Abstract
Historical development of hydrology had three major milestones: descriptive, utilitarian, and scientific. New hydrologic disciplines are emerging at present. Hydrologic processes are investigated by five deterministic, stochastic, and combined deterministic-stochastic approaches. Hydrologic diversities stem from trends in water resources, complexities of processes and environments, and quantity and quality of basic data. Evolution from single-purpose, single-water source and single structure to multiple purpose, source, and structure approaches to the development of water resources highly affected research and application of utilitarian hydrology. Four classical statistical techniques of hydrology (sampling of samples, frequency distribution, correlation, and testing of hypotheses) were supplemented by spatialtemporal stochastic processes during the last three decades. Simple precipitation-runoff responses are being replaced by complex distributed rainfall-runoff models. Trends in water resources require new types of research and application of research results for the 21st century. Many basic questions of physical hydrology require answers, and a critical review of models which use a large number of parameters. Stress in research may well shift from shape to scale aspects of rainfall-runoff models. Historical extrapolation of application of unit hydrograph from floods to all flows, from small to larger catchments, and from humid to arid regions, need a careful re-evaluation. Taking into account the relationships of temporal input, state and output processes would increase the reliability of water-resources decisions. Study of tendency, intermittency, periodicity, and stochasticity of hydrologic temporal processes need physical supports for inferred properties. Spatial models should cover in detail the spatial distribution of parameters, changes in correlation in space of a point process with the other point processes, and the relationship of spatial correlation to the series time interval, distance and azymuth, with physical backing of statistically derived results.
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References
Abbott, M. B., Bathurst, J. C., Cunge, J. A., O'Connell, P. E., and Rasmussen, J., 1986, An Introduction to the European Hydrological Systems—Système Hydrologique Europeén, ‘SHE’, 1. History and philosophy of a physically-based, distributed modelling system, J. Hydrol. 87, 45–59; 2. Structure of a physically-based, distributed modelling system, J. Hydrol. 87, 61–77.
Bevan, K., 1989, Changing ideas in hydrology—The case of physically based models, J. Hydrol. 105, 157–172.
Freeze, R. A., 1980, A stochastic-conceptual analysis of rainfall-runoff processes on a hillslope, Water Resour. Res. 16, 391–408.
Guerrero-Salazar, P. and Yevjevich, V., 1975, Analysis of drought characteristics by the theory of runs, Colorado State Univ. Hydrol. paper No. 80.
Gomide, F. L. S., 1975, Range and deficit analysis using Markov chains, Colorado State Univ. Hydrol. paper No. 79.
Hipel, K. W., 1985, The series analysis in perspective, Water Res. Bull. (Amer. Water Res. Ass.) 21(4), 609–624.
Shenandoah Watershed Study: Calibration of a topography-based, variable contributing area hydrological model to a small forested catchment, Water Resour. Res. 21, 1841–1850.
Ibbitt, R. P., 1972, Effects of random data errors on the parameter values for a conceptual model, Water Resour. Res. 8, 70–78.
Kelman, J., 1977, Stochastic modeling of hydrologic, inter mittent daily processes, Colorado State Univ. Hydrol. paper No. 89.
Klemes, V., 1986, Dilettantism in hydrology—Transition or destiny? Water Resour. Res. 22(9), 177S-188S.
Pregram, G. G. S., Salas, J. D., Boes, D. C., and Yevjevich, V., 1980, Stochastic properties of water storage, Colorado State Univ. Hydrol. paper No. 100.
Richardson, W. C., 1977, A model of stochastic structure of daily precipitation over an area, Colorado State Univ. Hydrol. paper No. 91.
Rogers, P. P. and Fiering, M. B., 1986, Use of systems analysis in water management, Water Resour. Res. 22(9), 146S-158S.
Sorooshian, S., and Gupta, V. K., 1983, Automatic calibration of conceptual rainfall-runoff models: The question of parameter observability and uniquesness, Water Resour. Res. 19, 260–268.
Todorovic, P., and Yevjevich, V., 1969, Stochastic process of precipitation, Colorado State Univ. Hydrol. paper No. 35.
Waymire, E., and Gupta, V. K., 1981, The mathematical structure of rainfall representations: 1. A review of the stochastic rainfall models. Water Resour. Res. 17(5), 1261–1272; 2. A review of the theory of point processes, Water Resour. Res. 17(5), 1273–1285; 3. Some applications of the point process theory to rainfall processes, Water Resour. Res. 17(5), 1287–1294.
Woolhiser, A. D. and Roldan, J., 1982, Stochastic daily precipitation models 2. A comparison of distributions of amounts, Water Resour. Res. 18(5), 1461–1468.
Yevjevich, V., and Harmancioĝlu, B. N., 1985, Past and future of analysis of water resources time series, Water Resour. Bull. (Amer. Water Resour. Ass.) 21(4), 625–633.
Yevjevich, V., 1987, Stochastic models in hydrology, J. Stoch. Hydrol. Hydraul. 1(1), 17–36.
Yevjevich, V. and Harmancioĝlu, B. N., 1987, Some reflections on the future of hydrology, Water for the Future: Hydrology in Perspective, Proceedings of the Rome Symposium, April 1987, IAHS Publ. No. 164, pp. 405–414.
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Yevjevich, V. Tendencies in hydrology research and its applications for 21st century. Water Resour Manage 5, 1–23 (1991). https://doi.org/10.1007/BF00422036
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DOI: https://doi.org/10.1007/BF00422036