Abstract Information on vertical Soil Moisture Content (SMC) profile is important for several hydro-meteorological processes. This study borrows the idea of coupling the memory and forcing from a previous study and develops a spatially-varying Statistical Soil Moisture Profile (SSMP) model to estimate the vertical SMC profile. It uses only surface soil moisture (0–5 cm) values and Hydrological Soil Groups (HSGs) information of the location. The focus of the study is incorporation of the HSG information to ensure the spatial transferability of the proposed model by capturing the spatial variations of soil moisture profile with the change in soil hydraulic properties. The wide range of soil moisture data for model development as well as for spatial validation is obtained from 171 stations from different networks of International Soil Moisture Network (ISMN) at five different depths, i.e., 5, 10, 20, 51 and 102 cm. The HSG information at the locations are extracted from the Web Soil Survey (WSS) database. The potential of spatial transferability of the SSMP model is assessed by applying it to the new stations within the corresponding HSG. Model performances are promising for all four depth pairs (5–10, 10–20, 20–51 and 51–102 cm) of all four HSGs during both model development and spatial validation given the model complexity. Hence, the spatially-varying SSMP model is suitable at the ungauged locations by incorporating the HSG information. The potential application of the proposed model shows the future scope to assimilate the satellite based surface SMC data into the model to develop a vertical soil moisture profile map over a large area.

中文翻译：

---

使用水文土壤组通过耦合记忆和强迫建立空间变化统计土壤水分剖面模型

摘要 有关垂直土壤水分含量 (SMC) 剖面的信息对于若干水文气象过程很重要。本研究借鉴了先前研究中耦合记忆和强迫的思想，并开发了一个空间变化的统计土壤水分剖面 (SSMP) 模型来估计垂直 SMC 剖面。它仅使用该位置的表层土壤水分 (0–5 cm) 值和水文土壤组 (HSG) 信息。研究的重点是结合 HSG 信息，通过捕捉土壤水分剖面随土壤水力特性变化的空间变化来确保所提出模型的空间可转移性。用于模型开发和空间验证的广泛土壤水分数据是从来自国际土壤水分网络 (ISMN) 不同网络的 171 个站点在五个不同深度，即 5、10、20、51 和 102 厘米处获得的。这些位置的 HSG 信息是从网络土壤调查 (WSS) 数据库中提取的。通过将 SSMP 模型应用于相应 HSG 内的新站来评估 SSMP 模型的空间可转移性潜力。考虑到模型的复杂性，在模型开发和空间验证期间，所有四个 HSG 的所有四个深度对（5-10、10-20、20-51 和 51-102 厘米）的模型性能都是有希望的。因此，空间变化的 SSMP 模型通过结合 HSG 信息适用于未测量的位置。