|

|
Soil–Vegetation–Atmosphere Transfer Schemes and Large-Scale Hydrological Models
Edited by A. J. Dolman, A. J. Hall, M. L. Kavvas, T. Oki & J. W. Pomeroy
IAHS Publication no. 270 (published July 2001) in the IAHS Series of Proceedings and Reports
ISBN 1-901502-61-9; 372 + x pp.; price £ 59.50
|
Soil–vegetation–atmosphere interactions determine, to a large extent, the global climate and the behaviour of the hydrological cycle. Model predictions thus depend critically on adequate parameterization of this interaction. This volume represents a "state of the art" in Soil–Vegetation–Atmosphere Transfer (SVAT) modelling in the hydrological community; it contains 48 papers presented at a symposium on SVAT schemes held during the Sixth IAHS Scientific Assembly (Maastricht, July 2001).
Several key issues in SVAT models are poorly parameterized or simply not well enough understood. Current SVAT schemes include increasingly complex descriptions of the physical mechanisms governing land surface processes requiring large numbers of soil and land surface parameters controlling the vertical fluxes. The underlying rationale is that improved process representation will result in parameters which are easier to measure or estimate, and in improved model performance and robustness. However, this is not necessarily so. Studies show that characterizing surface properties is fraught with difficulties, as determining representative parameterizations is non-trivial due to our inability to accurately measure land surface properties. Hence, data assimilation, whereby measurements are integrated with models, is increasingly used to keep hydrological models on track. Remote sensing of the state of the land surface plays is important in efforts to improve data assimilation. However, these issues are particularly difficult for snow-covered areas, where vegetation communities are strongly coupled with patterns of snow accumulation and snowmelt.
This book is organized into five sections:
- Han Dolman, Alan Hall, Levent Kavvas, Taikan Oki & John Pomeroy
Preface, v-vi
- General SVAT Modelling
- Eleanor Blyth
Relative influence of vertical and horizontal processes in large-scale water and energy balance modelling, 3-10
- A. J. Dolman, M. Soet, B. J. J. M. Van Den Hurk, R. J. M. Ijpelaar & R. J. Ronda
The representation of the seasonal hydrological cycle in a regional climate model in west Europe, 11-18
- Wonsik Kim, Yasushi Agata, Shinjiro Kanae, Taikan Oki & Katumi Musiake
Hydrological simulation by SiB2-Paddy in the Chao Phraya River basin, Thailand, 19-26
- Alain Pietroniro, Eric D. Soulis, Ken Snelgrove & Nick Kouwen
A framework for coupling atmospheric and hydrological models, 27-34
- Angel Utset & Gilberto Lopez
Regional mechanistic estimations of sugar-cane water use, 35-40
- Tetsuo Kobayashi, Shuh Matsuda, Hideyuki Nagai & Jun’ichi Tesima
A bucket with a bottom hole (BBH) model of soil hydrology, 41-45
- Tosiyuki Nakaegawa & Masato Sugi
Impact of soil moisture movement schemes in a SVATS on the global climate of an AGCM, 47-52
- Koji Tamai
Estimation model for litter moisture content ratio on forest floor, 53-57
- Zongxue Xu, Jingyu Li & Kazumasa Ito
Development of the evaporation component for the physically-based distributed tank model, 59-62
- SVAT and Precipitation Runoff Modelling
- Parameter Estimation for Large-Scale Hydrological Models
- Yong Nam Yoon, Jae Soo Lee, Chulsang Yoo & Jae Hyun Ahn
An analysis of the variation in hydrological conditions in the Korean peninsula due to global warming, 119-124
- Dawen Yang, Shinjiro Kanae, Taikan Oki & Katumi Musiake
Expanding distributed hydrological modelling to the continental scale, 125-134
- Li Lan
A physically-based rainfall–runoff model and distributed dynamic hybrid control inverse technique, 135-142
- Petra Döll, Frank Kaspar & Bernhard Lehner
Calibration of a global hydrological model against measured discharge, 143-149
- L. Phil Graham, Göran Lindström, Björn Bringfelt, Marie Gardelin, Stefan Gollvik, Sten Bergström & Patrick Samuelsson
Using conceptual hydrological modelling to develop better sub-grid variability in the Rossby Centre Regional Atmospheric Model, 151-158
- A. W. Jayawardena & S. P. P. Mahanama
Daily river discharge prediction using GCM generated atmospheric data, 159-165
- Shenglian Guo, Jinxing Wang & Jin Yang
A semi-distributed hydrological model and its application in a macroscale basin in China, 167-174
- Lev Kuchment
Parameterization of sub-grid effects in a large-scale hydrological model, 175-181
- Huaxia Yao & Michio Hashino
A completely-formed distributed rainfall–runoff model for the catchment scale, 183-190
- Junichi Yoshitani, M. L. Kavvas & Z.-Q. Chen
Coupled regional-scale hydrological–atmospheric model for the study of climate impact on Japan, 191-198
- David C. Garen, Joachim Geyer, Andreas H. Schumann & Danny Marks
Spatially-distributed snowmelt, water balance and streamflow modelling for a large mountainous catchment: Boise River, Idaho, USA, 199-207
- M. Ouedraogo, J. E. Paturel, G. Mahé, E. Servat, A. Dezetter & D. Conway
Influence de la nature et de l’origine des données sur la modélisation hydrologique de grands bassins versants en Afrique de l’Ouest, 209-214
- Data Assimilation in Large-Scale Hydrological Models
M. F. McCabe, S. W. Franks & J. D. Kalma
Improved conditioning of SVAT models with observations of infrared surface temperatures, 217-224
- S. W. Franks, S. R. McKee, J. D. Kalma, B. J. J. M. Van den Hurk & Yaping Shao
Thermal remote sensing of the land surface for numerical weather prediction models, 225-231
- Maria Helena Ramos, Stephane Sénési, Jean-Dominique Creutin & Christophe Morel
Contribution of satellite and lightning data to convective rainfall frequency analysis, 233-239
- E. L. Muzylev & A. B. Uspensky
Modelling the hydrological cycle of river basins using high resolution satellite information, 241-247
- A. Weisse, C. Michel, D. Aubert & C. Loumagne
Assimilation of soil moisture in a hydrological model for flood forecasting, 249-256
- E. E. van Loon & P. A. Troch
Directives for 4-D soil moisture data assimilation in hydrological modelling, 257-267
- Radhia M’Chirgui, Zoubeida Bargaoui & András Bárdossy
Incidence de l’incertitude pluviométrique sur la modélisation pluie–débit, 269-278
- S. R. Fassnacht, K. R. Snelgrove & E. D. Soulis
Daytime long-wave radiation approximation for physical hydrological modelling of snowmelt: a case study of southwestern Ontario, 279-286
- Takashi Ishii, Makoto Nashimoto & Hisashi Shimogaki
Large-scale mapping of leaf area index using remote sensing data, 287-290
- Vladimir Konovalov
Regional extrapolation of meteorological data in a distributed hydrological model, 291-295
- Snow–Vegetation Interaction
- J. W. Pomeroy, P. Höller, P. Marsh, D. A.Walker & M. Williams
Snow vegetation interactions: issues for a new initiative, 299-305
- E. A. Kowalczyk & J. L. McGregor
The impact of the representation of soil–vegetation–atmosphere interaction upon snow processes, 307-315
- Joseph P. McFadden, Glen E. Liston, Matthew Sturm, Roger A. Pielke, Sr & F. Stuart Chapin, III
Interactions of shrubs and snow in arctic tundra: measurements and models, 317-325
- Xieyao Ma, Yoshihiro Fukushima & Tetsuo Ohata
Hydrological modelling of river ice processes in cold regions, 327-331
- W. L. Quinton & D. M. Gray
Estimating subsurface drainage from organic-covered hillslopes underlain by permafrost: toward a combined heat and mass flux model, 333-341
- Richard Essery & John Pomeroy
Sublimation of snow intercepted by coniferous forest canopies in a climate model, 343-347
- David C. Garen & Danny Marks
Spatial fields of meteorological input data including forest canopy corrections for an energy budget snow simulation model, 349-353
- Peter Höller
Snow gliding and avalanches in a south-facing larch stand, 355-358
- Christian Rixen, Veronika Stoeckli, Christine Huovinen & Kai Huovinen
The phenology of four subalpine herbs in relation to snow cover characteristics, 359-362
- ilena Kocianova & Helena Štursova
A new possible site to study the effects of climate warming on tundra ecosystems: the Giant Mountains, Czech Republic, 363-367