Modeling water stable isotope transport in soil is crucial to sharpen our understanding of water cycles in terrestrial ecosystems. Although several models for soil water isotope transport have been developed, many rely on a semi-coupled numerical approach, solving isotope transport only after obtaining solutions from water and heat transport equations. However, this approach may increase instability and errors of model. Here, we developed an algorithm that solves one-dimensional water, heat, and isotope transport equations with a fully coupled method (MOIST). Our results showed that MOIST is more stable under various spatial and temporal discretization than semi-coupled method and has good agreement with semi-analytical solutions of isotope transport. We also validated MOIST with long-term measurements from a lysimeter study under three scenarios with soil hydraulic parameters calibrated by HYDRUS-1D in the first two scenarios and by MOIST in the last scenario. In scenario 1, MOIST showed an overall NSE, KGE, and MAE of simulated delta 18O of 0.47, 0.58, and 0.92 parts per thousand, respectively, compared to the 0.31, 0.60, and 1.00 parts per thousand from HYDRUS-1D; In scenario 2, these indices of MOIST were 0.33, 0.52, and 1.04 parts per thousand, respectively, compared to the 0.19, 0.58, and 1.15 parts per thousand from HYDRUS-1D; In scenario 3, calibrated MOIST exhibited the highest NSE (0.48) and KGE (0.76), the smallest MAE (0.90) among all scenarios. These findings indicate MOIST has better performance in simulating water flow and isotope transport in simplified ecosystems than HYDRUS-1D, suggesting the great potential of MOIST in furthering our understandings of ecohydrological processes in terrestrial ecosystems.

Stable isotopes of hydrogen and oxygen in water are common tools for investigating water uptake apportionment, but many of the existing methods rely on simple linear mixing approaches that do not mechanistically incorporate additional information about site physical properties and conditions. Here, we develop a 'physically based root water uptake isotope mixing estimation' model (PRIME) that combines a continuous and parametric probability density function for root water uptake with site physical data in a process-based linear mixing framework. To demonstrate the application of PRIME, water uptake patterns of boreal forest Pinus banksiana trees were estimated on four dates in 2019. To aid in validation, estimates were compared with that of the Bayesian linear mixing model framework, MixSIAR. The two approaches provided similar results, but due to its continuous and parametric nature, PRIME provided estimates of superior resolution, certainty, and model parsimony. Although both models incorporate additional physical information into their mixing frameworks, PRIME does so in a mechanistic manner, thereby reflecting the relevant hydrological processes more effectively than the purely empirical approach taken by MixSIAR. Furthermore, because PRIME uses a continuous function to describe the predicted uptake pattern, it allows users to quantify water uptake with essentially infinite resolution, through integration over the desired depth ranges. These findings demonstrate the advantages of utilizing a continuous, parametric, and process-based mixing model to estimate root water uptake apportionment, thus providing a relatively simple yet powerful tool with which to approach plant water sourcing.

The depth‐wise distribution of root water uptake is typically inferred through linear mixing models that utilize knowledge of stable water isotopes in soil and plants. However, these existing models often represent the water uptake profile in discrete segments, potentially introducing significant uncertainty and bias into results. In this study, we introduced a novel root water uptake mixing model that combines a Bayesian linear mixing framework with a continuous root water uptake pattern, named CrisPy. To evaluate the performance of CrisPy, we conducted virtual and field‐based tests under several types of prior information. CrisPy showed accurate and robust reconstruction of the true root water uptake profile under various prior information settings in the virtual test. By contrast, the discrete mixing model, MixSIAR was greatly influenced by the prior information and deviated from the true profile. The root mean squared error of the uptake proportions from CrisPy ranged from 3.6% to 7.4%, while MixSIAR exhibited values of 6.3%–15.2%. Furthermore, posterior predictive checking indicated that CrisPy effectively reconstructed the mean and standard deviations of plant water isotopic compositions in both virtual and field‐based tests. MixSIAR, however, underestimated the mean and overestimated the standard deviation of these compositions. These findings collectively support the enhanced accuracy, greater robustness, and reduced uncertainty of CrisPy in comparison to MixSIAR. Therefore, CrisPy provides a powerful tool for partitioning plant water sources.

Abstract. Modeling water stable isotope transport in soil is crucial to sharpen our understanding of water cycles in terrestrial ecosystems. However, isotope and soil water transport are not fully coupled in current models. In this study, we developed MOIST: a MATLAB-based one-dimensional isotope and soil water transport model, a program that solves one-dimensional water, heat, and isotope transport equations simultaneously. Results showed that the MOIST model has good agreements to the theoretical tests and semi-analytical solutions of isotope transport under fixed boundary conditions. Furthermore, we validated the program with short- and long-term measurements from lysimeters studies. The overall Nash-Sutcliff efficiency coefficient (NSE) of soil water and deuterium (2H) transport for the short-term measurements are 0.66 and 0.69, respectively, with respective determine coefficient (R2) of 0.82 and 0.70, mean absolute error (MAE) of 0.02 m3 m-3 and 11.84 ‰. For the long-term lysimeter study, the overall NSE, R2, and MAE of simulated δ18O are 0.47, 0.49, and 0.92 ‰, respectively. These indices indicated the excellent performance of the MOIST model in simulating water flow and isotope transport in simplified ecosystems, suggesting a great potential of our program in promoting understandings of ecohydrological processes in terrestrial ecosystems.

Deep soil water is important for trees to combat droughts and thus is an important consideration for assessing sustainability of afforestation. However, the extent to which trees could depend on deep soil for root water uptake (RWU), remains poorly understood. Here we selected five apple orchards, planted in 2008, 2005, 2001, 1998 and 1994 (named A2008, A2005, A2001, A1998, and A1994, respectively) from the Chinese Loess Plateau and measured water isotopes from tree xylem and soil to the depth up to 23 m. We then used the Bayesian mixing model MixSIAR with dual isotopes (H-2, O-18) to quantify the seasonal contribution ratio of each soil layer (0-0.4 m, 0.4-2 m, 2-5 m, and 5 m to maximum rooting depth) to RWU in normal years 2017, 2018 and wet year 2019. Results showed that with increasing orchard age, rooting depth increased from 10.2 m to 23.2 m, resulting in cumulative deep soil (below 5 m) water deficits from 74.5 mm in 9-year-old orchard to 1191.8 mm in 25-year-old orchard. And annual deep soil water below 5 m contributed 9-39% to the total RWU over the orchard lifetime. Although fine roots in shallow 0-2 m soils in old orchards A1998 and A1994 only accounted for 20% of that in the entire profiles, these roots contributed, on average, 64% of the total absorbed water in 2017-2019. Relative to the normal year, apple trees relied less on deep soil water in wet year. Our findings is of particular significance to the ongoing eco-restoration on the Chinese Loess Plateau (CLP).

Study region: Yuanzegou Watershed in Qingjian, Wangdonggou watershed in Changwu, the Chinese Loess Plateau. Study focus: Hillslopes are the predominant land form unit on Earth, and despite its importance in maintaining groundwater supplies in many parts of the world, groundwater recharge on hillslopes is poorly understood. We hypothesize that groundwater recharge in the deep unsaturated zones of hillslopes is facilitated mainly by soil matrix flow, and the recharge rates are much smaller in hillslopes than on flat landscapes. To test the hypothesis, seven 15-20 m-long cores were collected from areas of different land uses to determine the groundwater recharge rates and its controls in deep unsaturated zones of hillslopes at a sub-humid and a semi-arid watershed located on the Chinese Loess Plateau. New hydrologic insights for the region: The tritium distribution in each soil profile exhibits a well-defined bell-shape, signifying that soil matrix displacement is the main recharge mechanism. The tritium peak was located between depths of 9.33 m-11.01 m at the semiarid watershed and 6.29 m-7.22 m at the sub-humid watershed, and the recharge rates varied from 24.5 to 33.8 mm yr(-1). These recharge rates account for 4 %-7 % of the long-term precipitation, which is approximately 56 % of the recharge typically seen on flat landscapes. Groundwater recharges were mainly controlled by soil texture, and land use changes, but exhibited little impact from the climatic difference between the two watersheds.

In the Alberta oil sands, many soils available for reclamation contain portions of oil sand referred to as aggregated oil sand material (AOSM). The objective of this study was to determine the infiltration rates of soils and AOSM from various salvage depths and with various concentrations of interstitial petroleum hydrocarbons (PHCs). The water infiltration rates of AOSM and surrounding soil were determined using a miniaturized infiltrometer, revealing that the soil allows significantly (P < 0.05) greater infiltration than the AOSM. Furthermore, highly-weathered AOSM which originate from the near-surface, exhibit significantly lower PHC contents and greater infiltration rates than medium- and low-weathered AOSM, which are found at depth. The infiltration of 95% ethanol indicates water repellency (WR) is present in both the AOSM and surrounding soil; however, the ethanol results also suggest that the reduced water infiltration rates of AOSM in comparison to the soil, are primarily due to structural differences such as reductions in total porosity and pore connectivity resulting from interstitial PHCs. The diminished infiltration of water into AOSM indicates the ability to slow the downward flow of water and increase the residence time of water in overlying coarse-textured soils, potentially altering the soil water regime and associated ecosite.

This study assesses the water repellency (WR) of aggregated oil sand material (AOSM) from the Athabasca region, Canada, and evaluates the onion-skin weathering hypothesis, which postulates that with increasing depth into the soil profile or into individual AOSM samples, the exposure to and extent of weathering of AOSM decreases and petroleum hydrocarbon (PHC) content and WR increase. WR and PHC content were determined for outer and inner portions of AOSM from depths of 15-200 cm. Results show AOSM displays a wide range of WR, in terms of both contact angle (0 degrees-129 degrees) and water drop penetration time (0 to > 3600 s). As salvage depth or depth into AOSM increases, PHC content and WR increase, confirming onion-skin weathering. These findings imply the benefit of discreet salvaging into separate layers, as opposed to composite salvaging of shallow and deep soils. Deep materials, which contain relatively high PHC contents, can be salvaged and replaced as deep layers to avoid the excessive drying and expression of WR which may occur in the near-surface. By controlling the location of AOSM within the soil profile, water storage in the rooting zone may be increased, allowing the establishment of relatively productive ecosystems.

V2O5 thin films are well-known "smart" materials due to their reversible wettability under UV irradiation and dark storage. Their surfaces are usually hydrophobic and turn into hydrophilic under UV irradiation. However, the V2O5 thin films deposited by magnetron sputtering in present work are superhydrophilic and turned into hydrophobic after days' of storage in air. This change can be recovered by heating. The effects of many factors including surface roughness, irradiation from visible light, UV, & X-ray, and storage in air & vacuum on the reversible switching of wettability were investigated. The results show that air absorption is the main factor causing the film surface change from superhydrophilicity to hydrophobicity. (C) 2017 Elsevier B.V. All rights reserved.