کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6411513 1629926 2015 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Mapping soil water retention curves via spatial Bayesian hierarchical models
ترجمه فارسی عنوان
منحنی های احتباس آب خاک را با استفاده از مدل سلسله مراتبی بیزی انجام می شود
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
چکیده انگلیسی


- Construct spatial van Genuchten models to predict water retention curves.
- The models are built on a Bayesian hierarchical framework.
- The models can add soil properties and physical factors to correlate the curves.
- We show soil types and spatial effects are essential to predict the curves.
- We map the hydraulic parameters of the van Genuchten model and the water retention curves.

SummarySoil water retention curves are an important parameter in soil hydrological modeling. These curves are usually represented by the van Genuchten model. Two approaches have previously been taken to predict curves across a field - interpolation of field measurements followed by estimation of the van Genuchten model parameters, or estimation of the parameters according to field measurements followed by interpolation of the estimated parameters. Neither approach is ideal as, due to their two-stage nature, they fail to properly track uncertainty from one stage to the next. In this paper we address this shortcoming through a spatial Bayesian hierarchical model that fits the van Genuchten model and predicts the fields of hydraulic parameters of the van Genuchten model as well as fields of the corresponding soil water retention curves. This approach expands the van Genuchten model to a hierarchical modeling framework. In this framework, soil properties and physical or environmental factors can be treated as covariates to add into the van Genuchten model hierarchically. Consequently, the effects of covariates on the hydraulic parameters of the van Genuchten model can be identified. In addition, our approach takes advantage of Bayesian analysis to account for uncertainty and overcome the shortcomings of other existing methods. The code used to fit these models are available as an appendix to this paper. We apply this approach to data surveyed from part of the alluvial plain of the river Rhône near Yenne in Savoie, France. In this data analysis, we demonstrate how the inclusion of soil type or spatial effects can improve the van Genuchten model's predictions of soil water retention curves.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Hydrology - Volume 524, May 2015, Pages 768-779
نویسندگان
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