ERRORS RELATED TO RANDOM STREAM TEMPERATURE DATA COLLECTION IN UPPER MISSISSIPPI RIVER WATERSHED1

ABSTRACT: Records of hourly water temperatures for two streams in the Upper Mississippi River basin were used to find the error between instantaneous measurements of stream water temperatures and true daily averages. The instantaneous summer water temperature measurements were assumed to be collected during daylight hours, and measurement times were selected randomly. The absolute error at the 95 percent confidence level of randomly collected stream water temperatures was less than 0.9°C for a 1 to 5m deep large river, but as large as 3.6°C for a 0.3 to lm deep small stream. Temperature readings of morning samples were usually below daily average values, and afternoon readings were usually above. Daily mean water temperatures were obtained with less than 0.23°C standard deviation from true daily averages if the daily maximum and minimum water temperatures were averaged. Sample results were obtained for the open water (summer) season only, since diurnal water temperature fluctuations in ice covered streams are usually negligible.     

Comparison of two stream temperature models and evaluation of potential management alternatives for the Speed River, Southern Ontario

Concerns over increased water temperature of the Speed River as it flows through the City of Guelph in Southern Ontario and an observed relationship between summer stream temperatures and low dissolved oxygen levels in the river prompted an investigation into potential stream temperature management practices. Two mechanistic stream temperature models, SNTEMP and CE-QUAL-W2, were applied to the Speed River in order to gauge the effectiveness of various stream temperature management options. Calibrated versions of both models performed well (0.2 degrees C相似文献   

ESTIMATING AVERAGE MONTHLY LAKE EVAPORATION IN THE NORTHEAST UNITED STATES1

ABSTRACT: A methodology to estimate the average monthly lake evaporation, E(τ), (month τ=1,12) for fresh water bodies located in the northeast United States is presented. The approach combines analysis of at‐site, lake‐specific vertical water temperature profile data and a previously developed regional air temperature based model approximation of the widely accepted modified Penman energy budget estimate of mean monthly potential evaporation, E_p(τ) (mm/day). The paper presents procedures to develop site‐specific estimates of E_p(τ) and to convert water temperature data to average monthly conductive heat flux, G(τ). With monthly estimates of G(τ), the average monthly potential evaporation, E_p(τ), is then convertible to estimates of the average monthly lake evaporation, E(τ). This new method permits a good estimate of site‐specific lake evaporation rates without the data and computational requirements of the Penman energy budget procedure nor the comparatively expensive, time consuming field eddy correlation approach.     

KALMAN FILTER CALCULATION OF SAMPLING FREQUENCY WHEN DETERMINING ANNUAL MEAN SOLUTE CONCENTRATIONS

ABSTRACT: A linear filter (Kalman filter) technique was used with a Streamflow-concentration model the minimize surface water quality sampling frequencies when determining annual mean solute concentrations with a predetermined allowable error. The Kalman filter technique used the stream discharge interval as a replacement for the more commonly used time interval. Using filter computations, the measurement error variance was minimized within the sample size constraints. The Kalman filter application proposed here is applicable only under several conditions including: monitoring is solely to estimate annual mean concentration; discharge measurement errors are negligible; the Streamflow-concentration model is valid; and monthly samples reflect the total variance of the solute in question.     

HYDROLOGIC LANDSCAPES ON THE DELMARVA PENINSULA PART 2: ESTIMATES OF BASE-FLOW NITROGEN LOAD TO CHESAPEAKE BAY1

ABSTRACT: Base-flow samples were collected from 47 sampling sites for four seasons from 1990–91 on the Delmarva Peninsula in Delaware and Maryland to relate stream chemistry to a “hydrologic landscape” and season. Two hydrologic landscapes were determined: (1) a well-drained landscape, characterized by a combination of a low percentage of forest cover, a low percentage of poorly drained soil, and elevated channel slope; and (2) poorly drained landscape, characterized by a combination of an elevated percentage of forest cover, an elevated percentage of poorly drained soil, and low channel slope. Concentrations of nitrogen were significantly related to the hydrologic landscape. Nitrogen concentrations tended to be higher in well-drained landscapes than in poorly drained ones. The highest instantaneous nitrogen yields occurred in well-drained landscapes during the winter. These yields were extrapolated over the part of the study area draining to Chesapeake Bay in order to provide a rough estimate of nitrogen load from base flow to the Bay and its estuarine tributaries. This estimate was compared to an estimate made by extrapolating from an existing long-term monitoring station. The load estimate from the stream survey data was 5 ± 10⁶ kg of N per year, which was about four times the estimate, made from the existing long-term monitoring station. The stream-survey estimate of base flow represents about 40 percent of the total nitrogen load that enters the Bay and estuarine tributaries from all sources in the study area.     

EVALUTING STREAM STANDARD VIOLATIONS USING A WATER QUALITY DATA BASE1

ABSTRACT: Cumulative density functions (c.d.f.'s) for water quality random variables may be estimated using data from a routine grab sampling program. The c.d.f. may then be used to estimate the probability that a single grab sample will violate a given stream standard and to determine the anticipated number of violations in a given number of samples. Confidence limits about a particular point on the c.d.f. may be used to reflect the accuracy with which the sample estimate represents the true c.d.f. Methods are presented here for calculating such confidence limits using both a normal model and a nonparametric model. Examples are presented to illustrate the usefulness of an estimated c.d.f. and associated confidence limits in assessing whether an observed number of standard violations is the result of natural variability or represents real degradation in water quality.     

Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States1

Preston, Stephen D., Richard B. Alexander, Gregory E. Schwarz, and Charles G. Crawford, 2011. Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States. Journal of the American Water Resources Association (JAWRA) 47(5):891‐915. DOI: 10.1111/j.1752‐1688.2011.00577.x Abstract: We compared the results of 12 recently calibrated regional SPARROW (SPAtially Referenced Regressions On Watershed attributes) models covering most of the continental United States to evaluate the consistency and regional differences in factors affecting stream nutrient loads. The models – 6 for total nitrogen and 6 for total phosphorus – all provide similar levels of prediction accuracy, but those for major river basins in the eastern half of the country were somewhat more accurate. The models simulate long‐term mean annual stream nutrient loads as a function of a wide range of known sources and climatic (precipitation, temperature), landscape (e.g., soils, geology), and aquatic factors affecting nutrient fate and transport. The results confirm the dominant effects of urban and agricultural sources on stream nutrient loads nationally and regionally, but reveal considerable spatial variability in the specific types of sources that control water quality. These include regional differences in the relative importance of different types of urban (municipal and industrial point vs. diffuse urban runoff) and agriculture (crop cultivation vs. animal waste) sources, as well as the effects of atmospheric deposition, mining, and background (e.g., soil phosphorus) sources on stream nutrients. Overall, we found that the SPARROW model results provide a consistent set of information for identifying the major sources and environmental factors affecting nutrient fate and transport in United States watersheds at regional and subregional scales.     

EFFECTS OF LAND USE AND TOPOGRAPHY ON SOME WATER QUALITY VARIABLES IN FORESTED EAST TEXAS1

ABSTRACT: Spatial variation of five water quality variables were analyzed using composite water samples collected periodically from eight small watersheds (11.4–71.6 km²) in forested East Texas during 1977 through 1980. Based on 31 observations during the four-year period the average yield of nitrate-nitrite nitrogen (NNN), total kjeldahl nitrogen (TKN), total phosphorus (PO4), chloride (CHL), and total suspended sediment (TSS) were 1.43, 21.96, 3.09, 50.11, and 90.39 ka/ha/yr, respectively. Compared to the water quality standards of the U.S. Environmental Protection Agency (1976) and the Texas Department of Water Resources (1976) for CHL, TSS, and NNN, none of the observations exceeded the limits for public water supplies. The study showed that forested watersheds normally yielded stream flow with better quality than that from agricultural watersheds. Watersheds of greater percent of pasture area, mean slope, stream segment frequency, and drainage density produced greater concentrations for these five chemical parameters in water samples. Meaningful equations were developed for estimating mean average yields for each chemical parameter for each watershed with R² ranging from 0.77 to 0.96 and standard error of estimates from 17 to 33 percent of the observed means.     

Modeling Variability and Trends in Pesticide Concentrations in Streams1

Abstract: A parametric regression model was developed for assessing the variability and long‐term trends in pesticide concentrations in streams. The dependent variable is the logarithm of pesticide concentration and the explanatory variables are a seasonal wave, which represents the seasonal variability of concentration in response to seasonal application rates; a streamflow anomaly, which is the deviation of concurrent daily streamflow from average conditions for the previous 30 days; and a trend, which represents long‐term (inter‐annual) changes in concentration. Application of the model to selected herbicides and insecticides in four diverse streams indicated the model is robust with respect to pesticide type, stream location, and the degree of censoring (proportion of nondetections). An automatic model fitting and selection procedure for the seasonal wave and trend components was found to perform well for the datasets analyzed. Artificial censoring scenarios were used in a Monte Carlo simulation analysis to show that the fitted trends were unbiased and the approximate p‐values were accurate for as few as 10 uncensored concentrations during a three‐year period, assuming a sampling frequency of 15 samples per year. Trend estimates for the full model were compared with a model without the streamflow anomaly and a model in which the seasonality was modeled using standard trigonometric functions, rather than seasonal application rates. Exclusion of the streamflow anomaly resulted in substantial increases in the mean‐squared error and decreases in power for detecting trends. Incorrectly modeling the seasonal structure of the concentration data resulted in substantial estimation bias and moderate increases in mean‐squared error and decreases in power.     

STREAM TEMPERATURE CORRELATIONS WITH AIR TEMPERATURES IN MINNESOTA: IMPLICATIONS FOR CLIMATE WARMING1

ABSTRACT: Air temperatures are sometimes used as easy substitutes for stream temperatures. To examine the errors associated with this substitution, linear relationships between 39 Minnesota stream water temperature records and associated air temperature records were analyzed. From the lumped data set (38,082 daily data pairs), equations were derived for daily, weekly, monthly, and annual mean temperatures. Standard deviations between all measured and predicted water temperatures were 3.5°C (daily), 2.6°C (weekly), 1.9°C (monthly), and 1.3°C (annual). Separate analyses for each stream gaging station gave substantially lower standard deviations. Weather monitoring stations were, on average, 37.5 km from the stream. The measured water temperatures follow the annual air temperature cycle closely. No time lags were taken into account, and periods of ice cover were excluded from the analysis. If atmospheric CO₂ doubles in the future, air temperatures in Minnesota are projected (CCC GCM) to rise by 4.3°C in the warm season (April-October). This would translate into an average 4.1°C stream temperature rise, provided that stream shading would remain unaltered.     

REGION OF INFLUENCE REGRESSION FOR ESTIMATING THE 50-YEAR FLOOD AT UNGAGED SITES1

ABSTRACT: Five methods of developing regional regression models to estimate flood characteristics at ungaged sites in Arkansas are examined. The methods differ in the manner in which the State is divided into subregions. Each successive method (A to E) is computationally more complex than the previous method. Method A makes no subdivision. Methods B and C define two and four geographic subregions, respectively. Method D uses cluster/discriminant analysis to define subregions on the basis of similarities in watershed characteristics. Method E, the new region of influence method, defines a unique subregion for each ungaged site. Split-sample results indicate that, in terms of root-mean-square error, method E (38 percent error) is best. Methods C and D (42 and 41 percent error) were in a virtual tie for second, and methods B (44 percent error) and A (49 percent error) were fourth and fifth best.     

AN EVAPORATION EQUATION FOR AN OPEN BODY OF WATER EXPOSED TO THE ATMOSPHERE1

ABSTRACT Evaporation is identified as having two additive components: natural evaporation in the absence of wind and forced evaporation in the presence of wind. An evaporation equation is obtained for an open body of water exposed at the atmosphere by conversion of standard horizontal flat plate heat transfer relationships to a mass transfer or evaporation equation. For an average air temperature of 68°F, the final equation for evaporative heat flux is A comparison of numerical values predicted by the above equation is made with evaporation equations deduced from field measurements, and the agreement is favorable. The major differences between this equation and those previously developed are: a) the above equation was derived strictly from standard heat transfer expressions, and b) a dependency of average fetch and air temperature (through transport properties) is shown. This approach establishes the correct dependencies of the field parameters so that future experimental measurements will have a sound theoretical basis.     

Non-Point-Source Impacts on Stream Nutrient Concentrations Along a Forest to Urban Gradient

We conducted statistical analyses of a 10-year record of stream nutrient and sediment concentrations for 17 streams in the greater Seattle region to determine the impact of urban non-point-source pollutants on stream water quality. These catchments are dominated by either urban (22–87%) or forest (6–73%) land cover, with no major nutrient point sources. Stream water phosphorus concentrations were moderately strongly (r²=0.58) correlated with catchment land-cover type, whereas nitrogen concentrations were weakly (r²=0.19) and nonsignificantly (at < 0.05) correlated with land cover. The most urban streams had, on average, 95% higher total phosphorus (TP) and 122% higher soluble reactive phosphorus (SRP) and 71% higher turbidity than the most forested streams. Nitrate (NO₃), ammonium (NH₄), and total suspended solids (TSS) concentrations did not vary significantly with land cover. These results suggest that urbanization markedly increased stream phosphorus concentrations and modestly increased nitrogen concentrations. However, nutrient concentrations in Seattle region urban streams are significantly less than those previously reported for agricultural area streams.     

A basin-scale approach to estimating stream temperatures of tributaries to the lower Klamath River, California

Stream temperature is an important component of salmonid habitat and is often above levels suitable for fish survival in the Lower Klamath River in northern California. The objective of this study was to provide boundary conditions for models that are assessing stream temperature on the main stem for the purpose of developing strategies to manage stream conditions using Total Maximum Daily Loads. For model input, hourly stream temperatures for 36 tributaries were estimated for 1 Jan. 2001 through 31 Oct. 2004. A basin-scale approach incorporating spatially distributed energy balance data was used to estimate the stream temperatures with measured air temperature and relative humidity data and simulated solar radiation, including topographic shading and corrections for cloudiness. Regression models were developed on the basis of available stream temperature data to predict temperatures for unmeasured periods of time and for unmeasured streams. The most significant factor in matching measured minimum and maximum stream temperatures was the seasonality of the estimate. Adding minimum and maximum air temperature to the regression model improved the estimate, and air temperature data over the region are available and easily distributed spatially. The addition of simulated solar radiation and vapor saturation deficit to the regression model significantly improved predictions of maximum stream temperature but was not required to predict minimum stream temperature. The average SE in estimated maximum daily stream temperature for the individual basins was 0.9 +/- 0.6 degrees C at the 95% confidence interval.     

Planning for global environmental change in Bangkok's informal settlements

Government agencies in cities across Asia recognise that municipalities must take steps to adapt to projected climate changes if people and places are to be kept above water. This paper focuses on planning for climate change in Bangkok because it ranks among the top 10 port cities vulnerable to climate change related flooding. It is also understood that the most devastating impacts of climate change will be suffered by the city's most vulnerable residents: the poor. Not only do impoverished people occupy physically vulnerable space, such as riverbanks, but they are also the least equipped to recover from the disruption of their livelihoods.

Several scholars have identified “institutional traps” that prevent the Thai government from successfully aiding poor and marginalised flood victims in the past. These include poor coordination, lack of monitoring and evaluation, rigidity, crisis management and elite capture. Lebel, Manuta, and Garden (2011, 56) Lebel, L., J.B. Manuta, and P. Garden. 2011. “Institutional Traps and Vulnerability to Changes in Climate and Flood Regimes in Thailand.” Regional Environmental Change 11 (1): 45–58.[Crossref], [Web of Science ®] , [Google Scholar] pose the crucial question: “How have individuals – from local community leaders through to national level politicians and bureaucrats – successfully influenced policy and programmes to avoid institutional traps and improve adaptive capacities to climate change?”

In this paper, we begin to address this question through examining emergent methods of “community based adaptation” and reviewing case studies of adaptation action from other vulnerable communities in the Global South. These lessons – such as overcoming institutional rigidity and avoiding elite capture – are important for Bangkok and other cities in the Global South that face many different challenges by global environmental change.     

Modeling Habitat Suitability for Complex Species Distributions by Environmental-Distance Geometric Mean

This paper presents a new habitat suitability modeling method whose main properties are as follows: (1) It is based on the density of observation points in the environmental space, which enables it to fit complex distributions (e.g. nongaussian, bimodal, asymmetrical, etc.). (2) This density is modeled by computing the geometric mean to all observation points, which we show to be a good trade-off between goodness of fit and prediction power. (3) It does not need any absence information, which is generally difficult to collect and of dubious reliability. (4) The environmental space is represented either by an expert-selection of standardized variables or the axes of a factor analysis [in this paper we used the Ecological Niche Factor Analysis (ENFA)].We first explain the details of the geometric mean algorithm and then we apply it to the bearded vulture (Gypaetus barbatus) habitat in the Swiss Alps. The results are compared to those obtained by the median algorithm and tested by jack-knife cross-validation. We also discuss other related algorithms (BIOCLIM, HABITAT, and DOMAIN). All these analyses were implemented into and performed with the ecology-oriented GIS software BIOMAPPER 2.0.The results show the geometric mean to perform better than the median algorithm, as it produces a tighter fit to the bimodal distribution of the bearded vulture in the environmental space. However, the median algorithm being quicker, it could be preferred when modeling more usual distribution.     

A HYPOTHESIS ABOUT FACTORS THAT AFFECT MAXIMUM SUMMER STREAM TEMPERATURES ACROSS MONTANE LANDSCAPES1

ABSTRACT: Temperature is an important variable structuring lotic biotas, but little is known about how montane landscapes function to determine stream temperatures. We developed an a priori hypothesis that was used to predict how watershed elements would interact to affect stream temperatures. The hypothesis was tested in a series of path analyses using temperature data from 26 sites on second‐order to fourth‐order streams across a fifth‐order Rocky Mountain watershed. Based on the performance of the first hypothesis, two revised versions of the hypothesis were developed and tested that proved to be more accurate than the original hypothesis. The most plausible of the revised hypotheses accounted for 82 percent of the variation in maximum stream temperature, had a predicted data structure that did not deviate from the empirical data structure, and was the most parsimonious. The final working hypothesis suggested that stream temperature maxima were directly controlled by a large negative effect from mean basin elevation (direct effect = ‐0.57, p < 0.01) and smaller effects from riparian tree abundance (direct effect = ‐0.28, p = 0.03), and cattle density (direct effect = 0.24, p = 0.05). Watershed slope, valley constraint, and the abundance of grass across a watershed also affected temperature maxima, but these effects were indirect and mediated through cattle density and riparian trees. Three variables included in the a priori hypothesis ‐ watershed aspect, stream width, and watershed size ‐ had negligible effects on maximum stream temperatures and were omitted from the final working hypothesis.     

Reduced complexity models for regional aquatic habitat suitability assessment

Generalizable methods that identify suitable aquatic habitat across large river basins and regions are needed to inform resource management. Habitat suitability models intersect environmental variables to predict species occurrence, but are often data intensive and thus are typically developed at small spatial scales. This study estimated mean monthly aquatic habitat suitability throughout Utah (USA) for Bonneville Cutthroat Trout (Oncorhynchus clarkii utah) and Bluehead Sucker (Catostomus discobolus) with publicly available, geospatial datasets. We evaluated 15 habitat suitability models using unique combinations of percent of mean annual discharge, velocity, gradient, and stream temperature. Environmental variables were validated with observed conditions and species presence observations to verify habitat suitability estimates. Stream temperature, gradient, and discharge best predicted Bonneville Cutthroat Trout presence, and gradient and discharge best predicted Bluehead Sucker presence. Simple aquatic habitat suitability models outperformed models that used only streamflow to estimate habitat for both species, and are useful for conservation planning and water resources decision-making. This modeling approach could enable resource managers to prioritize stream restoration across vast regions within their management domain, and is potentially compatible with water management modeling to improve ecological objectives in management models.     

Recreational Stream Crossing Effects on Sediment Delivery and Macroinvertebrates in Southwestern Virginia,USA

Trail-based recreation has increased over recent decades, raising the environmental management issue of soil erosion that originates from unsurfaced, recreational trail systems. Trail-based soil erosion that occurs near stream crossings represents a non-point source of pollution to streams. We modeled soil erosion rates along multiple-use (hiking, mountain biking, and horseback riding) recreational trails that approach culvert and ford stream crossings as potential sources of sediment input and evaluated whether recreational stream crossings were impacting water quality based on downstream changes in macroinvertebrate-based indices within the Poverty Creek Trail System of the George Washington and Jefferson National Forest in southwestern Virginia, USA. We found modeled soil erosion rates for non-motorized recreational approaches that were lower than published estimates for an off-road vehicle approach, bare horse trails, and bare forest operational skid trail and road approaches, but were 13 times greater than estimated rates for undisturbed forests and 2.4 times greater than a 2-year old clearcut in this region. Estimated soil erosion rates were similar to rates for skid trails and horse trails where best management practices (BMPs) had been implemented. Downstream changes in macroinvertebrate-based indices indicated water quality was lower downstream from crossings than in upstream reference reaches. Our modeled soil erosion rates illustrate recreational stream crossing approaches have the potential to deliver sediment into adjacent streams, particularly where BMPs are not being implemented or where approaches are not properly managed, and as a result can negatively impact water quality below stream crossings.