Abstract
Stream runoff is perhaps the most poorly represented process in ecohydrological stochastic soil moisture models. Here we present a rainfall-runoff model with a new stochastic description of runoff linked to soil moisture dynamics. We describe the rainfall-runoff system as the joint probability density function (PDF) of rainfall, soil moisture and runoff forced by random, instantaneous jumps of rainfall. We develop a master equation for the soil moisture PDF that accounts explicitly for a general state-dependent rainfall-runoff transformation. This framework is then used to derive the joint rainfall-runoff and soil moisture-runoff PDFs. Runoff is initiated by a soil moisture threshold and a linear progressive partitioning of rainfall based on the soil moisture status. We explore the dependence of the PDFs on the rainfall occurrence PDF (homogeneous or state-dependent Poisson process) and the rainfall magnitude PDF (exponential or mixed-exponential distribution). We calibrate the model to 63 years of rainfall and runoff data from the Upper Little Tennessee watershed (USA) and show how the new model can reproduce the measured runoff PDF.
Original language | English |
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Article number | 20150389 |
Pages (from-to) | 1-26 |
Number of pages | 26 |
Journal | Proceedings of the Royal Society A: Mathematical, Physical, and Engineering Sciences |
Volume | 471 |
Issue number | 2183 |
Early online date | 28 Oct 2015 |
DOIs | |
Publication status | Published - 8 Nov 2015 |
Bibliographical note
FundingThis work was supported by the Agriculture and Food Research Initiative of the USDA National Institute of Food and Agriculture (2011-67003-30222); National Science Foundation (grants CBET-1033467, EAR-1331846, FESD-1338694 and EAR-1316258); and by the US Department of Energy (DOE) Office of Biological and Environmental Research (BER) Terrestrial Carbon Processes Program (DE-SC0006967).
Acknowledgements
We thank Gaby Katul and Larry Band for early discussions. Thanks to Duke University and UNC Chapel Hill for the Keohane Professorship support of J.J.M. during the preparation of this manuscript. Data sets were provided by the Climate and Hydrology Database Projects, a partnership between the Long-Term Ecological Research program and the US Forest Service Pacific Northwest Research Station, Corvallis, Oregon. Significant funding for these data was provided by the National Science Foundation Long-Term Ecological Research program and the USDA Forest Service.
Keywords
- stochastic models in hydrology
- watershed rainfall-runoff model
- nonlinear thresholds
- antecedent soil moisture
- marked Poisson
- state-dependent Poisson process
- WATER-CONTROLLED ECOSYSTEMS
- STORM SURFACE RUNOFF
- HYDROLOGIC PROCESSES
- HEADWATER CATCHMENT
- ACTIVE-ROLE
- GENERATION
- VEGETATION
- CLIMATE
- BALANCE
- INFILTRATION