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Irrigation is an important component of the terrestrial water cycle, but it is often poorly accounted for in models. Recent studies have attempted to integrate satellite data and land surface models via data assimilation (DA) to (a) detect and quantify irrigation, and (b) better estimate the related land surface variables such as soil moisture, vegetation, and evapotranspiration. In this study, different synthetic DA experiments are tested to advance satellite DA for the estimation of irrigation. We assimilate synthetic Sentinel‐1 backscatter observations into the Noah‐MP model coupled with an irrigation scheme. When updating soil moisture, we found that the DA sets better initial conditions to trigger irrigation in the model. However, DA updates to wetter conditions can inhibit irrigation simulation. Building on this limitation, we propose an improved DA algorithm using a buddy check approach. The method still updates the land surface, but now the irrigation trigger is not primarily based on the evolution of soil moisture, but on an adaptive innovation (observation minus forecast) outlier detection. The new method was found to be optimal for more temperate climates where irrigation events are less frequent and characterized by higher application rates. It was found that the DA outperforms the model‐only 14‐day irrigation estimates by about 20% in terms of root‐mean‐squared differences, when frequent (daily or every other day) observations are available. With fewer observations or high levels of noise, the system strongly underestimates the irrigation amounts. The method is flexible and can be expanded to other DA systems, also real‐world cases. Plain Language Summary: Irrigation has an important impact on the terrestrial water cycle. However, it remains poorly simulated by models and it is hard to quantify through satellite observations alone. The combination of models and satellite observations to detect and quantify irrigation has been explored in the last few years. Recently, Sentinel‐1 radar (microwave) observations have been assimilated into the Noah‐MP land surface model in order to quantify irrigation, and better estimate the related land surface variables, such as soil moisture and vegetation. This system has shown benefits but also limitations, which are highlighted and addressed in our study using synthetic experiments. We propose an improved data assimilation algorithm and test it for different sites and levels of model and observation error. For temperate regions, the new method estimates irrigation more accurately (20%) than the model alone, provided that frequent (daily or every other day) observations are available. With further developments, the new methodology could be used in a real‐world experiment. Key Points: Model‐driven irrigation estimation has limitations, also when based on improved soil moisture conditions obtained via data assimilationA new method based on an adaptive outlier detection improves the estimated irrigation in a synthetic backscatter data assimilation setupThe method performs best with frequent data assimilation in a temperate climate, reducing irrigation errors by 20% [ABSTRACT FROM AUTHOR]

Peatlands are poorly represented in global Earth system modeling frameworks. Here we add a peatland‐specific land surface hydrology module (PEAT‐CLSM) to the Catchment Land Surface Model (CLSM) of the NASA Goddard Earth Observing System (GEOS) framework. The amended TOPMODEL approach of the original CLSM that uses topography characteristics to model catchment processes is discarded, and a peatland‐specific model concept is realized in its place. To facilitate its utilization in operational GEOS efforts, PEAT‐CLSM uses the basic structure of CLSM and the same global input data. Parameters used in PEAT‐CLSM are based on literature data. A suite of CLSM and PEAT‐CLSM simulations for peatland areas between 40°N and 75°N is presented and evaluated against a newly compiled data set of groundwater table depth and eddy covariance observations of latent and sensible heat fluxes in natural and seminatural peatlands. CLSM's simulated groundwater tables are too deep and variable, whereas PEAT‐CLSM simulates a mean groundwater table depth of −0.20 m (snow‐free unfrozen period) with moderate temporal fluctuations (standard deviation of 0.10 m), in significantly better agreement with in situ observations. Relative to an operational CLSM version that simply includes peat as a soil class, the temporal correlation coefficient is increased on average by 0.16 and reaches 0.64 for bogs and 0.66 for fens when driven with global atmospheric forcing data. In PEAT‐CLSM, runoff is increased on average by 38% and evapotranspiration is reduced by 19%. The evapotranspiration reduction constitutes a significant improvement relative to eddy covariance measurements. Plain Language Summary: Peatlands are wetlands in which plant matter has accumulated over thousands of years under almost permanently water‐logged conditions. Alterations in these conditions as a result of global climate change can lead to the release of the huge peatland carbon pool as carbon dioxide over much shorter timescales than were required for accumulation. The additional emissions would amplify global warming. A better representation of the peatland hydrology in global Earth system models can help quantify how peatlands respond to a changing climate. In this paper, we add a peatland‐specific land surface hydrology module to the land surface model used in NASA's GEOS Earth system modeling framework. Comparisons of numerical simulations encompassing northern peatlands against field observations show that the new model version significantly improves our ability to capture the hydrological dynamics of peatlands. The new peatland representation in GEOS offers new opportunities, including the potential for merging model information and remote sensing observations in a way that improves our understanding of the overall role played by peatlands in the global water and carbon cycles. Key Points: A peatland‐specific land surface hydrology was added to an Earth system model and constrained by literature data, without parameter tuningSimulations were evaluated with a data set of groundwater table depth and evapotranspiration with unprecedented coverage in high latitudesThe peatland model version performs significantly better in terms of hydrological variables over peatlands than the operational model [ABSTRACT FROM AUTHOR]

Hydraulic conductivity at and near saturation is difficult to predict. We investigated, for the first time, the potential of boosted regression trees to identify the key factors that determine saturated and near-saturated hydraulic conductivities in undisturbed soils with a globalmeta-database of tension infiltrometermeasurements. Our results demonstrate that pedotransfer functions developed from meta-databases may strongly over-estimate prediction performance unless they are validated against each individual data source separately. For such a source-wise cross-validation, we estimated the hydraulic conductivity at a tension of 10 cm (K10) and the saturated hydraulic conductivity (Ks) with coefficients of determination of 0.36 and 0.15, respectively. The most important predictors for K10 were the average annual precipitation and temperature at the measurement location, which are key variables for pedogenesis and constrain soilmanagement. More research is required for the in-depth interpretation of their influence on hydraulic conductivity. The soil clay and organic carbon contents were also important predictors of K10, with hydraulic conductivity decreasing as organic carbon contents increased up to 1.5% and as clay contents increased between about 10 and 40%. The direction of the tension-sequence with which the infiltrometer data were collected was also a significant predictor. Land use and bulk density were the most important predictors for Ks. The direction of the tension-sequence and the soil texture class were also important, with both coarse and fine-textured soils generally having larger Ks values than medium-textured soils. [ABSTRACT FROM AUTHOR]

Random walk particle tracking (RWPT) is a well established and efficient alternative to grid-based Eulerian approaches when simulating the advection-dispersion transport problem in highly heterogeneous porous media. However, RWPT methods suffer from a lack of accuracy when the dispersion tensor or the water content is spatially discontinuous. We present improvements to the concept of a partially reflecting barrier used to account for these discontinuities: (1) the nonlinear time splitting with √Δt = √Δt1 + √Δt2 that corrects for the systematic overestimation of the second dispersion displacement across an element interface when linear time splitting is used; (2) the one-sided reflection coefficient that correctly represents the effect of discontinuous dispersion coefficients and water content but eliminates redundant reflections of the two-sided reflection coefficient and limits the error for discrete Δt; and (3) the transformation of the dispersive displacement across the element interface for complex multidimensional transport problems. The proposed improvements are verified numerically by comparison with an analytical solution and a reference RWPT method. The results indicate an increased efficiency and accuracy of the new RWPT algorithm. Because the new algorithm efficiently simulates both advection- and dispersion-dominated transport conditions, it enhances the applicability of RWPT to scenarios in which both conditions occur, as, for example, in the highly transient unsaturated zone. The algorithm is easily implemented and it is shown that the computational benefit increases with increasing variability of the hydraulic parameter field. [ABSTRACT FROM AUTHOR]

Magnetic resonance imaging (MRI) was applied to the study of flow processes in model and natural soil cores. Flow velocities in soils are mostly too slow to be monitored directly by MRI flow velocity imaging. Therefore, we used for the first time diethylenetriaminepentaacetate in the form Gd-DTPA2- as a tracer in spin echo multislice imaging protocols with strong weighting of longitudinal relaxation time T1 for probing slow flow velocities in soils. Apart from its chemical stability, the main advantage of Gd-DTPA2- is the anionic net charge in neutral aqueous solution. We showed that this property hinders adsorption at soil mineral surfaces and therefore retardation. We found that Gd-DTPA2- is a very convenient conservative tracer for the investigation of flow processes in model and natural soil cores. With respect to the flow processes in the coaxial model soil column and the natural soil column, we observed totally different flow patterns. In the first case, the tracer plume moved quite homogeneously in the inner highly conductive core only and the migration into the outer fine material was very limited. A numerical forward simulation based on independently obtained parameters showed good agreement between experiment and simulation and thus proves the convenience of Gd-DTPA as a tracer in MRI for soil physical investigations. The natural soil core, in contrast, showed a flow pattern characterized by preferential paths, avoiding dense regions and preferring loose structures. In the case of the simpler model column, the local flow velocities were also calculated by applying a peak tracking algorithm. [ABSTRACT FROM AUTHOR]

Time domain reflectometry (TDR) is commonly used to determine the soil bulk electrical conductivity. To obtain accurate measurements, the three parameters of a series resistor model (probe constant Kp cable resistance, Rc and remaining resistance, R0) are typically calibrated using liquids with known electrical conductivity. Several studies have reported discrepancies between calibrated and directly measured parameters of the series resistor model. In this study, we examined the possibility that a technical issue with the TDR100 cable tester contributed to part of these inconsistencies. Our results showed that with an increasing level of waveform averaging, the refection coefficient, as well as Kp, Rc, and R0, approached a maximum value A comparison with independently determined values indicated that a high level of waveform averaging provided the physically most plausible results. Based on our results, we propose averaging at least 16 waveforms, each consisting of at least 250 points. An oscilloscope-based signal analysis showed that the increase in the reflection coefficient with increasing waveform averaging in saline media is related to a capacitance associated with electrode polarization in combination with a change in the pulse period of the pulse train when the TDR100 starts collecting data points. This capacitance resulted in a slow change of the average voltage in the TDR pulse train until a stable average voltage was reached. Higher levels of waveform averaging cancel the impact of the first erroneous voltage measurements out. In practical applications, the errors in the determination of the bulk electrical conductivity can be as high as 5% for the low-conductivity range (<0.1 S m1) and up to 370% in saline media (1.4 S m1) when waveform averaging is changed after calibration. [ABSTRACT FROM AUTHOR]

Upward water flow induced by evaporation can cause soil salinization and transport of contaminants to the soil surface and influences the migration of solutes to the groundwater. In this study, we used electrical resistivity tomography (ERT) to obtain time-lapse images of an upward-flow tracer experiment under evaporation conditions in a three-dimensional, spatially correlated heterogeneous laboratory soil composed of three different materials (coarse-, medium-, and fine-grained sands). The tracer experiment was performed during 40 d of quasi-steady-state, upward-flow conditions. Monitored transport was compared with three-dimensional numerical simulation based on the Richards and advection-dispersion equations. The ERT-derived and modeled solute transport correlated well in the lower part of the laboratory soil, while deviations increased toward the surface. Inversion of synthetic ERT data indicated that deviations cannot be explained by ERT data and inversion errors only, but also errors of the flow and transport model must be invoked. The classical potential/actual evaporation (Epot/Ea) concept underestimated the experimental evaporation, as locally Ea exceeded Epot, which was determined as the maximum evaporation from an insulated free water table minus soil heat flux. Increasing the potential evaporation rate uniformly in the model, so that wet high-evaporation zones can compensate for lower evaporation from dry zones, increased the correlation between experiment and model. Despite the remaining deviations, experiment and model showed a consistent and systematic pattern of preferential upward transport pathways. Close above the water table, most of the transport occurred in the coarse material, while with increasing height, transport was dominated by the finer materials. This study is an experimental benchmark for three-dimensional flow and transport models using simplified evaporation boundary conditions and for ERT to monitor upward transport. [ABSTRACT FROM AUTHOR]

Tropical peatlands are among the most carbon-dense ecosystems on Earth, and their water storage dynamics strongly control these carbon stocks. The hydrological functioning of tropical peatlands differs from that of northern peatlands, which has not yet been accounted for in global land surface models (LSMs). Here, we integrated tropical peat-specific hydrology modules into a global LSM for the first time, by utilizing the peatland-specific model structure adaptation (PEATCLSM) of the NASA Catchment Land Surface Model (CLSM). We developed literature-based parameter sets for natural (PEATCLSM Trop,Nat ) and drained (PEATCLSM Trop,Drain ) tropical peatlands. Simulations with PEATCLSM Trop,Nat were compared against those with the default CLSM version and the northern version of PEATCLSM (PEATCLSM North,Nat ) with tropical vegetation input. All simulations were forced with global meteorological reanalysis input data for the major tropical peatland regions in Central and South America, the Congo Basin, and Southeast Asia. The evaluation against a unique and extensive data set of in situ water level and eddy covariance-derived evapotranspiration showed an overall improvement in bias and correlation compared to the default CLSM version. Over Southeast Asia, an additional simulation with PEATCLSM Trop,Drain was run to address the large fraction of drained tropical peatlands in this region. PEATCLSM Trop,Drain outperformed CLSM, PEATCLSM North,Nat , and PEATCLSM Trop,Nat over drained sites. Despite the overall improvements of PEATCLSM Trop,Nat over CLSM, there are strong differences in performance between the three study regions. We attribute these performance differences to regional differences in accuracy of meteorological forcing data, and differences in peatland hydrologic response that are not yet captured by our model., (© 2022 The Authors. Journal of Advances in Modeling Earth Systems published by Wiley Periodicals LLC on behalf of American Geophysical Union.)

Aim: This study assessed the impact of anti-infective periodontal therapy on the status of vascular health., Materials and Methods: Periodontal and vascular health of 55 patients with severe untreated chronic periodontitis was evaluated before and 12 months after anti-infective periodontal therapy. Observed parameters were bleeding on probing (BoP), pocket probing depth (PPD), periodontal inflamed surface area index (PISA), pulse wave velocity (PWV), augmentation index (AIx), central pulse pressure (PPao) and peripheral systolic pressure (RRsys)., Results: ΔPISA (baseline-12 months) correlated with ΔPWV (τ 0.21; p < .03), ΔAIx (τ 0.29; p < .002) and ΔPPao (τ 0.23; p < .02). ΔBoP% (baseline-12 months) correlated with ΔPWV (τ 0.18; p < .05) and ΔAIx (τ 0.25; p < .01), while mean ΔPPD (baseline-12 months) correlated with ΔPWV (τ 0.24; p < .01) and ΔAIx (τ 0.21; p < .03). Grouping patients evenly into three groups based on tertiles of BoP resolution after 12 months revealed a significant decrease in the observed PWV median value by -0.6 m/s (p < .04) in the best response tertile (ΔBoP ≥ 88%). In the worst response tertile (ΔBoP ≤ 66%), by contrast, significant increase in PPao (+10.5 mmHg; p < .02) and AIx (+5.5; p < .02) was observed., Conclusion: Efficacious resolution of periodontal inflammation may beneficially impact on vascular health., (© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)