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Mariotti, A., Landreau, A., & Simon, B. (1988). 15 N isotope biogeochemistry and natural denitrification process in groundwater: Application to the chalk aquifer of northern france. Geochimica Et Cosmochimica Acta, 52(7), 1869. Mariotti, A. (1981). Experimental determination of nitrogen kinetic isotope fractionation: Some principles illustration for the denitrification and nitrification processes. Plant and Soil, 62(3), 413. Martienssen, M., & Schops, R. (1999). Population dynamics of denitrifying bacteria in a model biocommunity. Water Research, 33(3), 639. McCray, J., Kirkland, S., Siegrist, R., & Thyne, G. (2005). Model parameters for simulating fate and transport of on-site wastewater nutrients. Groundwater, 43(4), 628- 639. Meyer-Baese, A. (2009). Lecture notes ISC5935 : Data mining. Unpublished manuscript. Miller, J. A. (1997). Ch 6 : Hydrogeology of forida. In A. F. Randazzo, & D. S. Jones (Eds.), The geology of florida. (Illustrated ed., pp. 69--88). Gainesville: University Press of Florida. Mulvaney, R. L. (1988). Evaluation of nitrogen-15 tracer techniques for direct measurement of denitrification in soil: III. laboratory studies. Soil Science Society of America Journal, 52(5), 1327-1332. National Research Council (U.S.) Panel on Nitrates. (1978). Nitrates : An environmental assessment : A report. Washington: National Academy of Sciences. New Jersey Department of Environmental Protection. (1999). Guidance for 50 or more realty improvement certifications. Retrieved November 14th, 2009, from http://www.state.nj.us/dep/dwq/pdf/50guide.pdf Oehler, F., Durand, P., Bordenave, P., Saadi, Z., & Salmon-Monviola, J. (2009). Modelling denitrification at the catchment scale. The Science of the Total Environment, 407(5), 1726. Oehler, F., Bordenave, P., & Durand, P. (2007). Variations of denitritication in a farming catchment area. Agriculture, Ecosystems Environment, 120(2-4), 313-324. Oehler, F., Rutherford, J., & Coco, G. (2010). The use of machine learning algorithms to design a generalized simplified denitrification model. Biogeosciences, 7(10), 3311-3332. Otis, R. J. (2007). Estimates of nitrogen loading to the groundwater from onsite waste water treatement systems in the wekiva study area. No. Task 2 Report). Florida: Florida Department of Health. Retrieved from http://www.doh.state.fl.us/Environment/ostds/wekiva/task2/FinalReport_06-07.pdf 203
Ozden, T., & Muhammetoglu, H. (2008). Predicting nitrogen concentration in groundwater beneath unsewered areas: Case study of liman region in antalya, turkey. London, UK: No longer published by Elsevier. Pabich, W. J. (2001). Denitrification of anthropogenic nitrogen in groundwater : Measurement and modeling using stable isotopic and mass balance approaches. Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering). Retrieved from http://dspace.mit.edu/handle/1721.1/8751?show=full PAYNE, W. (1991). A Review of methods for Field-Measurements of denitrification.. [Amsterdam]: Elsevier Science. Pfenning, K. S., & McMahon, P. B. (1997). Effect of nitrate, organic carbon, and temperature on potential denitrification rates in nitrate-rich riverbed sediments. Journal of Hydrology, 187(3-4), 283. Pinay, G., Roques, L., & Fabre, A. (1993). Spatial and temporal patterns of denitrification in a riparian forest. The Journal of Applied Ecology, 30(4), 581. Postma, D., Boesen, C., Kristiansen, H., & Larsen, F. (1991). Nitrate reduction in an unconfined sandy aquifer: Water chemistry, reduction processes, and geochemical modeling. Water Resources Research, 27(8), 2027. Poulin, P., Pelletier, E., & Saint-Louis, R. (2007). Seasonal variability of denitrification efficiency in northern salt marshes: An example from the st. lawrence estuary. Marine Environmental Research, 63(5), 490. Pribyl, A. L., McCutchan, J. H., Lewis, W. M., & Saunders, J. F. (2005). Whole-system estimation of denitrification in a plains river: A comparison of two methods. Biogeochemistry, 73(3), 439. Puckett, L. J. (2004). Hydrogeologic controls on the transport and fate of nitrate in groundwater beneath riparian buffer zones: Results from thirteen studies across the united states. Water Science and Technology, 49(3), 47. Puckett, L. J., & Cowdery, T. K. (2002). Transport and fate of nitrate in a glacial outwash aquifer in relation to groundwater age, land use practices, and redox processes. Journal of Environmental Quality., 31(3), 782. Rivett, M. O., Smith, J. W. N., Buss, S. R., & Morgan, P. (2007). Nitrate occurrence and attenuation in the major aquifers of england and wales. The Quarterly Journal of Engineering Geology, 40, 335. Rivett, M. O., Buss, S. R., Morgan, P., Smith, J. W. N., & Bemment, C. D. (2008). Nitrate attenuation in groundwater: A review of biogeochemical controlling processes. Water Research, 42(16), 4215. 204
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THE FLORIDA STATE UNIVERSITY ARTS A
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To my Dad, Mum and Brother iii
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Dr. Stephen Kish for his words of e
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1.5. Evaluation of methods to estim
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2.5.8. Texture 8 (Silt Loam).......
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4.2.6. Texture 6 (Sandy Clay Loam).
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LIST OF TABLES Table 1.1 Additional
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LIST OF FIGURES Figure 1.1 Oxidatio
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Figure 2.51 8-20-84; Denitrificatio
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Figure 3.6 Probability plot (Textur
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Three statistical methods were used
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• Microbial biomass/ plant uptake
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Figure 1.1 Oxidation of organic car
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possibility of denitrification (Smi
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50ºC (36ºF - 122ºF) (Brady & Wei
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1.2.6. Salinity Salinity is a known
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1.3.1. The Acetylene inhibition met
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Among the variety of successful met
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a first-order decay process. The ma
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look at the data shows that it fail
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Da is the denitrification rate (mg
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a simple linear regression of organ
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of the annual N2O emission and deni
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easons for the limitation of the mo
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Table 1.2 Continued dC / dt Organic
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also implies that the transferabili
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CHAPTER TWO 2. LINEAR REGRESSION An
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an improvement on the earlier attem
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2.3. Texture Table 2.1 Soil Textura
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2.3.5. Texture 5 (Sand) The surfici
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2.3.10. Texture 10 (Silty Clay Loam
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Textural Class Table 2.2 Coefficien
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R_d_n (kgN ha-1 d-1) R_d_n (kgN ha-
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2.4.3. Texture 3 (Loam) Texture 3 c
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R_d_n (kgN ha-1 d-1) Texture 3 Temp
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R_d_n (kgN ha-1 d-1) 6 5 4 3 2 1 0
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2.4.7. Texture 7 (Sandy Loam) The S
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Texture 7 Temperature 12 : Denitrif
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Rdn (kgN ha-1 d-1) Texture 9 Temper
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Rdn (kgN ha-1 d-1) 16 12 8 4 0 Text
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2.5. Break down by Texture, Tempera
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8-20-34 (n=3), 8-20-84 (n=4), 8-20-
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Subsets 9-7-100, 9-25-100 and 9-30-
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Texture 10 Temperature 25 WFP 100 :
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a significant linear relationship b
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Rdn (kgN ha-1 d-1) Rdn (kgN ha-1 d-
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C9 Rdn (kgN ha-1 d-1) 12 10 8 6 4 2
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Rdn (kgN ha-1 d-1) Texture 10 Tempe
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2.6.11. Texture 11 (Silt) No data a
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2.7.6. Texture 6 (Sandy Clay Loam)
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Rdn (kgN ha-1 d-1) Texture 8 Tepera
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Rdn (kgN ha-1 d-1) Texture 8 Tepera
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2.8. Summary The correlation coeffi
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where, M is the slope of the linear
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Hence for the first set of equation
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3.2.2. Texture-Temperature-WFP-pH T
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Organic Carbon (%) Actual Rdn Gener
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R dn Results C = 9.389 - 3.210* M -
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The actual denitrification values f
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Eigenvalue 1.5 1.4 1.3 1.2 1.1 1.0
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R indicated by the significant code
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R Table 4.5 Comparison of actual an
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Table 4.8 Texture 2, Comparison of
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Table 4.11 Comparison of actual and
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The two equations are applied to th
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R R dn dn = - 0.05 ∗Temperature (
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Table 4.19 Texture 8, Linear multi-
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Table 4.20 Continued Actual Rdn Pre
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Once again the equations developed
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4.2.11. Texture 11 (Silt) No data a
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CHAPTER FIVE 5. ANALYSIS USING NEUR
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Figure 5.2 McCulloch-Pitts (Meyer-B
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developed. In order to control over
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Eventually the final set of network
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5.4.4. Texture 5 (Sand) Figure 5.5
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5.4.6. Texture 8 (Silt Loam) Figure
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Page 175 and 176: CHAPTER SIX 6. USE OF ISOTOPES TO E
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Page 179 and 180: Figure 6.1 Estimation of Nitrate Lo
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Page 183 and 184: δ 18 O 20.00 18.00 16.00 14.00 12.
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Page 187 and 188: 7.2. Multiple Regression Three equa
Page 189 and 190: Table 7.4 Multi-Regression and Neur
Page 191 and 192: 8.3. Main Results The linear equati
Page 193 and 194: isotopes can be particularly useful
Page 195 and 196: APPENDIX B CONVERSION SHEET FOR DEN
Page 197 and 198: iv. v. vi. Given in the dataset: 1.
Page 199 and 200: Conversion from −3 −1 g N m d t
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Page 203 and 204: Texture 4 Variable Count N* Mean St
Page 205 and 206: Texture 10 Variable Count N* Mean S
Page 207 and 208: Texture-Temperature-WFP-pH Code Equ
Page 209 and 210: 09-15-25-09 Rdn = 0.0106688*OC + 0.
Page 211 and 212: Code Rdn - OC Code Rdn-WFP Code Rdn
Page 213 and 214: - Code Rdn - OC Code Rdn - pH Code
Page 215 and 216: - Code Rdn - OC Code Rdn - NO3 Conc
Page 217 and 218: Code Rdn - OC Code Rdn - pH 08-25-9
Page 219 and 220: REFERENCES Almasri, M. N., & Kaluar
Page 221 and 222: Fellows, C., Hunter, H., Eccleston,
Page 223: King, D., & Nedwell, D. B. (1985).
Page 227 and 228: Smith, R., Bohlke, J., Garabedian,
Page 229 and 230: Zhu, J., Liu, G., Han, Y., Zhang, Y
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