The Trials and Tribulations of Modeling and Measuring in Surface Water Hydrology

  • Soroosh Sorooshian
Conference paper
Part of the NATO ASI Series book series (volume 46)

Abstract

Historically speaking, modeling of the precipitation runoff process got its start in the engineering side of hydrology. The development of these models was primarily driven by societal needs for water resources structural design purposes (i. e., dams and reservoirs, aqueducts, etc.), and operational requirements, such as flood forecasting. Most such models are “lumped”, rather than “distributed”, and their structures (i. e., process equations) are influenced by availability of observations and data constraints. Precipitation runoff models vary in their levels of complexity, ranging from the rational formula, the Soil Conservation Service (SCS) curve number model (SCS, 1964), the antecedent precipitation index (API) method in the “simple” category to the more complex Stanford-type conceptual rainfall-runoff (CRR) models and, finally to the physically based distributed models such as HEC-1 (Feldman, 1995) and KINEROS (Woolhiser et al., 1990; Smith et al., 1995). The spatial and temporal scale of their application varies from model to model, but ranges from tens to thousands of square miles and from minutes and hours to a few days, respectively.

Keywords

Microwave Radar Expense Geophysics Defend 

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References

  1. Bathurst JC, PE O’Connell (1992) Future of distributed modeling: the Systeme Hydrologique Europeen, Hydrologic Processes, 6, 3:265–278.CrossRefGoogle Scholar
  2. Dawdy DR, T O’Donnell (1965) Mathematical models of catchment behavior, Journal of Hydraulic Division, American Society of Civil Engineering, 91 (HY4):113–137.Google Scholar
  3. Dickinson RE, A Henderson-Sellers, PJ Kennedy, MF Wilson (1986) Biosphere-Atmosphere Transfer Scheme (BATS) for the NCAR Community Climate Model, NCAR Technical Note, NCAR/TN-275+STR.Google Scholar
  4. Duan Q, (1991) A global optimization strategy for efficient and effective calibration of hydrologic models, Ph.D. Dissertation, Dept. of Hydrology and Water Resources, The University of Arizona, Tucson, Arizona, 371 p.Google Scholar
  5. Duan Q, S Sorooshian, VK Gupta (1992) Effective and efficient global optimization for conceptual rainfall-runoff models, Water Resources Research, 28, 4:1015–1031.CrossRefGoogle Scholar
  6. Famiglietti JS, EF Wood (1994) Multiscale modeling of spatially variable water and energy balance processes, Water Resources Research, 30, 11:3061–3078.CrossRefGoogle Scholar
  7. Faures JM, DC Goodrich, DA Woolhiser, S Sorooshian (1995) Impact of small-scale spatial rainfall variability on runoff simulation, Journal of Hydrology, 173:309–326.CrossRefGoogle Scholar
  8. Feldman AD (1995) HEC-1 Flood Hydrograph Package, Chapter 4 in Computer Models of Watershed Hydrology, Edited by VP Singh, pp. 119–150.Google Scholar
  9. FIFE (First ISLSCP Field Experiment, Special issue reprinted from Journal of Geophysical Research, 97, D17:18343–19109.Google Scholar
  10. Goodrich DC (1990) Geometric simplification of a distributed rainfall-runoff model over a range of basin scales, Ph.D. Dissertation, Dept. of Hydrology and Water Resources, The University of Arizona, Tucson, Arizona, 361 p.Google Scholar
  11. Goodrich DC, DA Woolhiser (1994) Comment on “Physically based hydrologic modeling 1:a terrain-based model for investigative purposes,” by RB Grayson, ID Moore, TA McMahon, Water Resources Research, 30, 3:8485–847.CrossRefGoogle Scholar
  12. Goodrich DC, TJ Schmugge, TJ Jackson, CL Unkrich, TO Keefer, R Parry, LB Bach, SA Amer (1994) Runoff simulation sensitivity to remotely sensed initial soil water content, Water Resources Research, 30, 5:1393–1405.CrossRefGoogle Scholar
  13. Goodrich DC, JM Faures, DA Woolhiser, LJ Lane, S Sorooshian (1995) Measurement and analysis of small-scale convective storm rainfall variability, Journal of Hydrology, 173:283–308.CrossRefGoogle Scholar
  14. Gupta VK, S Sorooshian (1983) Uniqueness and observability of conceptual rainfall-runoff model parameters: the percolation process examined, Water Resources Research, 19, 1:269–276.CrossRefGoogle Scholar
  15. Kustas WP, DC Goodrich (1994) Preface to the special session on Monsoon’90, Water Resources Research, 30, 5:1211–1225.CrossRefGoogle Scholar
  16. Lau WK-M, YC Sud, J-H Kim (1995) Intercomparison of hydrologic processes in global climate models, NASA Technical Memorandum 104617, 161 p.Google Scholar
  17. Loague K (1990) R-5 revisited, 2:re-evaluation of a quasi-physically based rainfall-runoff model with supplemental information, Water Resources Research, 26, 5:973–987.Google Scholar
  18. Loague K, RA Freeze (1985) A comparison of rainfall-runoff modeling techniques on small upland catchments, Water Resources Research, 21, 2:229–248.CrossRefGoogle Scholar
  19. Michaud J (1992) Rainfall-runoff modeling of flash floods in semi-arid watersheds, Ph.D. Dissertation, Dept. of Hydrology and Water Resources, The University of Arizona, Tucson, Arizona, 318 p.Google Scholar
  20. Michaud J, S Sorooshian (1994a) Comparison of simple versus complex distributed runoff models on a midsized semiarid watershed, Water Resources Research, 30, 3:593–605.CrossRefGoogle Scholar
  21. Michaud J, S Sorooshian (1994b) Effect of rainfall-sampling errors on simulations of desert flash floods, Water Resources Research, 30, 10:2765–2775.CrossRefGoogle Scholar
  22. Naef F (1981) Can we model the rainfall-runoff process today? Hydrological Sciences Bulletin, 26, 3:281–289.CrossRefGoogle Scholar
  23. Schmugge T, TJ Jackson, WP Kustas, R Roberts, R Parry, DC Goodrich, SA Amer, MA Weltz, Push broom microwave observations of surface soil moisture in Monsoon ’90, Water Resources Research, 30,5:1321–1327.Google Scholar
  24. Sellers PJ, Y Mintz, YC Sud, A Dalcher (1986) A simple biosphere model (SiB) for use within general circulation models, Journal of Atmospheric Sciences, 43:505–531.CrossRefGoogle Scholar
  25. Smith RE, DC Goodrich, DA Woolhiser, JR Simmons (1994) Comment on “Physically based hydrologic modeling, 2: is the concept realistic?” by RB Grayson, ID Moore, TA McMahon, Water Resources Research, 30, 3:851–854.CrossRefGoogle Scholar
  26. Smith, RE, DC Goodrich, DA Woolhiser, CL Unkrich (1995) KINEROS--A Kinematic Runoff and Erosion Model, Chapter 2 in Computer Models of Watershed Hydrology, Edited by VP Singh, pp. 697–732.Google Scholar
  27. Soil Conservation Service (1964) Hydrology: part 1—watershed planning, SCS National Engineering Handbook, Sec. 4, U.S. Dept. of Agriculture, Soil Conservation Service, Washington, D.C.Google Scholar
  28. Sorooshian S (1983) Surface water hydrology: on-line estimation, Reviews of Geophysics and Space Physics, 21, 3:706–721.CrossRefGoogle Scholar
  29. Sorooshian S, VK Gupta, JL Fulton (1983) Evaluation of maximum likelihood parameter estimation techniques for conceptual rainfall-runoff models: influence of calibration data variability and length on model credibility, Water Resources Research, 19, 1:251–259.CrossRefGoogle Scholar
  30. Sorooshian S, Q Duan, VK Gupta (1993) Calibration of rainfall-runoff models: application of global optimization to the Sacramento soil moisture accounting model, Water Resources Research, 29, 4:1185–1194.CrossRefGoogle Scholar
  31. WCRP/IGPO (1994) Project for Intercomparison of Land-Surface Parameterization Schemes (PILPS), in Soil Moisture Simulation: A Report of the RICE and PILPS Workshop, IGPO Publication Series #14, December.Google Scholar
  32. Wilcox BP, WJ Rawls, DL Brakensiek, JR Wight (1990) Predicting runoff from rangeland catchments: a comparison of two models, Water Resources Research, 26, 10:2401–2410.CrossRefGoogle Scholar
  33. Woolhiser DA, RE Smith, DC Goodrich (1990) A kinematic runoff and erosion manual, Documentation and User Manual, Rep. ARS 77, U.S. Dept. of Agriculture, Agricultural Research Service, Washington, D.C., 130 p.Google Scholar
  34. Woolhiser DA, RE Smith, J-V Giraldez (1996) Effects of spatial variability of saturated hydraulic conductivity on Hortonian overland flow, Water Resources Research, 32, 3:671–678.CrossRefGoogle Scholar
  35. Woolhiser DA (1996) Search for physically based runoff model--a hydrologic El Dorado?, Journal of Hydraulic Engineering, 122, 3:122–129.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Soroosh Sorooshian
    • 1
  1. 1.Dept. of Hydrology and Water ResourcesThe University of ArizonaTucsonUSA

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