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Soil moisture is one of the key hydrologic components indicating the performance of landfill final covers. Conventional compacted clay (CC) covers and evapotranspiration (ET) covers often suffer from moisture-induced stresses, such as desiccation cracking and irreversible hydraulic conductivity. Engineered turf (EnT) cover systems have been introduced recently as an alternative; however, their field-scale moisture distribution behavior remains unexplored. This study investigates and compares the soil moisture distribution characteristics of EnT, ET, and CC landfill covers at a shallow depth using one year of field-monitored data in a humid subtropical region. Three full-scale test Sections (3 m × 3 m × 1.2 m) were constructed side by side and instrumented with moisture sensors at a depth of 0.3 m. Distributional characteristics of moisture were evaluated with descriptive statistics, goodness-of-fit tests such as Shapiro–Wilk (SW) and Anderson–Darling (AD), Gaussian probability density functions, Q–Q plots, and standard-normal transformations. Results revealed that Shapiro–Wilk (W = 0.75–0.92, p < 0.001) and Anderson–Darling (A2=1.63×103to6.31×103,p<0.001) tests rejected normality for every cover, while Levene’s test showed unequal variances between EnT and the other covers (F>5.4×104,p<0.001) but equivalence between CC and ET (F = 0.23, p = 0.628). EnT cover exhibited the narrowest moisture envelope (95%range=0.156to0.240m3/m3; CV=10.6%), whereas ET and CC covers showed markedly broader distributions (CV = 38.6 % and 33.3 %, respectively). These findings demonstrated that EnT cover maintains a more stable shallow soil moisture profile under dynamic weather conditions. 

Soil water characteristic curve (SWCC) which describes the relationship between water content and matric suction is important to analyzing unsaturated soil behavior. Because of the degree of uncertainty in field conditions due to climatic variability and soil heterogeneities, it becomes necessary to probabilistically characterize the SWCC. A satisfactory probabilistic characterization of field-based SWCCs requires a substantial data pair of water content and suction and their distribution characteristics. In this study, the kernel density estimate (KDE) approach was applied to water content and suction data measured from field-installed co-located sensors of a compacted clay bed to (1) determine the modality of water content and suction distribution and their constitutive relationship at variable weather conditions and (2) demonstrate the importance of probabilistic analysis of SWCC. The Gaussian function was used in the KDE analysis. A moisture sensor and soil water potential sensor were juxtaposed at 0.3 m depth of the 3 m × 3 m compacted clay bed to collect the water content and suction data and determine their distribution under the field condition. The density plots of both water content and suction at 0.3 m depth exhibited multimodal distribution due to the uneven distribution of climatic events. The KDE reasonably identified the air entry value, saturated moisture content, and residual moisture content in the field conditions, which were validated with field-based SWCC plots. The study showed that probabilistic analysis better interprets the realistic scenarios of field unsaturated soil behavior. 

The expansive behavior of clayey soil in response to climate-induced changes in the soil water characteristic curve (SWCC) is a significant issue for many types of earth infrastructure. The application of geosynthetic material has been common to reduce the climate-induced changes in SWCC. Engineered turf, which is a composite geosynthetic material, has gained popularity for different earth systems to increase overall infrastructure resiliency. This paper’s objective was to investigate engineered turf’s effect on the climate-induced changes in SWCC at shallow depths in the field conditions using the statistical non-parametric measure: Spearman rank correlation coefficient (ρs). This research hypothesized that since the changes in soil moisture and suction would relatively be simultaneous for exposed ground under variable climate, thereby exhibiting a reasonable negative correlation between water content and suction, whereas the degree of simultaneity in the changes between water content and suction of the soil under the engineered turf would display arbitrary correlation. To test the hypothesis, two test beds, (1) a compacted clay bed (CCB) and (2) a compacted clay bed overlain by engineered turf (ETB), were constructed with expansive soil and instrumented with collocated moisture sensors and tensiometers identically to collect concurrent water content and suction data continuously. The analysis revealed that the estimated ρs values for CCB were almost −1.0 during different drying conditions indicating a very strong correlation. On the contrary, the estimated ρs values for ETB were +0.79 to −0.32 indicating an irrational to a weak correlation between ρs. The results indicated the engineered turf to be an effective barrier to climate-induced changes in SWCC. 

One of the major purposes of landfill final covers is to minimize the infiltration of precipitation into the underlying waste. Deployment of conventional clay covers, geosynthetic clay liner, evapotranspiration (ET) covers, etc., has mostly been in practice to achieve the purposes. However, they have their shortcomings in the full attainment of the goals. In recent years, engineered turf has been introduced for landfill closure as a precipitation barrier to enhance cover performance. However, the field demonstration of engineered turf cover as the infiltration barrier is very limited. Soil moisture being one of the performance indicators of landfill covers, the objective of this study was to investigate moisture distribution characteristics of three distinct prototype landfill final cover systems: ET cover, compacted clay cover, and engineered turf cover, under in a humid subtropical climatic region. All the test covers (3 m × 3 m) were constructed side by side and were instrumented with moisture sensors at shallow depth (0.3 m depth). Descriptive statistics and histograms were used to summarize the features of the moisture distribution. Gaussian distribution theorem was used to investigate the spread out of the moisture data. In addition, the original moisture data were transformed to the standard normal distribution for a consistent framework for investigating the moisture variability of different covers. The analysis showed that 95% of the data were clustered around 0.173 to 0.238 m3/m3 at 0.3 m depth of engineered turf cover. On the contrary, the other two covers’ soil had a similar wider spread out of moisture data ranging approximately from 0.041 to 0.34 m3/m3. Results obtained from this study indicated the efficiency of engineered turf cover as an effective barrier to precipitation.