Water Content Data Research Articles

Performance Evaluation of Different Insulating Materials using Field Temperature and Moisture Data

Including insulation layers in pavement structures has become a common strategy to minimize frost penetration in cold regions. This study investigated the performance of two different insulation materials, extruded polystyrene board and bottom ash, in a test road in Edmonton, Alberta, Canada, eight years after construction. The two insulation materials were used in a fully instrumented test road, including three insulated sections 20 m in length. The insulated sections are as follows: the first section has 1 m of bottom ash (B. Ash), the second section has a 10 cm polystyrene layer (Poly-10), and the third section has a 5 cm polystyrene layer (Poly-5). Both B. Ash and polystyrene layers were placed on top of the subgrade layer, at a depth of 70 cm from the surface. A conventional section next to these three sections was used as the control section. Volumetric water content data and temperature variation were used to analyze the influence of the insulation materials on the subgrade. It was concluded that both B. Ash and Poly-10 layers protected the subgrade from freezing. The Poly-10 section showed the lowest rate of change in subgrade temperature during the monitoring period. B. Ash and Poly-10 reduced the frost depth by 23% and 70% compared with the control section, respectively. It was concluded that Poly-10 protected the subgrade soil from freezing and excessive moisture more effectively than B. Ash; however, the temperature in the layer above the insulation layers (pavement base layer) was significantly lower during winter for the Poly-10 section.

Influence of Hydrate-Forming Gas Pressure on Equilibrium Pore Water Content in Soils

Natural gas hydrates (primarily methane hydrates) are considered to be an important and promising unconventional source of hydrocarbons. Most natural gas hydrate accumulations exist in pore space and are associated with reservoir rocks. Therefore, gas hydrate studies in porous media are of particular interest, as well as, the phase equilibria of pore hydrates, including the determination of equilibrium pore water content (nonclathrated water). Nonclathrated water is analogous to unfrozen water in permafrost soils and has a significant effect on the properties of hydrate-bearing reservoirs. Nonclathrated water content in hydrate-saturated porous media will depend on many factors: pressure, temperature, gas composition, the mineralization of pore water, etc. In this paper, the study is mostly focused on the effect of hydrate-forming gas pressure on nonclathrated water content in hydrate-bearing soils. To solve this problem, simple thermodynamic equations were proposed which require data on pore water activity (or unfrozen water content). Additionally, it is possible to recalculate the nonclathrated water content data from one hydrate-forming gas to another using the proposed thermodynamic equations. The comparison showed a sufficiently good agreement between the calculated nonclathrated water content and its direct measurements for investigated soils. The discrepancy was ~0.15 wt% and was comparable to the accuracy of direct measurements. It was established that the effect of gas pressure on nonclathrated water content is highly nonlinear. For example, the most pronounced effect of gas pressure on nonclathrated water content is observed in the range from equilibrium pressure to 6.0 MPa. The developed thermodynamic technique can be used for different hydrate-forming gases such as methane, ethane, propane, nitrogen, carbon dioxide, various gas mixtures, and natural gases.

Desiccation cracking at field scale on a vegetated infrastructure embankment

This paper presents a desiccation crack monitoring campaign conducted on a full-scale, vegetated infrastructure embankment subjected to one-year of seasonally variable weather. The field survey involved direct measurement of naturally developed, annually reoccurring cracks in a heavily instrumented, clay fill embankment (BIONICS, Newcastle University). Transient crack morphology was captured in terms of opening width, length and depth, in addition to meteorological and near-surface soil hydrological conditions. In order to assess any correlation between crack development and weather-driven changes in near surface soil conditions, the volume of cracks was estimated using an empirically derived equation. This research study identified crack behaviour in four stages: initiation, expansion, contraction and closure. These stages and the distribution of cracks on the slope are closely related to prevailing atmospheric conditions, namely wind direction, relative humidity, precipitation and potential evapotranspiration. These ultimately govern the soil hydrological conditions in the near surface, as manifested in the presented matric potential and volumetric water content data. Linearly descrete cracks are shown to form under such conditions in contrary to the polygonal patterns typically reported under laboratory conditions. Crack length growth terminates prior to full volumetric maturation with crack depth dominating the dynamic response regardless of overall crack size.

Evaluation of installation procedures of volumetric water content and matric potential probes: fundamentals for obtaining field and laboratory accordance

The current paper aims to analyze the influence of installation procedures when it comes to the accordance of the Soil Water Retention Curve and field monitoring data. The method comprises testing three different installation procedures: with driving the rod into the soil; with the application of mud inside the auger hole; and with a hardened steel gauge. Further, is evaluated the influence of the variation of Bulk density on volumetric water content values by using the Proctor and a double ring hydraulic equipment. To analyze the soil-rod coupling, a microtomography imaging routine was performed. The results point out that the probe’s data are connected to the Bulk density of the material, producing higher volumetric water content values with the increase of Bulk density. Comparing results of different installation methods with laboratory results, it is possible to conclude that driving the rod directly into the soil is the best way to install the equipment since the probe underestimates the volumetric water content data by 2,5%, while the mud application by 4%, and the gauge method by 5%.

An empirical model for estimating soil penetrometer resistance from relative bulk density, matric potential, and depth

Soil penetrometer resistance (PR), an indicator of soil strength, is often used to denote the force that roots need to exert to penetrate the soil. In this study, we propose an empirical model, which has a simplified form and fewer parameters than the previous ones, to estimate PR from relative bulk density, matric potential of soil water, and soil depth. The model was established by using field measurements of PR, bulk density, water content, and laboratory water retention data at various soil depths in a long-term tillage experiment during maize growing season in 2017. Relative bulk density was determined from soil texture, bulk density, and organic matter content. Model performance was evaluated by comparing the predictions from the new model against those obtained from four earlier models using independent field data collected from four soils of different textures in 2015, 2018 and 2019. The root mean square error of the new model ranged from 0.358 to 0.879 MPa, significantly lower than that of the other four models (0.404–2.689 MPa), indicating that the new model could be applied to estimate PR for a wide range of soil textures with improved accuracy.

A hybrid CNN-GRU model for predicting soil moisture in maize root zone

Soil water content in maize root zone is the main basis of irrigation decision-making. Therefore, it is important to predict the soil water content at different depths in maize root zone for rational agricultural irrigation. This study proposed a hybrid convolutional neural network-gated recurrent unit (CNN-GRU) integrated deep learning model that combines a CNN with strong feature expression capacity and a GRU neural network with strong memory capacity. The model was trained and tested with the soil water content and meteorological data from five representative sites in key maize producing areas, Shandong Province, China. We designed the model structure and selected the input variables based on a Pearson correlation analysis and soil water content autocorrelation analysis. The results showed that the hybrid CNN-GRU model performed better than the independent CNN or GRU model with respect to prediction accuracy and convergence rate. The average mean squared error (MSE), mean absolute error and root mean squared error of the hybrid CNN-GRU model on day 3 were 0.91, 0.51 and 0.93, respectively. The prediction accuracy of the model improved with increasing soil depth. Extending the forecast period, the prediction accuracy values of the hybrid CNN-GRU model for the soil water content on days 5, 7 and 10 were comparable, with an average MSE of less than 1.0.

Molecular dynamics data for modelling the microstructural behaviour of compacted sodium bentonites

The water retention curve deduced with low water content data allows the modelling of the bentonite void ratio associated with the pores located inside the clay aggregates, or micropores. However, if both the water content and the microporosity continue to increase, the latter can no longer be directly obtained from the former, because, in that case, the presence of water in the pores existing between the aggregates (macropores) may not be negligible. Therefore, it is not easy to obtain experimental evidence that allows to contrast whether the model's extrapolation of the microstructural void ratio obtained under dry conditions is valid for higher water contents. This work analyses the use of data obtained from molecular dynamics models to assess the validity of such extrapolations, and defines the variables needed to compare the results from molecular dynamics and laboratory experiments. The encouraging agreement obtained contributed to the confidence in the proposed procedure, which enabled a new strategy that uses molecular dynamics data to model the macroscopic behaviour of compacted sodium bentonites.

Effect Utilization Mangrove Rhizophora Sp Fruit Extract in Production of Coffee Powder in Perspective of Water Content and Organoleptic Test

Utilization of mangrove seeds is not as popular the use of wood tree. Utilization of wood from mangrove tree is used as raw material for making charcoal and building materials.The local community rarely uses mangrove seeds for food, drinks, scrubs and coloring. This is not enough of public knowledge about the benefits of mangrove seeds. The public mindset that the only sources of carbohydrates are rice and corn. There is not much knowledge about the potential and benefits of mangrove seeds as a coffee drink. The research method used in this research is experimental research. In this experiment, 3 repetitions of treatment and 3 replications. Water content data in the mangrove seed ground coffee was tested by normality test. The proximate test results show ash content of 1 to 4% when averaged is 2.6%. While the general requirement for roasted coffee (SNI.01.2983-1992) is 7-14% ash content. The color of coffee is influenced by the value of the extract content of the coffee, water soluble coffee juice will give it a deep black color ( Pastiniasih, 2012). The juice content of magrove coffee is high enough for each treatment so that the steeping gives a visually visible black color.

Deep soil water deficit and recovery in alfalfa fields of the Loess Plateau of China

Alfalfa (Medicago sativa L.) is the most widely planted forage crop on the semiarid Loess Plateau of China. It has a deep rooting system and high evapotranspiration rate, and how water content in deep soil is affected by continuous alfalfa planting and how soil water recovery responds to the conversion of alfalfa to annual crops are not fully understood. In this study, we conducted a meta‐analysis of soil water content data taken from 45 published studies conducted at 21 sites of the Loess Plateau to evaluate the effects of continuous alfalfa planting and the conversion of alfalfa to annual crops on soil water conditions in the 0−1500 cm profile. Response size (RS), the relative change in soil water content after initiating and stopping alfalfa compared to the long-term cropland, was calculated. The results show that the RS values in all soil layers from 100 to 1400 cm were significantly lower than zero (P < 0.05). RS values in soil layers below 200 cm linearly increased with increasing local rainfall (P < 0.05). The RS decreased with increasing alfalfa crop age, with average values of -0.143, -0.270, and -0.356 found for 0–5-, 5–10- and >10-year-old alfalfa fields, respectively. After converting alfalfa into annual crops for 1–28 years, the soil water content in the 0−300 cm layer was recovered, but that in the 300−1000 cm layer was still significantly lower than that in the reference field (P < 0.05) with an average RS value of -0.28. The relationship between RS and recovery years can be fit to linear equations (P < 0.001), and equations show that 18 and 23 years were needed to fully recover soil water depletion in the 200−500 and 500−1000 cm layers, respectively. The results of this study indicate that the long-term cultivation of alfalfa can severely reduce soil water content to a depth of 1500 cm and that the water deficit is difficult to recover. Short-term alfalfa and annual crop rotation is recommended to be applied to reduce the risk of deep soil desiccation.

Screening of mungbean for drought tolerance and transcriptome profiling between drought-tolerant and susceptible genotype in response to drought stress

Mungbean, is a widely cultivated pulse crop in India, experiences severe drought stress during the cultivation period. The mechanism of drought tolerance in mungbean is not well understood. In this presents study we screened 7 widely cultivated mungbean genotypes towards their drought sensitivity at seedling stage and transcriptome sequencing of drought-tolerant and susceptible genotype to understand the drought tolerance mechanism. Our physiological data such as increase in root length, shoot length, fresh weight, dry weight, relative water content (RWC), proline content, MDA content and molecular data in terms of quantitative expression of drought stress responsive genes under 3-d drought stress in mungbean suggests that, K851 seems to be most drought tolerant and PDM-139 as drought susceptible genotype. The transcriptomic study between K-851 and PDM-139 revealed 22,882 differentially expressed genes (DEGs) which were identified under drought stress, and they were mainly mapped to phytohormone signal transduction, carbon metabolism and flavonoid biosynthesis. Out of these, 10,235 genes were up-regulated and 12,647 genes were down-regulated. Furthermore, we found that, the DEGs related to, phytohormone signal transduction, carbon metabolism and flavonoid biosynthesis and they were more induced in K-851. Our data suggested that, the drought tolerant genotype K-851, scavenges the damage of drought stress by producing more amount of osmolytes, ROS scavengers and sugar biosynthesis.

Water content of liquid H2S in equilibrium with the hydrate phase

Acid gas injection containing H2S is one strategy for managing atmospheric sulfur emissions where sulfur recovery may not be feasible or economical in some locations. Apart from its toxicity and corrosivity in wet environments, H2S forms a high temperature hydrate in the presence of water, which can cause issues such as plugging of transport pipelines or injection wellheads. Before transportation to injection, liquid water is removed from an injectate within the interstage suction scrubbers before each compression cycle and/or by further dehydration. Water content data are important in order to determine and define the dehydration requirements of acid gas injectates. Prior to this work, there were no water content data for H2S at hydrate forming conditions because of the difficulties in measuring low concentration of water above hydrates and high H2S toxicity. In this study, we report the water content of pure H2S in the hydrate forming regions from p = 4.178 to 20.572 MPa and T = 247.65 to 298.28 K using tunable diode laser spectroscopy. The measured data show a relative water content difference of ca. 2.5% from the model reported in this work using the Sloan et al. (1976), and van der Waal & Platteeuw (1959) equations for the hydrate phase, and the fluid phase model of Bernard et al. (2012).

Hole irrigation process simulation using a soil water dynamical model with parameter inversion method

Soil water dynamics are an important part of agricultural irrigation evaluation standards; therefore, supplying water efficiently has become the focus of agricultural water-saving research, and different soil water movement models have been developed for various water supply models. In this work, a parameter inversion model is coupled with the soil water movement equation (the Richards equation) based on the main variable of the head (h)-based Richards equation to investigate the dynamics of soil moisture under hole irrigation. A mathematical model for hole irrigation with two hole diameters (5 cm or 7 cm) and two hole numbers (one or two) was constructed after verifying the model with field-scale soil water content data from different soil profile depths. The Richards equation based on the Gauss–Newton parameter inversion method was found to accurately simulate the soil moisture dynamics under hole irrigation (R2>0.9). The difference in the water content of the soil profile due to the difference in hole diameter did not exceed 2.7%, and the soil water content under single-hole irrigation was significantly higher than that under double-hole irrigation due to lower evaporation. The infiltration distance of the wetting front under single-hole irrigation, which was mainly distributed on the hole side of the planting ridge, was greater than that under double-hole irrigation at 378 ml irrigation water per plant, and the soil moisture was unevenly distributed at a certain depth. However, the wetting fronts under double-hole irrigation intersected and began to infiltrate the soil evenly within a short time (only 6% of the entire irrigation cycle). The results for wetting front movement under the different hole settings show that double-hole irrigation does not stimulate crop root growth on both sides of the plant in the long term; however, this growth pattern can be stimulated by alternating single-hole irrigation.

Evaluation and Development of Pedotransfer Functions for Predicting Saturated Hydraulic Conductivity for Mexican Soils

In the present work, we evaluate the prediction capability of six pedotransfer functions (PTFs), reported in the literature, for the saturated hydraulic conductivity estimations (KS). We used a database with 900 measured samples obtained from the Irrigation District 023, in San Juan del Rio, Queretaro, Mexico. Additionally, six new PTFs were constructed for KS from clay percentage, bulk density, and saturation water content data. The results show, for the evaluated models, that one model presents an overestimation for KS &gt; 0.5 cm h−1 values, three models have an underestimation for KS &gt; 1.0 cm h−1, and two models have a good correlation (R2 &gt; 0.98) but more than three parameters are necessary. Nevertheless, the last two models require 3–4 parameters in order to obtain optimization. On the other hand, the models proposed in this work have a similar correlation with fewer parameters. The fit is seen to be much better than using the existing ones, achieving a correlation of R2 = 0.9822 with only one variable and R2 = 0.9901 when we use two.

Coupling analysis of the heat-water dynamics and frozen depth in a seasonally frozen zone

Frozen depth has a great significance for the foundation engineering in cold regions, always showing a high correlation with some attendant engineering phenomena, including water aggregation, frost heave, and salt accumulation. To study the heat-water dynamics and frozen depth characteristics during the freezing process, soils in western Jilin Province of China, a typical seasonal frozen region, were selected for investigation. A coupled heat and water model was proposed to describe the water-heat coupling process during freezing, with full consideration of the unfrozen water variation, the ice layer formation, and the interaction among different elements. Then, the dynamics of the heat-water and frozen depth were simulated based on the boundary conditions of temperature variation with reference to the meteorological data. The in- situ monitoring data from the whole winter were used to analyse the model performance. The results show that water content and temperature data match the test data, and the Root Mean Square Error (RMSE) values of the temperatures (within 2 °C) at different depths were acceptable, indicating that the water-heat dynamics can predict the maximum frozen depth well. In addition, the temperature of the soil profile varies rapidly in the first 60 days of winter, and the frozen depth continues to increase even though the temperature starts to rise after freezing for 80 days. The moisture transfers upwards with the effect of heat flow, and the formation of ice occurred mainly at a depth of 1.5 m. Heat conduction plays an important role in modelling, predominantly leading to the hysteresis in the frozen depth variation during freezing. This new method can provide a reference for water-heat movement and the prediction of the frozen depth during freezing in the saline soil regions.

Study of the geostatistical grid maths operation method of quantifying water movement in soil layers of a cotton field*

AbstractThe precise quantification of water movement in different field soil layers is important for variable‐rate irrigation and fertilization. To this end, a field experiment based on a geostatistical approach was conducted in southern Anyang, Henan, China, to examine soil water movement in a cotton field with drip irrigation by measuring the soil water content (SWC) data on a regular 100 × 80 cm grid. The result shows that the temporal and spatial variation of soil moisture decreased with the increase of soil depth at different points, and apparent spatial heterogeneity was observed under different soil conditions through a semivariogram analysis. The variation of soil moisture at different soil profiles was affected by the cotton plants and drip lines in non‐irrigation and irrigation periods respectively. The level of the change at 20 cm was more than 70 cm in the horizontal direction in the two periods, however the degree of change at 40 cm in the irrigation period was more than 70 cm in the vertical direction, while contrary results were shown in the non‐irrigation period. Moreover, the results indicated that the trapezoidal rule could be applied to quantify the volume of water movement precisely.

Electrical resistivity imaging for monitoring soil water motion patterns under different drip irrigation scenarios

The use of hydrogeophysical methods provides insights for supporting optimal irrigation design and management. In the present study, the electrical resistivity imaging (ERI) was applied for monitoring the soil water motion patterns resulting from the adoption of water deficit scenarios in a micro-irrigated orange orchard (Eastern Sicily, Italy). The relationship of ERI with independent ancillary data of soil water content (SWC), plant transpiration (T) and in situ measurements of hydraulic conductivity at saturation (Ks, i.e., using the falling head method, FH) was evaluated. The soil water motion patterns and the maximum wet depths in the soil profile identified by ERI were quite dependent on SWC (R2 = 0.79 and 0.82, respectively). Moreover, ERI was able to detect T in the severe deficit irrigation treatment (electrical resistivity increases of about 20%), whereas this phenomenon was masked at higher SWC conditions. Ks rates derived from ERI and FH approaches revealed different patterns and magnitudes among the irrigation treatments, as consequence of their different measurement scales and the methodological specificity. Finally, ERI has been proved suitable for identifying the soil wetting/drying patterns and the geometrical characteristics of wet bulbs, which represent some of the most influential variables for the optimal design and management of micro-irrigation systems.

Optimization-Based Water-Salt Dynamic Threshold Analysis of Cotton Root Zone in Arid Areas

Threshold levels of soil moisture and salinity in the plant root zone can guide crop planting and farming practices by providing a baseline for adjusting irrigation and modifying soil salinity. This study describes a method of soil water and salinity control based on an optimized model for growing cotton in an arid area. Experiments were conducted in Akesu Irrigation District, southern Xinjiang, northwest China, to provide data for cotton yield and soil water content and salinity in the root zone at different growth stages. The sensitivity of cotton to soil water content and salinity was predicted for different growth periods using a modified Jensen model. An optimization model with 480 boundary conditions was created, with the objective of maximizing yield, to obtain the dynamically varying water and salt threshold levels in the root zone for scenarios that included three initial soil moisture content values (W0), eight irrigation quantities (M), five initial soil salt content values (S0), and four irrigation water salinity levels (K). Results showed that the flowering–boll stage is the crucial period for cotton yield, and the threshold levels of soil water content and salinity in the cotton root zone varied with the boundary conditions. The scenario chosen for the research area in this study was W0 = 0.85θfc (θfc is field capacity), S0 = 4 g kg−1, M = 400 mm, K = 0 g L−1. The predicted threshold levels of soil water for different growth stages (seedling, bud, flowering–boll, and boll-opening) were respectively 0.75–0.85θfc, 0.65–0.75θfc, 0.56–0.65θfc, and 0.45–0.56θfc. Corresponding threshold levels of salt were 4–4.16, 4.16–4.39, 4.39–4.64, and 4.64–4.97 g kg−1 when no action was taken to remove salt from the root zone. This study provides an innovation method for the determination of dynamically varying soil water content and salt thresholds.

Dynamics of soil penetration resistance in water-controlled environments

In water-controlled environments, because rainfall is one of the primary hydroclimatic forcings, its variability can affect the dynamics of soil water content and other related processes such as soil penetration resistance (PR), plant growth, and food production. The objective of this study was to simulate the relative soil water content (s) and PR year-round considering semi-arid rainfall conditions for different soil classes. An experiment was conducted to obtain relative soil water content (s) and PR data in sandy soil and this information was combined with a data set of four soils from a similar experiment conducted on different soil texture classes. The relative soil water content and PR were simulated at a daily timescale using a stochastic soil water balance model for the five soils. The parameters of the PR-s model can be estimated from the soil texture and bulk density. Under rainfed conditions, there is a short window for tillage (plowing and cultivation) of sandy soils compared with clay soils. During the majority of a typical hydrological year, the PR reaches high values (greater than 5.0 MPa) imposing a moderate to high physical limitation for root growth in sandy soils. In the same soils, limiting PR is reached at s levels very close to the field capacity during the drying process. This indicates that an extra input of water through irrigation may be required during the establishment of crops with a well-developed root system in order to prevent impairments to root growth. The daily PR values modeled over the course of a hydrological year followed a beta distribution with shape parameters (α and β) which were strongly correlated with the frequency of rainfall events during the wet season (λwet). The modeling framework presented here for simulating relative soil water content and soil penetration resistance can be applied to agricultural systems in order to prevent physical limitations on crop growth and to plan tillage management schedules.

Sap flow rates of Minquartia guianensis in central Amazonia during the prolonged dry season of 2015–2016

Minquartia guianensis Aubl. is a slow-growing species with several uses. In the juvenile state, it is well-adapted to low light conditions of the forest understory. However, it is still unknown how climate variability affects transpiration of this species, particularly under drought stress. In this study, we aimed to assess the effect of climatic variability on sap flow rates (SFR). SFR and radial growth were measured in six trees (14‒50 cm diameter) in 2015 and 2016. Climate (precipitation, irradiance, relative humidity and temperature) and soil water content (SWC) data were also collected. SFR tended to increase in the dry season, with a negative relationship between SFR and SWC and precipitation (p < 0.001), while there was a positive association between radial growth and monthly precipitation (p = 0.004). Irradiance and temperature were the environmental factors more closely correlated with SFR during daytime (p < 0.001), whereas relative humidity and vapor pressure deficit were the most important factors at night (p < 0.001). Although negative SFR were sometimes recorded at night, the mean nocturnal sap flow was positive and across trees the nighttime sap flow accounted for 12.5% of the total daily sap flow. Increased transpiration during the dry season suggests that the root system of Minquartia was able to extract water from deep soil layers. These results widen our understanding of the ecophysiology of Amazonian trees under drought and provide further insight into the potential effect of the forecasted decline in precipitation in the Amazon region.

Bayesian Updating of Soil–Water Character Curve Parameters Based on the Monitor Data of a Large-Scale Landslide Model Experiment

It is important to determine the soil–water characteristic curve (SWCC) for analyzing landslide seepage under varying hydrodynamic conditions. However, the SWCC exhibits high uncertainty due to the variability inherent in soil. To this end, a Bayesian updating framework based on the experimental data was developed to investigate the uncertainty of the SWCC parameters in this study. The objectives of this research were to quantify the uncertainty embedded within the SWCC and determine the critical factors affecting an unsaturated soil landslide under hydrodynamic conditions. For this purpose, a large-scale landslide experiment was conducted, and the monitored water content data were collected. Steady-state seepage analysis was carried out using the finite element method (FEM) to simulate the slope behavior during water level change. In the proposed framework, the parameters of the SWCC model were treated as random variables and parameter uncertainties were evaluated using the Bayesian approach based on the Markov chain Monte Carlo (MCMC) method. Observed data from large-scale landslide experiments were used to calculate the posterior information of SWCC parameters. Then, 95% confidence intervals for the model parameters of the SWCC were derived. The results show that the Bayesian updating method is feasible for the monitoring of data of large-scale landslide model experiments. The establishment of an artificial neural network (ANN) surrogate model in the Bayesian updating process can greatly improve the efficiency of Bayesian model updating.