PREDICTING MEASUREMENT ERROR OF AREAL MEAN PRECIPITATION DURING EXTREME EVENTS1

ABSTRACT: The areal mean precipitation (AMP) over a catchment is normally calculated using point measurements at rainfall gages. Error in AMP estimates occurs when an insufficient number of gages are used to sample precipitation which is highly variable in space. AMP error is investigated using historic, severe rainfalls with a set of hypothetical catchments and raingage networks. The potential magnitude of error is estimated for typical gage network densities and arrangements. Possible sources of error are evaluated, and a method is proposed for predicting the magnitude of error using data that are commonly available for severe, historic rainfall.     

Evaluation of tidal marsh restoration: Comparison of selected macroinvertebrate populations on a restored impounded valley marsh and an unimpounded valley marsh within the same salt marsh system in Connecticut,USA

Macroinvertebrates were examined on an impounded valley marsh in Stonington, Connecticut, that has changed from aTypha-dominated system to one with typical salt-marsh vegetation during 13 years following the reintroduction of tidal exchange. Animal populations on this restored impounded marsh were evaluated by comparing them with populations on a nearby unimpounded valley marsh of roughly the same size. Populations of the high marsh snail,Melampus bidentatus Say, were quantitatively sampled along transects that extended from the water-marsh edge to the upland; those of the ribbed mussel,Geukensia demissa Dillwyn, were sampled in low marsh areas on transects along the banks of creeks and mosquito ditches. The occurrence of other marsh invertebrates also was documented, but their abundance was not measured. The mean density ofMelampus was 332±39.6 SE/m² on the restored impounded marsh and 712±56.0 SE/m² on the unimpounded marsh. However, since snails were larger on the restored impounded marsh, the difference in snail biomass was less pronounced than the difference in snail density. MeanMelampus biomass was 4.96±0.52 SE g dry wt/m² on the restored impounded marsh and 6.96±0.52 SE g dry wt/m² on the unimpounded marsh. On the two marshes, snail density and biomass varied in relation to plant cover and other factors. The density and biomass ofGeukensia at the edge of the marsh were comparable on the restored impounded and unimpounded marshes. Mean mussel densities ranged from 80 to 240/m² and mean mussel biomass varied from 24.8–64.8 g dry wt/m² in different low marsh areas. In contrast, below the impoundment dike, meanGeukensia density was 1100±96.4 SE/m² and meanGeukensia biomass was 303.6±33.28 SE g dry wt/m². A consideration of all available evidence leads to the conclusion that the impounded marsh is in an advanced phase of restoration.     

BAYESIAN MODELS OF FORECASTED TIME SERIES1

Bayesian Processor of Forecasts (BPF) combines a prior distribution, which describes the natural uncertainty about the realization of a hydrologic process, with a likelihood function, which describes the uncertainty in categorical forecasts of that process, and outputs a posterior distribution of the process, conditional upon the forecasts. The posterior distribution provides a means of incorporating uncertain forecasts into optimal decision models. We present fundamentals of building BPF for time series. They include a general formulation, stochastic independence assumptions and their interpretation, computationally tractable models for forecasts of an independent process and a first-order Markov process, and parametric representations for normal-linear processes. An example is shown of an application to the annual time series of seasonal snowmelt runoff volume forecasts.     

GEOLOGIC INFERENCE FROM “FLOW NET” TRANSMISSIVITY DETERMINATION: THREE CASE STUDIES1

A graphical inverse method for determining the regional transmissivity distribution was applied to three field problems. The study areas were the Hanford Site, Washington; the Rocky Mountain Arsenal, Colorado; and the Nevada Test Site, Nevada. This method can aid in flow system conceptualization by revealing the location of bedrock controls for groundwater flow. It is a valuable tool for aiding the hydrogeologist in asking questions about the nature of trends in the pattern of transmissivity values. Quantitative estimates of regional transmissivities can be used as starting points for further parameter refinement. Sensitivity analysis using Monte Carlo simulation shows that quantitative estimates of transmissivity can be obtained when measurement error in the hydraulic head does not cause a large error in the hydraulic gradient.     

Groundwater mapping: An analysis of the United States Hydrological Investigation Atlas Series

Groundwater mapping is a critical component of efficient water resource management today. Difficulties arise when highly specialized and complex groundwater data are collected and presented in map form. This is an analysis of the map content and its presentation in the USGS Hydrological Investigation Atlas Series. This analysis reveals the problems to be surmounted in mapping groundwater information. The technical nature of the groundwater data requires special design considerations.     

Evaluation of methods for determining adverse impacts of air pollution on terrestrial ecosystems

Methods used to determine adverse impacts of air pollution on four levels of biological organization of terrestrial ecosystems were evaluated for their use in decision making by federal land managers of class I areas and as guidelines for scientists employed to design field studies in these areas. At the level of the individual, visible injury, biomass, and sulfur uptake were the most often used components; at the population level, natality and mortality; at the community level, diversity; and at the ecosystem level, biogeochemical cycling. Most studies focused on structural responses of individual organisms. These components are relatively sensitive and are easy and inexpensive to measure; however, linkages of these parameters to adverse impacts on populations, communities, or ecosystems are lacking. Measurements of effects of air pollution at the higher levels of organization are confounded by natural variability, long response times, climatic variation, pathogens, and other factors. In addition, the lack of replication and of true control areas creates severe problems for design of monitoring programs and testing of hypotheses concerning effects.     

RUNOFF PREDICTION USING REMOTE SENSING IMAGERY1

ABSTRACT: Percent imperviousness is an important parameter in modeling the urban rainfall-runoff process and is usually determined using manual methods such as random sampling or conventional accounting methods. In this study two computerized methods are used for estimating the percent imperviousness of urban watersheds using high altitude remote sensing imagery. These methods include the Laser Image Processing Scanner and the Video-Tape Camera system. Imperviousness is directly estimated in the former method while in the latter it is estimated as a function of the statistics of the responses on emulsions of the imagery. The percent imperviousness computed by utilizing remote sensing imagery was used with the conceptual models of rainfall-runoff models. The models were applied to four urban watersheds and the runoff prediction results indicate that imperviousness determined by using remote sensing imagery was as accurate as that obtained by the manual methods, and that the use of remote sensing imagery requires significantly less time and money.     

UNCERTAINTY ANALYSIS OF BMP EFFECTWENESS FOR CONTROLLING NITROGEN FROM URBAN NONPOINT SOURCES1

ABSTRACT: The effectiveness of urban Best Management Practices (BMPs) in achieving the No-Net-Increase Policy (NNTP), a policy designed to limit nonpoint nitrogen loading to Long Island Sound (US), is analyzed. A unit loading model is used to simulate annual nitrogen exported from the Norwalk River watershed (Connecticut) under current and future conditions. A probabilistic uncertainty analysis is used to incorporate uncertainty in nitrogen export coefficients and BMP nitrogen removal effectiveness. The inclusion of uncertainty in BMP effectiveness and nitrogen export coefficients implies that additional BMPs, or BMPs with a greater effectiveness in nitrogen removal, will be required to achieve the NNIP. Even though including uncertainty leads to an increase in BMP implementation rates or BMP effectiveness, this type of analysis provides the decision maker with a more realistic assessment of the likelihood that implementing BMPs as a management strategy will be successful. Monte Carlo simulation results indicate that applying BMPs to new urban developments alone will not be sufficient to achieve the NNIP since BMPs are not 100 percent effective in removing the increase in nitrogen caused by urbanization. BMPs must also be applied to selected existing urban areas. BMPs with a nitrogen removal effectiveness of 40–60 percent, probably the highest level of removal that can be expected over an entire watershed, must be applied to at least 75 percent of the existing urban area to achieve the NNIP This high rate of application is not likely to be achieved in urbanized watersheds in the LIS watershed; therefore, additional point source control will be necessary to achieve the NNIP     

地磁绝对测量对中等地震的反应

介绍了1993年获得的两个中等地震震例的情况,并以此验证据以往震例总结出的预报公式。验证的结果与实际符合较好。另外,文中指出了该手段的主要优点及克服其缺点的可能途径,即有些台站可采用地磁等变线差值法处理。     

ARCGIS‐SWAT: A GEODATA MODEL AND GIS INTERFACE FOR SWAT1

This paper presents ArcGIS‐SWAT, a geodata model and geographic information system (GIS) interface for the Soil and Water Assessment Tool (SWAT). The ArcGIS‐SWAT data model is a system of geodatabases that store SWAT geographic, numeric, and text input data and results in an organized fashion. Thus, it is proposed that a single and comprehensive geodatabase be used as the repository of a SWAT simulation. The ArcGIS‐SWAT interface uses programming objects that conform to the Component Object Model (COM) design standard, which facilitate the use of functionality of other Windows‐based applications within ArcGIS‐SWAT. In particular, the use of MS Excel and MATLAB functionality for data analysis and visualization of results is demonstrated. Likewise, it is proposed to conduct hydrologic model integration through the sharing of information with a not‐model‐specific hub data model where information common to different models can be stored and from which it can be retrieved. As an example, it is demonstrated how the Hydrologic Modeling System (HMS) ‐ a computer application for flood analysis ‐ can use information originally developed by ArcGIS‐SWAT for SWAT. The application of ArcGIS‐SWAT to the Seco Creek watershed in Texas is presented.