Soil Vegetation Atmosphere Research Articles

Soil–vegetation–atmosphere interaction over a hilly forest in the southern Huaihe River Basin: Long-term field experiment and preliminary analysis of basic observations 淮河流域南部丘陵森林地区土壤-植被-大气相互作用:长期野外试验观测的初步分析

To improve the understanding of the CO2 exchange and the cycling of energy and water between the land surface and atmosphere over a typical hilly forest in southeastern China, a long-term field experimental observatory was established in Huainan, Anhui Province. Here, the authors briefly describe the three parts of ongoing research activities: the environmental monitoring at the site, the meteorological observations on a high tower, and particularly the intensive measurement of soil–vegetation–atmosphere interaction on a lower tower. Specifically, the diurnal variation of basic meteorological variables on a typical clear day (13 July 2018), and their temporal variation in the first three months of the low tower's operation (4 June to 31 August 2018), and in combination with simultaneous data from the high tower, are analyzed. Results show that the data demonstrate reasonable variabilities, and the variables exhibit significant diurnal variation, characteristics of summer values, and considerable differences in summer months. The daily and monthly average albedos above the forest canopy were both 0.13. The daily average soil CO2 concentration was 1726 and 4481 ppm at 2 and 10 cm, respectively. The soil CO2 concentration changed with soil volumetric moisture contents, but showed a weak correlation with soil temperature in summer 2018. As the observatory continues to run and data continue to be collated, further investigation of the long-term variation of monsoon characteristics should be performed in the future. The experiment is useful in ecosystem and atmosphere interaction research, as well as for the development and evaluation of climate models, in the transitional climate zone of the Huaihe River basin.摘要本文简要介绍了包括三部分观测的安徽淮南长期野外试验观测站, 特别是土壤-植被-大气的集中观测, 对小塔运行前三个月 (2018年6月至8月) 的数据, 并结合同一时段大塔获得的数据, 进行了初步分析.结果表明这些资料有合理的变化特征, 日变化和夏季值特征显著, 各月份间气象变化有明显差异.土壤水分和温度受降雨影响, 在不同的下垫面条件下表现出不同的变化.土壤CO2日平均浓度在2 cm和10 cm处分别为1726和4481 ppm.2018年夏季土壤CO2浓度随土壤体积含水量的变化而变化, 但与土壤温度呈弱相关.

Energy, water and carbon exchanges in managed forest ecosystems: description, sensitivity analysis and evaluation of the INRAE GO+ model, version 3.0

Abstract. The mechanistic model GO+ describes the functioning and growth of managed forests based upon biophysical and biogeochemical processes. The biophysical and biogeochemical processes included are modelled using standard formulations of radiative transfer, convective heat exchange, evapotranspiration, photosynthesis, respiration, plant phenology, growth and mortality, biomass nutrient content, and soil carbon dynamics. The forest ecosystem is modelled as three layers, namely the tree overstorey, understorey and soil. The vegetation layers include stems, branches and foliage and are partitioned dynamically between sunlit and shaded fractions. The soil carbon submodel is an adaption of the Roth-C model to simulate the impact of forest operations. The model runs at an hourly time step. It represents a forest stand covering typically 1 ha and can be straightforwardly upscaled across gridded data at regional, country or continental levels. GO+ accounts for both the immediate and long-term impacts of forest operations on energy, water and carbon exchanges within the soil–vegetation–atmosphere continuum. It includes exhaustive and versatile descriptions of management operations (soil preparation, regeneration, vegetation control, selective thinning, clear-cutting, coppicing, etc.), thus permitting the effects of a wide variety of forest management strategies to be estimated: from close to nature to intensive. This paper examines the sensitivity of the model to its main parameters and estimates how errors in parameter values are propagated into the predicted values of its main output variables.The sensitivity analysis demonstrates an interaction between the sensitivity of variables, with the climate and soil hydraulic properties being dominant under dry conditions but the leaf biochemical properties being most influential with wet soil. The sensitivity profile of the model changes from short to long timescales due to the cumulative effects of the fluxes of carbon, energy and water on the stand growth and canopy structure. Apart from a few specific cases, the model simulations are close to the values of the observations of atmospheric exchanges, tree growth, and soil carbon and water stock changes monitored over Douglas fir, European beech and pine forests of different ages. We also illustrate the capacity of the GO+ model to simulate the provision of key ecosystem services, such as the long-term storage of carbon in biomass and soil under various management and climate scenarios.

A comprehensive dataset of vegetation states, fluxes of matter and energy, weather, agricultural management, and soil properties from intensively monitored crop sites in western Germany

Abstract. The development and validation of hydroecological land-surface models to simulate agricultural areas require extensive data on weather, soil properties, agricultural management, and vegetation states and fluxes. However, these comprehensive data are rarely available since measurement, quality control, documentation, and compilation of the different data types are costly in terms of time and money. Here, we present a comprehensive dataset, which was collected at four agricultural sites within the Rur catchment in western Germany in the framework of the Transregional Collaborative Research Centre 32 (TR32) “Patterns in Soil–Vegetation–Atmosphere Systems: Monitoring, Modeling and Data Assimilation”. Vegetation-related data comprise fresh and dry biomass (green and brown, predominantly per organ), plant height, green and brown leaf area index, phenological development state, nitrogen and carbon content (overall > 17 000 entries), and masses of harvest residues and regrowth of vegetation after harvest or before planting of the main crop (> 250 entries). Vegetation data including LAI were collected in frequencies of 1 to 3 weeks in the years 2015 until 2017, mostly during overflights of the Sentinel 1 and Radarsat 2 satellites. In addition, fluxes of carbon, energy, and water (> 180 000 half-hourly records) measured using the eddy covariance technique are included. Three flux time series have simultaneous data from two different heights. Data on agricultural management include sowing and harvest dates as well as information on cultivation, fertilization, and agrochemicals (27 management periods). The dataset also includes gap-filled weather data (> 200 000 hourly records) and soil parameters (particle size distributions, carbon and nitrogen content; > 800 records). These data can also be useful for development and validation of remote-sensing products. The dataset is hosted at the TR32 database (https://www.tr32db.uni-koeln.de/data.php?dataID=1889, last access: 29 September 2020) and has the DOI https://doi.org/10.5880/TR32DB.39 (Reichenau et al., 2020).

In situ measurements of soil and plant water isotopes: a review of approaches, practical considerations and a vision for the future

Abstract. The number of ecohydrological studies involving water stable isotope measurements has been increasing steadily due to technological (e.g., field-deployable laser spectroscopy and cheaper instruments) and methodological (i.e., tracer approaches or improvements in root water uptake models) advances in recent years. This enables researchers from a broad scientific background to incorporate water-isotope-based methods into their studies. Several isotope effects are currently not fully understood but might be essential when investigating root water uptake depths of vegetation and separating isotope processes in the soil–vegetation–atmosphere continuum. Different viewpoints exist on (i) extraction methods for soil and plant water and methodological artifacts potentially introduced by them, (ii) the pools of water (mobile vs. immobile) measured with those methods, and (iii) spatial variability and temporal dynamics of the water isotope composition of different compartments in terrestrial ecosystems. In situ methods have been proposed as an innovative and necessary way to address these issues and are required in order to disentangle isotope effects and take them into account when studying root water uptake depths of plants and for studying soil–plant–atmosphere interaction based on water stable isotopes. Herein, we review the current status of in situ measurements of water stable isotopes in soils and plants, point out current issues and highlight the potential for future research. Moreover, we put a strong focus and incorporate practical aspects into this review in order to provide a guideline for researchers with limited previous experience with in situ methods. We also include a section on opportunities for incorporating data obtained with described in situ methods into existing isotope-enabled ecohydrological models and provide examples illustrating potential benefits of doing so. Finally, we propose an integrated methodology for measuring both soil and plant water isotopes in situ when carrying out studies at the soil–vegetation–atmosphere continuum. Several authors have shown that reliable data can be generated in the field using in situ methods for measuring the soil water isotope composition. For transpiration, reliable methods also exist but are not common in ecohydrological field studies due to the required effort. Little attention has been paid to in situ xylem water isotope measurements. Research needs to focus on improving and further developing those methods. There is a need for a consistent and combined (soils and plants) methodology for ecohydrological studies. Such systems should be designed and adapted to the environment to be studied. We further conclude that many studies currently might not rely on in situ methods extensively because of the technical difficulty and existing methodological uncertainties. Future research needs to aim on developing a simplified approach that provides a reasonable trade-off between practicability and precision and accuracy.

Improving a land surface scheme for estimating sensible and latent heat fluxes above grasslands with contrasting soil moisture zones

Knowledge of soil–vegetation–atmosphere energy exchange processes is essential for examining the response of agriculture to changes in climate in both the short and long term. However, there are relatively few sites where all the flux measurements necessary for evaluating these responses are available; where they exist, data are often incomplete and/or of limited duration. At the same time, there is often an extensive observation network available that has gathered key meteorological data (sunshine, wind, rainfall, etc.) over decades. Simulating the terms of the surface energy balance (SEB) using available meteorological, soil and vegetation data can improve our understanding of how agricultural systems respond to climate and how this response will vary spatially. Here, we employ a physically-based scheme to simulate the SEB fluxes over a mid-latitude, maritime temperate environment using routine weather observations. The latent heat flux is a critical SEB term as it incorporates the response of the plant to environmental conditions including available energy and soil water. This response is represented in modeling schemes through surface resistance (rs), which is usually expressed as a function of near-surface water vapor alone. In this study, we simulate the SEB over two grassland sites, where eddy flux observations are available, representing imperfectly- and poorly- drained soils. We employ three different formulations of rs, representing varying degrees of sophistication, to estimate the surface fluxes. Due to differences in soil moisture characteristics between the sites, we ultimately focused our attention on an rs formulation that accounted for soil water retention capacity, based on the Jarvis conductance model; the results at both hourly and daily intervals are in good agreement, with RMSE values of ≈ 40 W m−2 for sensible and latent heat fluxes at both sites. The findings show the potential value of using routine weather observations to generate the SEB where flux observations are not available and the importance of soil properties in estimating surface fluxes. These findings could contribute to the assessment of past and future climate change on grassland ecosystems.

Long-term analysis of the shrinkage and swelling of clayey soils in a climate change context by numerical modelling and field monitoring

The shrinkage swelling phenomenon of clayey soils is affected by Soil-Vegetation-Atmosphere (SVA) interactions and can cause severe structural damage to lightly loaded constructions such as residential buildings. A soil-atmosphere interaction method was primarily presented along with a coupled hydro-thermal soil model. This approach was established to determine primarily, the natural time variable boundary conditions at the considered soil surface and secondly to determine the spatial–temporal changes of the soil suction, water content and temperature. Thereafter, the influence of the water uptake by vegetation was incorporated in the source term of the unsaturated water flow theory, using an existing root water uptake model. Subsequently, the variations of the soil suction were related to the volume change using a linear model. The associated volumetric indices in the void ratio-log suction plan, along with the complementary parameters of the linear model were correlated with basic geotechnical parameters. Comparisons between the simulation results and observation from a monitored site showed an acceptable performance of the predictions. The approach was then extended to study the influence of future climate projections (2050) on soil displacements using three Representative Concentration Pathway (RCP) climate change scenarios which revealed different possible behavior in both short and long-term.

Evapotranspiration partition using the multiple energy balance version of the ISBA-A-g<sub>s</sub> land surface model over two irrigated crops in a semi-arid Mediterranean region (Marrakech, Morocco)

Abstract. The main objective of this work is to question the representation of the energy budget in soil–vegetation–atmosphere transfer (SVAT) models for the prediction of the turbulent fluxes in the case of irrigated crops with a complex structure (row) and under strong transient hydric regimes due to irrigation. To this end, the Interaction between Soil, Biosphere, and Atmosphere (ISBA-A-gs) is evaluated at a complex open olive orchard and, for the purposes of comparison, on a winter wheat field taken as an example of a homogeneous canopy. The initial version of ISBA-A-gs, based on a composite energy budget (hereafter ISBA-1P for one patch), is compared to the new multiple energy balance (MEB) version of ISBA that represents a double source arising from the vegetation located above the soil layer. In addition, a patch representation corresponding to two adjacent, uncoupled source schemes (hereafter ISBA-2P for two patches) is also considered for the olive orchard. Continuous observations of evapotranspiration (ET), with an eddy covariance system and plant transpiration (Tr) with sap flow and isotopic methods were used to evaluate the three representations. A preliminary sensitivity analyses showed a strong sensitivity to the parameters related to turbulence in the canopy introduced in the new ISBA–MEB version. For wheat, the ability of the single- and dual-source configuration to reproduce the composite soil–vegetation heat fluxes was very similar; the root mean square error (RMSE) differences between ISBA-1P, ISBA-2P and ISBA–MEB did not exceed 10 W m−2 for the latent heat flux. These results showed that a composite energy balance in homogeneous covers is sufficient to reproduce the total convective fluxes. The two configurations are also fairly close to the isotopic observations of transpiration in spite of a light underestimation (overestimation) of ISBA-1P (ISBA–MEB). At the olive orchard, contrasting results are obtained. The dual-source configurations, including both the uncoupled (ISBA-2P) and the coupled (ISBA–MEB) representations, outperformed the single-source version (ISBA-1P), with slightly better results for ISBA–MEB in predicting both total heat fluxes and evapotranspiration partition. Concerning plant transpiration in particular, the coupled approach ISBA–MEB provides better results than ISBA-1P and, to a lesser extent, ISBA-2P with RMSEs of 1.60, 0.90, and 0.70 mm d−1 and R2 of 0.43, 0.69, and 0.70 for ISBA-1P, ISBA-2P and ISBA–MEB, respectively. In addition, it is shown that the acceptable predictions of composite convective fluxes by ISBA-2P for the olive orchard are obtained for the wrong reasons as neither of the two patches is in agreement with the observations because of a bad spatial distribution of the roots and a lack of incoming radiation screening for the bare soil patch. This work shows that composite convection fluxes predicted by the SURFace EXternalisée (SURFEX) platform and the partition of evapotranspiration in a highly transient regime due to irrigation is improved for moderately open tree canopies by the new coupled dual-source ISBA–MEB model. It also points out the need for further local-scale evaluations on different crops of various geometry (more open rainfed agriculture or a denser, intensive olive orchard) to provide adequate parameterisation to global database, such as ECOCLIMAP-II, in the view of a global application of the ISBA–MEB model.

Temporal interpolation of land surface fluxes derived from remote sensing – results with an unmanned aerial system

Abstract. Remote sensing imagery can provide snapshots of rapidly changing land surface variables, e.g. evapotranspiration (ET), land surface temperature (Ts), net radiation (Rn), soil moisture (θ), and gross primary productivity (GPP), for the time of sensor overpass. However, discontinuous data acquisitions limit the applicability of remote sensing for water resources and ecosystem management. Methods to interpolate between remote sensing snapshot data and to upscale them from an instantaneous to a daily timescale are needed. We developed a dynamic soil–vegetation–atmosphere transfer model to interpolate land surface state variables that change rapidly between remote sensing observations. The “Soil–Vegetation, Energy, water, and CO2 traNsfer” (SVEN) model, which combines the snapshot version of the remote sensing Priestley–Taylor Jet Propulsion Laboratory ET model and light use efficiency GPP models, now incorporates a dynamic component for the ground heat flux based on the “force-restore” method and a water balance “bucket” model to estimate θ and canopy wetness at a half-hourly time step. A case study was conducted to demonstrate the method using optical and thermal data from an unmanned aerial system at a willow plantation flux site (Risoe, Denmark). Based on model parameter calibration with the snapshots of land surface variables at the time of flight, SVEN interpolated UAS-based snapshots to continuous records of Ts, Rn, θ, ET, and GPP for the 2016 growing season with forcing from continuous climatic data and the normalized difference vegetation index (NDVI). Validation with eddy covariance and other in situ observations indicates that SVEN can estimate daily land surface fluxes between remote sensing acquisitions with normalized root mean square deviations of the simulated daily Ts, Rn, θ, LE, and GPP of 11.77 %, 6.65 %, 19.53 %, 14.77 %, and 12.97 % respectively. In this deciduous tree plantation, this study demonstrates that temporally sparse optical and thermal remote sensing observations can be used to calibrate soil and vegetation parameters of a simple land surface modelling scheme to estimate “low-persistence” or rapidly changing land surface variables with the use of few forcing variables. This approach can also be applied with remotely-sensed data from other platforms to fill temporal gaps, e.g. cloud-induced data gaps in satellite observations.

Advancing simulations of water fluxes, soil moisture and drought stress by using the LWF-Brook90 hydrological model in R

Soil vegetation atmosphere transport (SVAT) models are important for the quantification of water fluxes, soil water availability, drought stress and their uncertainties under climate change. We present LWFBrook90R, an enhanced implementation of the well-established, process-based SVAT model LWF-Brook90 for the R environment for statistical computing. The package provides new functions and sub-models for model parameterization, and facilitates parallel computing, sensitivity analysis and inverse calibration of the model. A case study comprising i) basic forward water balance simulations for temperate grassland vegetation, deciduous and evergreen forest, ii) a parallelized sensitivity analysis, and iii) Bayesian calibrations based on soil water storage observed in a poplar (Populus nigra × P. maximowiczii) Short Rotation Forest (SRF) demonstrates the utility of the R package. The sensitivity analysis revealed parameters affecting plant-available soil water storage capacity and the vegetation's timing and level of water demand to be most important for the annual course of simulated soil water storage, with seasonal and interannual differences in parameter importance rankings. The subsequent calibration yielded a very high agreement between daily simulated and observed soil water storage (0-200 cm soil depth) for the calibration and validation datasets, with Nash-Sutcliffe efficiencies of 0.97 and 0.95, respectively. The final model predicted high though realistic rates of annual evapotranspiration (2011: 844 ± 3.8 mm y-1, 2012: 733 ± 4.5 mm y-1) for the poplar SRF, regularly exceeding grass reference evaporation (ET0) by 20-47% during the months of the growing season. However, basing calibrations solely on observed soil water storage probably resulted in biased partitioning of evapotranspiration towards interception losses. The integration of the LWF-Brook90 hydrological model into R with its wide variety of extensions was successfully tested and may provide efficient, reliable and reproducible water balance predictions by facilitating complex statistical analyses and large-scale applications of the model.

Characterizing uncertainty in the hydraulic parameters of oil sands mine reclamation covers and its influence on water balance predictions

Abstract. One technique to evaluate the performance of oil sands reclamation covers is through the simulation of long-term water balance using calibrated soil–vegetation–atmosphere transfer models. Conventional practice has been to derive a single set of optimized hydraulic parameters through inverse modelling (IM) based on short-term (<5–10 years) monitoring datasets. This approach is unable to characterize the impact of variability in the cover properties. This study utilizes IM to optimize the hydraulic properties for 12 soil cover designs, replicated in triplicate, at Syncrude's Aurora North mine site. The hydraulic parameters for three soil types (peat cover soil, coarse-textured subsoil, and lean oil sand substrate) were optimized at each monitoring site from 2013 to 2016. The resulting 155 optimized parameter values were used to define distributions for each parameter/soil type, while the progressive Latin hypercube sampling (PLHS) method was used to sample parameter values randomly from the optimized parameter distributions. Water balance models with the sampled parameter sets were used to evaluate variations in the maximum sustainable leaf area index (LAI) for five illustrative covers and quantify uncertainty associated with long-term water balance components and LAI values. Overall, the PLHS method was able to better capture broader variability in the water balance components than a discrete interval sampling method. The results also highlight that climate variability dominates the simulated variability in actual evapotranspiration and that climate and parameter uncertainty have a similar influence on the variability in net percolation.

Crop growth and soil water fluxes at erosion‐affected arable sites: Using weighing lysimeter data for model intercomparison

AbstractAgroecosystem models need to reliably simulate all biophysical processes that control crop growth, particularly the soil water fluxes and nutrient dynamics. As a result of the erosion history, truncated and colluvial soil profiles coexist in arable fields. The erosion‐affected field‐scale soil spatial heterogeneity may limit agroecosystem model predictions. The objective was to identify the variation in the importance of soil properties and soil profile modifications in agroecosystem models for both agronomic and environmental performance. Four lysimeters with different soil types were used that cover the range of soil variability in an erosion‐affected hummocky agricultural landscape. Twelve models were calibrated on crop phenological stages, and model performance was tested against observed grain yield, aboveground biomass, leaf area index, actual evapotranspiration, drainage, and soil water content. Despite considering identical input data, the predictive capability among models was highly diverse. Neither a single crop model nor the multi‐model mean was able to capture the observed differences between the four soil profiles in agronomic and environmental variables. The model's sensitivity to soil‐related parameters was apparently limited and dependent on model structure and parameterization. Information on phenology alone seemed insufficient to calibrate crop models. The results demonstrated model‐specific differences in the impact of soil variability and suggested that soil matters in predictive agroecosystem models. Soil processes need to receive greater attention in field‐scale agroecosystem modeling; high‐precision weighable lysimeters can provide valuable data for improving the description of soil–vegetation–atmosphere process in the tested models.

Impacts of climate variability and landscape pattern change on evapotranspiration in a grassland landscape mosaic

AbstractEvapotranspiration (ET), a key component of the hydrological cycle, affects the transport of water and energy in the soil–vegetation–atmosphere system. Thus, quantifying the driving forces of ET dynamics is important to ensure rational water resource utilization. Based on meteorological and satellite data, spatiotemporal dynamics of ET were detected using the Surface Energy Balance System (SEBS) model, and effects of climate variability and landscape pattern change on ET dynamics in an arid to semiarid landscape mosaic during the growing season (April‐October) from 2001 to 2015 in Xilingol League, China were evaluated. The results indicated that (a) a significant increase (P < .05) in ET was found in the north‐eastern Xilingol League, and a significant decrease (P < .05) in ET was confined to the southwest and (b) climate variability had significant effects on ET dynamics. All climatic factors showed a positive correlation relationship with ET dynamics, and mean temperature (Ta) was the most influential climatic factor on ET dynamics followed by relative humidity (Rh), wind speed (Ws), and precipitation (Pr), respectively. The influence of landscape pattern change on ET dynamics was mainly reflected in the increase of the normalized difference vegetation index (NDVI) promoting ET dynamics. Several other landscape pattern metrics also had important impacts on ET dynamics, which were mainly reflected in the positive effect of the aggregation index (AI) on ET dynamics and the negative effects of the largest patch index (LPI), edge density (ED), and percentage of landscape (PLAND) on ET dynamics. To promote effective water resource utilization, landscape managers should continue to moderately implement vegetation restoration projects such as the Grain for Green Project, orient with conversion of low‐quality cropland into grassland, and conserve large areas of grassland. Appropriate management measures for forests and cropland scattered in the landscape mosaic, based on local climate and soil properties, as well as socioeconomic goals, are also required.

Ability of a soil–vegetation–atmosphere transfer model and a two-source energy balance model to predict evapotranspiration for several crops and climate conditions

Abstract. The heterogeneity of Agroecosystems, in terms of hydric conditions, crop types and states, and meteorological forcing, is difficult to characterize precisely at the field scale over an agricultural landscape. This study aims to perform a sensitivity study with respect to the uncertain model inputs of two classical approaches used to map the evapotranspiration of agroecosystems: (1) a surface energy balance (SEB) model, the Two-Source Energy Balance (TSEB) model, forced with thermal infrared (TIR) data as a proxy for the crop hydric conditions, and (2) a soil–vegetation–atmosphere transfer (SVAT) model, the SEtHyS model, where hydric conditions are computed from a soil water budget. To this end, the models' skill was compared using a large and unique in situ database covering different crops and climate conditions, which was acquired over three experimental sites in southern France and Morocco. On average, the models provide 30 min estimations of latent heat flux (LE) with a RMSE of around 55 W m−2 for TSEB and 47 W m−2 for SEtHyS, and estimations of sensible heat flux (H) with a RMSE of around 29 W m−2 for TSEB and 38 W m−2 for SEtHyS. A sensitivity analysis based on realistic errors aimed to estimate the potential decrease in performance induced by the spatialization process. For the SVAT model, the multi-objective calibration iterative procedure (MCIP) is used to determine and test different sets of parameters. TSEB is run with only one set of parameters and provides acceptable performance for all crop stages apart from the early growing season (LAI < 0.2 m2 m−2) and when hydric stress occurs. An in-depth study on the Priestley–Taylor key parameter highlights its marked diurnal cycle and the need to adjust its value to improve flux partitioning between the sensible and latent heat fluxes (1.5 and 1.25 for France and Morocco, respectively). Optimal values of 1.8–2 were highlighted under cloudy conditions, which is of particular interest due to the emergence of low-altitude drone acquisition. Under developed vegetation (LAI > 0.8 m2 m−2) and unstressed conditions, using sets of parameters that only differentiate crop types is a valuable trade-off for SEtHyS. This study provides some scientific elements regarding the joint use of both approaches and TIR imagery, via the development of new data assimilation and calibration strategies.

Analysis of climate-driven processes in clayey slopes for early warning system design

The activity of deep landslides in slopes formed of clayey turbidites has been observed to be connected to the climatic regime in the Mediterranean, based on field data and phenomenological interpretations. With the aim of investigating this connection, the effects of the soil–vegetation–atmosphere interaction on the piezometric regime were investigated by means of hydraulic finite-element analyses of the transient seepage across a prototype clayey slope. The ground surface condition was defined accounting for rainfall and evapotranspiration flux, estimated through the United Nations' Food and Agriculture Organization Penman–Monteith approach. The predicted excursions of the piezometric head within the slope over time were found to agree with field observations. The predicted piezometric profiles were investigated to evaluate the infiltration processes during the year and show how these bring about seasonal piezometric excursions. The results of the hydraulic analyses were then input into limit equilibrium analyses to assess the impact of the slope–vegetation–atmosphere interaction on the stability of landslide bodies of different depths. The results show how such impact depends on the stratigraphy of the slope. Furthermore, the variability of the climatic precursor of landsliding with landslide depth was characterised to guide the design of early warning systems for mitigation purposes.

From NEON Field Sites to Data Portal: A Community Resource for Surface–Atmosphere Research Comes Online

AbstractThe National Ecological Observatory Network (NEON) is a multidecadal and continental-scale observatory with sites across the United States. Having entered its operational phase in 2018, NEON data products, software, and services become available to facilitate research on the impacts of climate change, land-use change, and invasive species. An essential component of NEON are its 47 tower sites, where eddy-covariance (EC) sensors are operated to determine the surface–atmosphere exchange of momentum, heat, water, and CO2. EC tower networks such as AmeriFlux, the Integrated Carbon Observation System (ICOS), and NEON are vital for providing the distributed observations to address interactions at the soil–vegetation–atmosphere interface. NEON represents the largest single-provider EC network globally, with standardized observations and data processing explicitly designed for intersite comparability and analysis of feedbacks across multiple spatial and temporal scales. Furthermore, EC is tightly integrated with soil, meteorology, atmospheric chemistry, isotope, phenology, and rich contextual observations such as airborne remote sensing and in situ sampling bouts. Here, we present an overview of NEON’s observational design, field operation, and data processing that yield community resources for the study of surface–atmosphere interactions. Near-real-time data products become available from the NEON Data Portal, and EC and meteorological data are ingested into AmeriFlux and FLUXNET globally harmonized data releases. Open-source software for reproducible, extensible, and portable data analysis includes the eddy4R family of R packages underlying the EC data product generation. These resources strive to integrate with existing infrastructures and networks, to suggest novel systemic solutions, and to synergize ongoing research efforts across science communities.

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.

The Impact of Climate Change on the Water Balance of Oil Sands Reclamation Covers and Natural Soil Profiles

Abstract The design of reclamation soil covers at oil sands mines in northern Alberta, Canada, has been conventionally based on the calibration of soil–vegetation–atmosphere transfer (SVAT) models against field monitoring observations collected over several years, followed by simulations of long-term performance using historical climate data. This paper evaluates the long-term water balances for reclamation covers on two oil sands landforms and three natural coarse-textured forest soil profiles using both historical climate data and future climate projections. Twenty-first century daily precipitation and temperature data from CanESM2 were downscaled based on three representative concentration pathways (RCPs) employing a stochastic weather generator [Long Ashton Research Station Weather Generator (LARS-WG)]. Relative humidity, wind speed, and net radiation were downscaled using the delta change method. Downscaled precipitation and estimated potential evapotranspiration were used as inputs to simulate soil water dynamics using physically based models. Probability distributions of growing season (April–October) actual evapotranspiration (AET) and net percolation (NP) for the baseline and future periods show that AET and NP at all sites are expected to increase throughout the twenty-first century regardless of RCP, time period, and soil profile. Greater increases in AET and NP are projected toward the end of the twenty-first century. The increases in future NP at the two reclamation covers are larger (as a percentage increase) than at most of the natural sites. Increases in NP will result in greater water yield to surface water and may accelerate the rate at which chemical constituents contained within mine waste are released to downstream receptors, suggesting these potential changes need to be considered in mine closure designs.

Examination of deep root water uptake using anomalies of soil water stable isotopes, depth-controlled isotopic labeling and mixing models

Knowledge on the water uptake depths of vegetation is crucial for understanding water transport processes of the soil-vegetation atmosphere continuum and relevant for many applications (e.g. the estimation of groundwater recharge, irrigation planning and the parameterization of (eco-) hydrological models). The identification and quantification of water uptake from deep soil layers and groundwater remain challenging. This study uses a combined framework based on natural abundances of stable water isotopes and isotopic labeling experiments with deuterium oxide (2H2O) to study root water uptake and identify uptake from deep soil in a semi-arid environment.Between 2013 and 2016, more than 1000 soil (isotope depth profiles); plant (xylem and transpiration) and water (precipitation and groundwater) samples for the analysis of isotope ratios were collected. Two experiments using isotopic labeling were carried out in order to assess root water uptake depths. Herein, we i) present series of deep soil water isotope depth profiles, interpret water transport dynamics and ecohydrological feedbacks; ii) examine the suitability of natural isotope depth profiles for identifying deep root water uptake; iii) apply the Bayesian mixing model MixSIAR to quantify deep root water uptake and iv) constrain water uptake depths using isotopic labeling experiments and derive an active root water uptake distribution.Our results show that the form of isotope depth profiles of soil in water-limited environments follows characteristic shapes for the end of the rainy and dry seasons, respectively. Isotope ratios in the upper 4 m of the soil are heavily dependent on the character of the respective rainy season. Under certain conditions – e.g. droughts or weak rainy seasons – the isotope depth profile displays an enrichment in heavy isotopes up to 4 m depth. Such pronounced anomalies provide an opportunity for studies on source water partitioning. In the present experiment, the studied individuals of Acacia erioloba were found to obtain 37% [24–52%] of their water from deep soil (>4 m) and groundwater at the end of the dry season of 2015. All other investigated trees (individuals of B. plurijuga, S. luebertii, T. sericea and C. collinum) mainly utilize water originating from 1 m to 2.5 m depth. Under “average” rainy season conditions, the similarity of isotope ratios of potential plant water sources hinders a conclusive identification of water uptake depths.Deep natural isotope depth profiles in dry environments can – under certain conditions – be used to identify and quantify access of vegetation to deep water resources. Isotopic labeling enables to determine active root distributions for the lateral root zone. Combined frameworks contribute to a better understanding of deep water uptake. A differentiated consideration of water uptake from the lateral root zone and deep, potentially groundwater-tapping roots is required in order to fully investigate ecohydrological feedbacks and for a proper parameterization of models.

Diurnal and seasonal coupling of conifer sap flow and vapour pressure deficit across topoclimatic gradients in a subalpine catchment

AbstractThe hydroclimatic controls on transpiration often follow hillslope‐ or catchment‐scale topography in water‐limited ecosystems; however, rates of transpiration may deviate from these patterns due to microtopographic variation in environmental conditions or physiology. Here, we assessed the microtopographic effects on water use of five conifer species within four subcatchments in western Montana along a water availability gradient that was driven by aspect and elevation. To infer physiological processes at both diurnal and seasonal time scales, we analysed the relationship between sap velocity, Vs, and vapour pressure deficit, D, using instantaneous (half‐hourly) and aggregated (daily mean) values of Vs and D. Both within and across species, daily mean Vs was more tightly coupled to D at higher elevation sites (1,720 m), whereas trees 350 m lower in elevation became decoupled from D as snowmelt‐derived soil moisture declined. At the diurnal scale, we found that the degree of decoupling of Vs from D during soil moisture deficits decreased when a time lag between Vs and D was considered. Additionally, contrary to the common inference of plant hydraulic capacitance based on Vs lagging behind D at the diurnal scale, half‐hourly Vs tended to lead D in three of the five conifer species we studied. Predawn and midday branch water potential measurements provided additional evidence that topography influenced plant water status. These results suggest that improved understanding of soil–vegetation–atmosphere coupling in mountainous terrain requires further inquiry into the spatial variability of plant hydraulic regulation.

Monitoring of a Full-Scale Embankment Experiment Regarding Soil–Vegetation–Atmosphere Interactions

Slope mass-wasting like shallow slides are mostly triggered by climate effects, such as rainfall, and soil–vegetation–atmosphere (SVA) interactions play a key role. SVA interactions are studied by a full-scale embankment with different orientations (North and South) and vegetation covers (bare and vegetated) in the framework of the prediction of climate change effects on slope stability in the Pyrenees. A clayey sand from the Llobregat river delta was used for the construction of the embankment and laboratory tests showed the importance of suction on the strength and hydraulic conductivity. Sixty sensors, which are mostly installed at the upper soil layer of the embankment, registered 122 variables at four vertical profiles and the meteorological station with a 5 min scan rate. Regarding temperature, daily temperature fluctuation at the shallow soil layer disappeared at a depth of about 0.5 m. There was great influence of orientation with much higher values at the South-facing slope (up to 55 °C at −1 cm depth) due to solar radiation. Regarding rainfall infiltration, only long duration rainfalls produced an important increase of soil moisture and pore water pressure, while short duration rainfalls did not trigger significant variations. However, these changes mostly affected the surface soil layer and decreased with depth.