improvements in the RAT framework are demonstrated in this study using the Mekong River Basin as an example. A novel multi-sensor reservoir area mapping technique was developed using complementary strengths of optical and SAR sensors at a 1-5 day temporal resolution, allowing the quantification of sub-weekly reservoir operations. Additionally, the skill of radar altimeters in the RAT framework was tested using the Jason-3 altimeter. Using in-situ data from three Thai reservoirs in the Mekong Basin, consistent improvements were observed as compared to the original RAT framework. A functionality for visualizing forecasted outflow was also added using historically inferred reservoir operations or stakeholder-driven target storage expectations.

Reservoirs↗
NASA NTRSDate not supplied

Assessing Sediment Inputs into the Shoshone River in Wyoming to Determine Areas for Protection and Restoration Practices

In 2016, a routine repair operation at the Willwood Dam released tons of built-up sediment into the Shoshone River, polluting the river and killing thousands of fish. This release greatly concerned the communities that rely on the river for farming, recreation, and tourism. In partnership with the Wyoming Department of Environmental Quality (WDEQ), Shoshone River Partners, and the United States Geological Survey (USGS) Wyoming-Montana Water Science Center, this multipart project illustrated the application of high-resolution satellite imagery and hydrological modeling techniques to identify major tributaries contributing to sediment influxes into the Shoshone River between the Buffalo Bill Dam and the Willwood Dam. The team used PlanetScope and Sentinel-2 Multi-Spectral Instrument (MSI) satellite images to assess changes in the surface reflectance of the river in response to precipitation events. To determine these storm events, the team selected dates of interest using Global Precipitation Measurement (GPM) Integrated Multi-Spectral Retrieval (IMERG) and gauge precipitation data from the Global Historical Climatology Network Daily (GHCNd). The continuation of this research further quantified sediment influx in the Shoshone River following snowfall and melt events using the Soil & Water Assessment Tool (SWAT). The precipitation analysis and sediment contribution maps helped the partner organizations prioritize their current decision making and best management practices to specific sites along the river. The results demonstrated the feasibility of using PlanetScope data for categorizing sediment in the Shoshone River.

Caroline Williams↗
NASA NTRS2022

Working Toward A National Coordinated Soil Moisture Monitoring Network: Vision, Progress, and Future Directions

Soil moisture is a critical land surface variable, impacting the water, energy, and carbon cycles. While in situ soil moisture monitoring networks are still developing, there is no cohesive strategy or framework to coordinate, integrate, or disseminate these diverse data sources in a synergistic way that can improve our ability to understand climate variability at the national, state, and local levels. Thus, a national strategy is needed to guide network deployment, sustainable network operation, data integration and dissemination, and user-focused product development. The National Coordinated Soil Moisture Monitoring Network (NCSMMN) is a federally led, multi-institution effort that aims to address these needs by capitalizing on existing wide-ranging soil moisture monitoring activities, increasing the utility of observational data, and supporting their strategic application to the full range of decision-making needs. The goals of the NCSMMN are to 1) establish a national “network of networks” that effectively demonstrates data integration and operational coordination of diverse in situ networks; 2) build a community of practice around soil moisture measurement, interpretation, and application—a “network of people” that links data providers, researchers, and the public; and 3) support research and development (R&D) on techniques to merge in situ soil moisture data with remotely sensed and modeled hydrologic data to create user-friendly soil moisture maps and associated tools. The overarching mission of the NCSMMN is to provide coordinated high-quality, nationwide soil moisture information for the public good by supporting applications like drought and flood monitoring, water resource management, agricultural and forestry planning, and fire danger ratings.

C. Bruce Baker↗
NASA NTRS2023

Kankakee Water Resources: Monitoring Temperature and Vegetation to Detect River Flow Impediments at Energy Intake Structures

In recent years, unpredictable grassing events have occurred at the Dresden Generating Station, located on the Kankakee River in northern Illinois. Grassing events are characterized by large mats of aquatic vegetation that accumulate downstream, resulting in the clogging of water intake structures and leading to major disruptions in power generation. Currently, employees at the Dresden Generating Station are responsible for reactively responding to each grassing event individually. This project, in partnership with Constellation Nuclear and the United States Geological Survey (USGS), assessed the feasibility of using Earth observations (Landsat 9 OLI-2, Landsat 8 OLI, Sentinel-2 MSI, DOVE PlanetScope, WorldView-3, and GPM IMERG) to detect floating aquatic vegetation within the Kankakee River and identify predictive factors that trigger grassing events, as doing so will provide the Dresden Generating Station the ability to anticipate future grassing events and enhance general hydrologic modeling efforts held by the USGS. The results of this study illustrated that, while aquatic vegetation can be detected by satellites with up to moderate spatial resolution (30 m), temporal resolution is a major limiting factor for tracking movements in floating aquatic vegetation and identifying predictive measures for these events. In addition, correlation results suggest a possible negative relationship between grassing events and river discharge (-0.875 correlation coefficient). In the future, pairing these results with ground control surveys and sensors with higher temporal capabilities would allow our project partners to predict and proactively address future grassing events, ensuring the reliable operation of the Dresden Generating Station.

Marisa Smedsrud↗
NASA NTRS2023

Robustness of Gridded Precipitation Products for Vietnam Basins using the Comprehensive Assessment Framework of Rainfall

The use of satellite–based precipitation products (SPPs) have become increasingly prevalent as key inputs to provide regional rainfall for improving hydrological simulations in data–spare regions. This study introduces a new approach – Comprehensive Assessment Framework of Rainfall (CAFR) to evaluate six satellite–based precipitation products (SPPs) for eleven basins with different sizes across Vietnam (2007–2015). These SPPs include the Global Precipitation Mission (GPM) Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Final run Version 6 (GPM IMERGF V6), Multi–Source Weighted–Ensemble Precipitation (MSWEP) V2.2, Soil Moisture to Rain (SM2RAIN) – Advanced SCATterometer (ASCAT) V1.5, Asian Precipitation–Highly–Resolved Observational Data Integration Towards Evaluation (APHRODITE) V1901, Climate Hazards group Infrared Precipitation with Stations (CHIRPS) V2.0, and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) – Climate Data Record (CDR) V1.0. With the proposed CAFR: (1) IMERGF is suggested to have the best performance overall, especially when simulating flood peaks; (2) SM2RAIN–ASCAT demonstrates the best skills in metrics related to the dry season; (3) For streamflow simulations, SPPs' performance is sensitive to basin size, with larger basins showing better performance skills. In this study, we demonstrate the capability of our proposed framework to better understand SPP applications in hydrological modeling.

Comprehensive Assessment Framework of Rainfall (CA↗
NASA NTRS2024

Satellite-Based Tracking of Reservoir Operations for Flood Management During the 2018 Extreme Weather Event in Kerala, India

Uncoordinated management of hydropower dams during extreme and unexpected precipitation events in mountainous terrain can have disastrous consequences due to the competing nature of flood control and hydropower generation. Numerous cases of flooding events that have been exacerbated due to insufficient storage conditions in hydropower dams have been reported worldwide. There is a need for a scalable and publicly accessible monitoring framework that is capable of providing reliable, near-real time, and transparent reservoir operations data. A fully satellite-based framework is the most viable solution to build such capability. The Reservoir Assessment Tool (RAT 3.0), which utilizes high frequency remote sensing-based surface area and reservoir storage estimation alongside hydrological modelled inflow was applied here for the 2018 Kerala floods in India as a globally representative case for a mountainous river basin with high precipitation and hydropower dams. Application of satellite-based RAT 3.0 in monitoring the state of 19 reservoirs in Kerala during the flood event showed very promising results. In general, RAT 3.0, using satellite remote sensing, was found to be able to capture the temporal trend of the reservoir storage and pinpoint the sudden shift in filling or release decisions made by the dam operator. Inflow modelling in such regions was found to require careful calibration with identification of reservoirs that are heavily regulated being a critical aspect. The perennial high cloud cover in such regions necessitate and highlights the central role played by microwave and radar-based satellite sensors, such as the Surface Water and Ocean Topography (SWOT) mission, in tracking reservoir state. An operational version of RAT 3.0 for stakeholder agencies tailored for hydropower dams operating in high precipitation and mountainous environments is a real-world outcome of this study.

Sarath Suresh↗
NASA NTRS2024

Detection and Socio-Economic Attribution of Groundwater Depletion in India

Groundwater is a critical resource for both consumption and food security in India, where groundwater management faces significant challenges due to climate change and anthropogenic activities. Although several studies explored groundwater variability in India, few have focused on the socioeconomic attribution of these changes, utilizing data from industries, population and water demand. In this study, trends in groundwater storage were examined by leveraging the largest in situ dataset ever collated in India from ~27,000 groundwater wells, satellite-based terrestrial-water-storage estimates, and hydrological model simulations. Five major hotspots of groundwater depletion across India were identified using in situ measurements and previously untapped socioeconomic datasets to attribute these trends. Approximately 16% of Indian groundwater monitoring stations exhibited systematically decreasing trends in groundwater levels. These hotspots are primarily concentrated in the northern and northwestern parts of India as well as in the states of Chhattisgarh, West Bengal, and Kerala. The north/northwestern hotspots have experienced a staggering loss of ~6.46 × 10^10 m3 of water over the past two decades. The factors contributing to this depletion include population growth, rapid urbanization, proliferation of factories and the expansion of agriculture.

Gautam Kunwar↗
DOE OSTI2023

Characterizing uncertainty in Community Land Model version 5 hydrological applications in the United States

Abstract Land surface models such as the Community Land Model Version 5 (CLM5) are essential tools for simulating the behavior of the terrestrial system. Despite the extensive application of CLM5, limited attention has been paid to the underlying uncertainties associated with its hydrological parameters and how these uncertainties affect water resource applications. To address this long-standing issue, we use five meteorological datasets to conduct a comprehensive hydrological parameter uncertainty characterization of CLM5 over the hydroclimatic gradients of the conterminous United States. Key datasets produced from the uncertainty characterization experiment include: a benchmark dataset of CLM5 default hydrological performance, parameter sensitivities for 28 hydrological metrics, and large-ensemble outputs for CLM5 hydrological predictions. The presented datasets will assist CLM5 calibration and support broad applications, such as evaluating drought and flood vulnerabilities. The datasets can be used to identify the hydroclimatological conditions under which parametric uncertainties demonstrate substantial effects on hydrological predictions and clarify where further investigations are needed to understand how hydrological prediction uncertainties interact with other Earth system processes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Impact of microwave derived soil moisture on hydrologic simulations using a spatially distributed water balance model

Spatial distributions of soil moisture over an agricultural watershed with a drainage area of 60 ha were derived from two NASA microwave remote sensors, and then used as a feedback to determine the initial condition for a distributed water balance model. Simulated hydrologic fluxes over a period of twelve days were compared with field observations and with model predictions based on a streamflow derived initial condition. The results indicated that even the low resolution remotely sensed data can improve the hydrologic model's performance in simulating the dynamics of unsaturated zone soil moisture. For the particular watershed under study, the simulated water budget was not sensitive to the resolutions of the microwave sensors.

Lin, D. S.↗
NASA NTRS1985

The use of remotely sensed soil moisture data in large-scale models of the hydrological cycle

Manabe (1982) has reviewed numerical simulations of the atmosphere which provided a framework within which an examination of the dynamics of the hydrological cycle could be conducted. It was found that the climate is sensitive to soil moisture variability in space and time. The challenge arises now to improve the observations of soil moisture so as to provide up-dated boundary condition inputs to large scale models including the hydrological cycle. Attention is given to details regarding the significance of understanding soil moisture variations, soil moisture estimation using remote sensing, and energy and moisture balance modeling.

Salomonson, V. V.↗
NASA NTRS1974

Impact of remote sensing upon the planning, management, and development of water resources

A survey of the principal water resource users was conducted to determine the impact of new remote data streams on hydrologic computer models. The analysis of the responses and direct contact demonstrated that: (1) the majority of water resource effort of the type suitable to remote sensing inputs is conducted by major federal water resources agencies or through federally stimulated research, (2) the federal government develops most of the hydrologic models used in this effort; and (3) federal computer power is extensive. The computers, computer power, and hydrologic models in current use were determined.

Loats, H. L.↗
DOE OSTI2025

Coupled Hydrological-Thermal-Biogeochemical Modeling for Predicting Arctic Carbon Emissions (CH4PACE)

The Arctic, with nearly 1,700 billion metric tons of carbon stored in its soils, is experiencing significant warming trends that raise concerns about the potential release of greenhouse gases, particularly methane. This report investigates the conversion of carbon stored in Arctic soils and permafrost into methane and its subsequent atmospheric release over the coming decades. Recent data indicate a rise in global methane concentrations, highlighting the importance of understanding the mechanisms of methane generation under anaerobic conditions prevalent in thawing permafrost. Our study employs a multi-faceted approach that integrates fieldwork, benchtop experiments, and numerical simulations to explore the subsurface hydrological-thermal-biogeochemical systems influencing methane emissions. We focus on the relationship between microbial activity in decomposing organic matter under oxygen-limited conditions and the transport of methane out of these saturated wetland soils. Key hydrological parameters, including permeability, porosity, and thermal conductivity, were measured on soil samples from Fairbanks, Alaska, and used to parameterize PFLOTRAN, a coupled hydrological-thermal-reactive transport simulator. Our model enables prediction of the evolution of the active layer and its impact on methane production and release. Our findings underscore the critical need for a mechanistic understanding of methane dynamics in permafrost environments to improve predictions of methane emissions in Earth systems models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Limits on Runoff Episode Duration for Early Mars: Integrating Lake Hydrology and Climate Models

Fluvio-lacustrine features on the martian surface attest to a climate that was radically different in the past. Since climate models have difficulty sustaining a liquid hydrosphere at the surface, multiple cycles of runoff episodes may have characterized the ancient Mars climate. A fundamental question thus remains: what was the duration of these runoff-producing episodes? Here we use morphometric measurements from newly identified coupled lake systems, containing both an open- and a closed-basin lake (n=7). We combined hydrological balances with precipitation outputs from climate models, and found that breaching runoff episodes likely lasted 102−105yr; other episodes may have been shorter but could not be longer. Runoff episode durations are model-dependent and spatiallyvariable, and no27climate model scenario can satisfy a unique duration for all coupled systems. In the near future, these quantitative constraints on early Mars lake persistence may be tested through in situ observations from Perseverance rover. Plain Language Summary Ancient river and lake beds on the martian surface point to a climate that was radically different in the past, unlike the dry, cold desert that Mars is today. It experienced significant liquid water flowing across the surface (i.e., ‘runoff’) and hosted long-lived bodies of water (lakes and seas). However, scientists that generate models to simulate the ancient Mars climate have difficulty sustaining this proposed liquid water cycle at the surface. One possible hypothesis is that multiple cycles of individual liquid water episodes may have characterized the ancient martian climate (i.e. runoff episodes). A fundamental question thus remains: what was the duration of these individual runoff-producing episodes? Here we use an approach that takes advantage of unique martian lake system, ‘coupled’ lake systems, and their shapes. We combined these measurements with precipitation results from previous climate models, and found that runoff episodes likely lasted 100-10,000 years, requiring a global climate mechanism that generated repeated cycles of this duration. Ultimately, our results can be tested through observations made by NASA’s Perseverance rover, shedding light on the uninterrupted duration of surface water on Mars and its potential to host life in the past.

Gaia Stucky de Quay↗
DOE OSTI2020

Comparative Study of Hydrology and Icemelt in Three Nepal River Basins Using the Glacio-Hydrological Degree-Day Model (GDM) and Observations From the Advanced Scatterometer (ASCAT)

An assessment of the water supply and its seasonal and annual changes over the century in the High Mountain Asia (HMA) region is of increasing interest due to its potential impact on one-sixth of the global population. In order to understand the changing hydrology and snow and ice melt, we used remotely sensed Advanced Scatterometer (ASCAT) observations of glacier melt (GM) and a distributed and gridded Glacio-hydrological Degree-day Model (GDM) in three river basins: Tamor, Trishuli and Marsyangdi. The GDM-estimated contribution of snowmelt, icemelt, rainfall and baseflow in river flows is found to be most accurate in the Trishuli River basin, with Nash-Sutcliffe efficiency (NSE) between the estimated and observed discharges of 0.81 and volume differences of -0.5%, and reasonably accurate in the Tamor River basin, with NSE of 0.69 and volume difference of -7.51%. Similarly, NSE of 0.81 and volume difference of 4.64% in Marsyangdi River basin. We find strong similarities in the timing of glacier melting using the GDM and from observations from the ASCAT GM, determining the seasonal start of glacier melting to within 6 days on average. In all basins ASCAT GM observes melting at higher elevations relative to GDM, average of 5,328 m a.s.l. Systematic differences in glacier melting area determined by modeling and satellite observations indicate ASCAT may have suboptimal resolution, view geometry and/or polarimetry for delineating glacier melting at the process-scale in complex topography, especially in the ablation zone. This is the first step in examining the remote sensing products that could potentially be incorporated into hydrologic models to increase the accuracy of the hydrologic flow as well as the ability to estimate river discharge in other basins with limited data.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

A model for the hydrologic and climatic behavior of water on Mars

An analysis is carried out of the hydrologic response of a water-rich Mars to climate change and to the physical and thermal evolution of its crust, with particular attention given to the potential role of the subsurface transport, assuming that the current models of insolation-driven change describe reasonably the atmospheric leg of the planet's long-term hydrologic cycle. Among the items considered are the thermal and hydrologic properties of the crust, the potential distribution of ground ice and ground water, the stability and replenishment of equatorial ground ice, basal melting and the polar mass balance, the thermal evolution of the early cryosphere, the recharge of the valley networks and outflow, and several processes that are likely to drive the large-scale vertical and horizontal transport of H2O within the crust. The results lead to the conclusion that subsurface transport has likely played an important role in the geomorphic evolution of the Martian surface and the long-term cycling of H2O between the atmosphere, polar caps, and near-surface crust.

Clifford, Stephen M.↗