Parsimonious modeling of hydrologic responses in engineered watersheds: Structural heterogeneity versus functional homogeneity

Water Resources Research

Volumn 46, Issue 4, 2010, Pages

  Basu, Nandita B ^a,b   Rao, P S C ^a,c   Winzeler, H Edwin ^c,d   Kumar, Sanjiv ^a   Owens, Phillip ^c   Merwade, Venkatesh ^a  

^a PURDUE UNIVERSITY   (United States)

^b UNIVERSITY OF IOWA   (United States)

^c PURDUE UNIVERSITY   (United States)

^d Materials Matter Inc   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CALIBRATION; EXPONENTIAL FUNCTIONS; LAGRANGE MULTIPLIERS; LAND USE; SOIL MOISTURE; SOILS;

AVAILABLE SOIL WATERS; FUNCTIONAL HOMOGENEITY; HYDROLOGIC RESPONSE; INTENSIVE MANAGEMENT; PARAMETER CALIBRATION; PARSIMONIOUS MODELING; STRUCTURAL HETEROGENEITY; THRESHOLD EXCEEDANCE;

WATERSHEDS;

DRAINAGE BASIN; HETEROGENEITY; HYDROGRAPH; HYDROLOGICAL MODELING; HYDROLOGICAL RESPONSE; LAND USE; PARAMETERIZATION; PARSIMONY ANALYSIS; SOIL WATER; SPATIAL VARIATION; THRESHOLD; WATERSHED;

INDIANA; UNITED STATES;

EID: 77951069141     PISSN: 00431397     EISSN: None     Source Type: Journal    
DOI: 10.1029/2009WR007803     Document Type: Article

References (94)

1. Abbott, M. B., J. C. Bathurst, J. A. Cunge, P. E. Oconnell, and J. Rasmussen (1986), An introduction to the European Hydrological System-Systeme Hydrologique Europeen, "SHE", 2: Structure of a physically based distributed modeling system, J. Hydrol., 87(1-2), 61-77, doi:10.1016/0022- 1694(86)90115-0.
2. Akay, O., and G. A. Fox (2007), Experimental investigation of direct connectivity between macropores and subsurface drains during infiltration, Soil Sci. Soc. Am. J., 71, 1600-1606, doi:10.2136/sssaj2006.0359. (Pubitemid 350202653)
3. Alexander, R. B., R. A. Smith, and G. E. Schwarz (2000), Effect of stream channel size on the delivery of nitrogen to the Gulf of Mexico, Nature, 403, 758-761, doi:10.1038/35001562. (Pubitemid 30111834)
4. Algoazany, A. S. (2006), Longterm effects of agricultural chemicals and management practices on water quality in a subsurface drained watershed, Ph.D. dissertation, Univ. of Ill. at Urbana-Champaign, Urbana.
5. Allen, R. G., L. S. Pereira, M. Smith, D. Raes, and J. L. Write (2005), FAO-56 dual crop coefficient method for estimating evaporation from soil and application extensions, J. Irrig. Drain. Eng., 131, 2-13, doi:10.1061/(ASCE) 0733-9437(2005)131:1(2). (Pubitemid 40191067)
6. Arabi, M., R. S. Govindaraju, and M. M. Hantush (2006), Cost-effective allocation of watershed management practices using a genetic algorithm, Water Resour. Res., 42, W10429, doi:10.1029/2006WR004931. (Pubitemid 44859722)
7. Arnold, J. G., and P. M. Allen (1999), Automated methods for estimating baseflow and ground water recharge from streamflow records, J. Am. Water Resour. Assoc., 35, 411-424, doi:10.1111/j.1752-1688.1999. tb03599.x.
8. Arnold, J. G., R. Srinivasan, R. S. Muttiah, and J. R. Williams (1998), Large area hydrologic modeling and assessment, part I: Model development, J. Am. Water Resour. Assoc., 34, 73-89, doi:10.1111/j.1752-1688.1998.tb05961.x. (Pubitemid 28190080)
9. Atkinson, S. E., R. A. Woods, and M. Sivapalan (2002), Climate and landscape controls on water balance model complexity over changing timescales, Water Resour. Res., 38(12), 1314, doi:10.1029/2002WR001487.
10. Atkinson, S. E., M. Sivapalan, R. A. Woods, and N. R. Viney (2003), Dominant physical controls on hourly flow predictions and the role of spatial variability: Mahurangi catchment, New Zealand, Adv. Water Resour., 26, 219-235, doi:10.1016/S0309-1708(02)00183-5. (Pubitemid 36238575)
11. Balland, V., J. A. P. Pollacco, and P. A. Arp (2008), Modeling soil hydraulic properties for a wide range of conditions, Ecol. Modell., 219, 300-316, doi:10.1016/j.ecolmodel.2008.07.009.
12. Band, L. E., D. J. Peterson, S. W. Running, J. C. Coughlan, R. Lammers, J. Dungan, and R. Nemani (1991), Forest ecosystem processes at the watershed scale: Basis for distributed simulation, Ecol. Modell., 56, 171-196, doi:10.1016/0304-3800(91)90199-B.
13. Beven, K. (1995), Linking parameters across scales-Subgrid parameterizations and scale-dependent hydrological models, Hydrol. Processes, 9, 507-525, doi:10.1002/hyp.3360090504.
14. Beven, K. (2001), How far can we go in distributed hydrological modelling?, Hydrol. Earth Syst. Sci., 5, 1-12.
15. Beven, K., and A. Binley (1992), The future of distributed models: Model calibration and uncertainty prediction, Hydrol. Processes, 6, 279-298, doi:10.1002/hyp.3360060305.
16. Bloschl, G. (2001), Scaling in hydrology, Hydrol. Processes, 15, 709-711, doi:10.1002/hyp.432.
17. Bloschl, G., and M. Sivapalan (1995), Scale issues in hydrological modeling: A review, Hydrol. Processes, 9, 251-290, doi:10.1002/hyp.3360090305.
18. Bonell, M. (1998), Selected challenges in runoff generation research in forests from the hillslope to the headwater drainage basin scale, J. Am. Water Resour. Assoc., 34, 765-785, doi:10.1111/j.1752-1688.1998. tb01514.x.
19. Breuer, L., et al. (2009), Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM). I: Model intercomparison with current land use, Adv. Water Resour., 32, 129-146, doi:10.1016/j. advwatres.2008.10.003.
20. Cerdan, O., Y. Le Bissonnais, G. Govers, V. Lecomte, K. van Oost, A. Couturier, C. King, and N. Dubreuil (2004), Scale effects on runoff from experimental plots to catchments in agricultural areas in Normandy, J. Hydrol., 299, 4-14, doi:10.1016/j.jhydrol.2004.02.017. (Pubitemid 39350852)
21. Cho, H. D., and F. Olivera (2009), Effect of the spatial variability of land use, soil type, and precipitation on streamflows in small watersheds, J. Am. Water Resour. Assoc., 45, 673-686, doi:10.1111/j.1752-1688.2009.00315.x.
22. Committee on Environment and Natural Resources (2000), Integrated Assessment of Hypoxia in the Northern Gulf of Mexico, Natl. Sci. and Technol. Counc., Washington, D. C.
23. Cooke, R. A., S. Badiger, and A. M. Garcia (2001), Drainage equations for random and irregular tile drainage systems, Agric. Water Manage., 48, 207-224, doi:10.1016/S0378-3774(00)00136-0. (Pubitemid 32449290)
24. Dehotin, J., and I. Braud (2008), Which spatial discretization for distributed hydrological models? Proposition of a methodology and illustration for medium to large-scale catchments, Hydrol. Earth Syst. Sci., 12, 769-796.
25. Dingman, S. L. M. (1994), Physical Hydrology, MacMillan, New York.
26. Donner, S. D., and C. J. Kucharik (2008), Corn-based ethanol production compromises goal of reducing nitrogen export by the Mississippi River, Proc. Natl. Acad. Sci. U. S. A., 105(11), 4513-4518, doi:10.1073/ pnas.0708300105.
27. Evans, R. O., and N. R. Fausey (1999), Effects of inadequate drainage on crop growth and yield, in Agricultural Drainage, Agron. Monogr. Ser., vol.38, edited by R. W. Skaggs and J. Van Schilfgaarde, pp. 13-54, Am. Soc. of Agron., Madison, Wis.
28. Famiglietti, J. S., and E. F. Wood (1994), Multiscale modeling of spatially variable water and energy balance processes, Water Resour. Res., 30, 3061-3078, doi:10.1029/94WR01498. (Pubitemid 293013)
29. Farmer, D., M. Sivapalan, and C. Jothityangkoon (2003), Climate, soil, and vegetation controls upon the variability of water balance in temperate and semiarid landscapes: Downward approach to water balance analysis, Water Resour. Res., 39(2), 1035, doi:10.1029/2001WR000328.
30. Fink, M., P. Krause, S. Kralisch, U. Bende-Michl, and W. A. Flugel (2007), Development and application of the modelling system J2000-S for the EU-water framework directive, Adv. Geosci., 11, 123-130.
31. Gassman, P. W., M. R. Reyes, C. H. Green, and J. G. Arnold (2007), The Soil and Water Assessment Tool: Historical development, applications, and future research directions, Trans. ASABE, 50(4), 1211-1250.
32. Gordon, L. J., G. D. Peterson, and E. M. Bennett (2008), Agricultural modifications of hydrological flows create ecological surprises, Trends Ecol. Evol., 23(4), 211-219, doi:10.1016/j.tree.2007.11.011.
33. Grayson, R., I. Moore, and T. McMahon (1992a), Physically based hydrologic modeling: 1. A terrain-based model for investigative purposes, Water Resour. Res., 28(10), 2639-2658, doi:10.1029/92WR01258. (Pubitemid 23376342)
34. Grayson, R. B., I. D. Moore, and T. A. McMahon (1992b), Physically based hydrologic modeling: 2. Is the concept realistic?, Water Resour. Res., 28(10), 2659-2666, doi:10.1029/92WR01259. (Pubitemid 23376343)
35. Gupta, H. V., S. Sorooshian, and P. O. Yapo (1998), Toward improved calibration of hydrologic models: Multiple and non-commensurable measures of information, Water Resour. Res., 34, 751-763, doi:10.1029/ 97WR03495.
36. Richards (2004), Fractal-based scaling and scale-invariant dispersion of peak concentrations of crop protection chemicals in rivers, Environ. Sci. Technol., 38, 2995-3003, doi:10.1021/es030522p. (Pubitemid 38691697)
37. Harter, T., and J. W. Hopmans (2004), Role of vadose zone flow processes in regional scale hydrology: Review, opportunities and challenges, in Unsaturated Zone Modeling: Progress, Challenges and Applications, edited by R. A. Feddes, G. H. De Rooij, and J. C. van Dam, pp. 179-210, Kluwer Acad., Dordrecht, Netherlands.
38. Haws, N. W., B. Liu, C. W. Boast, P. S. C. Rao, E. J. Kladivko, and D. P. Franzmeier (2004), Spatial variability and measurement scale of infiltration rate on an agricultural landscape, Soil Sci. Soc. Am. J., 68, 1818-1826.
39. Holling, C. S. (1973), Resilience and stability of ecosystems, Annu. Rev. Ecol. Syst., 4, 1-23, doi:10.1146/annurev.es.04.110173.000245.
40. Hoosebeck, M. R., R. G. Amundson, and R. B. Bryant (1999), Pedological modeling, in Handbook of Soil Science, edited by M. A. Sumner, pp. E77-E116, CRC Press, Boca Raton, Fla.
41. Hopmans, J. W., and G. H. Schoups (2005), Soil water flow at different spatial scales, in Encyclopedia of Hydrologic Sciences, vol.2, edited by M. G. Anderson and F. J. McDonnell, pp. 1-11, John Wiley, New York.
42. Jain, S. K., and K. P. Sudheer (2008), Fitting of Hydrologic Models: A close look at the Nash-Sutcliffe index, J. Hydrol. Eng., 13(10), 981-986, doi:10.1061/(ASCE)1084-0699(2008)13:10(981).
43. Jana, R. B., B. P. Mohanty, and E. P. Springer (2008), Multi-scale Bayesian neural networks for soil water content estimation, Water Resour. Res., 44, W08408, doi:10.1029/2008WR006879.
44. Kalita, P. K., R. A. C. Cooke, S. M. Anderson, M. C. Hirschi, and J. K. Mitchell (2007), Subsurface drainage and water quality: The Illinois experience, Trans. ASABE, 50(5), 1651-1656.
45. Kladivko, E. J., L. C. Brown, and J. L. Baker (2001), Pesticide transport to subsurface tile drains in humid regions of North America, Crit. Rev. Sci. Technol., 31(1), 1-62, doi:10.1080/20016491089163.
46. Klemeš, V. (1983), Conceptualization and scale in hydrology, J. Hydrol., 65, 1-23, doi:10.1016/0022-1694(83)90208-1.
47. Krause, P. (2002), Quantifying the impact of land use changes on the water balance of large catchments using the J2000 model, Phys. Chem. Earth, 27, 663-667.
48. Krause, P., D. P. Boyle, and F. Base (2005a), Comparison of different efficiency criteria for hydrological model assessment, Adv. Geosci., 5, 89-97.
49. Krause, P., S. Kralisch, and W. A. Flugel (Eds.) (2005b), Model integration and development of modular modelling systems, Adv. Geosci., 4, 1-2.
50. Krysanova, V., and J. G. Arnold (2008), Advances in ecohydrological modeling with SWAT: A review, Hydrol. Sci. J., 53(5), 939-947, doi:10.1623/hysj.53.5.939.
51. Krysanova, V., D. I. Muller-Wohlfeil, and A. Becker (1998), Development and test of a spatially distributed hydrological water quality model for mesoscale watersheds, Ecol. Modell., 106, 261-289, doi:10.1016/ S0304-3800(97)00204-214
52. Krysanova, V., F. Hattermann, and F. Wechsung (2005), Development of the ecohydrological model SWIM for regional impact studies and vulnerability assessment, Hydrol. Processes, 19, 763-783, doi:10.1002/ hyp.5619.
53. Kumar, S., and V. Merwade (2009), Impact of watershed subdivision and soil data resolution on model calibration and parameter uncertainty using SWAT, J. Am. Water Resour. Assoc., 45, 1179-1196, doi:10.1111/ j.1752-1688.2009.00353. x.
54. Kumar, S., J. Kam, K. Thurner, and V. Merwade (2007), Exploring the link between streamflow trends and climate change in Indiana, USA, Eos Trans. AGU, 88(52), Fall Meet. Suppl., Abstract GC33A-0953.
55. Larose, M., G. C. Heathman, L. D. Norton, and B. Engel (2007), Hydrologic and atrazine simulation of the Cedar Creek Watershed using the SWAT model, J. Environ. Qual., 36, 521-531, doi:10.2134/jeq2006.0154. (Pubitemid 46446963)
56. Li, Z., and Y.-K. Zhang (2008), Multi-scale entropy analysis of Mississippi River flow, Stochastic Environ. Res. Risk Assess., 22, 507-512, doi:10.1007/s00477-007-0161-y. (Pubitemid 351596004)
57. Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges (1994), A simple hydrologically based model of land-surface water and energy fluxes for general-circulation models, J. Geophys. Res., 99(D7), 14,415- 14,428, doi:10.1029/94JD00483.
58. Liu, J., et al. (2007), Complexity of coupled human and natural systems, Science, 317, 1513-1516, doi:10.1126/science.1144004. (Pubitemid 47417424)
59. Madsen, H. (2003), Parameter estimation in distributed hydrological catchment modeling using automatic calibration with multiple objectives, Adv. Water Resour., 26, 205-216, doi:10.1016/S0309-1708(02)00092-1. (Pubitemid 36093693)
60. Marcé, R., C. E. Ruiz, and J. Armengol (2008), Using spatially distributed parameters and multi-response objective functions to solve parameterization of complex applications of semi-distributed hydrological models, Water Resour. Res., 44, W02436, doi:10.1029/2006WR005785. (Pubitemid 351442512)
61. Mark, D. M., and F. Csillag (1989), The nature of boundaries on "areaclass" maps, Cartographia, 26, 65-78.
62. McCuen, R. H., Z. Knight, and A. G. Cutler (2006), Evaluation of the Nash-Sutcliffe efficiency index, J. Hydrol. Eng., 11(6), 597-602, doi:10.1061/(ASCE)1084-0699(2006)11:6(597). (Pubitemid 44594112)
63. McDonnell, J. J., et al. (2007), Moving beyond heterogeneity and process complexity: A new vision for watershed hydrology, Water Resour. Res., 43, W07301, doi:10.1029/2006WR005467. (Pubitemid 350194455)
64. Merz, R., and G. Bloschl (2009), A regional analysis of event runoff coefficients with respect to climate and catchment characteristics in Austria, Water Resour. Res., 45, W01405, doi:10.1029/2008WR007163.
65. National Climatic Data Center (2004), Weather data, http://www.ncdc. noaa.gov, Asheville, N. C.
66. National Resources Conservation Service (2006), Major land resource regions report, USDA Agric. Handbk. 296, U.S. Dep. of Agric., Washington, D. C.
67. Ogden, F. L., J. Garbrecht, P. A. DeBarry, and L. E. Johnson (2001), GIS and distributed models II: Modules, interfaces and models, J. Hydrol. Eng., 6(6), 515-523, doi:10.1061/(ASCE)1084-0699(2001)6:6(515). (Pubitemid 33038453)
68. Pinter, N., B. S. Ickes, J. H. Wlosinski, and R. R. van der Ploeg (2006), Trends in flood stages: Contrasting results from the Mississippi and Rhine River systems, J. Hydrol., 331, 554-566, doi:10.1016/j. jhydrol.2006.06.013.
69. Qi, F., and A. X. Zhu (2003), Knowledge discovery from soil maps using inductive learning, Int. J. Geogr. Inf. Sci., 17(8), 771-795, doi:10.1080/ 13658810310001596049. (Pubitemid 37431647)
70. Quisenberry, V. L., and R. E. Phillips (1976), Percolation of surface applied water into the field, Soil Sci. Soc. Am. J., 40, 484-489.
71. Radcliff, D. E., and T. C. Rasmussen (2000), Soil water movement, in Handbook of Soil Science, edited by M. E. Sumner, pp. A87-A127, CRC Press, Boca Raton, Fla.
72. Refsgaard, J. C., and B. Storm (1995), MIKE SHE, in Computer Models of Watershed Hydrology, edited by V. P. Singh, pp. 809-846, Water Resour. Publ., Highland Ranch, Colo.
73. Rinaldo, A., G. Botter, E. Bertuzzo, A. Uccelli, T. Settin, and M. Marani (2006a), Transport at basin scale: 1. Theoretical framework, Hydrol. Earth Syst. Sci., 10, 19-30.
74. Rinaldo, A., G. Botter, E. Bertuzzo, A. Uccelli, T. Settin, and M. Marani (2006b), Transport at basin scale: 2. Applications, Hydrol. Earth Syst. Sci., 10, 31-48.
75. Rogowski, A. S., and J. K. Wolf (1994), Incorporating variability into soil map unit delineations, Soil Sci. Soc. Am. J., 58, 163-174.
76. Savenije, H. H. G. (2008), The art of hydrology, Hydrol. Earth Syst. Sci. Discuss., 5, 3157-3168.
77. Scavia, D., N. N. Rabalais, R. E. Turner, D. Justic, and W. Wiseman Jr. (2003), Predicting the response of Gulf of Mexico hypoxia to variations in Mississippi River nitrogen load, Limnol. Oceanogr., 48(3), 951-956.
78. Scavia, D., and K. A. Donnelly (2007), Reassessing hypoxia forecasts for the Gulf of Mexico, Environ. Sci. Technol., 41(23), 8111-8117, doi:10.1021/es0714235. (Pubitemid 350224420)
79. Schilling, K. E., and M. Helmers (2008), Effect of subsurface drainage tiles on streamflow in Iowa agricultural watersheds: Exploratory hydrograph analysis, Hydrol. Processes, 22, 4497-4506, doi:10.1002/hyp.7052.
80. Sivapalan, M. (2003), Process complexity at hillslope scale, process simplicity at the watershed scale: Is there a connection?, Hydrol. Processes, 17, 1037-1041, doi:10.1002/hyp.5109.
81. Sivapalan, M. (2005), Pattern, process and function: Elements of a new unified hydrologic theory at the catchment scale, in Encyclopedia of Hydrologic Sciences, vol.13, edited by M. G. Anderson, pp. 193-219, John Wiley, New York.
82. Skaggs, R. W., M. A. Breve, A. T. Mohammad, J. E. Parsons, and J. W. Gilliam (1995), Simulation of drainage water quality with DRAINMOD, Irrig. Drain. Syst., 9, 259-277, doi:10.1007/BF00880867.
83. Son, K., and M. Sivapalan (2007), Improving model structure and reducing parameter Uncertainty in conceptual water balance models through the use of auxiliary data, Water Resour. Res., 43, W01415, doi:10.1029/ 2006WR005032.
84. Stillman, J. S., N. W. Haws, R. S. Govindaraju, and P. S. C. Rao (2006), A model for transient flow to a subsurface tile drain under macroporedominated flow conditions, J. Hydrol., 317, 49-62, doi:10.1016/j. jhydrol.2005.04.028.
85. Stisen, S., K. H. Jensen, I. Sandholt, and D. I. F. Grimes (2008), A remote sensing driven distributed hydrological model of the Senegal River basin, J. Hydrol., 354, 131-148, doi:10.1016/j.jhydrol.2008.03.006.
86. Todini, E. (2007), Hydrological catchment modeling: Past, present and future, Hydrol. Earth Syst. Sci., 11, 468-482.
87. Vache, K. B., and J. J. McDonnell (2006), A process-based rejectionist framework for evaluating catchment runoff model structure, Water Resour. Res., 42, W02409, doi:10.1029/2005WR004247.
88. Wagener, T., N. McIntyre, M. J. Lees, H. S. Wheater, and H. V. Gupta (2003), Towards reduced uncertainty in conceptual rainfall-runoff modeling: Dynamic identifiability analysis, Hydrol. Processes, 17, 455-476, doi:10.1002/hyp.1135. (Pubitemid 36234589)
89. Wagener, T., M. Sivapalan, P. Troch, and R. Woods (2007), Catchment classification and hydrologic similarity, Geogr. Compass, 1, 901-931, doi:10.1111/j.1749-8198.2007.00039.x.
90. Wessolek, G., W. H. M. Duijnisveld, and S. Trinks (2008), Hydropedotransfer functions HPTFs) for predicting annual percolation rate on a regional scale, J. Hydrol., 356, 17-27, doi:10.1016/j. jhydrol.2008.03.007.
91. Wigmosta, M. S., L. W. Vail, and D. P. Lettenmaier (1994), A distributed hydrology vegetation model for complex terrain, Water Resour. Res., 30, 1665-1679, doi:10.1029/94WR00436.
92. Zehe, E., and M. Sivapalan (2009), Threshold behavior in hydrological systems as (human) geo-ecosystems: Manifestations, controls, implications, Hydrol. Earth Syst. Sci., 13, 1273-1297.
93. Zhang, L., N. Potter, K. Hickel, Y. Zhang, and Q. Shao (2008), Water balance modeling over variable time scales based on the Budyko framework-Model development and testing, J. Hydrol., 360, 117-131, doi:10.1016/j.jhydrol.2008. 07.021.
94. Zhu, A. X., L. E. Band, B. Dutton, and T. J. Nimlos (1996), Automated soil inference under fuzzy logic, Ecol. Modell., 90, 123-145, doi:10.1016/ 0304-3800(95)00161-171