A modified spatial soil moisture storage capacity distribution curve for the Xinanjiang model

Citation
Aw. Jayawardena et Mc. Zhou, A modified spatial soil moisture storage capacity distribution curve for the Xinanjiang model, J HYDROL, 227(1-4), 2000, pp. 93-113
Citations number
25
Categorie Soggetti
Environment/Ecology,"Civil Engineering
Journal title
JOURNAL OF HYDROLOGY
ISSN journal
00221694 → ACNP
Volume
227
Issue
1-4
Year of publication
2000
Pages
93 - 113
Database
ISI
SICI code
0022-1694(20000131)227:1-4<93:AMSSMS>2.0.ZU;2-5
Abstract
The Xinanjiang model provides a statistically integral structure to describ e the runoff generation on partial areas over a catchment. In the original version of the model, a single parabolic curve is used to describe the soil moisture variation. In reality however, the spatial and temporal distribut ion of soil moisture is quite complex because many different states, which change with seasons of the year, co-exist in the catchment. In this study, a more general double parabolic curve is proposed to describe the complex s oil moisture variation. It consists of lower and upper branches, with the l ower branch for the wet condition, the upper branch for the dry condition, and a smooth transition. Two parameters, c and b represent the relative wei ght between the lower and the upper branches and their gradients. The singl e parabolic curve of the original Xinanjiang model can be thought of as a s pecial case of the proposed double parabolic curve. Both the single and dou ble parabolic curves perform similarly when used with storm events isolated from daily data in the wet seasons, but the double parabolic curve improve s the predictions significantly when used with data from the dry seasons. W hen used with hourly event data there is no significant difference between the two curves because of the dominance of the wet soil moisture condition. Even in this case, the double parabolic curve differentiates the parameter values more clearly for different soil moisture states. There is also a sl ight improvement on the predictions for storms in the dry seasons. (C) 2000 Elsevier Science B.V. All rights reserved.