An Exploration of Nutrient and Community Variables in Effluent Dependent Streams in Arizona David Walker, Ph.D University of Arizona Christine Goforth University of Arizona Samuel Rector Arizona Department of Environmental Quality EPA Grant Number X-828014-01-01 Acknowledgements Without the help of several persons, this work would not have been possible. Shelby Flint. UofA graduate student. Without Shelby’s organizational skills both in the field and lab, this project probably would have come to a screeching halt long ago. Shelby has moved on to bigger and better things but will always be sorely missed. Patti Spindler. Aquatic ecologist from ADEQ provided invaluable field and technical expertise. Emily Hirleman.. UofA graduate student. Field, laboratory, and comedic assistance. Nick Paretti. UofA graduate student. Field and laboratory assistance. Leah Bymers. UofA graduate student. Field and laboratory assistance. Elzbieta and Wit Wisniewski. UofA graduate students. Field assistance. Linda Taunt. Head of the Hydrological Support and Assessment Unit, ADEQ. Moral support (did I say I’d have it done on Wednesday?....I meant Thursday…or Friday…maybe next week) Susan Fitch. ADEQ. An endless supply of moral support. Steven Pawlowski. ADEQ. Technical expertise, reviewer, grant manager, and good guy. 2 Introduction 3 Relatively little information is known about waters within Arizona designated “aquatic and wildlife, effluent dependent” (EDW) and even less is known about biological communities living in waters designated as such. Nutrient levels are not routinely required in NPDES permits from these waters so that historical data is either lacking or non-existent. One aspect of EDW’s that is certain is that they will increase in number and importance as population centers increase. As EDW’s increase in number, they are also expected to become more hydrologically-linked with “natural” surface waters over time. Increasing water withdraws from natural systems means that EDW’s will become important ecosystems for aquatic organisms. This study identifies some of the organisms currently inhabiting EDW’s in the state and then examines what constraints to biological diversity of macroinvertebrates exist in each EDW individually and collectively. Since most of the EDW’s are fishless systems, we chose aquatic macroinvertebrates as our indicator trophic group. Aquatic macroinvertebrates are often used in aquatic studies and for good reason; they are ubiquitous and have species-specific life history requirements including pollution tolerances. While metrics have been devised using aquatic macroinvertebrates to determine the health of naturally-occurring freshwater streams in Arizona, we believe that EDW’s are too different from their “natural” counterparts for this metric to be of much significance. We chose instead to keep it simplistic and just measure species diversity of aquatic macroinvertebrates and correlate this with other variables collected from five EDW’s throughout the state. We chose to use the Shannon-Weiner Diversity index which places emphasis on the relative abundance of each species. We believe this is important, especially in aquatic systems known to have some level of pollution because these areas are often typified by having a large biomass of only a few species. A high biomass of only pollution tolerant species does not mean that an area is fulfilling any standard of biological integrity. The formula for the Shannon-Weiner Diversity Index is: H’ = [∑ (pi)(ln pi)] -Where H’ represents the amount of diversity in an ecosystem and will be greatest if species are equally abundant. - pi represents the proportion, or “relative abundance”, of each individual species to the total. We chose 5 effluent dependent waters within Arizona. Rio de Flag serving the city of Flagstaff. Bitter Creek serving the city of Jerome Jack’s Canyon (Big Park WWTP) serving the Village of Oak Creek The Santa Cruz River (Roger Road WWTP) serving much of the city of Tucson The Santa Cruz River (Nogales IWWTP) serving the cities of Nogales Arizona and Nogales, Sonora Mexico. Response variables chosen are from 4 major categories; biological, physical, chemical, and physico-chemical. Physical variables consisted of measuring gradient, embeddedness, floodprone and bankfull width, substrate classification and fractionation by category sizes, and flow. 4 Chemical variables consisted of nutrients such as ammonia-N, nitrate+nitrite-N, TKN, orthophosphate, total phosphorous, total and dissolved organic carbon, general chemistry (hardness, alkalinity, etc.), and suites of total and dissolved metals. Physico-chemical variables consisted of dissolved oxygen (mg/L and percent saturation), pH, temperature, specific conductivity, oxidation-reduction potential, total suspended solids, turbidity, and mean diel dissolved oxygen. Biological variables included chlorophyll a (peri- and phytoplankton), peri- and phytoplankton identification and enumeration, and macroinvertebrate collection (using ADEQ protocol), identification, and enumeration (sub-sampled using a Caton tray). Aquatic Consulting and Testing performed all of the chemical analyses. Biological analyses were performed at the University of Arizona’s Environmental Research Laboratory. Physicochemical data was collected using a Hydrolab Surveyor 4 sonde and data collector. In order to examine correlations between response variables and diversity, we used principal components analysis (PCA). Principal components analysis is a classical statistical method also called a Karhounen-Louve transformation or a Hotteling transformation. PCA uses linear transformation and matrix algebra to choose a new coordinate system for the data cloud so that the centroid is set to zero and the first principal component axis goes through the maximum amount of variation with the second axis exactly orthogonal to the first. This sets the framework for the remaining principal component axis. In essence, PCA reduces dimensionality of a data set so that correlations among several variables can be examined simultaneously. We used a 3-dimensional representation of the data cloud (Gabriel bi-plot) so that the PCA axes could be visualized. The relative distances between each axis are eigenvectors and a vector report is published below each bi-plot. The method in which the bi-plot represents the 3-dimensional correlations is that axes that are closest to one another have some degree of positive correlation (the closer they are, the higher the positive correlation) while those in opposite quadrants are inversely correlated. We sampled once during the summer and once during the winter at each EDW and chose the upstream site as close as feasible to the outfall in every case. The second site was chosen based upon linear profiles of dissolved oxygen and we attempted to find a “recovery zone” where dissolved oxygen levels began to once again increase. We were able to find this recovery zone in some of the less polluted EDW’s while others were never found as dissolved oxygen actually decreased with distance from the outfall in a few circumstances. All field data as well as laboratory samples were collected and analyzed using ADEQ protocol and QA/QC. 5 Rio de Flag 6 Background The Rio de Flag (RDF) wastewater treatment plant (WWTP) is a 4 MGD plant that serves the city of Flagstaff Arizona. This plant produces class A+ water through a process involving screening, primary sedimentation, aeration, secondary sedimentation, filtration, and disinfection using ultraviolet sterilization. A two-stage anoxic/aerobic Bardenpho process is used and is designed to reduce nitrogen content in wastewater. The use of UV sterilization greatly reduces the need or use of chlorine. Wastewater that is not used for irrigation is released into the drainage of the same name, the Rio de Flag. Influent to the RDF WWTP and amount discharged into the Rio de Flag drainage from June 2003 to June 2004 is listed below. Month Influent (MG) Discharge (MG) June 61.190 15.346 July 69.432 18.783 August 70.522 51.971 September 66.862 49.085 October 62.739 31.255 November 55.987 49.515 December 56.916 50.233 January 57.107 50 February 54.16 43.737 March 62.739 7.4845 April 56.591 28.911 May 62.739 7.4845* June 67.447 7.7838* Total for Year 799.460 445.580 Average/month 61.497 34.275 * Much of the discharge that would have gone to the Rio de Flag drainage was diverted to irrigate a new golf course. The Rio de Flag drainage exists both above and below the WWTP and is a tributary of San Francisco Wash, which is a tributary of the Little Colorado River. The stream itself originates on the southwestern slopes of the San Francisco Peaks near Big Leroux and Little Leroux Springs (Figure 2a). Along its length, the Rio de Flag drainage has many tributaries. The total drainage area of the watershed is 302 km2. The elevation changes along the length of the drainage from approximately 12,000 feet at the height of the San Francisco Peaks to about 6800 feet in the wide, flat valleys southeast of Flagstaff. Besides discharge from the RDF WWTP, winter snowmelt from the San Francisco Peaks in winter and spring and rainfall during the summer monsoons of July and August contribute to flow in the Rio de Flag. Average annual precipitation for the drainage area is approximately 20 inches in Flagstaff to 35 inches on the San Francisco Peaks with 25 inches of this precipitation occurring as snowfall. The Rio de Flag floodplain is intensively developed upstream of the sampling sites as it crosses through the center of Flagstaff. Nearly half of the land use within the 100-year floodplain is 7 considered residential with other land uses consisting of recreation, schools, light industry, railroad, utility easements, and retail businesses (U.S. Army COE). Besides the effluent released from the WWTP, the Rio de Flag had no contribution of flow from upstream areas during the course of this study. Lack of attenuation of flood peaks due to urbanization along the middle reach of the Rio de Flag may mean that flows are more flashy and sporadic than what they have been historically.