148 resultados para streamflow


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EXTRACT (SEE PDF FOR FULL ABSTRACT): Four broad regions of the western United States within which annual streamflows exhibit strong spatial coherence are identified using principal component analysis with a varimax rotation. Geographically, the four regions encompass the Pacific Northwest, Far West-Great Basin, Central Rockies-High Plains, and Northern Great Plains. These regions are really consistent with previously documented, descriptively derived streamflow regimes as well as with general atmospheric circulation and precipitation modes of variation. Collectively, the four regional components account for nearly 63 percent of the total annual variation in western U.S. streamflow. The time history of most principal component patterns exhibit little or no persistence.

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EXTRACT (SEE PDF FOR FULL ABSTRACT): The annual cycle and non-seasonal variability of streamflow over a network of stations in western North America and Hawaii is studied in terms of atmospheric forcing elements. The phase lag between the annual cycle of streamflow and precipitation varies considerably over this network, as does the persistence of monthly streamflow anomalies. This lag effect appears to be largely a function of the relative amount of snow laid down in a particular basin. In addition to the rather strong annual cycle that exists in mean streamflow and its variance at most of the stations, there is also a distinct annual cycle in the autocorrelation of streamflow anomalies that is related to the interplay between the temperature and precipitation annual cycles; of particular importance is the existence of stored water in the form of a snow pack.

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EXTRACT (SEE PDF FOR FULL ABSTRACT): Streamflow values show definite seasonal patterns in their month-to-month correlation structure. The structure also seems to vary as a function of the type of stream (coastal versus mountain or humid versus arid region). The standard autoregressive moving average (ARMA) time series model is incapable of reproducing this correlation structure. ... A periodic ARMA time series model is one in which an ARMA model is fitted to each month or season but the parameters of the model are constrained to be periodic according to a Fourier series. This constraint greatly reduces the number of parameters but still leaves the flexibility for matching the seasonally varying correlograms.

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Linear regression models are constructed to predict seasonal runoff by fitting streamflow to temperature, precipitation, and snow water content across a range of elevations. The models are quite successful in capturing the differences in discharge between different elevation watersheds and their interannual variations. This exercise thus provides insight into seasonal changes in streamflow at different elevation watersheds that might occur under a changed climate.

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EXTRACT (SEE PDF FOR FULL ABSTRACT): The high index phase of the Southern Oscillation (SO), La Niña, has not been given as much attention as its counterpart, the low index phase of the SO, El Niño. One reason may be related to the fact that many similarities exist among El Niño events but not among La Niña events. ... In this study, we focus on the influences of La Niña phenomena on streamflow anomalies ... to explore the SO-related signal over the United States.

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Precipitation is a difficult variable to understand and predict. In this study, monthly precipitation in California is divided into two classes according to the monthly temperature to better diagnose the atmospheric circulation that causes precipitation, and to illustrate how temperature compounds the precipitation to runoff process.

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This study investigates the extent of the affect [sic] of the El Niño/Southern Oscillation on South American streamflow. The response of South American precipitation and temperature to the extreme phases of ENSO (El Niño and La Niña events) is well documented; but the response of South American hydrology has been barely studied. Such paucity of research contrasts sharply with that available on the response of North American streamflow to ENSO events.

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EXTRACT (SEE PDF FOR FULL ABSTRACT): We have analyzed streamflow variations recorded at 15 USGS gauging stations in California during the past 90 years or so. The anomalies (departures from the 1960-1990 mean discharge) of streamflow on annual-to-decadal time scales are strongly correlated with precipitation anomalies in each drainage basin. ... Although causes of the decadal climate (precipitation) variability are not known with certainty, the use of streamflow records may help us understand the relative strengths of moisture sources and shift of the jet stream in atmospheric circulation.

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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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A novel approach is proposed to estimate the natural streamflow regime of a river and to assess the extent of the alterations induced by dam operation related to anthropogenic (e.g., agricultural, hydropower) water uses in engineered river basins. The method consists in the comparison between the seasonal probability density function (pdf) of observed streamflows and the purportedly natural streamflow pdf obtained by a recently proposed and validated probabilistic model. The model employs a minimum of landscape and climate parameters and unequivocally separates the effects of anthropogenic regulations from those produced by hydroclimatic fluctuations. The approach is applied to evaluate the extent of the alterations of intra-annual streamflow variability in a highly engineered alpine catchment of north-eastern Italy, the Piave river. Streamflows observed downstream of the regulation devices in the Piave catchment are found to exhibit smaller means/modes, larger coefficients of variation, and more pronounced peaks than the flows that would be observed in the absence of anthropogenic regulation, suggesting that the anthropogenic disturbance leads to remarkable reductions of river flows, with an increase of the streamflow variability and of the frequency of preferential states far from the mean. Some structural limitations of management approaches based on minimum streamflow requirements (widely used to guide water policies) as opposed to criteria based on whole distributions are also discussed. Copyright © 2010 by the American Geophysical Union.

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Droughts tend to evolve slowly and affect large areas simultaneously, which suggests that improved understanding of spatial coherence of drought would enable better mitigation of drought impacts through enhanced monitoring and forecasting strategies. This study employs an up-to-date dataset of over 500 river flow time series from 11 European countries, along with a gridded precipitation dataset, to examine the spatial coherence of drought in Europe using regional indicators of precipitation and streamflow deficit. The drought indicators were generated for 24 homogeneous regions and, for selected regions, historical drought characteristics were corroborated with previous work. The spatial coherence of drought characteristics was then examined at a European scale. Historical droughts generally have distinctive signatures in their spatio-temporal development, so there was limited scope for using the evolution of historical events to inform forecasting. Rather, relationships were explored in time series of drought indicators between regions. Correlations were generally low, but multivariate analyses revealed broad continental-scale patterns, which appear to be related to large-scale atmospheric circulation indices (in particular, the North Atlantic Oscillation and the East Atlantic West Russia pattern). A novel methodology for forecasting was developed (and demonstrated with reference to the United Kingdom), which predicts drought from drought i.e. uses spatial coherence of drought to facilitate early warning of drought in a target region, from drought which is developing elsewhere in Europe.Whilst the skill of the methodology is relatively modest at present, this approach presents a potential new avenue for forecasting, which offers significant advantages in that it allows prediction for all seasons, and also shows some potential for forecasting the termination of drought conditions.

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Due to the increase in water demand and hydropower energy, it is getting more important to operate hydraulic structures in an efficient manner while sustaining multiple demands. Especially, companies, governmental agencies, consultant offices require effective, practical integrated tools and decision support frameworks to operate reservoirs, cascades of run-of-river plants and related elements such as canals by merging hydrological and reservoir simulation/optimization models with various numerical weather predictions, radar and satellite data. The model performance is highly related with the streamflow forecast, related uncertainty and its consideration in the decision making. While deterministic weather predictions and its corresponding streamflow forecasts directly restrict the manager to single deterministic trajectories, probabilistic forecasts can be a key solution by including uncertainty in flow forecast scenarios for dam operation. The objective of this study is to compare deterministic and probabilistic streamflow forecasts on an earlier developed basin/reservoir model for short term reservoir management. The study is applied to the Yuvacık Reservoir and its upstream basin which is the main water supply of Kocaeli City located in the northwestern part of Turkey. The reservoir represents a typical example by its limited capacity, downstream channel restrictions and high snowmelt potential. Mesoscale Model 5 and Ensemble Prediction System data are used as a main input and the flow forecasts are done for 2012 year using HEC-HMS. Hydrometeorological rule-based reservoir simulation model is accomplished with HEC-ResSim and integrated with forecasts. Since EPS based hydrological model produce a large number of equal probable scenarios, it will indicate how uncertainty spreads in the future. Thus, it will provide risk ranges in terms of spillway discharges and reservoir level for operator when it is compared with deterministic approach. The framework is fully data driven, applicable, useful to the profession and the knowledge can be transferred to other similar reservoir systems.