Geoscience Reference
In-Depth Information
Smith P. J., Beven K. J. and Tawn J. A. Detection of structural inadequacy in process-based hydrological models:
A particle-filtering approach. Water Resources Research , 44(1):W01410, DOI:10.1029/2006WR005205,
2008b.
Smith P. J., Tawn J. and Beven K. J. Informal likelihood measures in model assessment: Theoretic development
and investigation. Advances in Water Resources , 31:1087-1100, 2008a.
Smith R. E. Approximate soil water movement by kinematic characteristics. Soil Science Society of America
Journal , 47:3-8, 1983.
Smith R. E., Corradini C. and Melone F. A conceptual model for infiltration and redistribution in crusted soils.
Water Resources Research , 35:1385-1393, 1999.
Smith R. E. and Goodrich D. C. Model for rainfall excess patterns on randomly heterogeneous areas. ASCE
Journal of Hydrologic Engineering , 5:355-362, 2000.
Smith R. E., Goodrich D. C., Woolhiser D. A. and Unkrich C. L. KINEROS - a KINematic runoff and EROSion
model. In Singh V. P., editor, Computer Models of Watershed Hydrology , pages 697-732. Water Resource
Publications, Highlands Ranch, CO, 1995.
Smith R. E. and Parlange J.-Y. A parameter efficient infiltration model. Water Resources Research , 14:533-538,
1978.
Smith R. E. and Woolhiser D. A. Overland flow on an infiltrating surface. Water Resources Research , 7(4):899,
1971.
Smith R. N. B., Blyth E. M., Finch J. W., Goodchild S., Hall R. L. and Madry S. Soil state and surface hydrology
diagnosis based on MOSES in the Met Office Nimrod nowcasting system. Meteorological Applications ,
13:89-109, 2006.
Smith
T.
J.
and
Marshall
L.
A.
Bayesian
methods
in
hydrologic
modeling:
A
study
of
recent
ad-
vancements
in
Markov
Chain
Monte
Carlo
techniques. Water Resources Research ,
44:W00B05,
DOI:10.1029/2007WR006705, 2008.
Snell J. D. and Sivapalan M. Application of the meta-channel concept: Construction of the meta-channel
hydraulic geometry for a natural channel. Hydrological Processes , 9:485-505, 1995.
Solomatine D. P. and Dulal K. N. Model trees as an alternative to neural networks in rainfall-runoff modelling.
Hydrological Sciences Journal , 48(3):399-411, 2003.
Sorooshian S., Duan Q. and Gupta V. K. Calibration of the SMA-NWSRFS conceptual rainfall-runoff model
using global optimisation. Water Resources Research , 29:1185-1194, 1992.
Sorooshian S. and Gupta V. K. Model calibration. In Singh V. P., editor, Computer Models of Watershed
Hydrology , pages 23-68. Water Resource Publications, Highlands Ranch, CO, 1995.
Sorooshian S., Gupta V. K. and Fulton J. L. Evaluation of maximum likelihood parameter estimation tech-
niques for conceptual rainfall-runoff models: Influence of calibration data variability and length on model
credibility. Water Resources Research , 19:251-259, 1983.
Soulsby C., Malcolm R., Ferrier R. C., Helliwell R. C. and Jenkins A. Isotope hydrology of the Allt a'Mharcaidh
catchment, Cairngorms, Scotland: Implications for hydrological pathways and residence times. Hydrological
Processes , 14:747-762, 2000.
Soulsby C., Petry J., Brewer M. J., Dunn S. M., Otta B. and Malcolm I. A. Identifying and assessing uncertainty
in hydrological pathways: A novel approach to end member mixing in a Scottish agricultural catchment.
Journal of Hydrology , 274:109-128, 2003.
Spear R. C., Grieb T. M. and Shang N. Parameter uncertainty and interaction in complex environmental
models. Water Resources Research , 30:3159-3170, 1994.
Srinivasan R., Zhang X. and Arnold J. SWAT ungauged: Hydrological budget and crop yield predictions in
the upper Mississippi river basin. Transactions of the ASABE , 53:1533-1546, 2010.
Stadler D., Wunderli H., Auckenthaler A. and Fl uhler H. Measurement of frost-induced snowmelt runoff in
a forest soil. Hydrological Processes , 10:1293-1304, 1996.
Stedinger J. R., Vogel R. M., Lee S. U. and Batchelder R. Appraisal of the generalized likelihood uncertainty
estimation (GLUE) method. Water Resources Research , 44:W00B06, DOI:10.1029/2008WR006822,
2008.
Steel M. E., Black A. R., Werrity A. and Littlewood I. G. Reassessment of flood risk for Scottish rivers using
synthetic runoff data. In Hydrological Extremes: Understanding, Predicting, Mitigating , Int. Assoc. Sci.
Hydrol. Publ. No. 255:209-215, Wallingford, UK, 1999.
Search WWH ::




Custom Search