Hydrologic models are simplified, conceptual representations of a part of the hydrologic cycle. They are primarily used for hydrologic prediction and for understanding hydrologic processes. Two major types of hydrologic models can be distinguished:
- Stochastic Models. These models are black box systems, based on data and using mathematical and statistical concepts to link a certain input (for instance rainfall) to the model output (for instance runoff). Commonly used techniques are regression, transfer functions, neural networks and system identification. These models are known as stochastic hydrology models.
- Process-Based Models. These models try to represent the physical processes observed in the real world. Typically, such models contain representations of surface runoff, subsurface flow, evapotranspiration, and channel flow, but they can be far more complicated. These models are known as deterministic hydrology models. Deterministic hydrology models can be subdivided into single-event models and continuous simulation models.
Recent research in hydrologic modelling tries to have a more global approach to the understanding of the behaviour of hydrologic systems to make better predictions and to face the major challenges in water resources management
Surface water modelling
Runoff model (empirical)
These models use an empirical method to convert rainfall volume into runoff volume. An example is the Curve Number method.
The runoff curve number (also called a curve number or simply CN) is an empirical parameter used in hydrology for predicting direct runoff or infiltration from rainfall excess. It can be used with a unit hydrograph to derive the runoff rate from the direct runoff by convolution.
Runoff model (reservoir)
Hydrological transport model
These models describe the flow and routing of water once it has entered a river/stream system and the transport of dissolved or suspended material and debris in a river/stream. Examples include MIKE 11, MOHID, WAFLEX and DSSAM.
Distributed hydrological model
Distributed hydrological models are grid-cell based and take into account the spatial variability of meteorological input and other inputs like terrain, soils, vegetation and land use. In distributed hydrological models runoff generated in a grid cell is transported downstream through a grid cell to grid cell network using the local drain direction of each grid cell. Examples of distributed hydrological models are PCR-GLOBWB, DHVSM, HL-RDHM and the glacio-hydrological SPHY model. Cardenas  reported the use of non-parametric modelling and imprecise probabilities in a distributed rainfall model for landslide mapping.
Many models combine two of these types, for example HBV, which is combines an empirical runoff model and a hydrological transport model. Some models combine elements of surface water models and groundwater models, for example GSSHA, MIKE SHE, WEAP and RS MINERVE.
Agricultural hydro-salinity modelling
Agricultural hydro-salinity models like SaltMod, Swatre  and Drainmod  are models integrating hydrological factors like irrigation, evapotranspiration and groundwater flow to simulate the behavior of the water table and soil salinization and to assess agricultural engineering measures like watertable control and soil salinity control by subsurface drains, drainage by wells and salt leaching.
- Surface runoff
- Hydrology (agriculture)
- Groundwater model
- Watertable control
- Water quality
- Soil salinity control
- International trade and water
- WaterGAP global hydrological and water use model
- Rushton, K.R., 2003, Groundwater Hydrology: Conceptual and Computational Models. John Wiley and Sons Ltd. ISBN 0-470-85004-3
- United States Department of Agriculture (1986). Urban hydrology for small watersheds (PDF). Technical Release 55 (TR-55) (Second ed.). Natural Resources Conservation Service, Conservation Engineering Division.
- RainOff  a rainfall-runoff model based on the concept of a nonlinear reservoir.
- Vijay P. Singh,, Computer Models of Watershed Hydrology, Water Resource Publications, pgs. 563-594 (1995)
- Cardenas, IC (2008). "Non-parametric modeling of rainfall in Manizales City (Colombia) using multinomial probability and imprecise probabilities. Modelación no paramétrica de lluvias para la ciudad de Manizales, Colombia: una aplicación de modelos multinomiales de probabilidad y de probabilidades imprecisas". Ingenieria e Investigación 28 (2).
- "SaltMod: A tool for interweaving of irrigation and drainage for salinity control". In: W.B.Snellen (ed.), Towards integration of irrigation and drainage management. Special report, pp. 41–43. International Institute for Land Reclamation and Improvement (ILRI), Wageningen, The Netherlands. On line: 
- Swatre agro-hydro-salinity model
- Drainmod agro-hydro-salinity model
- Polygonal agro-hydro-salinity-groundwater model SahysMod