38 resultados para Hydrologic Stratigraphy


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We report a Monte Carlo representation of the long-term inter-annual variability of monthly snowfall on a detailed (1 km) grid of points throughout the southwest. An extension of the local climate model of the southwestern United States (Stamm and Craig 1992) provides spatially based estimates of mean and variance of monthly temperature and precipitation. The mean is the expected value from a canonical regression using independent variables that represent controls on climate in this area, including orography. Variance is computed as the standard error of the prediction and provides site-specific measures of (1) natural sources of variation and (2) errors due to limitations of the data and poor distribution of climate stations. Simulation of monthly temperature and precipitation over a sequence of years is achieved by drawing from a bivariate normal distribution. The conditional expectation of precipitation. given temperature in each month, is the basis of a numerical integration of the normal probability distribution of log precipitation below a threshold temperature (3°C) to determine snowfall as a percent of total precipitation. Snowfall predictions are tested at stations for which long-term records are available. At Donner Memorial State Park (elevation 1811 meters) a 34-year simulation - matching the length of instrumental record - is within 15 percent of observed for mean annual snowfall. We also compute resulting snowpack using a variation of the model of Martinec et al. (1983). This allows additional tests by examining spatial patterns of predicted snowfall and snowpack and their hydrologic implications.

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Environmental managers strive to preserve natural resources for future generations but have limited decision-making tools to define ecosystem health. Many programs offer relevant broad-scale, environmental policy information on regional ecosystem health. These programs provide evidence of environmental condition and change, but lack connections between local impacts and direct effects on living resources. To address this need, the National Oceanic and Atmospheric Administration/National Ocean Service (NOAA/NOS) Cooperative Oxford Laboratory (COL), in cooperation with federal, state, and academic partners, implemented an integrated biotic ecosystem assessment on a sub-watershed 14-digit Hydrologic Unit Code (HUD) scale in Chesapeake Bay. The goals of this effort were to 1) establish a suite of bioindicators that are sensitive to ecosystem change, 2) establish the effects of varying land-use patterns on water quality and the subsequent health of living resources, 3) communicate these findings to local decision-makers, and 4) evaluate the success of management decisions in these systems. To establish indicators, three sub-watersheds were chosen based on statistical analysis of land-use patterns to represent a gradient from developed to agricultural. The Magothy (developed), Corsica (agricultural), and Rhode (reference) Rivers were identified. A random stratified design was developed based on depth (2m contour) and river mile. Sampling approaches were coordinated within this structure to allow for robust system comparisons. The sampling approach was hierarchal, with metrics chosen to represent a range from community to cellular level responses across multiple organisms. This approach allowed for the identification of sub-lethal stressors, and assessment of their impact on the organism and subsequently the population. Fish, crabs, clams, oysters, benthic organisms, and bacteria were targeted, as each occupies a separate ecological niche and may respond dissimilarly to environmental stressors. Particular attention was focused on the use of pathobiology as a tool for assessing environmental condition. By integrating the biotic component with water quality, sediment indices, and land- use information, this holistic evaluation of ecosystem health will provide management entities with information needed to inform local decision-making processes and establish benchmarks for future restoration efforts.

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We describe a preliminary investigation into large-scale atmospheric and surface moisture variations over North America. We compare large-scale hydrologic budgets in the Los Alamos general circulation model (GCM) to observed precipitation and vertically integrated atmospheric moisture fluxes derived from the National Meteorological Center's operational analyses. THe GCM faithfully simulates the integrated flux divergence and P-E differences. However, the integrated moisture content is too low, and precipitation and evaporation are too high. The model produces summertime soil moisture dryness, which supports previous studies showing increased droughts under warmer conditions.

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EXTRACT (SEE PDF FOR FULL ABSTRACT): We estimate monthly runoff for a 2-dimensional solution domain containing those areas tributary to Pyramid Lake, Nevada (the Truckee River drainage basin) at a 1-kilometer grid cell spacing. ... To calculate the effect of snow on the hydrologic system, we perform two experiments. In the first we assume that all precipitation falls as rain; in the second we assume that some precipitation falls as snow, thus available water is a combination of rain and snowmelt. We find that considering the effect of snow results in a more accurate representation of mean monthly flow rates, in particular the peak flow during the melt season in the Sierra Nevada. These preliminary results indicate that a relatively simple snow model can improve the representation of Truckee River basin hydrology, significantly reducing errors in modeled seasonal runoff.

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EXTRACT (SEE PDF FOR FULL ABSTRACT): A 323-meter (about 800,000 year) core of lake deposits beneath Owens Lake playa, Inyo County, California, contains a nearly continuous paleolimnological record based on diatom assemblages. ... Throughout most of its history, Owens Lake was characterized by freshwater diatoms, indicating a positive hydrologic input from the Owens River and overflow to lake systems downstream.

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EXTRACT (SEE PDF FOR FULL ABSTRACT): Evaluations of the impact of climate change (such as a greenhouse effect) upon water resources should represent both the expected change and the uncertainty in that expectation. Since water resources such as streamflow and reservoir levels depend on a variety of factors, each of which is subject to significant uncertainty, it is desirable to formulate methods of representing that uncertainty in the forcing factors and from this determine the uncertainty in the response variables of interest. We report here progress in the representation of the uncertainty in climate upon the uncertainty in the estimated hydrologic response.

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Recent papers provide detailed analyses of more than 40 high-resolution time series culled from the extensive paleoclimate literature that appear to define cyclical elements of the Solar-Insolation/Tidal-Resonance Climate Model. This model was earlier referred to as the Milankovitch/Pettersson Climatic Theory. This paper provides comparable analyses of an additional 20 or so, evidently supportive, climate and volcanic time series. The tree-ring, historical, pollen, cultural, time-frequency, and hydrologic records range in length from 400 to 90,000 years and spatially from Alaska to Tierra del Fuego.

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A brief review is made of the hydrologic conditions at the Sofala Bank, mainly based on the research data obtained from 1978 to 1982. A description is attempted of the circulation pattern and the distribution of water masses in the area, four hydrologic regimes being identified. These are compared with the distributions of different pelagic and demersal fish species. A tendency is found for different groups of species to prefer different hydrologic regimes.