A Java-based, object-oriented modeling system for southern African hydrology

Transactions of the ASABE

Volumn 49, Issue 5, 2006, Pages 1419-1433

  Kiker, Gregory A ^a   Clark, David J ^b   Martinez, Christopher J ^a   Schulze, Roland E ^b  

^a University of Florida   (United States)

^b UNIVERSITY OF KWAZULU NATAL   (South Africa)

Author keywords

ACRU2000; Hydrologic modeling; Java; Mgeni River watershed; Object oriented; South Africa; Water supply; Watershed

Indexed keywords

HYDROLOGIC MODELING; MGENI RIVER WATERSHED; ROOT MEAN SQUARED ERROR; UPSTREAM MANAGEMENT;

COMPUTER SIMULATION; HYDROLOGY; JAVA PROGRAMMING LANGUAGE; LAND USE; MATHEMATICAL MODELS; REGIONAL PLANNING;

OBJECT ORIENTED PROGRAMMING;

AGRICULTURAL CATCHMENT; HYDROLOGICAL MODELING; LAND USE; SIMULATION; SOFTWARE; STREAMFLOW; WATERSHED;

AFRICA; KWAZULU-NATAL; MGENI ESTUARY; SOUTH AFRICA; SOUTHERN AFRICA; SUB-SAHARAN AFRICA;

EID: 33845631141     PISSN: 21510032     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (70)

1. Abbot, M. B., J. C. Bathurst, J. A. Cunge, P. E. O'Connell, and J. Rasmussen. 1986a. An introduction to the European Hydrological System - Système Hydrologique Européen, SHE: 1. History and philosophy of a physically-based, distributed modelling system. J. Hydrology 87(1-2): 45-59.
2. Abbot, M. B., J. C. Bathurst, J. A. Cunge, P. E. O'Connell, and J. Rasmussen. 1986b. An introduction to the European Hydrological System - Système Hydrologique Européen, SHE: 2. Structure of a physically-based, distributed modelling system. J. Hydrology 87(1-2): 61-77.
3. Arnold, J. G., R. Srinivasan, R. S. Muttiah, and J. R. Williams. 1998. Large-area hydrologic modeling and assessment: Part I. Model development. J. American Water Resources Assoc. 34(1): 73-89.
4. Band, L. E., C. L. Tague, S. E. Brun, D. E. Tenenbaum, and R. A. Fernandes. 2000. Modeling watersheds as spatial object hierarchies: Structure and dynamics. Trans. GIS: 4(3): 181-196.
5. Beven, K. J. 1989. Changing ideas in hydrology: The case of physically-based models. J. Hydrology 105(1-2): 157-172.
6. Beven, K. J., and A. M. Binley. 1992. The future of distributed models: Model calibration and predictive uncertainty. Hydrol. Process. 6(3): 279-298.
7. Beven, K. J., and M. J. Kirkby. 1979. A physically based, variable contributing area model of basin hydrology. Hydrol. Sci. Bull. 24(1): 43-69.
8. Binley, A., K. Beven, and J. Elgy. 1989. A physically based model of heterogeneous hillslopes: 2. Effective hydraulic conductivities. Water Resour. Res. 25(6): 1227-1233.
9. Blaney, H. F., and W. D. Criddle. 1950. Determining water requirements in irrigated areas from climatological data. Technical Publication 96. Washington, D.C.: USDA-SCS.
10. Booch, G. 1991. Object-Oriented Design - With Applications. Redwood City, Cal.: Benjamin/Cummings.
11. Booch, G., J. Rumbaugh, and I. Jacobsen. 1998. Unified Modeling Language User Guide. Reading Mass.: Addison-Wesley.
12. Bromley, K. A. 1989. Land cove classes in the Mgeni River Catchment. Supplement to CSIR Report AAL 21. Pietermaritzburg, South Africa: University of Natal, Institute of Natural Resources.
13. Calver, A., and W. L. Wood. 1995. The Institute of Hydrology distributed model. In Computer Models of Watershed Hydrology, 595-626. V. P. Singh, ed. Highlands Ranch, Colo.: Water Resource Publications.
14. Campbell, K. L., G. A. Kiker, and D. J. Clark. 2001. Development and testing of a nitrogen and phosphorus process model for southern African water quality issues. ASAE Paper No. 012085. St. Joseph, Mich.: ASAE.
15. Clark, D. J., and J. C. Smithers. 2005. Hydrological decision support framework - Initial design. In Proc. 12th South African National Hydrology Symposium. Midrand, South Africa: South African National Chapter of the International Association of Hydrologic Sciences.
16. Clark, D. J., G. A. Kiker, and R. E. Schulze. 2001. Object-oriented restructuring of the ACRU agrohydrological modelling system. In Proc. 10th South African National Hydrology Symposium. Pietermaritzburg, South Africa: South African National Chapter of the International Association of Hydrologic Sciences.
17. DWAF and Umgeni Water. 1996. The Mgeni Catchment management plan - A framework for an integrated water management plan for the Mgeni Catchment. WOM U200/00/01/0196. Pretoria, South Africa: Department of Water Affairs and Forestry and Umgeni Water.
18. Dent, M. C., S. D. Lynch, and R. E. Schulze. 1989. Mapping mean annual and other rainfall statistics over southern Africa. Report 109/1/89. Pretoria, South Africa: Water Research Commission.
19. Donigan, A. S. D., B. R. Bicknell, and J. C. Imhoff. 1995. Hydrological simulation program - Fortran. In Computer Models of Watershed Hydrology, 395-442. V. P. Singh, ed. Highlands Ranch, Colo.: Water Resource Publications.
20. Freeze, R. A., and R. L. Harlan. 1969. Blueprint for a physically-based, digitally-simulated hydrologic response model. J. Hydrology 9(3): 237-258.
21. Grayson, R. B., I. D. Moore, and T. A. McMahon. 1992. Physically based hydrologic modelling: 2. Is the concept realistic? Water Resour. Res. 26(10): 2659-2666.
22. Hargreaves, G. H., and Z. A. Samani. 1982. Estimating potential evapotranspiration. J. Irrig. Drain. Eng. 108(IR3): 223-230.
23. Hargreaves, G. H., and Z. A. Samani. 1985. Reference crop evaporation from temperature. Applied Eng. in Agric. 1(2): 96-99.
24. Hjelmfelt, A. T. 1980. Curve number procedure as infiltration method. J. Hydraulics Div. ASCE 106(6): 1107-1111.
25. Jones, C. A., and J. R. Kiniry. 1986. CERES-Maize: A simulation model of maize growth and development. College Station, Texas: Texas A&M University Press.
26. Kienzle, S. W., S. A. Lorentz, and R. E. Schulze. 1997. Hydrology and water quality of the Mgeni Catchment. Report TT87/97. Pretoria, South Africa: Water Research Commission.
27. Kiker, G. A., and D. J. Clark. 2001a. The development of a Java-based, object-oriented modeling system for simulation of southern African hydrology. ASAE Paper No. 012030. St. Joseph, Mich.: ASAE.
28. Kiker, G. A., and D. J. Clark. 2001b. Testing and validation of a Java-based, object-oriented modeling system in the Mgeni River watershed, KwaZulu-Natal, South Africa. ASAE Paper No. 012031. St. Joseph, Mich.: ASAE.
29. Kiker, G. A., and D. J. Clark. 2001c. Development and testing of a natural vegetation, herbivore, and fire model for southern African rangeland management. ASAE Paper No. 017025. St. Joseph, Mich.: ASAE.
30. Kirchner, J. W. 2006. Getting the right answers for the right reasons Linking measurements, analysis, and models to advance the science of hydrology. Water Resour. Res. 42: W03S04, doi: 10.1029/2005WR004362.
31. Leavesley, G. H., and L. G. Stannard. 1995. The precipitation-runoff modeling system - PRMS. In Computer Models of Watershed Hydrology, 281-310. V. P. Singh, ed. Highlands Ranch, Colo.: Water Resource Publications.
32. Legates, D. R., and G. J. McCabe, Jr. 1999. Evaluating the use of "goodness-of-fit" measures in hydrologic and hydroclimatic model validation. Water Resour. Res. 35(1): 233-241.
33. Linacre, E. T. 1977. A simple formula for estimating evaporation rates in various climates, using temperature data alone. Agric. Meteorol. 18(6): 409-424.
34. Linacre, E. T. 1984. Unpublished manuscript. Sydney, Australia: School of Earth Sciences, Macquarie University.
35. Linacre, H. T. 1991. Unpublished manuscript. Sydney, Australia: School of Earth Sciences, Macquarie University.
36. Martinez, C. J., K. L. Campbell, M. D. Annable, and G. A. Kiker. An object-oriented hydrologic model for humid, shallow water-table environments. Submitted to J. Hydrology.
37. Nash, J. E., and J. V. Sutcliffe. 1970. River flow forecasting through conceptual models: Part 1. A discussion of principals. J. Hydrology 10(3): 282-240.
38. NWA 1998. National Water Act No. 36. Pretoria, South Africa: Government Printer.
39. Penman, H. L. 1948. Natural evaporation from open water, bare soil, and grass. Proc. Royal Society. London A 193(1032): 120-146.
40. Perks, L. A., R. E. Schulze, G. A. Kiker, M. J. C. Horan, and M. Maharaj. 1999. Preparation of climate data and information for application in impact studies of climate change over Southern Africa. Report to the South African Country Study on Climate Change. Pretoria, South Africa: Department of Environmental Affairs and Tourism.
41. Pike, A., and R. E. Schulze. 1995. AUTOSOILS: A program to convert ISCW soils attributes to variables usable in hydrological models. Pietermaritzburg, South Africa: University of KwaZulu-Natal, School of Bioresources Engineering and Environmental Hydrology.
42. Refsgaard, J.-C. 1997. Parameterisation, calibration, and validation of distributed hydrological models. J. Hydrology 198: 69-97.
43. Ritchie, J. T. 1972. A model for predicting evaporation from a row crop with incomplete cover. Water Resour. Res. 8(5): 1204-1213.
44. Rosenzweig, M. L. 1968. Net primary productivity of terrestrial communities: Prediction from climatological data. American Naturalist 102(923): 67-74.
45. Schmidt, E. J., and R. E. Schulze. 1987. Flood volume and peak discharge from small catchments in southern Africa, based on the SCS technique. Report TT/3/87. Pretoria, South Africa: Water Research Commission.
46. Schulze, R. E. 1975. Catchment evapotranspiration in the Natal Drakensburg. Unpublished PhD diss. Pietermaritzburg, South Africa: University of Natal, Department of Geography.
47. Schulze, R. E. 1984. Hydrological models for application to small rural catchments in southern Africa: Refinements and development. Report 63/2/84. Pretoria, South Africa: Water Research Commission.
48. Schulze, R. E. 1989. ACRU: Background, concepts, and theory. Report 154/1/89. Pretoria, South Africa: Water Research Commission.
49. Schulze, R. E. 1995. Hydrology and agrohydrology: A text to accompany the ACRU 3.00 agrohydrological modelling system. Report TT69/95. Pretoria, South Africa: Water Research Commission.
50. Schulze, R. E. 2004. Chapter 3: Determination of baseline land cover variables for applications in assessing land use impacts on hydrological responses in South Africa. In Development and Evaluation of an Installed Hydrological Modelling System, 37-50. R. E. Schulze and A. Pike, eds. Pretoria, South Africa: Water Research Commission.
51. Schulze, R. E., and W. J. George. 1987. A dynamic process-based, user-oriented model of forest effects on water yield. Hydrol. Process. 1(3): 293-307.
52. Schulze, R. E., and L. A. Perks. 2000. Assessment of the impact of climate change on hydrology and water resources in South Africa. Report to the South African Country Study on Climate Change. Pretoria, South Africa: Department of Environmental Affairs and Tourism.
53. Schulze, R. E., and J. C. Smithers. 2004. Chapter 3: The ACRU modelling system as of 2002: Background, concepts, structure, typical applications, and operations. In Modelling as a Tool in Integrated Water Resources Management: Conceptual Issues and Case Study Applications, 47-83. Report 749/1/02. R. E. Schulze, ed. Pretoria, South Africa: Water Research Commission.
54. Schulze, R. E., G. A. Kiker, and R. P. Kunz. 1993a. Global climate change and agricultural productivity in southern Africa. Global Environ. Change 3(4): 330-349.
55. Schulze, R. E., E. J. Schmidt, and J. C. Smithers. 1993b. SCS-SA user manual. ACRU Report 40. Pietermaritzburg, South Africa: University of Natal, Department of Agricultural Engineering.
56. Sivipalan, M., N. R. Viney, and C. G. Jeevaraj. 1996. Water and salt balance modelling to predict the effects of land use changes in forested catchments: 3. The large catchment model. Hydrol. Process. 10(3): 429-446.
57. Smithers, J. C., and R. E. Caldecott. 1993. Development and verification of hydrograph routing in a daily simulation model. Water SA 19(3): 263-267.
58. Smithers, J. C., and R. E. Schulze. 1995. ACRU Agrohydrological modelling system. Report TT70/95. Pretoria, South Africa: Water Research Commission.
59. SIRI. 1987. Memoirs on the agricultural natural resources of South Africa. Land Type Series. Pretoria, South Africa: Department of Agriculture and Water Supply, Soil and Irrigation Research Institute (now named the Agricultural Research Council - Institute for Soil, Climate and Water).
60. Steenhuis, T. S., M. Winchell, J. Rossing, J. A. Zollweg, and M. F. Walter. 1995. SCS Runoff equation revisited for variable-source runoff areas. J. Irrig. Drain. 121(3): 234-238.
61. Tarboton, K. C., and R. E. Schulze. 1992. Distributed hydrological modelling system for the Mgeni catchment. Report 234/1/92. Pretoria, South Africa: Water Research Commission.
62. Thornthwaite, C. W. 1948. An approach towards a rational classification of climate. Geogr. Rev. 38: 55-94.
63. USDA. 1985. Section 4: Hydrology. In National Engineering Handbook. Washington, D.C.: USDA Soil Conservation Service.
64. VanderKwaak, J. E., and K. Loague. 2001. Hydrologic-response simulations for the R-5 catchment with a comprehensive physics-based model. Water Resour. Res. 37(4): 999-1013.
65. Viessman, W., G. L. Lewis, and J. W. Knapp. 1989. Introduction to Hydrology. New York, N.Y.: Harper and Row.
66. Von Hoyningen-Huene, J. 1983. Die Interzeption des Niederschalges in landwirtschaftlichen Pflanzenbeständen. Deutscher Verband für Wasserwirtschaft und Kulturbau. Hamburg, Germany: Verlag Paul Parey. Schriften 57, 1-66.
67. Wang, J., T. A. Endreny, and J. M. Hassett. 2005a. A flexible modeling package for topographically based watershed hydrology. J. Hydrology 314: 78-91.
68. Wang, J., J. M. Hassett, and T. A. Endreny. 2005b. An object-oriented approach to the description and simulation of watershed-scale hydrologic processes. Comput. and Geosci. 31(4): 425-435.
69. Weddepohl, J. P. 1988. Design rainfall distributions for southern Africa. Unpublished MSc thesis. Pietermaritzburg, South Africa: University of Natal, Department of Agricultural Engineering.
70. Yang, L. 2006. Coupled simulation modeling of flatwoods hydrology, nutrient, and vegetation dynamics. PhD diss. Gainesville, Fla.: University of Florida, Department of Agricultural and Biological Engineering.