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A preferential flow leaching index
Author(s) -
McGrath Gavan Sean,
Hinz Christoph,
Sivapalan Murugesu
Publication year - 2009
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2008wr007265
Subject(s) - surface runoff , sorption , leaching (pedology) , infiltration (hvac) , environmental science , soil science , groundwater , vadose zone , soil water , hydrology (agriculture) , streams , flow (mathematics) , subsurface flow , environmental chemistry , chemistry , geology , geotechnical engineering , mechanics , ecology , meteorology , geography , computer network , physics , organic chemistry , adsorption , computer science , biology
The experimental evidence suggests that for many chemicals surface runoff and rapid preferential flow through the shallow unsaturated zone are significant pathways for transport to streams and groundwater. The signature of this is the episodic and pulsed leaching of these chemicals. The driver for this transport is the timing and magnitude of rainfall events which trigger rapid flow and the release of solute from a source zone, located near the soil surface. Based on these considerations we develop a conceptual model capable of reproducing many of the signatures of this rapid transport. This driver‐source‐trigger‐signature framework forms the basis of the development of a new leaching index which describes the potential for rapid solute transport by preferential flow or surface runoff. This preferential flow (PF) index is based upon soil and chemical parameters as well as the timing and magnitude of rainfall and preferential flow events. The PF index suggests that a chemical's potential to experience rapid transport increases as sorption strength increases, however, when an approximation to account for sorption kinetics is considered the PF index peaks at moderate sorption values. The model is sensitive to the timing and magnitude of rapid flow events, which may require existing data or infiltration models for their estimation.