The role of spatial variability of soil moisture for modelling surface runoff generation at the small catchment scale
The role of spatial variability of soil moisture for modelling surface runoff generation at the small catchment scale
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DOI：
10.5194/hess-3-505-1999
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发表时间：
1999-12
影响因子：
6.3
通讯作者：
A. Bronstert;A. Bárdossy
中科院分区：
文献类型：
--
作者：
A. Bronstert;A. Bárdossy
贝叶斯方法描述了处理的问题，填充和生成随机流序列，使用降雨数据来指导流量生成过程，并包括有界（审查）观测流量和降雨数据提供额外的信息。使用吉布斯抽样程序获得的解决方案。特别讨论的问题包括开发新的程序拟合转换时，有界值，应付额外的信息的形式的价值观，或界限，总流量在几个网站，和发展之间的关系，年流量和降雨量数据。示例显示了两个填充值的未知的过去的河流流量，与不确定性的评估，并实现代表什么可能发生在未来的流量。验证模型输出的几个程序进行了描述和中央估计的流量，作为历史观测流量的替代品，与长期的区域流量和降雨量数据进行比较。
A Bayesian approach is described for dealing with the problem of infilling and generating stochastic flow sequences using rainfall data to guide the flow generation process, and including bounded (censored) observed flow and rainfall data to provide additional information. Solutions are obtained using a Gibbs sampling procedure. Particular problems discussed include developing new procedures for fitting transformations when bounded values are available, coping with additional information in the form of values, or bounds, for totals of flows across several sites, and developing relationships between annual flow and rainfall data. Examples are shown of both infilled values of unknown past river flows, with assessment of uncertainty, and realisations of flows representative of what might occur in the future. Several procedures for validating the model output are described and the central estimates of flows, taken as a surrogate for historical observed flows, are compared with long term regional flow and rainfall data.