Magnitude Of Streamflow Research Articles

Accurate Computation of a Streamflow Drought Index

In this study, the authors investigated an approach to calculate the standardized streamflow index (SSI), which allows accurate spatial and temporal comparison of the hydrological conditions of a stream or set of streams. For this purpose, the capability of six three-parameter distributions (lognormal, Pearson Type III, log-logistic, general extreme value, generalized Pareto, and Weibull) and two different approaches to select the most suitable distribution the best monthly fit (BMF) and the minimum orthogonal distance (MD), were tested by using a monthly streamflow data set for the Ebro Basin (Spain). This large Mediterranean basin is characterized by high variability in the magnitude of streamflows and in seasonal regimes. The results show that the most commonly used probability distributions for flow frequency analysis provided good fits to the streamflow series. Thus, the visual inspection of the L-moment diagrams and the results of the Kolmogorov-Smirnov test did not enable the selection of a single optimum probability distribution. However, no single probability distribution for all the series was suitable for obtaining a robust standardized streamflow series because each of the distributions had one or more limitations. The BMF and MD approaches improved the results in the expected average, standard deviation, and the frequencies of extreme events of the SSI series in relation to the selection of a unique distribution for each station. The BMF and MD approaches involved using different probability distributions for each gauging station and month of the year to calculate the SSI. Both approaches are easy to apply and they provide very similar results in the quality of the obtained hydrological drought indexes. The proposed procedures are very flexible for analyses involving contrasting hydrological regimes and flow characteristics.

Channel response in a semiarid stream to removal of tamarisk and Russian olive

We report observed short‐term (3 years) channel adjustment in an incised, semiarid stream to the removal of invasive plants, tamarisk (Tamarix spp.) and Russian olive (Elaeagnus angustifolia) by (1) removing the above‐ground portion of the plant (cut‐stump method) and (2) removing the entire plant (whole‐plant method). The stream flows through Canyon de Chelly National Monument in Arizona, USA., draining an ∼1500 km2 catchment. Average channel width is 13 m; average thalweg depth is 2–3 m, although channel banks exceed 8 m locally. Channels adjusted primarily through widening, with significantly larger changes occurring in whole‐plant removal reaches; however, neither plant removal method elicited large‐scale bank destabilization, and the channels remained entrenched. Particular site conditions limiting large‐scale destabilization include the absence of sufficient streamflow magnitudes, the presence of clay layers at the bank toe, the remaining presence of native vegetation, and the entrenched morphology. Our findings serve as a cautionary note regarding the temporal and spatial variability in channel response to invasive plant removal and underscore the importance of considering site‐specific conditions in future restoration projects that include invasive plant removal.

Modeling hydrologic and water quality extremes in a changing climate: A statistical approach based on extreme value theory

Although information about climate change and its implications is becoming increasingly available to water utility managers, additional tools are needed to translate this information into secondary products useful for local assessments. The anticipated intensification of the hydrologic cycle makes quantifying changes to hydrologic extremes, as well as associated water quality effects, of particular concern. To this end, this paper focuses on using extreme value statistics to describe maximum monthly flow distributions at a given site, where the nonstationarity is derived from concurrent climate information. From these statistics, flow quantiles are reconstructed over the historic record and then projected to 2100. This paper extends this analysis to an associated source water quality impact, whereby the corresponding risk of exceeding a water quality threshold is examined. The approach is applied to a drinking water source in the Pacific Northwest United States that has experienced elevated turbidity values correlated with high streamflow. Results demonstrate that based on climate change information from the most recent Intergovernmental Panel on Climate Change assessment report, the variability and magnitude of extreme streamflows substantially increase over the 21st century. Consequently, the likelihood of a turbidity exceedance increases, as do the associated relative costs. The framework is general and could be applied to estimate extreme streamflow under climate change at other locations, with straightforward extensions to other water quality variables that depend on extreme hydroclimate.

Alteration of streamflow magnitudes and potential ecological consequences: a multiregional assessment

Human impacts on watershed hydrology are widespread in the US, but the prevalence and severity of stream‐flow alteration and its potential ecological consequences have not been quantified on a national scale. We assessed streamflow alteration at 2888 streamflow monitoring sites throughout the conterminous US. The magnitudes of mean annual (1980–2007) minimum and maximum streamflows were found to have been altered in 86% of assessed streams. The occurrence, type, and severity of streamflow alteration differed markedly between arid and wet climates. Biological assessments conducted on a subset of these streams showed that, relative to eight chemical and physical covariates, diminished flow magnitudes were the primary predictors of biological integrity for fish and macroinvertebrate communities. In addition, the likelihood of biological impairment doubled with increasing severity of diminished streamflows. Among streams with diminished flow magnitudes, increasingly common fish and macroinvertebrate taxa possessed traits characteristic of lake or pond habitats, including a preference for fine‐grained substrates and slow‐moving currents, as well as the ability to temporarily leave the aquatic environment.

High-resolution streamflow trend analysis applicable to annual decision calendars: a western United States case study

Changes in the seasonality of streamflow in the western United States have important implications for water resources management and the wellbeing of coupled human-natural systems. An assessment of changes in the timing and magnitude of streamflow resolved at fine time scales (days to weeks and seasons) is highly relevant to adaptive management strategies that are responsive to changing hydrologic baselines. In this paper, we present a regional analysis of the changes in streamflow seasonality through a broad classification of streams and quantification of increases and decreases in flow, based on a quantile regression methodology. This analysis affords a useful research product to examine the diversity of trends across seasons for individual streams. The trend analysis methodology can identify windows of change, thus revealing vulnerabilities within decision calendars and species lifecycles, an important consideration for adaptation and mitigation efforts.

Hydro‐climatic variability and trends in Washington State for the last 50 years

AbstractHistorical records of monthly streamflow and precipitation coupled with mean, minimum, and maximum air temperatures for Washington State were used to study the variation and the trend characteristics that occurred over the last 50 years (1952–2002). Results indicate that the 1967 statewide water resource assessment needs to be updated because all of the stations used in that study exhibited a decreasing trend in annual streamflow ranging from −0·9% to −49·3%, with an arithmetic mean of −11·7% and a median value of −9·8%. Furthermore, a slightly decreasing trend in annual streamflow, although not statistically significant, was detected. The decreasing streamflow magnitude was about −1·178 mm year−2, or 4·88 m3 s−1 year−1, which caused a decrease in annual streamflow in the state of about 58·9 mm, or 244 m3 s−1. This magnitude was about 9·6% of the average annual streamflow for the entire state from 1952 to 2002. Contrastingly, the overall annual precipitation in the entire state increased 1·375 mm year−2. Overall the annual means of daily mean, maximum, and minimum temperature increased by 0·122, 0·048, and 0·185 °C/10 years, respectively, during the study period. Thus the corresponding annual means of daily mean, maximum, and minimum temperatures increased by 0·61, 0·24, and 0·93 °C, respectively. All of these trends and magnitudes were found to vary considerably from station to station and month to month. The possible reasons resulting in these detected trends include, but are not limited to, human activities, climate variability and changes, and land use and land cover changes. Copyright © 2009 John Wiley & Sons, Ltd.

Evaluation of ensemble‐based distributed hydrologic model response with disaggregated precipitation products

The disaggregation of coarse precipitation products is desirable for spatially distributed hydrological applications where high‐resolution rainfall fields are required. In this study, we generate an ensemble of satellite‐based precipitation estimates using a spatiotemporal disaggregation framework for use in a spatially explicit hydrologic model. The framework effectively reproduced small, localized storm events using coarse precipitation estimates while simultaneously including known error characteristics into the precipitation fields. Ensemble precipitation inputs were propagated through a distributed hydrologic model to evaluate the impact on simulated hydrologic states and fluxes, such as streamflow, soil moisture content, and evapotranspiration. The disaggregation framework adds utility to the coarse satellite precipitation measurements by inducing a realistic hydrologic response in a manner similar to high‐resolution ground‐based radar observations. Errors introduced in the precipitation ensembles, namely, the overestimation of high‐intensity, short‐duration storm events, were tracked through the hydrological system, and physical mechanisms for the soil moisture and streamflow uncertainty are discussed. It was found that increases in streamflow magnitude and decreases in catchment area resulted in increased ensemble streamflow dispersion. In addition, precipitation uncertainty affected soil moisture predictions with more pronounced ensemble dispersion near the surface. Finally, spatial ensemble statistics were used to assess the precipitation and topographic control over soil moisture statistics in the study catchment.

Estimates of Canadian Arctic Archipelago runoff from observed hydrometric data

Summary Small basin studies in the remote Canadian Arctic Archipelago have revealed the general nature of runoff processes and the annual rhythms and magnitude of streamflow in the region, but widespread monitoring of hydrological cycle components is absent. The result is that an understanding of large scale freshwater fluxes from the Arctic Archipelago does not exist. Such understanding is important for sound domestic water management decisions and international obligations to quantify Canada’s freshwater supply to the oceans. The study summarized by this paper, initiated under the auspices of the International Polar Year, extrapolated observed streamflow attributes across the Arctic Archipelago using statistical regionalization tools. The paucity of hydrometric data necessitated the construction of a dataset, which was limited to the period from 1972 to 1994. Reliable estimates of mean May–October freshwater flux were possible from ∼70% of the Archipelago and these total ∼190 km 3 . Maximum daily runoff can be up to 13% of the total annual flux from some catchments. Flows were highest from southern Baffin Island, decreasing westward. The scarcity of data compelled an error analysis that showed average confidence intervals around constructed and regionalized data of ±123% and ±63%, respectively. Dataset construction errors were inversely related to basin area. There was no spatial pattern to the dataset construction errors, but regionalization error tended to be higher in the west. It will be argued that our community has little to no idea of the current freshwater flux from the Arctic Archipelago, or if it is changing. Much work is needed to improve these estimates, including establishing a sustainable, effective and efficient monitoring and research program of high arctic freshwater systems that can build upon the legacy of the International Polar Year.

Hydrologic comparison between a forested and a wetland/lake dominated watershed using SWAT

AbstractThe Soil and Water Assessment Tool (SWAT) is a physically‐based hydrologic model developed for agricultural watersheds, which has been infrequently validated for forested watersheds, particularly those with deep overwinter snow accumulation and abundant lakes and wetlands. The goal of this study was to determine the applicability of SWAT for modelling streamflow in two watersheds of the Ontonagon River basin of northern Michigan which differ in proportion of wetland and lake area. The forest‐dominated East Branch watershed contains 17% wetland and lake area, whereas the wetland/lake‐dominated Middle Branch watershed contains 26% wetland and lake area. The specific objectives were to: (1) calibrate and validate SWAT models for the East Branch and Middle Branch watersheds to simulate monthly stream flow, and (2) compare the effects of wetland and lake abundance on the magnitude and timing of streamflow. Model calibration and validation was satisfactory, as determined by deviation of discharge D and Nash and Sutcliffe coefficient values E that compared simulated monthly mean discharge versus measured monthly mean discharge. Streamflow simulation discrepancies occurred during summer and fall months and dry years. Several snow melting parameters were found to be critical for the SWAT simulation: TIMP (snow temperature lag factor) and SMFMX and SMFMN (melting factors). Snow melting parameters were not transferable between adjacent watersheds. Differences in seasonal pattern of long‐term monthly streamflow were found, with the forest‐dominated watershed having a higher peak flow during April but a lower flow during the remainder of the year in comparison to the wetland and lake‐dominated watershed. The results suggested that a greater proportion of wetland and lake area increases the capacity of a watershed to impound surface runoff and to delay storm and snow melting events. Representation of wetlands and lakes in a watershed model is required to simulate monthly stream flow in a wetland/lake‐dominated watershed. Copyright © 2007 John Wiley & Sons, Ltd.

Sand deposition in shoreline eddies along five Wild and Scenic Rivers, Idaho

AbstractSand bars deposited along the lateral margin of a river channel are frequently a focus of recreational activities. Sand bars are appealing sites on which to camp, picnic, fish and relax because they are relatively flat, soft, non‐cohesive sand, free of vegetation and near the water's edge. The lack of vegetation and cohesion make sand bars easily erodible. Without appreciable deposition of new material, number and size of bars through a given reach of river will decline substantially over a period of years. We studied 63 beaches and their associated eddies located throughout 10 selected reaches within the designated Wild and Scenic River sections of the Lochsa, Selway, Middle Fork Clearwater, Middle Fork Salmon and Salmon Rivers in Idaho to determine the relation of beaches to the frequency and magnitude of streamflows that deposit appreciable quantities of sand. At present, these rivers have been altered little, if at all, by flow regulation, and only the Salmon River has substantial diversion upstream of a study reach. The river reaches studied have an abundance of sand bar beaches of appreciable size, in spite of suspended sand concentrations that rarely exceeded a few hundred milligrams per litre even during the largest floods.Calculated mean annual rates of deposition in an eddy vary from 5.8 to more than 100 cm depending primarily on: (1) the duration of streamflows that inundate the eddy sand bar depositions; (2) the rate of the flow exchange between the channel and an eddy and (3) the concentrations of suspended sand in the primary channel. The annual thickness of sand deposition in an eddy varies greatly from year to year depending on the duration of relatively large streamflows. Maximum annual sand depositions in an eddy are three to nine times the estimated long‐term mean values. Relatively large, sustained floods deposit an appreciable portion of total deposition over a period of years. For the period of record, 1930–2002, the seven largest annual depositions, which represent more than 40% of all material deposited over the Lochsa River 21.9 km eddy, occurred in the years with the seven largest instantaneous annual peak floods. Beach area and volume for most beaches, however, are less variable year‐to‐year than the variation in annual deposition would indicate. Accumulative 10‐year weighed deposition rate was computed to estimate the effective variability of beach deposition. Although less variable than the annual deposition, the cumulative 10‐year deposition calculated for the longest hydrologic records, 71 years, existing on the Idaho Wild and Scenic Rivers varied by more than an order of magnitude from less than 20 cm to more than 220 cm. Published in 2006 by John Wiley & Sons, Ltd.

Upper versus lower Colorado River sub‐basin streamflow: characteristics, runoff estimation and model simulation

AbstractStreamflow in the upper Colorado River in the western USA is always snowmelt dominated, whereas the lower river's perennial streamflows are snowmelt dominated only 50% of the time. The magnitude and timing of peak flows is important for water resources management. In the upper basin the annual maximum daily discharge usually occurs in May or June, and in the lower basin this peak is observed to occur in any month except May or June. The timing of one‐half of the specific runoff is used as a second measure of the variability in timing and magnitude of streamflows. For the upper basin, nine watersheds are used to illustrate streamflow trends, with the Yampa River used as a sample sub‐basin. For the lower basin, five watersheds are used, of which Salt River is used as sample sub‐basin. The differences in monthly flow variation over 20‐year time periods (1920–1939, 1940–1959, 1960–1979, and 1980–1999) are substantial for the Salt River but not for the Yampa River.Three model types were used to estimate streamflow characteristics. An autocorrelation model was used to generate winter specific runoffs, which were more reasonable for the Yampa River than the Salt River. A regression between snow water equivalent (SWE) and winter specific runoff showed a good correlation for the two sub‐basins. A weaker relationship exists between SWE and non‐winter flows for the sample lower basin watershed. Streamflow was simulated relatively well using the Precipitation Runoff Modeling System hydrological model. Copyright © 2006 John Wiley & Sons, Ltd.

Emergence Cues Of A Mayfly In A High-Altitude Stream Ecosystem: Potential Response To Climate Change

To understand the consequences of human accelerated environmental change, it is important to document the effects on natural populations of an increasing frequency of extreme climatic events. In stream ecosystems, recent climate change has resulted in extreme variation in both thermal and hydrological regimes. From 2001 to 2004, a severe drought in western United States corresponded with earlier emergence of the adult stage of the high-altitude stream mayfly, Baetis bicaudatus. Using a long-term database from a western Colorado stream, the peak emergence date of this mayfly population was predicted by both the magnitude and date of peak stream flow, and by the mean daily water temperature, suggesting that Baetis may respond to declining stream flow or increasing water temperature as proximate cues for early metamorphosis. However, in a one-year survey of multiple streams from the same drainage basin, only water temperature predicted spatial variation in the onset of emergence of this mayfly. To decouple the effects of temperature and flow, we separately manipulated these factors in flow-through microcosms and measured the timing of B. bicaudatus metamorphosis to the adult stage. Mayflies emerged sooner in a warmed-water treatment than an ambient-water treatment; but reducing flow did not accelerate the onset of mayfly emergence. Nonetheless, using warming temperatures to cue metamorphosis enables mayflies to time their emergence during the descending limb of the hydrograph when oviposition sites (protruding rocks) are becoming available. We speculate that large-scale climate changes involving warming and stream drying could cause significant shifts in the timing of mayfly metamorphosis, thereby having negative effects on populations that play an important role in stream ecosystems.

Long‐lead probabilistic forecasting of streamflow using ocean‐atmospheric and hydrological predictors

A geostatistically based approach with a local regression method is used to predict the magnitude of seasonal streamflow using ocean‐atmospheric signals and the hydrological condition of a basin as predictors. The model characterizes the stochastic behavior of a forecast variable by generating a conditional distribution of the predicted value for different hydroclimatic conditions. The correlation structure between dependent and independent variables is represented by the variography of the predicted values in which the distance variable in the variogram is determined by measuring the distance between the predictors. This variogram in a virtual field constructed from the predictors makes it possible to predict variables as unmeasured points while considering historic information as measurement points of the field. Different types of kriging, as well as a generalized linear model regression, are used to predict data in interpolation and extrapolation modes. The forecast skill is evaluated using a linear error in probability space score for different combinations of predictors and different kriging methods. The method is applied to a case study of the Zayandeh‐rud River in Isfahan, Iran. The utility of the method is demonstrated for forecasting autumn‐winter and spring streamflow using the Southern Oscillation Index, the North Atlantic Oscillation, serial correlation between seasonal streamflow series, and the snow budget. The study analyzes the application of the proposed method in comparison with a K‐nearest neighbor regression method. The results of this study show that the proposed method can significantly improve the long‐lead probabilistic forecast skill for a nonlinear relationship between hydroclimatic predictors and streamflow in a region.

Flow categorization model for improving forecasting

Prediction of high magnitude flows is of interest in many hydrological applications such as operation of flood control reservoirs, flood forecasting and gated spillways. Of the various types of existing streamflow prediction approaches, data driven models (such as ANN) are increasingly being preferred over the traditional conceptual models due to their simplicity, fast speed and ease of use. For models that consider only historical streamflow data, an attempt has been made to design a robust model over a wide range of streamflow magnitudes. The model inputs are the immediate past streamflow data which generally do not predict the typically high flows well, particularly for large lead times. In this study, the flow range is divided into three regions (low, medium and high flow regions) and the attributes are decided based on the underlying hydrological process of the flow region. A flow forecasting model is applied for each flow region, using only the historical streamflow data as input. The proposed approach is implemented in Tryggevælde Catchment (Denmark) for 1- and 3-lead days, using the Support Vector Machine (SVM), which yields promising results, particularly for high flows in a 3-lead day model.

Autumn synoptic conditions and rainfall in the subarctic Canadian Shield of the Northwest Territories, Canada

Autumn precipitation is important to the annual water budget and spring streamflow magnitude in the subarctic Canadian Shield portion of the Mackenzie Basin in northwestern Canada. The objective of this study is to improve understanding of the synoptic mechanisms generating this autumn precipitation by investigating a wet (1998) and a dry (1999) autumn over a portion of this region north of Great Slave Lake. Seven synoptic map patterns were identified using a hybrid manual–revised Kirchhofer correlation methodology. Cyclones were found to be the most important map pattern providing autumn rainfall. These cyclones tend to occur 2 to 3 days following the presence of a low in the Gulf of Alaska near the Aleutian Islands. The results of this study corroborate past research that shows Pacific atmospheric moisture transported inland provides the source for much of the cyclonic rainfall in the Mackenzie Basin. Aleutian lows, which encourage this transportation, were as common in 1998 as in 1999, but the mechanisms necessary to transfer moisture to the North Great Slave region were more entrenched in 1998 than in 1999. Winds along storm tracks through the region were weaker and more dispersed in 1999. In addition, conditions for cyclogenesis in the region were less favourable in 1999. Copyright © 2005 Royal Meteorological Society

Regional flow-duration curves: reliability for ungauged basins

A flow-duration curve (FDC) illustrates the relationship between the frequency and magnitude of streamflow. Applications of FDC are of interest for many hydrological problems related to hydropower generation, river and reservoir sedimentation, water quality assessment, water-use assessment, water allocation and habitat suitability. This study addresses the problem of FDC estimation for ungauged river basins, assessing the effectiveness and reliability of several regional approaches. The study refers to a wide region of eastern central Italy and adopts a jack-knife cross-validation procedure to evaluate the uncertainty of regional FDC’s, comparing it with the uncertainty of empirical FDC’s constructed from short samples of streamflow data. The results (a) provide an evaluation of the reliability of the regional FDC’s for ungauged sites, (b) show that the reliability of the three best performing regional models are similar to one another, and (c) demonstrate that empirical FDC’s based on limited data samples generally provide a better fit of the long-term FDC’s than regional FDC’s.

IMPACTS OF CALIFORNIA'S CLIMATIC REGIMES AND COASTAL LAND USE CHANGE ON STREAMFLOW CHARACTERISTICS1

ABSTRACT: To investigate the impacts of urbanization and climatic fluctuations on stream flow magnitude and variability in a Mediterranean climate, the HEC‐HMS rainfall/runoff model is used to simulate stream flow for a 14‐year period (October 1, 1988, to September 30, 2002) in the Atascadero Creek watershed located along the southern coast of California for 1929, 1998, and 2050 (estimated) land use conditions (8, 38 and 52 percent urban, respectively). The 14‐year period experienced a range of climatic conditions caused mainly by El Nino‐Southern Oscillation variations. A geographic information system is used to delineate the watershed and parameterize the model, which is calibrated using data from two stream flow and eight rainfall gauges. Urbanization is shown to increase peak discharges and runoff volume while decreasing stream flow variability. In all cases, the annual and 14‐year distributions of stream flow are shown to be highly skewed, with the annual maximum 24 hours of discharge accounting for 22 to 52 percent of the annual runoff and the maximum ten days of discharge from an average El Nino year producing 10 to 15 percent of the total 14‐year discharge. For the entire period of urbanization (1929 to 2050), the average increase in annual maximum discharges and runoff was 45 m3/s (300 percent) and 15 cm (350 percent), respectively. Additionally, the projected increase in urbanization from 1998 to 2050 is half the increase from 1929 to 1998; however, increases in runoff (22 m3/s and 7 cm) are similar for both scenarios because of the region's spatial development pattern.

Verification of National Weather Service Ensemble Streamflow Predictions for Water Supply Forecasting in the Colorado River Basin

The Ensemble Streamflow Prediction (ESP) system, developed by the National Weather Service (NWS), uses conceptual hydrologic models and historical data to generate a set, or ensemble, of possible streamflow scenarios conditioned on the initial states of a given basin. Using this approach, simulated historical probabilistic forecasts were generated for 14 forecast points in the Colorado River basin, and the statistical properties of the ensembles were evaluated. The median forecast traces were analyzed using “traditional” verification measures; these forecasts represented “deterministic ESP forecasts.” The minimum-error and historical traces were examined to evaluate the median forecasts and the forecast system. Distribution-oriented verification measures were used to analyze the probabilistic information contained in the entire forecast ensemble. Using a single-trace prediction, for example, the median, resulted in a loss of valuable uncertainty information about predicted seasonal volumes that is provided by the entire ensemble. The minimum-error and historical traces revealed that there are errors in the data, calibration, and models, which are part of the uncertainty provided by the probabilistic forecasts, but are not considered in the median forecast. The simulated ESP forecasts more accurately predicted future streamflow than climatology forecasts and, on average, provided useful information about the likelihood of future streamflow magnitude with a lead time of up to 7 months. Overall, the forecast provided stronger probability statements and became more reliable at shorter lead times. The distribution-oriented verification approach was shown to be applicable to ESP outlooks and appropriate for extracting detailed performance information, although interpretation of the results is complicated by inadequate sample sizes.

Forecasting monthly streamflow dynamics in the western United States: a nonlinear dynamical approach

An attempt is made in the present study to understand the dynamics of monthly streamflow in the western United States from a nonlinear dynamical perspective. For this purpose, streamflow data observed at 79 stations across 11 states in the western United States are analyzed. A nonlinear prediction method with a local approximation approach is employed. The method uses the concept of phase-space reconstruction to represent the underlying dynamics, i.e. reconstruction of the single-dimensional (or variable) streamflow series in a multi-dimensional phase-space. The analysis is carried out by grouping the 79 stations under three categories, on the basis of the magnitude of (mean) streamflow, as: (1) low-flow stations, having mean streamflow values less than 2.832 m 3/s; (2) high-flow stations, having mean streamflow values more than 28.32 m 3/s; and (3) medium-flow stations, having mean streamflow values between 2.832 and 28.32 m 3/s. Detailed analyses and results are presented only for three stations, selected to represent the low-flow, medium-flow, and high-flow categories, respectively. The results indicate that the local approximation prediction approach yields, in general, reasonably good predictions of streamflow dynamics irrespective of the flow regime, but the predictions for the low-flow stations are found to be relatively better than that obtained for the medium-flow and high-flow stations. These results seem to suggest the possible presence of chaotic behavior in the monthly streamflow dynamics in the western United States. Studies to verify and support the present results are underway.

Streamflow response of mixed-species eucalypt forests to patch cutting and thinning treatments

An 11-year paired-catchment study was implemented to assess the effect of differing logging practices on streamflow in mixed-species eucalypt forest at Tantawangalo Creek, southeastern Australia. Following a 3-year calibration period, Ceb catchment was retained as a control, Wicksend catchment was patch-cut to remove 22% of basal area, and Willbob catchment was thinned to remove 12% of basal area. The treatments resulted in an initial increase in monthly total streamflow and baseflow at both treated catchments. In annual terms, total streamflow increased by 10% in the first 3 years after logging at Wicksend, and by 31% for the first 4 years at Willbob, despite the difference in basal area removed. Streamflow then returned to pre-treatment levels for 1 year and subsequently declined by 20% below pre-treatment levels over the next 4 years at Wicksend. Willbob displayed a return to, but not below, pre-treatment levels over the same period. Although there were some large post-treatment stormflows, changes in baseflows were largely responsible for the streamflow increases, and at Wicksend, explained the streamflow decreases in the latter observation period. Differences in regeneration densities between the treated catchments indicate the greater magnitude and persistence of flow increases at Willbob were due to poor regeneration following the thinning treatment, while dense and vigorous under- and overstorey regeneration dampened initial flow increases and facilitated significant decreases at Wicksend. Significant streamflow decreases after disturbance have not been widely reported for mixed-species eucalypt forests, and the magnitude of streamflow increases after only 12% basal area removal at Willbob is unusual.