Developments in hydrological modeling can be broadly classified as belonging to two eras,  the pre-computer era and the post computer era.  Historical highlights of the pre-computer era include the rational method (First hydrological model, Mulvany, 1850), regression models, unit hydrograph method (Sherman, 1932), infiltration theories (Green & Ampt, 1911; Horton, 1933; Philip, 1954), extreme value theory (Gumbel, 1941), and  kinematic wave theory (Lighthill & Whitham, 1955).  In late 1940’s came the analog models (now outdated) where the analogy between water flow and electricity flow has been used. 

In the computer era, developments in hydrological modelling took place as a result of advances in computing capabilities, advances in methodologies (non-linearities, scaling  etc.), remote sensing, GIS and the Web.  Highlights of the computer era include the Tank model (Sugawara, 1956), Stanford watershed model (Crawford and Linsley, 1966), Xinanjiang model (Zhao, 1977, 1984; Zhao and Liu, 1995), HEC series (USACE, 1960’s  onwards), linear cascade model (Nash, 1957, 1958, 1959, 1960), linear  channel (Dooge, 1959), variable infiltration capacity (VIC) model (Wood et al, 1992) among others.  They all belong to the conceptual type of models.  Physics-based models using the laws of  conservation of mass, momentum and energy with various types of simplifications and different types of solution schemes and domain discretizations  led to better understanding of the fluid mechanics and hydraulics components of hydrology.   Although many examples of ‘physics-based models’ can be found in the literature many such  models end up as data driven models due to unavailability of high resolution data for calibration.  The closest to a real physics-based model may be the Système Hydrologique Europèen (SHE) Model). 

More recently, attention has shifted to data driven models that include Regression models, Stochastic models that lead to time series analysis, Kalman filtering, different types of artificial neural networks, support vector machines, genetic algorithms and genetic programming, fuzzy logic models, neuro-fuzzy models, dynamical systems approach type models that use concepts of  chaos theory, among others.   Some data driven models use concepts of artificial intelligence.

In this paper, some applications of recent hydrological models and modeling techniques including guiding principles for the choice of a model as well as the challenges for future which include data issues, modeling issues, parameter calibration issues, scale issues etc. will be addressed.

A. W. Jayawardena, a retired professor with over 40 years of experience in the fields of hydrology, water resources and environmental engineering in academia, government, consulting engineers and international organizations.  He is a Chartered Engineer, a Fellow of the UK Institution of Civil Engineers, a Fellow of the Hong Kong Institution of Engineers and a Life Member of the American Society of Civil Engineers.  At present, he is an Adjunct Professor in the Department of Civil Engineering of the University of Hong Kong (HKU) where he has been teaching for many years, and a Visiting Professor in the Department of Civil Engineering of Chu Hai College of Higher Education in Hong Kong.  In the past he has been a Technical Advisor to the Research and Development Centre of Nippon Koei Co. Ltd (Consulting Engineers), Japan, Research and Training Advisor to the International Centre for Water Hazard and Risk Management (ICHARM) under the auspices of UNESCO, Japan, and concurrently a Professor in the National Graduate Institute for Policy Studies (GRIPS), Japan, a Guest Professor of Beijing Normal University, China, a Visiting Professor of Hohai University, China, Honorary Professor in the Department of Statistics and Actuarial Sciences of the University of Hong Kong and a Visiting Professor of Tsinghua University of China, and an Adjunct Professor of Vellore Institute of Technology, India. 

Jayawardena's research interests are in the broad area of hydro-environment.  The diversity of his  research contributions in this broad area comes from topics such as distributed catchment modelling using finite elements, dispersion in open channel flows, moisture transport through partially saturated porous media, secondary flows in curved channels, stochastic analysis of rainfall data, chaotic dynamics of hydro-meteorological time series, moving finite elements for convective dominant transport problems, artificial neural networks and genetic algorithms in hydrology, inter-rill sediment delivery and rainfall kinetic energy, Xinanjiang model and its modifications, basin scale hydrology coupled with atmospheric processes, red tide prediction, fuzzy logic systems, support vector machines, and climate change.  He has over 175 refereed publications which are well cited.  His research supervision  includes 8 Ph.D's, and over 70 M.Phil/M.Sc's.  

His international profile includes participation in various activities of UNESCO, IUGG, UNEP, WWAP, WWDR, IPCC etc.  His awards include the ASCE Environmental and Water Resources Institute (EWRI) Visiting International Fellow (2002) and the International Award of the Japan Society of Hydrology and Water Resources (2013).  He has authored the book "Environmental and Hydrological Systems Modelling" published by Taylor and Francis Group and CRC Press in 2014.  He has also carried out specialist consultancy work for various consulting engineering companies and the Drainage Services Department of HKSAR Government.