CLIMATOLOGICAL WATERSHED CALIBRATION1

ABSTRACT: This study tests the hypothesis that climatic data can be used to develop a watershed model so that stream flow changes following forest harvest can be determined. Measured independent variables were precipitation, daily maximum and minimum temperature, and concurrent relative humidity. Computed variables were humidity deficit, saturated vapor pressure, and ambient vapor pressure. These climatic variables were combined to compute a monthly evaporation index. Finally, the evaporation index and monthly precipitation were regressed with measured monthly stream flow and the monthly estimates of stream flow were combined for the hydrologic year. A regression of predicted versus measured annual stream flow had a standard error of 1.5 inches (within 6.1 percent of the measured value). When 10, 15, and 20 years of data were used to develop the regression equations, predicted minus measured stream flow for the last 7 years of record (1972–1978) were within 16.8, 11.5, and 9.7 percent of the measured mean, respectively. Although single watershed calibration can be used in special conditions, the paired watershed approach is expected to remain the preferred method for determining the effects of forest management on the water resource.     

Effectiveness of forestry streamside management zones in the sand-clay hills of Mississippi: early indications

During the past decade, compliance with initiatives to promote forestry best management practices (BMPs) has been monitored in most states of the southern U.S. and suggests an excellent level of acceptance throughout the region. However, effectiveness of these practices to protect water quality and aquatic habitat in streams that are potentially impacted by forest management activities has not been as thoroughly documented as the degree of compliance. The objective of this study was to determine effectiveness of streamside management zones (SMZs), a key element of BMPs designed for protection of water quality, aquatic habitat, and macroinvertebrate communities, in low-order streams within a region of north central Mississippi that is subjected to intensive forest management. Three SMZ treatments (undisturbed reference, clear-cut logging with an SMZ designated by forest managers, or clear-cut logging with no SMZ) were evaluated using a study with three replications of each treatment. Response metrics including water quality parameters, mineral soil exposure and net deposition/erosion within riparian zones, stream habitat indicators, and aquatic macroinvertebrate communities were comparable between streams receiving SMZs and undisturbed reference streams at all sampling intervals during the first year after treatment. Furthermore, significant elevation of streamwater temperature, decline in habitat stability rating, and increase in density of macroinvertebrates occurring in streams without an SMZ in comparison to reference streams provides additional evidence of SMZ effectiveness during the initial year after harvesting.     

PREDICTION OF STREAM TEMPERATURE IN FORESTED WATERSHEDS1

ABSTRACT: Removal of streamside vegetation changes the energy balance of a stream, and hence its temperature. A common approach to mitigating the effects of logging on stream temperature is to require establishment of buffer zones along stream corridors. A simple energy balance model is described for prediction of stream temperature in forested headwater watersheds that allows evaluation of the performance of such measures. The model is designed for application to “worst case” or maximum annual stream temperature, under low flow conditions with maximum annual solar radiation and air temperature. Low flows are estimated via a regional regression equation with independent variables readily accessible from GIS databases. Testing of the energy balance model was performed using field data for mostly forested basins on both the west and east slopes of the Cascade Mountains, and was then evaluated using the regional equations for low flow and observed maximum reach temperatures in three different east slope Cascades catchments. A series of sensitivity analyses showed that increasing the buffer width beyond 30 meters did not significantly decrease stream temperatures, and that other vegetation parameters such as leaf area index, average tree height, and to a lesser extent streamside vegetation buffer width, more strongly affected maximum stream temperatures.     

A NEW FLASHINESS INDEX: CHARACTERISTICS AND APPLICATIONS TO MIDWESTERN RIVERS AND STREAMS1

ABSTRACT: The term flashiness reflects the frequency and rapidity of short term changes in streamflow, especially during runoff events. Flashiness is an important component of a stream's hydrologic regime. A variety of land use and land management changes may lead to increased or decreased flashiness, often to the detriment of aquatic life. This paper presents a newly developed flashiness index, which is based on mean daily flows. The index is calculated by dividing the pathlength of flow oscillations for a time interval (i.e., the sum of the absolute values of day‐to‐day changes in mean daily flow) by total discharge during that time interval. This index has low interannual variability, relative to most flow regime indicators, and thus greater power to detect trends. Index values were calculated for 515 Midwestern streams for the 27‐year period from 1975 through 2001. Statistically significant increases were present in 22 percent of the streams, primarily in the eastern portion of the study area, while decreases were present in 9 percent, primarily in the western portion. Index values tend to decrease with increasing watershed area and with increasing unit area ground water inputs. Area compensated index values often shift at ecoregion boundaries. Potential index applications include evaluation of programs to restore more natural flow regimes.     

REVIVING URBAN STREAMS: LAND USE,HYDROLOGY, BIOLOGY,AND HUMAN BEHAVIOR1

ABSTRACT: Successful stream rehabilitation requires a shift from narrow analysis and management to integrated understanding of the links between human actions and changing river health. At study sites in the Puget Sound lowlands of western Washington State, landscape, hydrological, and biological conditions were evaluated for streams flowing through watersheds with varying levels of urban development. At all spatial scales, stream biological condition measured by the benthic index of biological integrity (B‐IBI) declined as impervious area increased. Impervious area alone, however, is a flawed surrogate of river health. Hydrologic metrics that reflect chronic altered streamflows, for example, provide a direct mechanistic link between the changes associated with urban development and declines in stream biological condition. These measures provide a more sensitive understanding of stream basin response to urban development than do treatment of each increment of impervious area equally. Land use in residential backyards adjacent to streams also heavily influences stream condition. Successful stream rehabilitation thus requires coordinated diagnosis of the causes of degradation and integrative management to treat the range of ecological stressors within each urban area, and it depends on remedies appropriate at scales from backyards to regional storm water systems.     

STREAMBED HYDRAULIC CONDUCTIVITY FOR RIVERS IN SOUTH‐CENTRAL NEBRASKA1

ABSTRACT: This paper presents hydraulic conductivities of streambeds measured in three rivers in south‐central Nebraska: the Platte, Republican, and Little Blue Rivers. Unlike traditional permeameter tests in streams that determine only the vertical hydraulic conductivity (K_v), the extended permeameter methods used in this study can measure K in both vertical and horizontal as well as oblique directions. As a result, the anisotropy of channel sediments can be determined from streambed tests of similar sediment volumes. Sandy streambeds with occasional silt/clay layers exist in the Republican and Platte Rivers. The average K_v values range from about 15 to 47 m/day for the sandy streambed and about 1.6 m/day for the silt/clay layers. Statistical analyses indicated that the K_v values of sand and gravel in the Platte and Republican Rivers essentially have the same mean; but the K_v values from the Little Blue River have a statistically different mean. K_v is about four times smaller than the horizontal hydraulic conductivity (K_h) for the top 40 cm of sandy streambed. Measured K_h values of the sandy streambed are in the same magnitude as the K_h of the alluvial aquifer determined using pumping tests. The smaller K_v value in the whole aquifer is the result of interbedded layers of silt and clay within the sand and gravel sediments.     

EVALUATION OF A STREAM AQUIFER ANALYSIS TEST USING ANALYTICAL SOLUTIONS AND FIELD DATA1

ABSTRACT: Considerable advancements have been made in the development of analytical solutions for predicting the effects of pumping wells on adjacent streams and rivers. However, these solutions have not been sufficiently evaluated against field data. The objective of this research is to evaluate the predictive performance of recently proposed analytical solutions for unsteady stream depletion using field data collected during a stream/aquifer analysis test at the Tamarack State Wildlife Area in eastern Colorado. Two primary stream/aquifer interactions exist at the Tamarack site: (1) between the South Platte River and the alluvial aquifer and (2) between a backwater stream and the alluvial aquifer. A pumping test is performed next to the backwater stream channel. Drawdown measured in observation wells is matched to predictions by recently proposed analytical solutions to derive estimates of aquifer and streambed parameters. These estimates are compared to documented aquifer properties and field measured streambed conductivity. The analytical solutions are capable of estimating reasonable values of both aquifer and streambed parameters with one solution capable of simultaneously estimating delayed aquifer yield and stream flow recharge. However, for long term water management, it is reasonable to use simplified analytical solutions not concerned with early‐time delayed yield effects. For this site, changes in the water level in the stream during the test and a varying water level profile at the beginning of the pumping test influence the application of the analytical solutions.     

ESTIMATION OF EPISODIC STREAM ACIDIFICATION BASED ON MONTHLY OR ANNUAL SAMPLING1

ABSTRACT: Programs of monthly or annual stream water sampling will rarely observe the episodic extremes of acidification chemistry that occur during brief, unpredictable runoff events. When viewed in the context of data from several streams, however, baseflow measurements of variables such as acid neutralizing capacity, pH and NO₃· are likely to be highly correlated with the episodic extremes of those variables from the same stream and runoff season. We illustrate these correlations for a water chemistry record, nearly two years in length, obtained from intensive sampling of 13 small Northeastern U.S. streams studied during USEPA's Episodic Response Project. For these streams, simple regression models estimate episodic extremes of acid neutralizing capacity, pH, NO₃·, Ca²⁺, SO₄^2?, and total dissolved Al with good relative accuracy from statistics of monthly or annual index samples. Model performances remain generally stable when episodic extremes in the second year of sampling are predicted from first-year models. Monthly or annual sampling designs, in conjunction with simple empirical models calibrated and maintained through intensive sampling every few years, may estimate episodic extremes of acidification chemistry with economy and reasonable accuracy. Such designs would facilitate sampling a large number of streams, thereby yielding estimates of the prevalence of episodic acidification at regional scales.     

KALMAN FILTER ESTIMATION AND PREDICTION OF DAILY STREAM FLOWS: I. REVIEW,ALGORITHM, AND SIMULATION EXPERIMENTS1

An important class of models, frequently used in hydrology for the forecasting of hydrologic variables one or more time periods ahead, or for the generation of synthetic data sequences, is the class of autoregressive(AR) models. As the AR models belong to the family of linear stochastic difference equations, they have both a deterministic and a stochastic component. The stochastic component is often assumed to have a Gaussian distribution. It is well known that hydrologic observations (e.g., stream flows) are heavily affected by noise. To account explicitly for the observation noise, the linear stochastic difference equation is expressed in state variable form and an observation model is introduced. The discrete Kalman filter algorithm can then be used to obtain estimates of the state variable vector. Typically, in hydrologic systems, model parameters, system noise statistics and measurement noise statistics are unknown, and have to be estimated. In this study an adaptive algorithm is discussed which estimates these quantities simultaneously with the state variables. The performance of the algorithm is evaluated by using simulated data.     

GENERALIZED WATERSHED LOADING FUNCTIONS FOR STREAM FLOW NUTRIENTS1

ABSTRACT: Loading functions are proposed as a general model for estimating monthly nitrogen and phosphorus fluxes in stream flow. The functions have a simple mathematical structure, describe a wide range of rural and urban nonpoint sources, and couple surface runoff and ground water discharge. Rural runoff loads are computed from daily runoff and erosion and monthly sediment yield calculations. Urban runoff loads are based on daily nutrient accumulation rates and exponential wash off functions. Ground water discharge is determined by lumped parameter unsaturated and saturated zone soil moisture balances. Default values for model chemical parameters were estimated from literature values. Validation studies over a three-year period for an 850 km² watershed showed that the loading functions explained at least 90 percent of the observed monthly variation in dissolved and total nitrogen and phosphorus fluxes in stream flow. Errors in model predictions of mean monthly fluxes were: dissolved phosphorus - 4 percent; total phosphorus - 2 percent; dissolved nitrogen - 18 percent; and total nitrogen - 28 percent. These results were obtained without model calibration.