The Effect of Soil-Vegetation-Atmosphere Interaction on Slope Stability: A Numerical Study

The stability of a dike is influenced strongly by its water content, by way of changes in effective stress and weight. While flow through porous media is relatively well understood, water flux in and out of a dike through a vegetated surface is not as well understood. This paper presents a numerical study of the soil-vegetation-atmosphere interaction and discusses how it influences the stability of dikes covered with grass. A crop model was used to simulate vegetation growth and infiltration in response to meteorological forcing. The PLAXIS finite-element method model was used to simulate the impact of this infiltration on hydromechanical behaviour and dike stability. Results from a 4-year analysis indicated a strong correlation between root zone water content (WC rz) and factor of safety, although the relationship is not unique. The leaf area index (LAI) was also found to have a strong, lagged correlation with the water flux into the dike. This suggests that monitoring LAI could be a useful tool to identify vulnerable locations along dikes. It is therefore proposed that vegetation and root zone water content could be used as an indication to detect vulnerable dikes in the early stage.</p

Towards improved understanding of land-atmosphere coupling: An alternative metric of coupling strength

Water ManagementCivil Engineering and Geoscience

Sentinel-1 SAR Backscatter Response to Agricultural Drought in The Netherlands

Drought is a major natural hazard that impacts agriculture, the environment, and socio-economic conditions. In 2018 and 2019, Europe experienced a severe drought due to below average precipitation and high temperatures. Drought stress affects the moisture content and structure of agricultural crops and can result in lower yields. Synthetic Aperture Radar (SAR) observations are sensitive to the dielectric and geometric characteristics of crops and underlying soils. This study uses data from ESA’s Sentinel-1 SAR satellite to investigate the influence of drought stress on major arable crops of the Netherlands, its regional variability and the impact of water management decisions on crop development. Sentinel-1 VV, VH and VH/VV backscatter data are used to quantify the variability in the spatio-temporal dynamics of agricultural crop parcels in response to drought. Results show that VV and VH backscatter values are 1 to 2 dB lower for crop parcels during the 2018 drought compared to values in 2017. In addition, the growth season indicated by the cross-ratio (CR, VH/VV) for maize and onion is shorter during the drought year. Differences due to irrigation restrictions are observed in backscatter response from maize parcels. Lower CR values in 2019 indicate the impact of drought on the start of the growing season. Results demonstrate that Sentinel-1 can detect changes in the seasonal cycle of arable crops in response to agricultural drought.Mathematical Geodesy and Positionin

Impact of soil moisture data resolution on soil moisture and surface heat flux estimates through data assimilation: A case study in the Southern Great Plains

The spatial heterogeneity and temporal variation of soil moisture and surface heat fluxes are key to many geophysical and environmental studies. It has been demonstrated that they can be mapped by assimilating soil thermal and wetness information into surface energy balance models. The aim of this work is to determine whether enhancing the spatial resolution or temporal sampling frequency of soil moisture data could improve soil moisture or surface heat flux estimates. Two experiments are conducted in an area mainly covered by grassland, and land surface temperature (LST) observations from the Geostationary Operational Environmental Satellite (GOES) mission are assimilated together with either an enhanced L-band passive soil moisture product (9 km, 2-3 days) from the Soil Moisture Active Passive (SMAP) mission or a merged product (36 km, quasi-daily) from the SMAP and the Soil Moisture Ocean Salinity (SMOS) mission. The results suggest that the availability of soil moisture observations is increased by 41% after merging data from the SMAP and the SMOS missions. A comparison with results from a previous study that assimilated a coarser SMAP soil moisture product (36 km, 2-3 days) suggests that enhancing the temporal sampling frequency of soil moisture observations leads to improved soil moisture estimates at both the surface and root zone, and the largest improvement is seen in the bias metric (0.008 and 0.007m 3 m -3 on average at the surface and root zone, respectively). Enhancing the spatial resolution, however, does not significantly improve soil moisture estimates, particularly at the surface. Surface heat flux estimates from assimilating soil moisture data of different spatial or temporal resolutions are very similar.Water Resource

Can vegetation indices predict slope (stability) conditions?

Climatic conditions and vegetation cover influence the water flux in a dike body, which affect the effective stress and self-weight, hence its stability. The vegetation is the intermediate layer between the atmosphere and the soil, and therefore this layer influences the boundary water flux by transpiration and leaf interception, so considering vegetation in numerical analysis of slope stability provides insight into changing stability. This study investigates Soil-Vegetation-Atmosphere (SVA) interaction impact on macro stability of grass covered dikes. Two numerical models have been used in the current study: (i) a crop model for simulating the water balance in the root zone (unsaturated zone); (ii) a Finite Element Method (FEM) coupled to the crop model for hydro-mechanical andsafety analysis to calculate the Factor of Safety (FoS). Results of idealised analysis show that the Leaf Area Index (LAI) is coupled to the moisture in the root zone with a time lag, therefore, it is likely that it could be used as an indicator of safety. This proof-of-concept study enables dike managers to use the mentioned parameters as a proxy to identify vulnerable locations along a dike even in an early stage due to the lag correlation. This offers the opportunity to use remote sensing rather than physical inspection or installing sensors, along with history matching, to initially identify vulnerable locations along dikes.Geo-engineeringWater Resource

A Data-Driven Surrogate Approach for the Temporal Stability Forecasting of Vegetation Covered Dikes

Climatic conditions and vegetation cover influence water flux in a dike, and potentially the dike stability. A comprehensive numerical simulation is computationally too expensive to be used for the near real-time analysis of a dike network. Therefore, this study investigates a random forest (RF) regressor to build a data-driven surrogate for a numerical model to forecast the temporal macro-stability of dikes. To that end, daily inputs and outputs of a ten-year coupled numerical simulation of an idealised dike (2009–2019) are used to create a synthetic data set, comprising features that can be observed from a dike surface, with the calculated factor of safety (FoS) as the target variable. The data set before 2018 is split into training and testing sets to build and train the RF. The predicted FoS is strongly correlated with the numerical FoS for data that belong to the test set (before 2018). However, the trained model shows lower performance for data in the evaluation set (after 2018) if further surface cracking occurs. This proof-of-concept shows that a data-driven surrogate can be used to determine dike stability for conditions similar to the training data, which could be used to identify vulnerable locations in a dike network for further examination

The impact of evaporation induced cracks and precipitation on temporal slope stability

The stability of a dike is influenced strongly by its water content, via both changing its weight and strength. While safety calculations using both analytical and numerical methods are well studied, the impact of surface boundaries exposed to natural conditions is rarely considered, nor is the fact that this surface is covered in vegetation and is susceptible to cracking. This paper presents a numerical study of stability of dikes covered with grass, subject to meteorological forcing and crack formation due to drying conditions. Building on a previous study and adding the impact of cracking, a crop model and a Finite Element Method (FEM) model are integrated together using an optimisation method to ensure mass balance and consistency. The crop model, used to simulate vegetation growth and infiltration/evaporation in response to meteorological forcing, is modified to consider preferential flow due to cracking. The FEM model, used to simulate the dike stability and hydro-mechanical behaviour, has the material properties modified to simulate the impact of cracks. Results simulating a ten-year period indicate a strong impact of cracking on the factor of safety. The vegetation was found to be responsive to both crack presence and an increase in the amount of cracks, which suggests that monitoring vegetation could be a useful tool to identify cracked (vulnerable to cracking) locations along dikes.Geo-engineeringWater Resource

Use of displacement as a proxy for dike safety

Climatic conditions and vegetation cover influence water flux in a slope which affect the pore water pressure and self weight, hence its stability. High evapotranspiration and low precipitation rates during summer cause dry soil with low soil moisture (SM) that leads to soil shrinkage, which leads to cracking and reduced shear strength, which consequently decreases the stability of slopes. Soil re-wetting increases slope weight and exerts an additional driving force on the slope. Using Earth Observation (EO) data facilitates frequent, large-scale monitoring to identify the vulnerable areas along the slopes to avoid instability. Here we study the displacement of a vegetated dike subject to SM variations under varying climatic conditions.Results show that the SM and magnitude of total displacement at a desired location are highly positively correlated without time lag. This proof-of-concept study shows that near surface displacement due to interaction with the atmosphere has a strong relation with the water availability in the slope and therefore the Factor of Safety (FoS)Geo-engineeringWater Resource

The Effect of Soil-Vegetation-Atmosphere Interaction on Slope Stability: A Numerical Study

The stability of a dike is influenced strongly by its water content, by way of changes in effective stress and weight. While flow through porous media is relatively well understood, water flux in and out of a dike through a vegetated surface is not as well understood. This paper presents a numerical study of the soil-vegetation-atmosphere interaction and discusses how it influences the stability of dikes covered with grass. A crop model was used to simulate vegetation growth and infiltration in response to meteorological forcing. The PLAXIS finite-element method model was used to simulate the impact of this infiltration on hydromechanical behaviour and dike stability. Results from a 4-year analysis indicated a strong correlation between root zone water content (WC rz) and factor of safety, although the relationship is not unique. The leaf area index (LAI) was also found to have a strong, lagged correlation with the water flux into the dike. This suggests that monitoring LAI could be a useful tool to identify vulnerable locations along dikes. It is therefore proposed that vegetation and root zone water content could be used as an indication to detect vulnerable dikes in the early stage.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Geo-engineeringWater Resource

Assessing total water storage and identifying flood events over Tonlé Sap basin in Cambodia using GRACE and MODIS satellite observations combined with hydrological models

Abstract In this study, satellite observations including gravity (GRACE), terrestrial reflectance (MODIS), and global precipitation (TRMM) data, along with the output from the PCR-GLOBWB hydrological model, are used to generate monthly and sub-monthly terrestrial water storage (TWS) estimates and quantify flood events over the Tonlé Sap basin between 2002 and 2014. This study is the first time GRACE data have been used to investigate the hydrological processes over the Tonlé Sap basin. To improve the accuracy of the TWS estimates from GRACE, a signal restoration method was applied in an effort to recover the signal loss (i.e., signal leakage) inherent in the standard GRACE post-processing scheme. The method applies the correction based on the GRACE observations only, requiring no external data or hydrological models. The effectiveness of the technique over the Tonlé Sap basin was validated against several independent data sets. Based on the GRACE observations since 2002, the 2011 and 2013 flood events were clearly identified, and measured to have basin-averaged TWS values of 42 cm (40% higher than the long-term mean peak value) and 36 cm (34% higher) equivalent water height, respectively. Those same years also coincide with the largest observed flood extents, estimated from the MODIS data as 6561 km2 (91% above the long-term mean peak value) and 5710 km2 (66% above), respectively. Those flood events are also linked to the observed inter-annual variations of water storage between 2010 and 2014. It was shown that those inter-annual variations mainly reflect the variations in the surface water and groundwater storage components, influenced by the change of the precipitation intensity. In addition, this study presents a new approach for deriving monthly and sub-monthly TWS variations over a regularly inundated area by using MODIS reflectance data in addition to GRACE solutions. The results of this study show that GRACE data can be considered as an effective tool for monitoring certain small-scale (82,000 km2) hydrological basins