流域水文模型中的土壤质地转换与饱和导水率Ks值确定

STUDY ON THE CONVERSION OF DIFFERENT SOILS TEXTURE AND Ks VALUE FOR HYDORLOGICAL MODELLING

构建于GIS基础之上的分布式水文模型,近年来得到了普遍的应用和较快的发展。土壤质地数据是模型构建的重要参数,但实际运用中,常存在土壤数据多种统计口径并存、与模型运算所需的数据类型不一致等问题,限制了模型的应用和模拟的精度。根据土壤典型剖面值,利用3次样条函数曲线插值得出了模型所需土壤粒径分布。根据粒径组成,使用NeroTheta软件计算出饱和导水率Ks值。为构建分布式水文模型数据库,确定主要土壤参数提供了简便有效的方法。

The use of spatially distributed hydrological models for water and environmental management is becoming increasingly commonplace. Whilst such models have application throughout the globe, the data needed for parameterization, particularly soil data, is often in an incompatible classification scheme, and therefore cannot be directly applied to a model. This research addresses this by using cubic spline interpolation to convert the Chinese Soil Textural Classification Scheme to the International Society of Soil Science （ISSS） classification scheme, one which is suited to many hydrological models. The pedotransfer function （PTF） application NeuroTheta was then used to predict soil saturated hydraulic conductivity Ks value, a key parameter in hydrological models. This methodology proved to be a simple and convenient way for building a soil database compatible with the inputs for the majority of distributed hydrological models.