| Session Description |
Hydrology witnessed an enormous growth in the twentieth century, thanks to technological and methodological advances. Invention of powerful computers, remote sensors, geographic information systems, and worldwide networking have facilitated extensive data collection, better data sharing, formulation of sophisticated methods, and development of highly complex models. Despite this growth, however, there remain numerous challenges in performing hydrologic teaching, research, and practice. Two serious issues, among others, are dominating the discussions on the state of hydrology: (1) hydrologic models currently being developed are much more complex (having too many parameters and requiring too much data) than perhaps needed; and (2) despite their complexities, these models neither perform sufficiently well for the same situations they are developed nor allow ‘translation’ of results from one specific situation to another. These issues are being addressed in many different forms in the hydrologic literature: parameter estimation and uncertainty (including the ‘equifinality’ problem), model simplification and dominant processes concept, catchment classification framework, scale and scale-invariance, and predictions in ungaged basins. What is missing, however, are cohesive efforts to bring these mostly disparate forms together towards finding common grounds in our research that would provide better ways to address the current and future hydrologic challenges, especially with the role played by global climate change. This provides the motivation to bring a collective perspective on these issues, which this session is intended to achieve. Abstracts that address the supplementary and complementary role of each of these issues with respect to the others and their integration are especially encouraged. |
