Hydrologic predictions in a changing environment: behavioral modeling

Abstract

Most hydrological models are valid at most only in a few places and cannot be rea-sonably transferred to other places or to far distant time periods. Transfer in space isdifficult because the models are conditioned on past observations at particular placesto define parameter values and unobservable processes that are needed to fully characterize the structure and functioning of the landscape. Transfer in time has to deal withthe likely temporal changes to both parameters and processes under future changedconditions. This remains an important obstacle to addressing some of the most urgentprediction questions in hydrology, such as prediction in ungauged basins and predictionunder global change. In this paper, we propose a new approach to catchment hydrological modeling, based on universal principles that do not change in time and that remainvalid across many places. The key to this framework, which we call behavioral mod-eling, is to assume that these universal and time-invariant organizing principles canbe used to identify the most appropriate model structure (including parameter values)and responses for a given ecosystem at a given moment in time. The organizing principles may be derived from fundamental physical or biological laws, or from empiricallaws that have been demonstrated to be time-invariant and to hold at many places andscales. Much fundamental research remains to be undertaken to help discover theseorganizing principles on the basis of exploration of observed patterns of landscapestructure and hydrological behavior and their interpretation as legacy effects of past co-evolution of climate, soils, topography, vegetation and humans. Our hope is thatthe new behavioral modeling framework will be a step forward towards a new visionfor hydrology where models are capable of more confidently predicting the behavior ofcatchments beyond what has been observed or experienced before