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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Predicting Hydrological Drought: Relative Contributions of Soil Moisture and Snow Information to Seasonal Streamflow Prediction Skill

in this study we examine how knowledge of mid-winter snow accumulation and soil moisture conditions contribute to our ability to predict streamflow months in advance. A first "synthetic truth" analysis focuses on a series of numerical experiments with multiple sophisticated land surface models driven with a dataset of observations-based meteorological forcing spanning multiple decades and covering the continental United States. Snowpack information by itself obviously contributes to the skill attained in streamflow prediction, particularly in the mountainous west. The isolated contribution of soil moisture information, however, is found to be large and significant in many areas, particularly in the west but also in region surrounding the Great Lakes. The results are supported by a supplemental, observations-based analysis using (naturalized) March-July streamflow measurements covering much of the western U.S. Additional forecast experiments using start dates that span the year indicate a strong seasonality in the skill contributions; soil moisture information, for example, contributes to kill at much longer leads for forecasts issued in winter than for those issued in summer.

Koster, R.↗
NASA NTRS2012

Distributed Assimilation of Satellite-based Snow Extent for Improving Simulated Streamflow in Mountainous, Dense Forests: An Example Over the DMIP2 Western Basins

Snow cover area affects snowmelt, soil moisture, evapotranspiration, and ultimately streamflow. For the Distributed Model Intercomparison Project - Phase 2 Western basins, we assimilate satellite-based fractional snow cover area (fSCA) from the Moderate Resolution Imaging Spectroradiometer, or MODIS, into the National Weather Service (NWS) SNOW-17 model. This model is coupled with the NWS Sacramento Heat Transfer (SAC-HT) model inside the National Aeronautics and Space Administration's (NASA) Land Information System. SNOW-17 computes fSCA from snow water equivalent (SWE) values using an areal depletion curve. Using a direct insertion, we assimilate fSCAs in two fully distributed ways: 1) we update the curve by attempting SWE preservation, and 2) we reconstruct SWEs using the curve. The preceding are refinements of an existing simple, conceptually-guided NWS algorithm. Satellite fSCA over dense forests inadequately accounts for below-canopy snow, degrading simulated streamflow upon assimilation during snowmelt. Accordingly, we implement a below-canopy allowance during assimilation. This simplistic allowance and direct insertion are found to be inadequate for improving calibrated results, still degrading them as mentioned above. However, for streamflow volume for the uncalibrated runs, we obtain: (1) substantial to major improvements (64-81 %) as a percentage of the control run residuals (or distance from observations), and (2) minor improvements (16-22 %) as a percentage of observed values. We highlight the need for detailed representations of canopy-snow optical radiative transfer processes in mountainous, dense forest regions if assimilation-based improvements are to be seen in calibrated runs over these areas.

Yatheendradas, Soni↗
NASA NTRS1975

Improving estimates of streamflow characteristics using LANDSAT-1 (ERTS-1) imagery

The author has identified the following significant results. Streamflow characteristics in the Delmarva Peninsula derived from the records of daily discharge of 20 gaged basins are representative of the full range in flow conditions and include all of those commonly used for design or planning purposes. They include annual flood peaks with recurrence intervals of 2, 5, 10, 25, and 50 years, mean annual discharge, standard deviation of the mean annual discharge, mean monthly discharges, standard deviation of the mean monthly discharges, low-flow characteristics, flood volume characteristics, and the discharge equalled or exceeded 50 percent of the time. Streamflow and basin characteristics were related by a technique of multiple regression using a digital computer. A control group of equations was computed using basin characteristics derived from maps and climatological records. An experimental group of equations was computed using basin characteristics derived from LANDSAT imagery as well as from maps and climatological records. Based on a reduction in standard error of estimate equal to or greater than 10 percent, the equations for 12 stream flow characteristics were substantially improved by adding to the analyses basin characteristics derived from LANDSAT imagery.

Hollyday, E. F.↗
NASA NTRS2021

River streamflow, remotely-sensed water quality, and benthic composition of previously undescribed nearshore coral reefs in northern Puerto Rico

Land-based sediment stress represents a threat to many coral reefs in Puerto Rico primarily as a result of unrestricted land cover/land use changes and poor best management practices. The effects of such stresses have been documented along most coasts around the island. However, little attention has been paid to reefs located on the north coast, and very little is known about their composition and current state. Here, we present a study characterizing riverine inputs, water quality conditions, and benthic composition of two previously undescribed coral reefs (Tómbolo and Machuca reefs) located just eastward of the Río Grande de Manatí outlet in north-central Puerto Rico. This study utilizes a time series of remotely sensed ocean color products (diffuse vertical attenuation coefficient at 490 nm [Kd490] and chlorophyll-a concentration [Chl-a] estimated with data from the Visible Infrared Imaging Radiometer Suite [VIIRS]) to characterize water quality in this coastal region. In general, the months with relatively high mean daily river streamflow also coincide with months having the highest proportion of eastward wave direction, which can promote the eastward influence of river waters towards the two coral reefs sites. Kd490 and Chl-a showed a higher riverine influence closer to the watershed outlet. Kd490 and Chl-a monthly peaks also coincide with river streamflow highs, particularly at those pixels closer to shore. Tómbolo Reef, located farther eastward of the river outlet, shows a well-developed primary reef framework mainly composed of threatened reef-building species (Acropora palmata, Pseudodiploria) and high coral cover (19-51%). The benthos of Machuca Reef, located closer to the river outlet, is dominated by macroalgae with a significantly lower coral cover (0.2-2.7%) mainly composed of “weedy” coral species (Porites astroides, and S. radians). Cover of major benthic components correlates with distance from the river outlet, and with gradients in Kd490 and Chl-a, with higher coral cover and lower macroalgal cover farther from the river outlet. Coral cover at Tómbolo Reef is higher than what has been reported for similar sites around Puerto Rico and other Caribbean islands showing its ecological importance and, as up until now, an unrecognized potential refuge of reef-building threatened coral species.

benthic cover↗
NASA NTRS2024

Irrigation-Driven Groundwater Depletion in the Ganges-Brahmaputra Basin Decreases the Streamflow in the Bay of Bengal

Ganges and Brahmaputra, two of Asia’s most prominent rivers, have a crucial role in Southeast Asia’s geopolitics and economy and are home to one of the world’s biggest marine ecosystems. Irrigation-driven groundwater depletion and climate change affect the Ganges-Brahmaputra’s hydrology, threatening the stability of the Bay of Bengal. Here, we quantify, using results from a land reanalysis, the impacts of a changing climate and intensive irrigation on the surface water flowing into the Bay of Bengal. The effects of such activities mostly occurring in the Ganges basin, either intensified or lessened depending on the area by the climatic conditions, decrease freshwater flow into the bay by up to 1200 m 3 /s/year. While the increase in precipitation in the Ganges basin reduces the effects of groundwater depletion on the streamflow, the decrease in precipitation and the snowmelt decline in the Brahmaputra basin exacerbate streamflow reduction due to groundwater depletion at the delta.

Climate change↗
NASA NTRS1973

Monitoring of streamflow in the Verde River by ERTS-1 Data Collection System (DCS)

The Verde River watershed in central Arizona furnishes municipal, industrial, and agricultural water to the Salt River Valley --an area that contains more than half of Arizona's population and about one-fourth of the State's irrigated land. Water-management decisions related to the operation of large multiple-use reservoirs require accurate and continuous monitoring of moisture conditions over large remote areas. The U.S. Geological Survey in cooperation with the Salt River Valley Water Users' Association installed a specially designed gaging station on the Verde River near the town of Camp Verde to evaluate near-real time streamflow data furnished by the ERTS-1 Data Collection System (DCS). On Nov. 3, 1972, the installation was equipped with a Stevens digital water-level recorder, modified for telemetry, and an ERTS-1 data collection platform operating in the digital-parallel mode.

Schumann, H. H.↗
NASA NTRS1981

Use of aerial photography in determining land use and streamflow relationships on small developing watersheds

Using aerial photographs dating back to 1937, the historical trends of five land use classes (crop, forest, open field, urban and suburban) are determined. The relationships between these and various flow regime parameters are investigated. Annual runoff is found to be 7.5 inches greater now than in the year 1932. It is also found that growing season runoff increased by 3.5 inches during the same period. This increase is approximately equivalent to 160 area inches of excess runoff during the 45-year period of observation. The increase in runoff is found to be positively correlated with the percent basin area in the urban, suburban and open field land use classes. A negative correlation is established with forest and crop land. Although poor correlations are found with high flow, low flow, flow interval and flow date data, it is thought that a more precise quantification of land use or a smaller basin area may possibly have yielded more positive results for streamflow timing data.

Owe, M.↗
NASA NTRS1975

Seasonal streamflow estimation employing satellite snowcover observations

Low resolution meteorological satellite and high resolution earth resources satellite data have been used to map snow covered area over the upper Indus River and the Wind River Mountains of Wyoming, respectively. For the Indus River early spring snow covered area was extracted and related to April through June stream flow from 1967-1971 using a regression equation. Prediction of the April-June 1972 stream flow from the satellite data was within three percent of the actual total. Composited results from two years of data over seven Wind River Mountain watersheds indicated that LANDSAT-1 snow cover observations, separated on the basis of watershed elevation, could also be related to runoff in significant regression equations.

Rango, A.↗
NASA NTRS1975

A study of application of remote sensing to river forecasting. Volume 2: Detailed technical report, NASA-IBM streamflow forecast model user's guide

The Model is described along with data preparation, determining model parameters, initializing and optimizing parameters (calibration) selecting control options and interpreting results. Some background information is included, and appendices contain a dictionary of variables, a source program listing, and flow charts. The model was operated on an IBM System/360 Model 44, using a model 2250 keyboard/graphics terminal for interactive operation. The model can be set up and operated in a batch processing mode on any System/360 or 370 that has the memory capacity. The model requires 210K bytes of core storage, and the optimization program, OPSET (which was used previous to but not in this study), requires 240K bytes. The data band for one small watershed requires approximately 32 tracks of disk storage.

Source record↗
NASA NTRS1977

Application of remotely sensed land-use information to improve estimates of streamflow characteristics, volume 8

The author has identified the following significant results. Land use data derived from high altitude photography and satellite imagery were studied for 49 basins in Delaware, and eastern Maryland and Virginia. Applying multiple regression techniques to a network of gaging stations monitoring runoff from 39 of the basins, demonstrated that land use data from high altitude photography provided an effective means of significantly improving estimates of stream flow. Forty stream flow characteristic equations for incorporating remotely sensed land use information, were compared with a control set of equations using map derived land cover. Significant improvement was detected in six equations where level 1 data was added and in five equations where level 2 information was utilized. Only four equations were improved significantly using land use data derived from LANDSAT imagery. Significant losses in accuracy due to the use of remotely sensed land use information were detected only in estimates of flood peaks. Losses in accuracy for flood peaks were probably due to land cover changes associated with temporal differences among the primary land use data sources.

Pluhowski, E. J.↗
NASA NTRS1981

Improving streamflow estimates through the use of LANDSAT

Estimates of low flow and flood frequency in several southwestern Wisconsin basins were improved by determining land cover from LANDSAT imagery. With the use of estimates of land cover in multiple-regression techniques, the standard error of estimate (SE) for the least annual 7-day low flow for 2- and 10-year recurrence intervals of ungaged sites were lowered by 9% each. The SE of flood frequency in the 'Driftless Area' of Wisconsin for 10-, 50-, and 100-year recurrence intervals were lowered by 14%. Four of nine basin characteristics determined from satellite imagery were significant variables in the multiple-regression techniques, whereas only 1 of the 12 characteristics determined from topographic maps was significant. The percentages of land cover categories in each basin were determined by merging basin boundaries, digitized from quadrangles, with a classified LANDSAT scene. Both the basin boundary X-Y polygon coordinates and the satellite coordinates were converted to latitude-longitude for merging compatibility.

Allord, G. J.↗