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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Remote sensing applications to hydrologic modeling in the southern Sierra Nevada and portions of the San Joaquin Valley, volume 1

The author has identified the following significant results. Characteristics of LANDSAT MSS imagery present problems in using satellite radiation measurements to estimate the shortwave albedo of an alpine snow cover. Every 15 minute USGS quadrangle contains over 100,000 pixels which poses a computation problem if each pixel is to be evaluated individually. The sampling interval may be sufficiently great to mask some effects of terrain and vegetation on reflectance. Three frames of LANDSAT imagery are needed for complete coverage of the study area, yet less than one third of the area coverage from each frame covers an area of interest. Because of distortions inherent in the imagery, information regarding spacecraft altitude, attitude, and position must be statistically derived with respect to ground control points in the image whose geodetic locations are known. An inspection of shade points indicates that up to one third of the most heavily snow covered areas may saturate in bands 4 through 6. LANDSAT's 9 day repeat cycle is not optimum for snow cover reflectance modeling because the most pronounced changes in albedo occur most nearly following a new snowfall. Such a snowfall, occurring between overpasses, is inadequately represented by extrapolation from the previous overpasses.

Dozier, J.↗
NASA NTRS2011

Global Precipitation Measurement, Validation, and Applications Integrated Hydrologic Validation to Improve Physical Precipitation Retrievals for GPM

Land surface modeling and data assimilation can provide dynamic land surface state variables necessary to support physical precipitation retrieval algorithms over land. It is well-known that surface emission, particularly over the range of frequencies to be included in the Global Precipitation Measurement Mission (GPM), is sensitive to land surface states, including soil properties, vegetation type and greenness, soil moisture, surface temperature, and snow cover, density, and grain size. In order to investigate the robustness of both the land surface model states and the microwave emissivity and forward radiative transfer models, we have undertaken a multi-site investigation as part of the NASA Precipitation Measurement Missions (PMM) Land Surface Characterization Working Group. Specifically, we will demonstrate the performance of the Land Information System (LIS; http://lis.gsfc.nasa.gov; Peters-Lidard et aI., 2007; Kumar et al., 2006) coupled to the Joint Center for Satellite Data Assimilation (JCSDA's) Community Radiative Transfer Model (CRTM; Weng, 2007; van Deist, 2009). The land surface is characterized by complex physical/chemical constituents and creates temporally and spatially heterogeneous surface properties in response to microwave radiation scattering. The uncertainties in surface microwave emission (both surface radiative temperature and emissivity) and very low polarization ratio are linked to difficulties in rainfall detection using low-frequency passive microwave sensors (e.g.,Kummerow et al. 2001). Therefore, addressing these issues is of utmost importance for the GPM mission. There are many approaches to parameterizing land surface emission and radiative transfer, some of which have been customized for snow (e.g., the Helsinki University of Technology or HUT radiative transfer model;) and soil moisture (e.g., the Land Surface Microwave Emission Model or LSMEM).

Peters-Lidar, Christa D.↗
NASA NTRS2011

Recent GRACE-Enabled Hydrologic Research and Applications

This presentation will describe recent hydrology research and applications which make use of GRACE data. These include the following: 1) water balance estimates of evapotranspiration over several large river basins; 2) a summary of NASA's Energy and Water Cycle Study (NEWS) state of the global water budget project; 3) drought indicator products now being incorporated into the U.S. Drought Monitor; 4) new GRACE data assimilation results over several regions

Rodell, Matt↗
NASA NTRS1994

Integration of remote sensing and hydrologic modeling through multi-disciplinary semiarid field campaigns: Moonsoon 1990, Walnut Gulch 1992, and SALSA-MEX

A research and modeling strategy is presented for development of distributed hydrologic models given by a combination of remotely sensed and ground based data. In support of this strategy, two experiments Moonsoon'90 and Walnut Gulch'92 were conducted in a semiarid rangeland southeast of Tucson, Arizona, (U.S.) and a third experiment, the SALSA-MEX (Semi Arid Land Surface Atmospheric Mountain Experiment) was proposed. Results from the Moonsoon'90 experiment substantially advanced the understanding of the hydrologic and atmospheric fluxes in an arid environment and provided insight into the use of remote sensing data for hydrologic modeling. The Walnut Gulch'92 experiment addressed the seasonal hydrologic dynamics of the region and the potential of combined optical microwave remote sensing for hydrologic applications. SALSA-MEX will combine measurements and modeling to study hydrologic processes influenced by surrounding mountains, such as enhanced precipitation, snowmelt and recharge to ground water aquifers. The results from these experiments, along with the extensive experimental data bases, should aid the research community in large scale modeling of mass and energy exchanges across the soil-plant-atmosphere interface.

Moran, M. S.↗
NASA NTRS2012

SWOT: The Surface Water and Ocean Topography Mission. Wide- Swath Altimetric Elevation on Earth

The elevation of the surface of the ocean and freshwater bodies on land holds key information on many important processes of the Earth System. The elevation of the ocean surface, called ocean surface topography, has been measured by conventional nadirlooking radar altimeter for the past two decades. The data collected have been used for the study of large-scale circulation and sea level change. However, the spatial resolution of the observations has limited the study to scales larger than about 200 km, leaving the smaller scales containing substantial kinetic energy of ocean circulation that is responsible for the flux of heat, dissolved gas and nutrients between the upper and the deep ocean. This flux is important to the understanding of the ocean's role in regulatingfuture climate change.The elevation of the water bodies on land is a key parameter required for the computation of storage and discharge of freshwater in rivers, lakes, and wetlands. Globally, the spatial and temporal variability of water storage and discharge is poorly known due to the lack of well-sampled observations. In situ networks measuring river flows are declining worldwide due to economic and political reasons. Conventional altimeter observations suffers from the complexity of multiple peaks caused by the reflections from water, vegetation canopy and rough topography, resulting in much less valid data over land than over the ocean. Another major limitation is the large inter track distance preventing good coverage of rivers and other water bodies.This document provides descriptions of a new measurement technique using radar interferometry to obtain wide-swath measurement of water elevation at high resolution over both the ocean and land. Making this type of measurement, which addresses the shortcomings of conventional altimetry in both oceanographic and hydrologic applications, is the objective of a mission concept called Surface Water and Ocean Topography (SWOT), which was recommended by the National Research Council's first decadal survey of NASA's Earth science program. This document provides wide-ranging examples of research opportunities in oceanography and land hydrology that would be enabled by the new type of measurement. Additional applications in many other branches of Earth System science ranging from ocean bathymetry to sea ice dynamics are also discussed. Many of the technical issues in making the measurement are discussed as well. Also presented is a preliminary design of the SWOT Mission concept, which is being jointly developed by NASA and CNES, with contributions from the Canadian Space Agency.

altimetry↗
NASA NTRS2011

Hyperresolution Global Land Surface Modeling: Meeting a Grand Challenge for Monitoring Earth's Terrestrial Water

Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (approx.10-100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface-subsurface interactions due to fine-scale topography and vegetation; improved representation of land-atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 10(exp 9) unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a grand challenge to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

Wood, Eric F.↗
NASA NTRS1980

Operational Applications of Satellite Snowcover Observations

The history of remote sensing of snow cover is reviewed and the following topics are covered: various techniques for interpreting LANDSAT and NOAA satellite data; the status of future systems for continuing snow hydrology applications; the use of snow cover observations in streamflow forecasts by Applications Systems Verification and Transfer participants and selected foreign investigators; and the benefits of using satellite snow cover data in runoff prediction.

Rango, A.↗
NASA NTRS1982

Combining remotely sensed and other measurements for hydrologic areal averages

A method is described for combining measurements of hydrologic variables of various sampling geometries and measurement accuracies to produce an estimated mean areal value over a watershed and a measure of the accuracy of the mean areal value. The method provides a means to integrate measurements from conventional hydrological networks and remote sensing. The resulting areal averages can be used to enhance a wide variety of hydrological applications including basin modeling. The correlation area method assigns weights to each available measurement (point, line, or areal) based on the area of the basin most accurately represented by the measurement. The statistical characteristics of the accuracy of the various measurement technologies and of the random fields of the hydrologic variables used in the study (water equivalent of the snow cover and soil moisture) required to implement the method are discussed.

Johnson, E. R.↗
NASA NTRS2020

Autonomous Aerial Vehicles (AAVs) as a Tool for Improving the Spatial Resolution of Snow Albedo Measurements in Mountainous Regions

We present technical advances and methods to measure effective broadband physical albedo in snowy mountain headwaters using a prototype dual-sensor pyranometer mounted on an Autonomous Aerial Vehicle (an AAV). Our test flights over snowy meadows and forested areas performed well during both clear sky and snowy/windy conditions at an elevation of ~2650 m above mean sea level (MSL). Our AAV-pyranometer platform provided high spatial (m) and temporal resolution (sec) measurements of effective broadband (310–2700 nm) surface albedo. The AAV-based measurements reveal spatially explicit changes in landscape albedo that are not present in concurrent satellite measurements from Landsat and MODIS due to a higher spatial resolution. This AAV capability is needed for validation of satellite snow albedo products, especially over variable montane landscapes at spatial scales of critical importance to hydrological applications. Effectively measuring albedo is important, as annually the seasonal accumulation and melt of mountain snowpack represent a dramatic transformation of Earth’s albedo, which directly affects headwaters’ water and energy cycles.

albedo↗
NASA NTRS1984

Landsat Thematic Mapper studies of land cover spatial variability related to hydrology

Past accomplishments involving remote sensing based land-cover analysis for hydrologic applications are reviewed. Ongoing research in exploiting the increased spatial, radiometric, and spectral capabilities afforded by the TM on Landsats 4 and 5 is considered. Specific studies to compare MSS and TM for urbanizing watersheds, wetlands, and floodplain mapping situations show that only a modest improvement in classification accuracy is achieved via statistical per pixel multispectral classifiers. The limitations of current approaches to multispectral classification are illustrated. The objectives, background, and progress in the development of an alternative analysis approach for defining inputs to urban hydrologic models using TM are discussed.

Wharton, S.↗
NASA NTRS2011

Land Surface Verification Toolkit (LVT) - A Generalized Framework for Land Surface Model Evaluation

Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT) is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS), it also supports hydrological data products from other, non-LIS environments. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

Kumar, Sujay V.↗
NASA NTRS1978

International Symposium on Remote Sensing of Environment, 12th, Manila, Philippines, April 20-26, 1978, Proceedings. Volumes 1, 2 & 3

The papers outline the remote sensing activities being carried out in a number of countries throughout the world, and present details on a variety of individual projects. Topics studied include a worldwide approach to remote sensing and mineral exploration, a land use information system based on statistical inference, acoustic radar and remote sensing in the boundary layer, procedure for land-use analysis in developing countries, an airborne geochemical system, remote sensing of snowpack with microwave radiometers for hydrologic applications, wheat production forecasts based on Landsat data, airborne lidar aerosol measurements over the U.S. and Europe, Landsat inventory of agricultural and forest resources in Bangladesh, application of satellite imagery to flood plain mapping in Thailand, and vegetation mapping of Nigeria from radar.

Source record↗
NASA NTRS1981

Snow hydrology studies using data from the Heat Capacity Mapping Mission

This paper describes a study of the snow hydrology application of thermal infrared (IR) data from the Heat Capacity Mapping Mission (HCMM) satellite. The HCMM data in both imagery and digital tape formats are analyzed for two study areas: the Salt-Verde Watershed in central Arizona and the southern Sierra Nevada in California. The analysis procedures are described, including the development of a unique contour plotting program that makes it possible to overlay HCMM thermal contours directly onto the visible channel imagery. The results indicate that satellite thermal-IR data can provide the hydrologist with additional useful information on snow cover.

Barnes, J. C.↗
NASA NTRS1984

Hydrological planning studies using Landsat-4 Thematic Mapper (TM)

NASA, in cooperation with the U.S. Army Corps of Engineers, is evaluating the capabilities of Landsat 4 Thematic Mapper (TM) data for environmental and hydrological applications. Attention is given to the results of studies conducted at the Clinton River Basin in Michigan and the eastern shore of the Chesapeake Bay in Maryland. In the former, the evaluation conducted was for the band combinations: (1) 2, 3, and 4; (2) 3, 4, and 5; (3) 3, 4, 5, and 6; and (4) all seven bands. In the latter case, Multispectral Scanner (MSS) and TM data were classified for combinations (1), (3) and (4). Wetland classification accuracy for the 7-band TM data in this study was found to be 9 percent higher than with MSS data, allowing more reliable and accurate monitoring.

Gervin, J. C.↗
NASA NTRS2004

Comparison of Local Scale Measured and Modeled Brightness Temperatures and Snow Parameters from the CLPX 2003 by Means of a Dense Medium Radiative Transfer Theory Model

Microwave remote sensing offers distinct advantages for observing the cryosphere. Solar illumination is not required, and spatial and temporal coverage are excellent from polar-orbiting satellites. Passive microwave measurements are sensitive to the two most useful physical quantities for many hydrological applications: physical temperature and water content/state. Sensitivity to the latter is a direct result of the microwave sensitivity to the dielectric properties of natural media, including snow, ice, soil (frozen or thawed), and vegetation. These considerations are factors motivating the development of future cryospheric satellite remote sensing missions, continuing and improving on a 26-year microwave measurement legacy. Perhaps the biggest issues regarding the use of such satellite measurements involve how to relate parameter values at spatial scales as small as a hectare to observations with sensor footprints that may be up to 25 x 25 km. The NASA Cold-land Processes Field Experiment (CLPX) generated a dataset designed to enhance understanding of such scaling issues. CLPX observations were made in February (dry snow) and March (wet snow), 2003 in Colorado, USA, at scales ranging from plot scale to 25 x 25 km satellite footprints. Of interest here are passive microwave observations from ground-based, airborne, and satellite sensors, as well as meteorological and snowpack measurements that will enable studies of the effects of spatial heterogeneity of surface conditions on the observations. Prior to performing such scaling studies, an evaluation of snowpack forward modelling at the plot scale (least heterogeneous scale) is in order. This is the focus of this paper. Many forward models of snow signatures (brightness temperatures) have been developed over the years. It is now recognized that a dense medium radiative transfer (DMRT) treatment represents a high degree of physical fidelity for snow modeling, yet dense medium models are particularly sensitive to snowpack structural parameters such as grain size, density, and depth---parameters that may vary substantially within a snowpack. Microwave radiometric data and snow pit measurements collected at the Local-Scale Observation Site (LSOS) during the third Intensive Observation Period (IOP3) of the CLPX have been used to test the capabilities of a DMRT model using the Quasi Crystalline Approximation with Coherent Potential (QCA-CP). The radiometric measurements were made by the University of Tokyo s Ground Based Microwave Radiometer-7 (GBMR-7) system. We evaluate the degree to which a DMRT-based model can accurately reproduce the GBMR-7 brightness temperatures at different frequencies and incidence angles.

Tedescol, Marco↗
NASA NTRS2007

Soil Moisture Retrieval During a Corn Growth Cycle using L-band (1.6 GHz) Radar Observations

New opportunities for large-scale soil moisture monitoring will emerge with the launch of two low frequency (L-band 1.4 GHz) radiometers: the Aquarius mission in 2009 and the Soil Moisture and Ocean Salinity (SMOS) mission in 2008. Soil moisture is an important land surface variable affecting water and heat exchanges between atmosphere, land surface and deeper ground water reservoirs. The data products from these sensors provide valuable information in a range of climate and hydrologic applications (e.g., nume~cal weather prediction, drought monitoring, flood forecasting, water resources management, etc.). This paper describes a unique data set that was collected during a field campaign at OPE^ (Optimizing Production Inputs for Economic and Environmental Enhancements) site in Beltsville, Maryland throughout the eompj2ete corn growing in 2002. This investigation describes a simple methodology to correct active microwave observations for vegetation effects, which could potentially be implemented in a global soil moisture monitoring algorithm. The methodology has been applied to radar observation collected during the entire corn growth season and validation against ground measurements showed that the top 5-cm soil moisture can be retrieved with an accuracy up to 0.033 [cu cm/cu cm] depending on the sensing configuration.

Joseph, Alicia T.↗
NASA NTRS2008

Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model

The NASA Gravity Recovery and Climate Experiment (GRACE) system of satellites provides observations of large-scale, monthly terrestrial water storage (TWS) changes. In. this presentation we describe a land data assimilation system that ingests GRACE observations and show that the assimilation improves estimates of water storage and fluxes, as evaluated against independent measurements. The ensemble-based land data assimilation system uses a Kalman smoother approach along with the NASA Catchment Land Surface Model (CLSM). We assimilated GRACE-derived TWS anomalies for each of the four major sub-basins of the Mississippi into the Catchment Land Surface Model (CLSM). Compared with the open-loop (no assimilation) CLSM simulation, assimilation estimates of groundwater variability exhibited enhanced skill with respect to measured groundwater. Assimilation also significantly increased the correlation between simulated TWS and gauged river flow for all four sub-basins and for the Mississippi River basin itself. In addition, model performance was evaluated for watersheds smaller than the scale of GRACE observations, in the majority of cases, GRACE assimilation led to increased correlation between TWS estimates and gauged river flow, indicating that data assimilation has considerable potential to downscale GRACE data for hydrological applications. We will also describe how the output from the GRACE land data assimilation system is now being prepared for use in the North American Drought Monitor.

Reichle, Rolf H.↗