The soil sorptivity, S, and saturated hydraulic conductivity, Ks, are fundamental soil hydraulic properties that can be estimated from the cumulative infiltration curve measured with a disc infiltrometer. The Haverkamp infiltration model is widely used to estimate S and Ks. This model includes as inputs the constants β and γ and the difference between the initial, θi, and final, θs, volumetric water contents, Δθ. Since Δθ would be expressive of the possible measurement errors, and assuming β, γ, and θi as known values, the first objective of this work is to analyze the influence of θs on the optimization of Ks and S. To this end, a sensitivity analysis, which consists of estimating Ks and S for a range of θs was applied on synthetic infiltration curves simulated for homogeneous columns of sand and loam soil. Then, and working on real soils under different tillage management, we evaluated different procedures to measure θs and analyzed its impact on Ks and S estimation. Four different techniques were compared: the gravimetric-core method and two TDR invasive (3 and 5 cm) and a non-invasive (NiP) probes. All TDR probes were connected to a low-cost NanoVNA. The sensitivity analysis showed that θs, Ks and S can be optimized simultaneously from the inverse analysis of an infiltration curve when β and γ are known values and the infiltration curve is near the steady-state zone. However, due to the intrinsic complexities of real soils and the fact that β and γ are unknown variables, we recommended to optimize Ks and S using measured θs. The NiP sensor connected to a NanoVNA provided a fast, inexpensive, clean, accurate and robust alternative to measure θs at the end of the infiltration experiments.

中文翻译：

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饱和含水量对累积圆盘渗透仪测量估计土壤水力特性的影响


土壤吸附率 S 和饱和水力传导率 Ks 是基本的土壤水力特性，可以根据盘式渗透仪测量的累积渗透曲线进行估算。Haverkamp 渗透模型广泛用于估计 S 和 Ks。该模型包括常数 β 和 γ 以及初始 θi 和最终 θs 之间的差值、体积含水量 Δθ 作为输入。由于 Δθ 表示可能的测量误差，并假设 β、 γ 和 θi 为已知值，因此这项工作的首要目标是分析 θs 对 Ks 和 S 优化的影响。为此，对模拟的沙壤土均质柱的合成渗透曲线进行了敏感性分析，包括估计 θs 范围的 Ks 和 S。然后，在不同耕作管理下的真实土壤上，我们评估了测量 θs 的不同程序，并分析了其对 Ks 和 S 估计的影响。比较了四种不同的技术：重量法-核心法和两个 TDR 侵入性 （3 和 5 cm） 和一个非侵入性 （NiP） 探头。所有 TDR 探头都连接到低成本的 NanoVNA。敏感性分析表明，当 β 和 γ 为已知值且渗透曲线接近稳态区时，θs 、 Ks 和 S 可以从渗透曲线的逆分析中同时优化。然而，由于真实土壤的内在复杂性以及 β 和 γ 都是未知变量的事实，我们建议使用测量的 θs 来优化 Ks 和 S。连接到 NanoVNA 的 NiP 传感器提供了一种快速、廉价、清洁、准确和耐用的替代方案，可以在渗透实验结束时测量 θs。