USING FIELD SCALE MODELS TO PREDICT PEAK FLOWS ON AGRICULTURAL WATERSHEDS1

The goal of this study was to develop a methodology for generating storm hydrographs at a watershed scale based on daily runoff estimates from a field scale model. The methodology was evaluated on a small agricultural watershed using the ADAPT field scale process model. A comparison of observed and predicted peak flows for 11 of the largest events that occurred in a three year period gave r² values of 0.84, 0.82, and 0.81 when the watershed was subdivided into 1, 5, and 10 sub watersheds. However, all other statistical measures improved when the watershed was subdivided into at least five sub watersheds. Guidelines need to be developed on the use of the procedure but it first needs to be evaluated on several watersheds that exhibit a range in sizes, land uses, slopes, and soil properties.     

TIMBER HARVEST IMPACTS ON SMALL HEADWATER STREAM CHANNELS IN THE COAST RANGES OF WASHINGTON1

ABSTRACT: We evaluated changes in channel habitat distributions, particle‐size distributions of bed material, and stream temperatures in a total of 15 first‐or second‐order streams within and nearby four planned commercial timber harvest units prior to and following timber harvest. Four of the 15 stream basins were not harvested, and these streams served as references. Three streams were cut with unthinned riparian buffers; one was cut with a partial buffer; one was cut with a buffer of non‐merchantable trees; and the remaining six basins were clearcut to the channel edge. In the clearcut streams, logging debris covered or buried 98 percent of the channel length to an average depth of 0.94 meters. The slash trapped fine sediment in the channel by inhibiting fluvial transport, and the average percentage of fines increased from 12 percent to 44 percent. The trees along buffered streams served as a fence to keep out logging debris during the first summer following timber harvest. Particle size distributions and habitat distributions in the buffered and reference streams were largely unchanged from the pre‐harvest to post‐harvest surveys. The debris that buried the clearcut streams effectively shaded most of these streams and protected them from temperature increases. These surveys have documented immediate channel changes due to timber harvest, but channel conditions will evolve over time as the slash decays and becomes redistributed and as new vegetation develops on the channel margins.     

ESTABLISHING WATERSHED MANAGEMENT IN LAW: NEW ZEALAND'S EXPERIENCE1

ABSTRACT: New Zealand is one of the first countries in the world to enshrine the concept of watershed management in law, through institutional arrangements and the Resource Management Act of 1991 ‐ a law constructed on a watershed management legacy begun in 1941. This paper outlines the development of New Zealand's Resource Management Act (as it applies to water management) and the lessons that have been learned in its implementation.     

ESTABLISHING STATISTICAL DESIGN CRITERIA FOR WATER QUALITY MONITORING SYSTEMS: REVIEW AND SYNTHESIS1

ABSTRACT: Regulatory water quality management has placed fairly extensive information expectations on routine, fixed-station monitoring without a corresponding emphasis being placed on the need to design monitoring systems to meet these expectations. To correct the situation there is increasing interest in developing more quantitative monitoring system design procedures which incorporate the statistical nature of sampling. In examining the development of such quantitative criteria, this paper describes the roles of statistics in a systematic approach to monitoring - initial design and routine reporting of results - and reviews the use of statistics in each. The paper emphasizes the need to tie the two together, via statistical design criteria, in order for the identified information expectations to be met in a statistically sound manner. However, the use of statistics in water quality monitoring is noted as currently being as much an art as it is a science.     

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.     

Water quality monitoring—Some practical sampling frequency considerations

Water quality monitoring involves sampling a population, water quality, that is changing over time. Sample statistics (e.g., sample mean) computed from data collected by a monitoring network can be affected by three general factors: (1) random changes due to storms, rainfall, etc.; (2) seasonal changes in temperature, rainfall, etc.; and (3) serial correlation or duplication in information from sample to sample. (Closely spaced samples will tend to give similar information).In general, these effects have been noted, but their specific effects on water quality monitoring network design have not been well defined quantitatively. The purpose of this paper is to examine these effects with a specific data set and draw conclusions relative to sampling frequency determinations in network design.The design criterion adopted for this study of effects due to the above factors is the width of confidence intervals about annual sample geometric means of water quality variables. The data base for the study consisted of a daily record of 5 water quality variables at 9 monitoring stations in Illinois for a period of 1 year.Three general regions of frequencies were identified: (1) greater than approximately 30 samples per year where serial correlation plays a dominant role; (2) between approximately 10 and 30 samples per year where the effects of seasonal variation and serial correlation tended to cancel each other out; and (3) less than approximately 10 samples per year where seasonal variation plays a dominant role. In region 2, either seasonal variation and serial correlation should both be considered or both ignored. To consider only seasonal variation introduces more error than ignoring it. These results are network averages (over variables and stations) from one network, thus results for individual variables may deviate considerably from the average and from those for other networks.Financial support for this study was provided, in part, by the U.S. Environmental Protection Agency, grant number R805759-01-0.     

Sensory ecology in a changing world: salinity alters conspecific recognition in an amphidromous fish, Pseudomugil signifer

Group fission and fusion processes are driven by state dependence, risk and the availability of information from others. Yet the availability of information changes under different environmental conditions, thus aiding or inhibiting group formation and maintenance. Chemical cues provide information on the location of individuals and can act as a mechanism for individuals to group together, although they can be greatly affected by environmental conditions. Using a flow channel, we studied how one shoaling fish species, the Pacific blue-eye (Pseudomugil signifer), responds to conspecific chemical cues (CCCs) in different environmental conditions (salinities). This species lives in estuarine environments, ranging in salinity from fresh to fully marine. P. signifer responded to CCCs in freshwater but not in saltwater. Furthermore, P. signifer did not respond to saltwater with CCCs added from freshwater. It took significantly longer for fish in saltwater, than in freshwater, to locate and join a shoal when only CCCs from the shoal were present. Finally, fish formed more cohesive shoals in freshwater than in brackish or saltwater. These results suggest that these fish do not rely on chemical cues in saltwater to locate conspecific shoals. Furthermore, the reduced amounts of these cues in saltwater may inhibit the maintenance of tight shoal structures. We suggest that fish utilise different sensory modalities in fresh or saltwater in order to locate one another, or the social structure of these groups is fundamentally different between these two water types. The importance of this study in relation to understanding how animals utilise and change different sensory modalities in varying environmental conditions is discussed.     

A TECHNIQUE FOR MEASURING SCOUR AND FILL OF SALMON SPAWNING RIFFLES IN HEADWATER STREAMS1

A 30 x 0.9 cm piece of steel rod bent in the shape of an “L” and attached by hose clamps to a 15 x 3.2 cm section of plastic pipe sliding on an 86 x 1.9 cm steel shaft was tested for use in measuring scour and fill of salmon spawning riffles. Installed along channel cross-sections, results of tests at four sites on two hydraulically different streams showed the device to be useful in monitoring event specific scour and fill. Measurement error was estimated to be ± 10 mm.     

APPLICATION OF THE BASINS DATABASE AND NPSM MODEL ON A SMALL OHIO WATERSHED1

ABSTRACT: The purpose of this study was to evaluate the Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) watershed management system. BASINS data were used with the NPSM model to predict discharge and sediment concentrations at the outlet of a 103 km² Ohio watershed. It was concluded that the NPSM model should always be calibrated but only a few of the parameters provided with BASINS needed to be calibrated. For a three‐year study period, there was a 2 percent underestimation of discharge using area weighted precipitation values and a 25 percent overestimation using the single station data in BASINS. A comparison of observed and predicted monthly discharge resulted in an r² of 0.86 with area‐weighted precipitation and an r² of 0.74 with the single station data. Calibrating the model to substantially improve sediment predictions was unsuccessful and we concluded that a calibration period of one year was too short. For the three‐year study period, the r² for sediment was 0.36 with a slope of 0.37 and an intercept of 18.8 mg/l. The mean observed and predicted sediment concentrations were 27.1 mg/l and 22.6 mg/l, respectively.