Soil-plant-atmosphere Continuum Research Articles

Interpretable machine learning of SPAC system via a mechanism-assisted gaussian process group: Representation of the system mechanism by data

Traditional models of the soil-plant-atmosphere continuum (SPAC) system are physics-based and their practical application has been hindered by issues of high parameterization, prior structural bias, and costly running. In this paper, we developed a machine learning modelling method based on the Gaussian process (GP) to avoid these difficulties of traditional modelling. At the same time, shortcomings of conventional machine learning in terms of interpretability and mechanism representation were addressed. The innovative method consisted of structuring a local GP group framework and improving kernel functions used in each local GP. The resultant model was endowed with advanced capacities, including representing interplays between subprocesses within the complex SPAC system, representing nonstationary subprocess dynamics caused by crop growth stage shifts, as well as automatically interpreting key low-order input interactions and dominant input variables for each subprocess. The performance of our model was examined on synthetic SPAC system datasets that covered three different soil conditions. Results demonstrated that its interpretations regarding subprocess mechanisms were robust across different soil conditions and consistent with domain knowledge. Compared to a conventional global GP model and two deep learning models (DNN and LSTM), our model performed significantly better not only in regular prediction experiments but also in generalization experiments that required models to be transferred across different conditions. Our study suggested that it is promising to enable a machine learning model interpretable by improving its feature representation function. For machine learning modelling of complex systems like the SPAC, it may be more important to enhance the model’s mechanism representation capability than simply using deeper networks.

Integrated sensing device for irrigation scheduling: field evaluation and crop water stress index estimation of wheat

ABSTRACT An integrated sensing device for irrigation scheduling was developed to assess the soil–plant–atmosphere continuum for irrigation scheduling. A field experiment was carried out to evaluate ISDI performance and CWSI estimation across various irrigation regimes in wheat crop at WTC farm, ICAR-IARI, New Delhi, India. The experiment considered were full irrigation (FI) and various deficit irrigation levels (DI-15, DI-30, DI-45, and DI-60), receiving 15, 30, 45, and 60% less water in comparison to FI, respectively. The calibration and performance of the ISDI sensor probes was done with gravimetric methods along with time domain reflectometry (TDR) and a handheld infrared thermometer. The field calibration of the ISDI's soil moisture probe and TDR gave promising results, with R2 values ranging from 0.76 to 0.81 and 0.81 to 0.86, respectively, for soil depths up to 45 cm. ISDI's infrared sensor probe also demonstrated strong alignment with a handheld infrared thermometer (R2: 0.95), indicating reliable methods. Furthermore, a regression equation of lower baseline and upper threshold for CWSI computation was derived as (Tc–Ta)ll = 1.97 × VPD – 1.43 (R2:0.86) and 1.93 °C, respectively. It was recommended to initiate irrigation when CWSI ≥ 0.35 for wheat to achieve optimal crop yields.

Interannual dynamics and controlling factors of the ratio of actual to potential evapotranspiration across typical ecosystems within the Heihe River Basin

AbstractThe ratio of actual to potential evapotranspiration (AET/PET) represents the water supply of terrestrial ecosystems and can be used to assess the water stress level of plants or ecosystems. This study quantified the control of meteorological, hydrological, and biological factors on AET/PET variations using variance partitioning analysis and path analysis. A soil–plant–atmosphere continuum model was validated and used to simulate AET and PET, as well as the interannual dynamics of AET/PET in typical ecosystems in the upper, middle, and downstream reaches of the Heihe River Basin from 2014 to 2016. The good agreement between measurements and simulations indicates that the model accurately represents the water/heat transfer process in various ecosystems within the Heihe River Basin. The study found that the alpine meadow ecosystem had the highest annual average AET/PET (0.89 ± 0.12), followed by the Populus euphratica ecosystem (0.72 ± 0.17) and cropland ecosystem (0.65 ± 0.15). AET/PET variation characteristics were comparable across the three ecosystems, showing apparent seasonality and interannual fluctuations. Plant transpiration stress was found to be a dominant indicator of ecosystem water availability. Changes in AET/PET were attributed to diverse environmental conditions in the three distinct ecosystems. While the relationship between soil water (SW) content and AET/PET weakened in cropland ecosystems with low water stress, the study demonstrates that SW content remains the most important factor governing AET/PET. The leaf are index and vapour pressure deficiency had significant indirect effects on AET/PET by influencing SW content. Overall, this study provides scientific support for optimizing water resource management in the Heihe River Basin by revealing the interannual variations and controlling factors of AET/PET in typical ecosystems.

Detecting soil water redistribution in subsurface drip irrigated processing tomatoes using electrical resistivity tomography, proximal sensing and hydrological modelling

In this study, multiple soil-plant-atmosphere continuum (SPAC) monitoring methodologies, including electrical resistivity tomography (ERT), proximal thermal sensing techniques, and micrometeorological data, were combined with two-dimensional (2-D) soil hydrological modelling using HYDRUS 2-D to explore the soil water redistribution, and infer the relative crop water status in a subsurface drip irrigated (SDI) processing tomato field located in California (Yolo County, USA). Specifically, time-lapse ERT surveys were performed at two transects distributed parallel and perpendicular, respectively, to the SDI line, during an irrigation event. The ERT results were compared to HYDRUS 2-D outputs and the relative differences were explained in the form of local heterogeneities in electrical resistivity (ER) changes, as a proxy for soil water content (SWC) variations. Concurrent simultaneous soil wetting and root water uptake during the last irrigation event of the season caused negligible changes in ER in the active root zone. Slight differences in ER were observed in the top 20 cm along the dripline, confirming that the emitter spacing is small enough to create a wetted strip along the processing tomato bed. These changes were also compared to SWC values measured with time domain reflectometry soil moisture sensors. A comparison between HYDRUS 2-D and ERT confirmed negligible changes in ER during irrigation due to simultaneous wetting and root water uptake processes. In addition, a good correlation was observed between the proximal sensed and the ERT results. Finally, the findings of this study underscore the necessity of using multiple methods for improving our knowledge of the SPAC system under real field conditions.

Response of Sap Flow Trends of Conifer and Broad-Leaved Trees to Rainfall Types in Sub-Humid Climate Region of China

Sap flow is one of the most important physiological water transport processes of trees, and the characteristics of sap flow are greatly affected by the spatial and temporal distribution of water in the SPAC (soil–plant–atmosphere continuum). However, different precipitation characteristics have great influence on the water environment of forest trees, which causes considerable differences in sap flow. Therefore, researching the response of sap flow to precipitation type is the key to accurately determining plant transpiration in semi-arid areas. We used K-means clustering analysis to divide the rainfall during the study period into three rainfall types (the highest rainfall amount and intensity (types I), medium rainfall amount and intensity, with a long duration (types II); and the lowest rainfall amount and intensity (types III)) based on the rainfall amount and intensity in order to compare the differences in the response of sap flow trends and influencing factors of Pinus tabulaeformis and Robinia pseudoacacia under different rainfall types. The results showed that, under the daily scale average sap flow of P. tabulaeformis and R. pseudoacacia, rainfall type II decreased significantly relatively to rainfall types I and III (p < 0.05). In rainfall type II, The sap flow characteristics of R. pseudoacacia were positively correlated with solar radiation (p < 0.05), while those of P. tabulaeformis were positively correlated with temperature, solar radiation, and VPD (p < 0.01). The sap flow of P. tabulaeformis and R. pseudoacacia were significantly positively correlated with temperature, solar radiation, VPD, and soil moisture content (p < 0.01) and negatively correlated with relative humidity (p < 0.05) in rainfall type III. The hourly sap flow of P. tabulaeformis and R. pseudoacacia on rainfall days was higher than before the rainfall. Rainfall type I promoted the daily sap flow of both species, and the proportion of the sap flow in daytime was also higher. On rainy days, the sap flow rates of rainfall type I and III showed a “midday depression”. In type I rainfall events, the sap flow “midday depression” after rainfall occurred an hour ahead compared to the sap flow “midday depression” before rainfall. In type II rainfall events, the daytime sap flow rates of P. tabulaeformis and R. pseudoacacia were obviously inhibited, but the nighttime sap flow rate increased. In type III rainfall events, the sap flow before rainfall presented a unimodal curve versus time. The daily average sap flow of R. pseudoacacia was more susceptible to rainfall type II, while P. tabulaeformis was more susceptible to rainfall types I and III. The sap flow rate of R. pseudoacacia decreased on rainy days. The results show that the effects of different rainfall types on the sap flow trends of P. tabulaeformis and R. pseudoacacia were different. They revealed the responses of their sap flow trends to meteorological factors under different rainfall types, which provided basic data and theoretical support for further predicting the sap flow trends on rainy days, clarifying the effects of rainfall amount, rainfall duration, and rainfall intensity on sap flow trends and accurately estimating the transpiration water consumption of typical tree species in the sub-humid climate regions of China.

Mean transit time of water bodies in a typical soil-plant-atmosphere continuum of the subtropical monsoon region

The mean transit time (MTT) is a good indicator of water cycle processes. We know little about the MTT of different water bodies within the soil-plant-atmosphere continuum (SPAC) in the subtropical monsoon region. We estimated the MTT of stratified soil water at different depths as well as the xylem water and leaf water in typical Cinnamomum camphora woodland located in Changsha City from March 2017 to October 2019. The main methods used in this study included the stable isotope technology, the linear mixed model and the sine wave fitting method. The results showed that the stable isotopes were more depleted in summer and enriched in winter for different water bodies within the SPAC. The δ2H values of soil water gradually decreased as depth increased. The δ2H values of xylem water closely resembled those of soil water, but the δ2H values of leaf water were more positive and exhibited larger variation. Results of the linear mixed model indicated that the lower MTT values of soil water and plant water occurred between June and September, while the higher values were often observed around January and from April to May. The precipitation replenishment exhibited a significant negative correlation with the MTT. The MTT of soil water generally increased with depth, although preferential flow could enhance the replenishment of deeper soil water and subsequently reduce the MTT. The mean MTT values of xylem water and leaf water were similar. Results of the sine wave fitting method showed that the young water fraction (Fyw) of soil water gradually decreased as depth increased, while the MTT of soil water gradually increased as depth increased. The Fyw and MTT of xylem water were lower and higher than those of leaf water, respectively. Both the mean MTT values of soil water based on the linear mixed model or the sine wave fitting method increased from the surface to the deeper soil layers. The former exhibited a smaller variation range and the latter showed a larger variation range. The mean MTT value of xylem water based on the linear mixed model was 2.4 days less than that of leaf water, while the MTT value of xylem water in the sine wave fitting method was 87.4 days higher than that of leaf water. These differences may be due to the parameterization of "new/young water", the uncertainty of results, and the effect of evaporative fractionation. This study contributes to a better understanding of water transport and consumption processes within the SPAC and provides valuable insights for agricultural production and water resources management in the subtropical monsoon region.

A passive method for sampling water in the soil-plant-atmosphere continuum for stable hydrogen and oxygen isotope analyses.

Hydrogen and oxygen isotopes in water molecules are powerful tools to constrain the dynamics of water cycling within the soil-plant-atmosphere continuum (SPAC). However, the recovery of water from the SPAC requires logistical arrangements and implementation of different time- and cost-consuming techniques in either the field or the laboratory. We developed a passive method to sample water from the three compartments of the SPAC by using a hygroscopic salt of a high water absorbance capacity (CaCl2 ). This method allows either H2 O(V) -H2 O(L) isotope equilibration in the case of infinite water reservoir (atmospheric water vapor (WV)) or quantitative absorption of water from a finite water reservoir (e.g. soil and plants). The water absorbed by CaCl2 was distilled first and subsequently processed for hydrogen and triple oxygen isotope mass spectrometry analyses. The distillation step can be bypassed when employing isotope analytical techniques that are based on equilibration. Our experiments show that anhydrous CaCl2 absorbs WV of 210 ± 6% and 130 ± 6% of its dry weight from an infinite WV reservoir at relative humidity of 60% and 30%, respectively. Chemical and isotope equilibrations between WV and absorbed water were attained within 3 days at room temperature, enabling the back-calculation of the isotope composition of atmospheric WV. Preliminary experiments to extract water from plant and sand (i.e. finite WV reservoir) demonstrate a quasi-complete recovery of water in these matrices without significant isotope fractionation. The reproducibility of our method is better than 1.6‰, 0.32‰, 0.17‰ and 6‰ per meg for δ2 H, δ18 O, δ17 O and 17 O-excess. The CaCl2 -H2 O absorption (passive) method requires very limited logistics in the field facilitating spatial and temporal water vapor/water sampling from atmosphere and soil at low resolution (i.e. average of 3-5 days). Moreover, it allows high sample throughput for the extraction of plant water in the laboratory. The reproducibility of this method is similar to the analytical uncertainty in mass spectrometry analyses.

New developments and opportunities for AI in viticulture, pomology, and soft-fruit research: a mini-review and invitation to contribute articles

Climate change constraints on horticultural production and emerging consumer requirements for fresh and processed horticultural products with an increased number of quality traits have pressured the industry to increase the efficiency, sustainability, productivity, and quality of horticultural products. The implementation of Agriculture 4.0 using new and emerging digital technologies has increased the amount of data available from the soil–plant–atmosphere continuum to support decision-making in these agrosystems. However, to date, there has not been a unified effort to work with these novel digital technologies and gather data for precision farming. In general, artificial intelligence (AI), including machine/deep learning for data modeling, is considered the best approach for analyzing big data within the horticulture and agrifood sectors. Hence, the terms Agriculture/AgriFood 5.0 are starting to be used to identify the integration of digital technologies from precision agriculture and data handling and analysis using AI for automation. This mini-review focuses on the latest published work with a soil–plant–atmosphere approach, especially those published works implementing AI technologies and modeling strategies.

Quantifying river water contributions to the transpiration of riparian trees along a losing river: lessons from stable isotopes and an iteration method

Abstract. River water plays a critical role in riparian plant water use and riparian ecosystem restoration along losing rivers (i.e., river water recharging underlying groundwater). How to quantify the contributions of river water to the transpiration of riparian plants under different groundwater levels and the related responses of plant water use efficiency is a great challenge. In this study, observations of stable isotopes of water (δ2H and δ18O), 222Rn, and leaf δ13C were conducted for the deep-rooted riparian weeping willow (Salix babylonica L.) in 2019 (dry year) and 2021 (wet year) along the Chaobai River in Beijing, China. We proposed an iteration method in combination with the MixSIAR model to quantify the river water contribution to the transpiration of riparian S. babylonica and its correlations with the water table depth and leaf δ13C. Our results demonstrated that riparian S. babylonica took up deep water (in the 80–170 cm soil layer and groundwater) by 56.5 % ± 10.8 %. River water recharging riparian deep water was an indirect water source and contributed 20.3 % of water to the transpiration of riparian trees near the losing river. Significantly increasing river water uptake (by 7.0 %) and decreasing leaf δ13C (by −2.0 ‰) of riparian trees were observed as the water table depth changed from 2.7 m in the dry year of 2019 to 1.7 m in the wet year of 2021 (p<0.05). The higher water availability probably promoted stomatal opening and thus increased transpiration water loss, leading to the decreasing leaf δ13C in the wet year compared to the dry year. The river water contribution to the transpiration of riparian S. babylonica was found to be negatively linearly correlated with the water table depth and leaf δ13C (p<0.01). The rising groundwater level may increase the water extraction from the groundwater and/or river and produce a consumptive river-water-use pattern of riparian trees, which can have an adverse impact on the conservation of both river flow and riparian vegetation. This study provides new insights into understanding the mechanisms of the water cycle in a groundwater–soil–plant–atmosphere continuum and managing water resources and riparian afforestation along losing rivers.

Correlations of the root–shoot ratio with soil water content in the patchy alpine grassland of the north‐eastern Qinghai–Tibetan Plateau using electrical resistivity tomography

AbstractThe root–shoot biomass ratio (R:S) changing the soil water redistribution is not well understood due to a lack of nondestructive technology to characterize the coexistence of plants and soil. This study aims to assess the correlations of the R:S ratios of Achnatherum splendens with soil water content by electrical resistivity tomography (ERT) on the north‐western Qinghai–Tibet Plateau (QTP). During the growing season, an experimental plot including bare patches (BK) and low‐ (LD) and high‐density (HD) A. splendens subplots was designed to quantify soil volumetric water content under different soil depths and antecedent total precipitation conditions for 7 days (AP7). The results showed that the R:S ratio was positive with soil water content in the surface soil layer of 0–10 cm. The synergistic effect of the R:S ratio on soil water in the surface soil layer promoted an increase in surface soil water. However, the nonsynergistic effect in the middle soil layer weakened the soil water increasing, and the effect of the R:S ratio on soil water in the deep soil layer of 40–80 cm was not obvious. In HD, soil water increased between 0.08% and 0.95% and was highest under AP7 > 20 mm conditions. In LD, soil water increased in the surface and deep soil layers but decreased in the middle soil layer, especially under AP7 = 10–20 mm conditions (−1.23%). These findings provide valuable insights that patchy alpine grass survival strategy under future climate change on the QTP, and the results are beneficial to the development of soil–plant–atmosphere continuum models.

Widespread and complex drought effects on vegetation physiology inferred from space

The response of vegetation physiology to drought at large spatial scales is poorly understood due to a lack of direct observations. Here, we study vegetation drought responses related to photosynthesis, evaporation, and vegetation water content using remotely sensed data, and we isolate physiological responses using a machine learning technique. We find that vegetation functional decreases are largely driven by the downregulation of vegetation physiology such as stomatal conductance and light use efficiency, with the strongest downregulation in water-limited regions. Vegetation physiological decreases in wet regions also result in a discrepancy between functional and structural changes under severe drought. We find similar patterns of physiological drought response using simulations from a soil–plant–atmosphere continuum model coupled with a radiative transfer model. Observation-derived vegetation physiological responses to drought across space are mainly controlled by aridity and additionally modulated by abnormal hydro-meteorological conditions and vegetation types. Hence, isolating and quantifying vegetation physiological responses to drought enables a better understanding of ecosystem biogeochemical and biophysical feedback in modulating climate change.

The need to decipher plant drought stress along the soil–plant–atmosphere continuum

Lacking comparability among rainfall manipulation studies is still a major limiting factor for generalizations in ecological climate change impact research. A common framework for studying ecological drought effects is urgently needed to foster advances in ecological understanding the effects of drought. In this study, we argue, that the soil–plant–atmosphere‐continuum (SPAC), describing the flow of water from the soil through the plant to the atmosphere, can serve as a holistic concept of drought in rainfall manipulation experiments which allows for the reconciliation experimental drought ecology. Using experimental data, we show that investigations of leaf water potential in combination with edaphic and atmospheric drought – as the three main components of the SPAC – are key to understand the effect of drought on plants. Based on a systematic literature survey, we show that especially plant and atmospheric based drought quantifications are strongly underrepresented and integrative assessments of all three components are almost absent in current experimental literature. Based on our observations we argue, that studying dynamics of plant water status in the framework of the SPAC can foster comparability of different studies conducted in different ecosystems and with different plant species and can facilitate extrapolation to other systems, species or future climates.

CPlantBox: a fully coupled modelling platform for the water and carbon fluxes in the soil–plant–atmosphere continuum

Abstract A plant’s development is strongly linked to the water and carbon flows in the soil–plant–atmosphere continuum. Expected climate shifts will alter the water and carbon cycles and will affect plant phenotypes. Comprehensive models that simulate mechanistically and dynamically the feedback loops between a plant’s three-dimensional development and the water and carbon flows are useful tools to evaluate the sustainability of genotype–environment–management combinations which do not yet exist. In this study, we present the latest version of the open-source three-dimensional Functional–Structural Plant Model CPlantBox with PiafMunch and DuMu${}^{\text{x}}$ coupling. This new implementation can be used to study the interactions between known or hypothetical processes at the plant scale. We simulated semi-mechanistically the development of generic C3 monocots from 10 to 25 days after sowing and undergoing an atmospheric dry spell of 1 week (no precipitation). We compared the results for dry spells starting on different days (Day 11 or 18) against a wetter and colder baseline scenario. Compared with the baseline, the dry spells led to a lower instantaneous water-use efficiency. Moreover, the temperature-induced increased enzymatic activity led to a higher maintenance respiration which diminished the amount of sucrose available for growth. Both of these effects were stronger for the later dry spell compared with the early dry spell. We could thus use CPlantBox to simulate diverging emerging processes (like carbon partitioning) defining the plants’ phenotypic plasticity response to their environment. The model remains to be validated against independent observations of the soil–plant–atmosphere continuum.

A multi-satellite framework to rapidly evaluate extreme biosphere cascades: The Western US 2021 drought and heatwave.

The increasing frequency and intensity of climate extremes and complex ecosystem responses motivate the need for integrated observational studies at low latency to determine biosphere responses and carbon-climate feedbacks. Here, we develop a satellite-based rapid attribution workflow and demonstrate its use at a 1-2-month latency to attribute drivers of the carbon cycle feedbacks during the 2020-2021 Western US drought and heatwave. In the first half of 2021, concurrent negative photosynthesis anomalies and large positive column CO2 anomalies were detected with satellites. Using a simple atmospheric mass balance approach, we estimate a surface carbon efflux anomaly of 132 TgC in June 2021, a magnitude corroborated independently with a dynamic global vegetation model. Integrated satellite observations of hydrologic processes, representing the soil-plant-atmosphere continuum (SPAC), show that these surface carbon flux anomalies are largely due to substantial reductions in photosynthesis because of a spatially widespread moisture-deficit propagation through the SPAC between 2020 and 2021. A causal model indicates deep soil moisture stores partially drove photosynthesis, maintaining its values in 2020 and driving its declines throughout 2021. The causal model also suggests legacy effects may have amplified photosynthesis deficits in 2021 beyond the direct effects of environmental forcing. The integrated, observation framework presented here provides a valuable first assessment of a biosphere extreme response and an independent testbed for improving drought propagation and mechanisms in models. The rapid identification of extreme carbon anomalies and hotspots can also aid mitigation and adaptation decisions.

Automatic Crop Canopy Temperature Measurement Using a Low-Cost Image-Based Thermal Sensor: Application in a Pomegranate Orchard under a Permanent Shade Net House.

Water scarcity in arid and semi-arid areas has led to the development of regulated deficit irrigation (RDI) strategies on most species of fruit trees in order to improve water productivity. For a successful implementation, these strategies require continuous feedback of the soil and crop water status. This feedback is provided by physical indicators from the soil-plant-atmosphere continuum, as is the case of the crop canopy temperature, which can be used for the indirect estimation of crop water stress. Infrared Radiometers (IRs) are considered as the reference tool for temperature-based water status monitoring in crops. Alternatively, in this paper, we assess the performance of a low-cost thermal sensor based on thermographic imaging technology for the same purpose. The thermal sensor was tested in field conditions by performing continuous measurements on pomegranate trees (Punica granatum L. 'Wonderful') and was compared with a commercial IR. A strong correlation (R2 = 0.976) between the two sensors was obtained, demonstrating the suitability of the experimental thermal sensor to monitor the crop canopy temperature for irrigation management.

Assessment of trunk microtensiometer as a novel biosensor to continuously monitor plant water status in nectarine trees.

The objective of this work was to validate the trunk water potential (Ψtrunk), using emerged microtensiometer devices, as a potential biosensor to ascertain plant water status in field-grown nectarine trees. During the summer of 2022, trees were subjected to different irrigation protocols based on maximum allowed depletion (MAD), automatically managed by real-time soil water content values measured by capacitance probes. Three percentages of depletion of available soil water (α) were imposed: (i) α=10% (MAD=27.5%); (ii) α=50% (MAD=21.5%); and (iii) α=100%, no-irrigation until Ψstem reached -2.0 MPa. Thereafter, irrigation was recovered to the maximum water requirement of the crop. Seasonal and diurnal patterns of indicators of water status in the soil-plant-atmosphere continuum (SPAC) were characterised, including air and soil water potentials, pressure chamber-derived stem (Ψstem) and leaf (Ψleaf) water potentials, and leaf gas exchange, together with Ψtrunk. Continuous measurements of Ψtrunk served as a promising indicator to determine plant water status. There was a strong linear relationship between Ψtrunk vs. Ψstem (R2 = 0.86, p<0.001), while it was not significant between Ψtrunk vs. Ψleaf (R2 = 0.37, p>0.05). A mean gradient of 0.3 and 1.8 MPa was observed between Ψtrunk vs.Ψstem and Ψleaf, respectively. In addition, Ψtrunk was the best matched to the soil matric potential. The main finding of this work points to the potential use of trunk microtensiometer as a valuable biosensor for monitoring the water status of nectarine trees. Also, trunk water potential agreed with the automated soil-based irrigation protocols implemented.

Temporal and spatial diurnal dynamics of the hysteresis of weighed transpiration and water transport in tomatoes

In studies of terrestrial water cycles and farmland irrigation management, plant transpiration is an important reference data source. There is a hysteresis effect between plant transpiration and meteorological factors, which is important for predicting plant transpiration. However, the hysteresis effect in diurnal dynamics (time) and between the processes of water from soil to air in the soilplantatmosphere continuum (SPAC) system (space) remains unclear. In this study, the intensity of light radiation (high radiation, HR; low radiation, LR) and the amount of water used for irrigation (high irrigation, HW; low irrigation, LW) were used to form four treatments (HRHW, HRLW, LRHW, and LRLW) on tomato plants in a greenhouse. The diurnal dynamics of the transpiration of the whole plant by weighting (weighted transpiration, WT), sap flow (SF), and lag time in the process of water transport in tomato plants were analyzed by the data of every 10 min. The results showed that the WT exceeded the SF in the HRHW during 10:00–18:00 and in the HRLW during 10:00–16:00. In the HRHW, the proportion of SF in the upper part to the lower part of the plants was significantly lower than that in the other treatments during the daytime. The hysteresis effect was prevalent in the process of water transport from soil through plants to the atmosphere during the daytime. The lag time of WT to net radiation (Rn) and SF to WT changed more dramatically during the daytime under HR- conditions, and the maximum lag time was 60 min. Compared with the hysteresis of middle SF to low SF of plants, the lag time of top SF to middle SF had a greater fluctuation, with a maximum of 50 min (LRLW) and 60 min (HRHW and HRLW), respectively. The longest times at which of stem diameter (SD), fruit diameter (FD) and substrate water content (SWC) lagged behind SF were 60 min (LRHW), 70 min (HRHW and LRHW) and 50 min (HRHW and HRLW), respectively. After temporal and spatial dynamic hysteresis were added to the structural equation modeling (SEM), the path coefficients between most variables were improved, and the overall effect of the model was enhanced in all treatments. This provides a valuable direction for the future improvements in transpiration models, irrigation efficiency, and crop yield.

A framework for assessing tunnel drainage-induced impact on terrestrial vegetation

The tunnel projects elevate the transport of large cities, but they also bring negative impacts on the terrestrial vegetation, particularly in mountainous rural areas. Aside from the immediate effects during construction, the tunnel drainage can have long-term effects on the terrestrial vegetation by depleting shallow groundwater resources adjacent to the tunnel. Previous research proposed a number of analytical and numerical methods for determining allowable tunnel drainage rates in order to keep terrestrial vegetation from wilting. These methods, however, only provide local estimates of drainage-induced drawdown and an approximate steady-state groundwater budget based on tunnel design parameters, ignoring soil water dynamics that have a direct influence on vegetation roots. As a result, we propose a comprehensive integral vulnerability assessment framework (IVAF) for assessing tunnel drainage's long-term regional impact on terrestrial vegetation. This framework couples a stochastic groundwater model, including tunnel parameters, with a topsoil model that includes soil–plant-atmosphere continuum (SPAC) components and creates regional vegetation vulnerability maps based on the vulnerability concept. It aims to provide a tool for tunneling experts by revealing the long-term tunnel drainage-induced changes between regional groundwater and soil water. The vulnerability assessment was applied to an example tunnel project in a moderately mountainous region. Vulnerability maps reveal the most likely influenced zones by tunnel drainage. The vulnerability index has been summarized via rooting depth segmentation, demonstrating the drawdown effect on topsoil. The assessment results show that IVAF is capable of establishing detailed groundwater and land cover connectivity on topsoil levels in poorly-sampled areas, as well as identifying potential vulnerability caused by tunnel drainage-induced drawdown.

Revisiting Soil Water Potential: Towards a Better Understanding of Soil and Plant Interactions

Soil water potential (SWP) is vital for controlling the various biological and non-biological processes occurring through and across the soil-plant-atmosphere continuum (SPAC). Although the dynamics and mechanisms of SWP have been investigated for several decades, they are not as widely explored in ecohydrology research as soil moisture, due at least partly to the limitation of field observation methods. This limitation restricts the understanding of the responses of plant physiology and ecological processes to the SWP gradient and the ecohydrological functions of SWP dynamics in different contexts. Hence, in this work, we first briefly revisit the origin and development of the concept of SWP and then analyze the comprehensive factors that influence SWP and the improvement of SWP observation techniques at field scales, as well as strategies for developing new sensors for soil water status. We also propose views of focusing on the response characteristics of plant lateral roots, rather than taproots, to SWP dynamics, and using hormone signaling research to evaluate plant response signals to water stress. We end by providing potential challenges and insights that remain in related research, such as the limitations of the SWP evaluation methods and the future development direction of SWP data collection, management, and analysis. We also emphasize directions for the application of SWP in controlling plant pathogens and promoting the efficiency of resource acquisition by plants. In short, these reflections revisit the unique role of SWP in eco-hydrological processes, provide an update on the development of SWP research, and support the assessment of plant drought vulnerability under current and future climatic conditions.

Non-overlap of suitable areas of agro-climatic resources and main planting areas is the main reason for potato drought disaster in Inner Mongolia, China

Potato bears the burden of eliminating hunger and supporting food security. Quantitative assessment of potato drought disaster risk can help the sustainable development of the potato industry and improve the regional disaster management capacity. This is also a major and urgent demand for food security. This study constructed a comprehensive drought condition index (CDCI) for different months of the potato growing season based on the Soil-Plant-Atmosphere Continuum (SPAC) system, quantitatively assessed potato drought disaster risk based on the four-factor theory of natural disaster risk formation, and discussed the historical and future planting environmental conditions in Inner Mongolia, China. The results showed that the non-overlap between suitable areas of agro-climatic resources and main planting areas is the main reason for the occurrence of potato drought disasters, and the “Extremely high risk area” and “High risk area” areas were concentrated in the current main planting areas, which was one of the problems encountered in the sustainable development of potato industry in Inner Mongolia. The analysis of future drought hazard changes indicates the need to pay attention not only to the possible persistence of drought hazard in Near term, but also to the possible waterlogging hazard in Mid-Long term. The different situations of land use/cover change (LUCC) in Inner Mongolia and various agricultural resources and environmental zones (AgriREZones) have confirmed the necessity of separating regions for agricultural drought risk analysis and management. The present study can be used as a reference for adjusting the layout of the potato industry and provide a basis for agricultural disaster prevention and reduction.