A WATERSHED-LEVEL ECOLOGICAL RISK ASSESSMENT METHODOLOGY1

ABSTRACT: We present an ecological risk assessment methodology at the watershed level for freshwater ecosystems. The major component is a pollutant transport and fate model (a modified EUTROMOD) with an integrated uncertainty analysis utilizing a two-phase Monte Carlo procedure. The uncertainty analysis methodology distinguishes between knowledge uncertainty and stochastic variability. The model assesses the ecological risk of lentic (lake) ecosystems in response to the stress of excess phosphorus resulting in eutrophication. The methodology and model were tested on the Wister Lake watershed in Oklahoma with the lake and its trophic state as the endpoint for ecological risk assessment. A geographic information system was used to store, manage, and manipulate spatially referenced data for model input.     

EFFECTS OF BASIN-SCALE TIMBER HARVEST ON WATER YIELD AND PEAK STREAMFLOW1

ABSTRACT: Streamflow changes resulting from clearcut harvest of lodgepole pine (Pinus contorta) on a 2145 hectare drainage basin are evaluated by the paired watershed technique. Thirty years of continuous daily streamflow records were used in the analysis, including 10 pre-harvest and 20 post-harvest years of data. Regression analysis was used to estimate the effects of timber harvest on annual water yield and annual peak discharge. Removal of 14 million board feet of lodgepole pine (Pinus contorta) from about 526 hectares (25 percent of the basin) produced an average of 14.7 cm additional water yield per year, or an increase of 52 percent. Mean annual daily maximum discharge also increased by 1.6 cubic meters per second or 66 percent. Increases occurred primarily during the period of May through August with little or no change in wintertime streamflows. Results suggest that clearcutting conifers in relatively large watersheds (> 2000 ha) may produce significant increases in water yield and flooding. Implications of altered streamflow regimes are important for assessing the future ecological integrity of stream ecosystems subject to large-scale timber harvest and other disturbances that remove a substantial proportion of the forest cover.     

REGIONAL SCALE TREND MONITORING OF INDICATORS OF TROPHIC CONDITION OF LAKES1

ABSTRACT: The U.S. Environmental Protection Agency has proposed a sample survey design to answer questions about the ecological condition and trends in condition of U.S. ecological resources. To meet the objectives, the design relies on a probability sample of the resource population of interest (e.g., a random sample of lakes) each year on which measurements are made during an index period. Natural spatial and temporal variability and variability in the sampling process all affect the ability to describe the status of a population and the sensitivity for trend detection. We describe the important components of variance and estimate their magnitude for indicators of trophic condition of lakes to illustrate the process. We also describe models for trend detection and use them to demonstrate the sensitivity of the proposed design to detect trends. If the variance structure that develops during the probability surveys is like that synthesized from available databases and the literature, then the trends in common indicators of trophic condition of the specified magnitude should be detectable within about a decade for Secchi disk transparency (0.5–1 percentiyear) and total phosphorus (2–3 percent/year), but not for chlorophyll-a (> 3–4 percent/year), which will take longer.     

BACTERIAL RELATIONSHIPS IN STORMWATERS1

ABSTRACT: Data were developed within a three-year period for indicator bacteria and three species of bacterial pathogens following rural storm event hydrographs. The first flush concept was confirmed in all hydrographs. Bacterial density peaking occurred at or before the hydrograph peaks. FC and FS values were higher in more developed areas than the primary rural test site and their numerical ratios followed similar trends. Chlorine demand of storm waters varied between 8 and 16 mg/l and, the ozone requirement was greater than 32 mg/l in the same waters. Aftergrowth of total coliform bacteria occurred following chlorine and ozone doses of 16 mg/l and 32 mg/l respectively. Fecal coliform, fecal streptococci, Salmonella sp., and Pseudomonas sp. all were reduced to near detectable limits by the disinfectants up to 8 days. Staphylococcus sp. demonstrated a propensity to restablish their populations. Multiple regression analysis of the bacterial groups and species in storm waters suggested the fecal streptococci to have been the most useful group in evaluating bacterial storm water quality, with staphylocci have been closely related insofar as their statistical significance was concerned.     

USE OF FIRST-ORDER UNCERTAINTY ANALYSIS TO OPTIMIZE SUCCESSFUL STREAM WATER QUALITY SIMULATION1

ABSTRACT: A first-order uncertainty technique is developed to quantify the relationship between field data collection and a modeling exercise involving both calibration and subsequent verification. A simple statistic (LTOTAL) is used to quantify the total likelihood (probability) of successfully calibrating and verifying the model. Results from the first-order technique are compared with those from a traditional Monte Carlo simulation approach using a simple Streeter-Phelps dissolved oxygen model. The largest single difference is caused by the filtering or removal of unrealistic outcomes within the Monte Carlo framework. The amount of bias inherent in the first-order approach is also a function of the magnitude of input variability and sampling location. The minimum bias of the first-order technique is approximately 20 percent for a case involving relatively large uncertainties. However the bias is well behaved (consistent) so as to allow for correct decision making regarding the relative efficacy of various sampling strategies. The utility of the first-order technique is demonstrated by linking data collection costs with modeling performance. For a simple and inexpensive project, a wise and informed selection resulted in an LTOTAL value of 86 percent, while an uninformed selection could result in an LTOTAL value of only 55 percent.     

COMPUTING THE RISKS ASSOCIATED WITH WASTELOAD) ALLOCATION MODELING1

ABSTRACT: The risks associated with a traditional wasteload allocation (WLA) analysis were quantified with data from a recent study of the Upper Trinity River (Texas). Risk is define here as the probability of failing to meet an established in-stream water quality standard. The QUAL-TX dissolved oxygen (DO) water quality model was modified to a Monte Carlo framework. Flow augmentation coding was also modified to allow an exact match to be computed between the predicted and an established DO concentration standard, thereby providing an avenue for linking input parameter uncertainty to the assignment of a wasteload permit (allowable mass loading rate). Monte Carlo simulation techniques were employed to propagate input parameter uncertainties, typically encountered during WLA analysis, to the computed effluent five-day carbonaceous biochemical oxygen demand requirements for a single major wastewater treatment plant (WWTP). The risk of failing to meet an established in-stream DO criterion may be as high as 96 percent. The uncertainty associated with estimation of the future total Kjeldahl nitrogen concentration for a single tributary was found to have the greatest impact on the determination of allowable WWTP loadings.     

FACTORS AFFECTING HERBICIDE YIELDS IN THE CHESAPEAKE BAY WATERSHED,JUNE 19941

ABSTRACT: Median concentrations and instantaneous yields of alachlor, metolachlor, atrazine, cyanazine, and simazine were generally highest at sites in the Lower Susquehanna River Basin and in agricultural subbasins. Instantaneous herbicide yields are related to land use, hydrogeologic setting, streamflow yield, and agricultural row cropping practices. The significance of these relations may be affected by the interdependence of the factors. The percentage of basin area planted in corn is the most influential factor in the prediction of herbicide yield. Instantaneous yields of all five herbicides measured in June 1994 related poorly to averaged 1990–94 herbicide use. Annually averaged herbicide-use data are too general to use as a predictor for short-term herbicide yields. An evaluation of factors affecting herbicide yields could be refined with more-current land use and land cover information and a more accurate estimate of the percentage of basin area planted in corn. Factors related to herbicide yields can be used to predict herbicide yields in other basins within the Chesapeake Bay watershed and to develop an estimate of herbicide loads to Chesapeake Bay.     

LAND-USE AND WATER-QUALITY RELATIONSHIPS IN THE GEORGES CREEK BASIN,MARYLAND1

ABSTRACT: Models developed in Ohio to predict water quality conditions resulting from various land uses associated with the surface mining of coal are employed to ascertain their transferability to Maryland conditions. Discriminant analysis is employed to assess patterns of association between water quality and land use variables, and predictive models were then constructed with which to quantify changes in stream quality to be expected from the changing mosaic of upstream land uses in the Georges Greek basin of western Maryland. Data collected under procedures specified by the regulatory authority in Maryland may have accounted for the lack of statistically significant results from these models. Suggested changes in the collection of data are made for the coal region of Maryland.     

Comparison of Stream Invertebrate Response Models for Bioassessment Metrics1

Waite, Ian R., Jonathan G. Kennen, Jason T. May, Larry R. Brown, Thomas F. Cuffney, Kimberly A. Jones, and James L. Orlando, 2012. Comparison of Stream Invertebrate Response Models for Bioassessment Metrics. Journal of the American Water Resources Association (JAWRA) 48(3): 570-583. DOI: 10.1111/j.1752-1688.2011.00632.x Abstract: We aggregated invertebrate data from various sources to assemble data for modeling in two ecoregions in Oregon and one in California. Our goal was to compare the performance of models developed using multiple linear regression (MLR) techniques with models developed using three relatively new techniques: classification and regression trees (CART), random forest (RF), and boosted regression trees (BRT). We used tolerance of taxa based on richness (RICHTOL) and ratio of observed to expected taxa (O/E) as response variables and land use/land cover as explanatory variables. Responses were generally linear; therefore, there was little improvement to the MLR models when compared to models using CART and RF. In general, the four modeling techniques (MLR, CART, RF, and BRT) consistently selected the same primary explanatory variables for each region. However, results from the BRT models showed significant improvement over the MLR models for each region; increases in R² from 0.09 to 0.20. The O/E metric that was derived from models specifically calibrated for Oregon consistently had lower R² values than RICHTOL for the two regions tested. Modeled O/E R² values were between 0.06 and 0.10 lower for each of the four modeling methods applied in the Willamette Valley and were between 0.19 and 0.36 points lower for the Blue Mountains. As a result, BRT models may indeed represent a good alternative to MLR for modeling species distribution relative to environmental variables.     

ASSESSING ENVIRONMENTAL EFFECTS OF SEVERE SUSTAINED DROUGHT1

ABSTRACT: Evaluation criteria for reservoir and stream resources were developed to provide decision makers with feedback on environmental consequences of water allocation decisions under conditions of severe sustained drought within the Colorado River Basin by using the AZCOL gaming simulation model. Seven categories of flow dependent resources were identified which highlight resource states associated with reservoirs or river reaches within the AZCOL model. AZCOL directly simulates impact of water management decisions on five resource categories: threatened, endangered or sensitive fish; native nonlisted fish; wetland and riparian elements; national or state wildlife refuges; and hatcheries or other flow dependent facilities. Two additional categories - cold and warm water sport fish - are not modeled explicitly but are incorporated in the evaluation of monetary benefits from recreation on Colorado River waters. Each resource category was characterized at each time step in the simulation according to one of four environmental states: stable, threatened, endangered, or extirpated. Changes in resource states were modeled by time and flow-dependent decision criteria tied to either reservoir level or stream flows within the AZCOL model structure. Gaming results using the AZCOL model indicate environmental impacts would be substantial and that water allocation decisions directly impacted environmental resource states.