Modeling Phosphorus Transport in the Blue River Watershed, Summit County, Colorado

Transcription

1 Modeling Phosphous Tanspot in the Blue Rive Wateshed, Summit County, Coloado Paula Jo Lemonds and John E. McCay Abstact Lake Dillon in Summit County, Coloado, is a pimay dinking-wate esevoi fo Denve. Eutophication of Lake Dillon is a concen, pimaily due to phosphous (P) loading. Thee is little agicultue in the wateshed. Thus, many local officials attibute the P loading to onsite wastewate systems (OWS). A wateshed modeling effot using the SWAT model is undeway to undestand the potential influence of vaious point and nonpoint souces of P in the Blue Rive wateshed (the most developed of thee watesheds that supply Lake Dillon). The wateshed model was calibated to measued flow ates and P concentations. The hydologic model esults ae most sensitive to the physical paametes of snowmelt, and oogaphic effects on pecipitation and evapotanspiation. Howeve, uncetainties in chemical-hydologic paametes peclude a igoous assignment of elative contibutions of vaious P souces. Rathe, the effot has esulted in a bette undestanding of P chemical paametes equied to simulate wateshed-scale tanspot. The model was most sensitive to the P soption coefficient, the P availability index, and the P enichment atio (a measue of P in unoff sediments compaed to immobile sediments). Modeling esults indicate that OWS ae not significant souces of P to Lake Dillon. Keywods: wateshed, modeling, phosphous, wastewate, hydology, SWAT Lemonds is a eseach associate, Coloado School of Mines, Golden, CO (cuently a wate esouces enginee at HDR, Denve, CO 803). paula.lemonds@hdinc.com. McCay is an associate pofesso at Coloado School of Mines, Depatment of Geology and Geological Engineeing, Golden, CO Intoduction Numeical models ae useful tools because they allow a quantitative assessment of the envionmental impacts of wastewate pollutants and impove undestanding of wateshed-scale pollutant tanspot. Pojecting futue wate quantity and quality is especially impotant in developing communities that ely on shallow goundwate as a souce of dinking wate while disposing of wastewate in the shallow subsuface. Some models capable of simulating wateshed-scale pollutant tanspot include Soil and Wate Assessment Tool (SWAT) (Anold 1998), MIKESHE (Danish Hydaulic Institute 1999), Wateshed Analysis Risk Management Famewok (WARMF) (Chen et al. 1999) and Hydologic Simulation Pogam Fotan (HSPF) (Bicknell et al. 1996). SWAT was used fo this effot because it is a public-domain model that can incopoate lage amounts of data and simulate many hydologic pocesses. Seveal wateshed-scale models have been developed using SWAT (Anold et al. 1999, Anold and Allen 1996, Fontaine et al. 02, Manguea and Engel 1998, Santhi et al. 01, Sinivasan et al. 1998). Howeve, these pojects did not specifically addess the wateshed-scale impacts of wastewate pollutants fom onsite wastewate systems (OWS). The goals of this study ae to accuately simulate mountain wateshed hydology and to quantify the impacts of OWS-deived phosphous (P) in the Lake Dillon Wateshed. The study aea is the Lake Dillon wateshed located in Summit County, Coloado (Figue 1). Lake Dillon is the main dinking-wate stoage esevoi fo Denve. Towns in the wateshed include Fisco, Dillon, Silvethone, Beckenidge, and Blue Rive. Model Setup The AcView Inteface fo SWAT was used in model development. Subwatesheds wee delineated using SWAT and a USGS 300-m esolution, 1-degee Digital 272

2 Elevation Model (DEM). Infomation extacted and calculated fom the DEM includes oveland slope, slope length, and elevation coections fo pecipitation and evapotanspiation. The subwateshed delineation is illustated in Figue 1. Coloado Lake Dillon wateshed Figue 1. The study aea is the Lake Dillon wateshed in Summit County, Coloado. The land-use infomation was deived fom 1:250,000- scale Landuse/Landcove Geogaphic Infomation Retieval Analysis System (GIRAS) spatial data. The land use/land cove digital data wee collected by the USGS and conveted to ARC/INFO by the USEPA. This infomation was used when simulating infiltation, unoff, ET, and natual souces of nutients. The soil attibutes wee taken fom the State Soil Geogaphic (STATSGO) Database, which was developed by the National Coopeative Soil Suvey (USDA-NRCS Soil Suvey 02). In the STATSGO database, soil attibutes ae stoed in polygon fomat. Each polygon includes multiple soil seies with infomation on its aeal pecentage of the polygon. In the SWAT AcView Inteface, the dominant soil seies is selected, and the inteface extacts popeties fo the model fom a elational database. Examples of the popeties extacted include soil textue, bulk density, hydaulic conductivity, available wate capacity, oganic cabon, and total depth of soil. These paametes ae used in computations fo infiltation, unoff, goundwate flow, and P tanspot. Pecipitation and tempeatue data wee available fom the National Climatic Data Cente (NCDC) and the Natual Resouces Consevation Sevice s (NRCS) Snowpack Telemety (SNOTEL) Data Netwok. Six stations wee available within the Lake Dillon Kilometes N Weathe Stations Steams Subbasins wateshed. Daily pecipitation and minimum/maximum tempeatue values wee incopoated into the model. Othe infomation defined in initial model setup included wastewate teatment plant point-souce dischages into the Blue Rive and its tibutaies, Lake Dillon wate levels, esevoi outflow, and suface aea of the esevoi. Infomation specific to each subwateshed, including steam-wate chemical popeties, goundwate-flow popeties, steam-outing paametes, consumptive wate use, and agicultual divesions wee included. Fo details on the model setup and simulation paametes, the eade is efeed to Lemonds (03). Incopoation of OWS Cuently, no algoithms exist in SWAT to specifically simulate OWS. Theefoe, a fetilize management pactice was used to simulate OWS input. The mass input ate of OWS pollutants was set equal to the mass of nutient input by the fetilize. OWS inputs wee established fom eviews of OWS effluent flow ates and wate-quality paametes completed by Kikland (01). Fetilize application input paametes wee adjusted in SWAT to achieve the appopiate inoganic P mass input ate to the subsuface based on the numbe of OWS in each subwateshed. It was assumed that implementing the fetilize management pactice in seven-day intevals would adequately epesent OWS effluent pocesses. SWAT allows the use to apply the fetilize into the fist soil laye. As a esult, the simulated OWS nutients ae not affected by unoff and ae allowed to pecolate though the vadose zone. The souce of pecolation is the natual pecipitation, which is odes of magnitude geate than OWS effluent input. Results Pio to simulating nutient tanspot, physical hydologic input paametes wee adjusted to calibate the model to steam flow ates. Adequate calibation of the physical hydologic system was citical to simulating nutient tanspot. Hydology Simulation and Calibation Measued steamflow was obtained fom two USGS gaging stations on the Blue Rive: one nea the headwates and the othe located appoximately one 273

3 half mile upsteam of Lake Dillon. The model simulation was executed fo 11 yeas ( ). The fist two yeas wee not used fo model evaluation because paametes such as soil wate content and esidue cove ae initially not in equilibium with actual physical conditions (Fontaine et al. 02; Santhi et al. 01). Pio to calibation, compaison of annualaveage steamflow data to simulated values show an unde-pediction of flow (Figue 2). Because SWAT was developed fo watesheds in nonmountainous teains, special adjustments wee necessay to accuately simulate hydologic pocesses that ae stongly affected by elevation changes chaacteistic of this wateshed. Fontaine et al. (02), who applied SWAT to the mountainous Wind Rive Basin in Wyoming, discoveed that oogaphic pocesses wee vey impotant. Pocesses that ae affected by elevation include evapotanspiation, pecipitation and snowmelt/snow-fomation pocesses. Flow (m 3 /s) Obseved Simulated Month ( ) Figue 2. Initial simulation of monthly steamflow. Lapse Rates and Elevation Bands Elevation in the Lake Dillon wateshed anges fom 2681m to 4350m ( ,272ft). To account fo the oogaphic effects on pecipitation and tempeatue (and thus evapotanspiation and snow pocesses), algoithms fo elevation bands and lapse ates wee used. In addition, seveal empiical paametes elated to snowmelt and snow fomation wee adjusted. The lapse ates wee computed by elating elevation to mean annual tempeatue and mean annual pecipitation at seven meteoological stations in the basin. The tempeatue deceases 4 o C fo an incease of 1km in elevation, and annual pecipitation inceases 5mm fo an incease of 1km in elevation. Theefoe, the tempeatue lapse ate was -4 o C/1km (R 2 =0.91, n=7); the pecipitation lapse ate was 5mm/1km (R 2 =0.82, n=6). These lapse ates wee implemented by dividing the wateshed into six elevation bands ( m) based on the DEM. When lapse ates ae defined in SWAT, subbasin tempeatues and pecipitation ae adjusted fo each elevation band in a subbasin as a function of the lapse ate and the diffeence between elevation of the meteoological gaging station and the aveage elevation specified fo the band (Neitsch et al. 00). Adjustment of Snowmelt/Snow Accumulation Paametes Paametes in SWAT that simulate snowmelt pocesses and contol the fomation of snow wee also adjusted to ceate a bette match to obseved steamflow data. The paametes that wee modified include a facto that accounts fo snow pack chaacteistics and two empiical factos that account fo the melting ate of snow. A lagging facto accounts fo tempeatue chaacteistics of the snow pack that influence the snow-pack density, snow-pack depth, exposue, and othe factos (Neitsch et al. 01). As the lagging facto appoaches 1.0, the mean ai tempeatue on the cuent day exets an inceasingly geate influence on the snow pack tempeatue, and the snow pack tempeatue fom the pevious day exets less and less influence (Neitsch et al. 01). In the model of the Lake Dillon wateshed, the value was adjusted to This value, which poduced the best fit to obseved data, is consistent with the findings of Fontaine et al. (02) who obseved values of the lag facto anging fom 0.0 to 0.5 fo aeas chaacteized by deep snowpack. The othe two factos influence the empiical elation used fo snowmelt. Snowmelt is calculated as a linea function of the diffeence between the theshold tempeatue fo snowmelt and the aveage snow-pack maximum ai tempeatue. Two paametes in SWAT epesent maximum and minimum melting values that occu on the summe and winte solstices, espectively. Fo the application of SWAT to the Lake Dillon wateshed, these values wee adjusted to 3.0 and 2.0 mm H 2 O/day- o C, espectively. Final Hydology Calibation The adjustment to snowmelt and snow fomation paametes, as well as the inclusion of lapse ates and elevation bands, made a substantial impovement in the simulation of steamflow (Figue 3). The ising limb of each yealy hydogaph begins at the coect time. The ecession limb of each yealy hydogaph begins at nealy the coect time. The yeas of highe dischage show impovement in the timing of the ecession limb of the hydogaph (Figues 2 and 3, Months 18, 46, 70, 274

4 and 92). The only poblem that was not completely esolved was that the simulated steamflow appoached 0.0 m 3 s -1 fo 2-3 months of the yea. Howeve, an impovement was made fom the initial calibation. Compaison of Figues 2 and 3 show that the simulated hydogaph was smoothed consideably and bette coesponds to the obseved values of steamflow. Statistics show the numeic impovement made in steamflow simulation. The initial R 2 value of monthlyaveaged steamflow was The simulation shown in Figue 3 exhibits an R 2 value of R 2 values of 0.65 to 0.70 fo monthly-aveaged steamflow ae appopiate consideing the numeous potential measuement eos in data collection. Fo example, spatial vaiability in ainfall, soils, and land use, eos in measuing steamflow, and eos caused by sampling stategies ae potential causes of inaccuate obseved values (Santhi et al. 01). Flow (m 3 /s) Obseved Simulated Month ( ) Figue 3. Model calibated to monthly steamflow. Phosphous Calibation To simulate pollutant tanspot, it is necessay to know the values fo moe than a dozen input paametes that influence the eaction, tansfomation, and intephase patitioning of the pollutants. Unfotunately, the available input data on these paametes, as well as obseved data equied to calibate a model, geneally ae not available in the Lake Dillon wateshed. This is tue in most watesheds. Thus, the fist step in model impovement should include a sensitivity study to undestand the elative impotance of these paametes on model output. The next step is to use the paametes that ae consideed most impotant (in tems of the influence on the model) to evaluate the pefomance of the model in simulating actual, but limited, data. This execise can also lend insight into designing a data-collection plan that would impove model pefomance. Sensitivity Study Fo the sensitivity study, obseved P concentation data fo seven yeas wee available at the Blue Rive station nea Lake Dillon (the same location of the measued steamflow data). The obseved P data ae fom the USEPA Stoage and Retieval (STORET) database (USEPA 02) and fom data collected by officials in Summit County, Coloado. The automated calibation softwae, UCODE (Poete and Hill 1998) was used to detemine sensitivity of the model to seveal P tanspot paametes. Thiteen paametes in SWAT potentially affect P tanspot (Lemonds 03). Of these paametes, the model was most sensitive to the P availability index (PAI), which specifies the faction of fetilize P that is in solution afte a peiod of apid eaction with the soil; the P enichment atio, which is the atio of the concentation of P tanspoted with the sediment to the concentation of P in the soil suface laye; the P-soil patitioning coefficient, which is the atio of the soil concentation of P to the aqueous concentation of P at equilibium; the initial P concentation in the soil; and the soil bulk density. Best-Fit Phosphous Model Paametes that had little affect on P tanspot wee assigned easonable values fom the liteatue (Lemonds, 03). The paametes that most stongly affected the model wee adjusted to yield a best-fit to obseved values (Table 1). These values ae all within easonable anges based on liteatue eview (Kikland 01, Bady and Weil 1999, Shapley 1984, Soil Suvey of Summit County Aea, Coloado 1980). Figue 4 shows the obseved P values vesus the bestfit simulated values. The simulation poduces P loading values that ae geneally within a facto of 10 of measued data and usually within a facto of 2. While the match is not igoous fo the entie simulation time, most of the impotant tends ae captued. Simulations with no OWS input of P wee also completed. The model-simulated P geneally changed by less than 5%. Theefoe, OWS is not likely to be an impotant contibuto to P pollution in the Lake Dillon wateshed. Rathe, natual souces in unoff sediments ae likely the most impotant contibuto. Table 1. P input paametes used in final simulation. 275

5 kg P/day Paamete, Units Value of Paamete fo Best-Fit Model P availability index, unitless 0.7 P-soil patitioning coefficient, m 3 Mg P enichment atio, unitless Model calculates fo each stom event Soil Laye Soil bulk density, Soil Laye g cm -3 Soil Laye Soil Laye Soil Laye 1 5 Initial soluble P soil Soil Laye 2 2 concentation, Soil Laye 3 2 mg P kg soil -1 Soil Laye Obseved Simulated Month ( ) Figue 4. Best-fit model to obseved P data. Conclusions Using public data that can be easily incopoated using the AcView inteface, SWAT accuately simulated mountain-wateshed hydologic pocesses. Vaiables associated with elevation-dependent tempeatue and pecipitation (e.g. oogaphic) effects and snowmelt wee adjusted. The oogaphic and snowmelt factos ae paticulaly significant in the Lake Dillon wateshed, whee the elevation vaies appoximately 00m. A sensitivity study was completed to assess the influence of input paametes on simulated P tanspot. Seveal model input paametes wee adjusted. Simulated P matched the oveall tends of the limited measued data along the Blue Rive upsteam of Lake Dillon. Because simulations without OWS contibutions showed little change in the concentation of P in the steam, OWS ae not believed to be the pimay souce of P in the lake. Instead, P in unoff sediments is the most likely contibuto to suface wate. The uncetainty associated with the assignment of some chemical and hydologic paametes indicates that additional infomation on the actual values and vaiability of pollutant-tanspot input vaiables is necessay. This is a feasible option, consideing that most of the paametes containing appoximated values (P soil-patitioning coefficient, mineal P concentation in the soil, and soil bulk density) may be quantified with additional collection and analysis of field data fom the Lake Dillon wateshed. Howeve, it is not clea that additional measuement would benefit these paticula simulations. Fo example, if paamete values vaied geatly ove the wateshed, it may be impactical to collect enough measuements to obtain accuate values of input paametes. In such cases, sensitivity studies that use the easonable ange of paametes to assess a ange in possible model outcomes still can be vey useful and may be the only option. Despite the uncetainties elated to model inputs, the model pefoms easonably well. Thus, the model may be used to investigate diffeent management options, such as using sewes vesus OWS fo a vaiety of pollutants, the influence of gowth and inceased OWS, o evaluating the effect of advanced OWS teatment systems on wateshed wate quality. Acknowledgments This eseach was funded in pat by the National Decentalized Wate Resouces Capacity Development Poject with funding povided to Coloado School of Mines by the U.S. Envionmental Potection Agency though a coopeative ageement (EPA No. CR ) with Washington Univesity in St. Louis. The National Science Foundation s Compute Science, Engineeing, and Mathematics Scholaships Pogam povided patial suppot fo this wok unde gant DUE Additional funding was eceived fom the Association of Engineeing Geologists (Engineeing Geology Foundation), Ameican Wate Resouces Association Coloado Section, and The Edna Bailey Sussman Foundation. The authos appeciate the thoough manuscipt eview by D. Kyle Muay. 276

6 Refeences Anold J.G. and P.M. Allen, Estimating hydologic budgets fo thee Illinois watesheds. Jounal of Hydology 176: Anold, J.G., R. Sinivasan, R.S. Muttiah, J.R. Williams Lage aea hydologic modeling and assessment pat I: model development: Jounal of Ameican Wate Resouces Association 34(1): Anold, J.G., R. Sinivasan, R.S. Muttiah, and P.M. Allen, Continental scale simulation of the hydologic balance. Jounal of the Ameican Wate Resouces Association, 35(5): Bicknell, B.R., J.C. Imhoff, J.L. Kittle, J. A.S. Donigian, J., and R.C. Johanson Hydological Simulation Pogam Fotan Use s Manual fo Release 11. EPA/600/R-93/174, U.S. Envionmental Potection Agency, Athens, GA. Bady, N.C., and R.R. Weil, The Natue and Popeties of Soils: Pentice Hall, Inc., Uppe Saddle Rive, New Jesey. 881 p. Chen, C.W., J. He, L. Ziemelis, R.A. Goldstein, and L. Olmsted Decision suppot system fo total maximum daily load: Jounal of Envionmental Engineeing 125, no. 7: Danish Hydaulic Institute, MIKE SHE pe- and post-pocessing use manual. DHI Softwae, Denmak. Fontaine, T.A., T.S. Cuickshank, J.G. Anold, and R.H. Hotchkiss, 02. Development of a snowfallsnowmelt outine fo mountainous teain fo the soil wate assessment tool (SWAT): Jounal of Hydology 262: Manguea, H.B. and B.A. Engel, Hydologic paameteization of watesheds fo unoff pediction using SWAT. Jounal of the Ameican Wate Resouces Association 34(5): Neitsch, S.L., J.G. Anold, J.R. Kiniy, and J.R. Williams. 01. Soil and Wate Assessment Tool Theoetical Documentation, Vesion 00. Poete, E.P. and M.C. Hill, Documentation of UCODE, a compute code fo univesal invese modeling, U.S. Geological Suvey, Wate-Resouces Investigation Repot Santhi, C., J.G. Anold, J.R. Williams, W.A Dugas, R. Sinivasan, and L.M. Hauck, 01. Validation of the SWAT model on a lage ive basin with point and nonpoint souces: Jounal of the Ameican Wate Resouces Association 37(5): Shapley, A.N., C. Gay, C.A. Jones, and C.V. Cole, A simplified soil and plant phosphous model. II. Pediction of labile, oganic, and sobed P amounts, In: Neitsch, S.L., J.G. Anold, J.R. Kiniy, and J.R. Williams. Soil and Wate Assessment Tool Theoetical Documentation, Vesion 00. Sinivasan R., T.S. Ramanaayanan, J.G. Anold, and S.T. Bednaz, Lage aea hydologic modeling and assessment pat II: model application. Jounal of the Ameican Wate Resouces Association 34(1): USDA-NRCS Soil Suvey. Decembe 5, 02. < USEPA 02. STORET, Septembe 24th, 02. < Kikland, S.L. 01. Coupling site-scale fate and tanspot with wateshed-scale modeling to assess the cumulative effects of nutients fom decentalized onsite wastewate systems. Thesis, Coloado School of Mines. Lemonds, P.J. 03. Modeling pollution tanspot and fate to assess the effects of onsite wastewate systems on the Lake Dillon wateshed, Coloado. Thesis, Coloado School of Mines. 277