用于确定非饱和土壤性质的 SWRC Fit 和 unsatfit
SWRC Fit and unsatfit for parameter determination of unsaturated soil properties
AI总结：
SWRC Fit 和 unsatfit 是用于确定非饱和土壤水分保持和导水率参数的程序，通过非线性最小二乘优化实现多种水力模型，并支持抑制近饱和区导水率极端变化，本文介绍了其使用方法。
摘要：
SWRC Fit 和 unsatfit 是为确定土壤水分保持和非饱和导水率函数参数而开发的程序，用于分析非饱和土壤中的水分运动。SWRC Fit 是一款 Web 应用程序，可根据测量数据一键绘制各种土壤水力模型的 SWRC（土壤水分保持曲线），可在 https://purl.org/net/swrc/ 获取。SWRC Fit 依赖于 Python 库 unsatfit，该库实现了各种类型的土壤水力模型，通过非线性最小二乘优化来确定水分保持和导水率参数。所实现的模型根据水分保持函数的自由度分为 DF3（Brooks and Corey, van Genuchten, Kosugi）模型、DF4（Fredlund, Fayer, Peters, bimodal-CH）模型和 DF5（bimodal）模型。大多数导水率函数是由水分保持函数和通用导水率函数推导而来的。一种用于抑制近饱和范围内导水率极端变化的修正模型可应用于任何水力模型。在 Seki et al. (2023) 中被证明适用于各种类型土壤的算法以示例 Python 代码的形式提供。本文介绍了如何使用 SWRC Fit 和 unsatfit。
英文摘要：
SWRC Fit and unsatfit are programs developed for determining parameters of the water retention and the unsaturated hydraulic conductivity functions of soils for analyzing water movement in the unsaturated soil. The SWRC Fit is a web application for drawing SWRC (soil water retention curves) of various soil hydraulic models from the measured data with just one click, available at https://purl.org/net/swrc/. The SWRC Fit depends on the Python library unsatfit that implements various types of soil hydraulic models to determine water retention and hydraulic conductivity parameters by nonlinear least-square optimization. The implemented models are classified as DF3 (Brooks and Corey, van Genuchten, Kosugi) models, DF4 (Fredlund, Fayer, Peters, bimodal-CH) models, and DF5 (bimodal) models by the degree of freedom of the water retention functions. Most of the hydraulic conductivity functions are derived from the water retention function and the general hydraulic conductivity function. A modified model to suppress extreme changes in hydraulic conductivity in the near-saturated range can be applied to any hydraulic model. The algorithm that was proved to work with various types of soils in Seki et al. (2023) is provided as the sample Python codes. This paper describes how to use SWRC Fit and unsatfit.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
