Soil Water Potential Measurements Research Articles

Soil water potential measurement using fiber-optic sensing technique

Accurate measurement of soil water potential or suction is crucial for hydrology and geotechnical engineering. Inspired by recent advances in fiber-optic sensing techniques, we develop an innovative geophysical method for measuring the soil suction by using fiber Bragg grating (FBG), named FBG-suction method. In this study, working principles and theoretical background associated with the FBG-suction method are discussed. For verification purposes, a series of laboratory-scale tests including calibration, suction measurement, and evaporation monitoring are performed on two clayey soils of low to high plasticity under different degrees of saturation. The calibration and measurement results demonstrate the efficacy and accuracy of the developed method for measuring a wide range of soil suction. The curves of soil saturation with suction obtained by WP4C and FBG-suction method are comparable and reflect the difference in the water retention capacity of the tested soils. Additionally, the evaporation monitoring results show that the FBG-suction method can measure the low suction during the drying process and accurately obtain the high suction above the measuring range of the PST-55 psychrometer. The findings affirm the scientific viability of the fiber-optic sensing technique for acquiring the spatial distribution of water potential or suction in unsaturated soils and provide a novel perspective for future investigations into the spatiotemporal evolution characteristics of in-situ unsaturated soil under climate change. As interdisciplinary collaborations continue to advance, it becomes increasingly apparent that methods based on fiber-optic sensing have the potential to revolutionize traditional approaches to characterizing dynamic subsurface processes.

Soil moisture response to seasonal drought conditions and post‐thinning forest structure

AbstractProlonged drought conditions in semi‐arid forests can lead to widespread vegetation stress and mortality. However, the distribution of these effects is not spatially uniform. We measured soil water potential at high spatial and temporal resolution using 112 sensors distributed across a ponderosa pine forest in northern Arizona, USA, during two abnormally dry years with below‐average total precipitation. We used the data to assess the effects of fore‐summer drought period on the timing, magnitude, and extent of drying throughout the top 100 cm of the soil profile. Additionally, we use high spatial resolution terrestrial lidar measurements of forest structure to develop relationships between soil drying and fine‐scale forest structure. We find that increasing drought from 2019 to 2020 caused significantly earlier onset of soil dying at all depths (25, 50 and 100 cm) and more days below a critical drying threshold for ponderosa pine. Additionally, our results show that significantly drier soils are found in areas with higher stand‐level basal area, canopy cover and tree density, and shorter trees. Our results from the unprecedented spatial and temporal resolution data suggest that tailored restoration thinning with specific tree density and size parameters can be used to increase and prolong the availability of deep soil water to trees during drought.

Observations on soil-atmosphere interactions after long-term monitoring at two sample sites subjected to shallow landslides

Soil-atmosphere interaction has implications in different scientific research contexts and is increasingly investigated through field measurements. This paper reports a detailed description of interaction between shallow soil and atmosphere at two test sites in Oltrepò Pavese area (Northern Italy). The two test sites are in the same climatic area but are characterised by different geological features. In fact, the first objective is to compare the behaviour of two different soils, namely a clayey-sandy silt (CL) and a silty clay (CH), under similar meteorological events. Soil-atmosphere interaction is studied on the basis of long-term (about 87 and 42 months for the two test sites, respectively) monitoring data of both volumetric water content and soil water potential, recorded at different depths along two vertical soil profiles in the first two metres from ground level. Field measurements, together with meteorological data such as precipitation and air temperature, allow for clear identification of the seasonal fluctuations of unsaturated soil hydraulic properties. To infer detailed information, the recorded data were processed and relationships between soil water potential and water content were investigated. Different time spans, from several months to a few days, even including single rainy events, are considered to show the hydraulic soil behaviour. The hysteretic cycles of water content with respect to soil water potential and non-equilibrium flow are highlighted. In particular, the measured soil water potential is in the range of 0–800 kPa and of 0–1500 kPa for the CL and CH soil, respectively. At both sites, the observed hysteretic cycles are more frequent in the hot season (summer) than in the cold season (winter) and tend to reduce with depth. The experimental results are compared with the soil water characteristic curves (SWCCs) to assess whether and to what extent the SWCCs are reliable in modelling the hydraulic behaviour of partially saturated soils, under atmospheric forcing, at least in the considered climatic contexts.

A Data-Driven Method for the Temporal Estimation of Soil Water Potential and Its Application for Shallow Landslides Prediction

Soil water potential is a key factor to study water dynamics in soil and for estimating the occurrence of natural hazards, as landslides. This parameter can be measured in field or estimated through physically-based models, limited by the availability of effective input soil properties and preliminary calibrations. Data-driven models, based on machine learning techniques, could overcome these gaps. The aim of this paper is then to develop an innovative machine learning methodology to assess soil water potential trends and to implement them in models to predict shallow landslides. Monitoring data since 2012 from test-sites slopes in Oltrepò Pavese (northern Italy) were used to build the models. Within the tested techniques, Random Forest models allowed an outstanding reconstruction of measured soil water potential temporal trends. Each model is sensitive to meteorological and hydrological characteristics according to soil depths and features. Reliability of the proposed models was confirmed by correct estimation of days when shallow landslides were triggered in the study areas in December 2020, after implementing the modeled trends on a slope stability model, and by the correct choice of physically-based rainfall thresholds. These results confirm the potential application of the developed methodology to estimate hydrological scenarios that could be used for decision-making purposes.

An ice correction model for dielectric sensor to improve accuracy of soil water potential measurement in frozen soils

Soil water potential is a key variable that determines water flow and indicates water availability and content. Although diverse techniques and methods have been developed for water potential measurement in unfrozen soils, most commercial techniques such as dielectric soil water potential (DSWP) sensors are not applicable for frozen soils due to potential errors of the dielectric measurement caused by ice formation within the sensor probes. Rather than directly recording sensor readings, these commercial DSWP sensors have to indirectly estimate soil water potential under equilibrium conditions by temperature measurement and the Clapeyron equation. Here we develop a mathematical model to correct the ice induced measurement error of the DSWP sensor in frozen soils. The DSWP sensor tested in this research was self-developed with a perforated cylinder coaxial (PCC) probe filled with a porous medium (gypsum). The central electrode was a temperature sensor (Pt100) replacing the usual steel pin. Sensor performance was demonstrated in a non-saline, loamy soil, by installing one sensor (DSWP-1) in a wetted soil sample prior to soil freezing, with two additional sensors (DSWP-2 and DSWP-3) installed later in frozen soil, prior to stepwise thawing. The results show that ice formed in the porous gypsum of the DSWP-1 sensor during soil freezing, as would be expected in the field with liquid water initially present to enter the probe. In comparison, no ice formed in the porous gypsums of the DSWP-2 and DSWP-3 sensors during the stepwise thawing process, allowing directly measurement of soil water potential in frozen soils and acting as a reference to develop an ice correction model based on a dielectric mixing model for the ice-formed DSWP-1 sensor to improve accuracy of soil water potential measurement. With the ice correction model, the RMSE between the readings of the DSWP-1 sensor and the reference values determined by the DSWP-3 sensor was decreased from 1.065 MPa to 0.491 MPa. In general, the ice correction model developed here can be used to improve accuracy of soil water potential measurement during soil freeze-thaw process using the DSWP sensor or other dielectric sensors and may extend application of the DSWP sensor to frozen soils under non-equilibrium conditions in the field.

Microtopographic refugia against drought in temperate forests: Lower water availability but more extensive fine root system in mounds than in pits

Water stress is one of the primary drivers of forest mortality and, with climate change, an increase in drought duration and severity is expected. Microtopography may offer hydrologic refugia against exposure to drought but how these local conditions affect fine root development of trees, and thus their sensitivity to drought, remains, however, poorly known. We studied how microtopography and water limitations influence the fine root system of two tree species, sugar maple (Acer saccharum) and bitternut hickory (Carya cordiformis), in natural forest stands at 16 sites in the temperate forest of southern Quebec (Canada). At each site, we measured the fine root standing crop and production (length, mass, and specific root length (SRL)) of four mature trees per species, located in pits and mounds. Half of them were also exposed to a rainfall exclusion for three months. We measured soil water potential at the base of each tree throughout the growing season. Soil water availability was significantly lower in mounds (mean ± SE: −22.5 ± 0.9 kPa) than in pits (−16.0 ± 1.0 kPa). We found a more extensive fine root system for trees in mounds than in pits, both in terms of length and mass; the standing crop length was 19% greater and the production length at a 20–40 cm depth was 77% greater in mounds than in pits. Fine root standing crop was slightly reduced in the rainfall exclusion treatment, whatever the microtopographical position. The sugar maple had a greater standing crop mass (but not length), and a greater fine root production at deeper soil layers (20–40 cm) than the bitternut hickory. Still, microtopography had a greater influence than tree species on fine root production at the deepest soil layer (30–40 cm). Overall, this study is a first step towards a better understanding of the interaction between micro-environmental conditions and rooting strategies. Our findings highlight the distinct acclimation to microtopography of the fine root system of trees, which could play a crucial role regarding their response to drought.

Irrigator Pro: Progression of a Peanut Irrigation Scheduling Decision Support System

HighlightsThe logic used in developing a decision support system for irrigating peanut based on max/min soil temperature is describedLogic to transform decision support system from peanut to irrigate corn and cotton with and without soil sensors.Progression of a decision support system from a desktop program to a web/mobile applicationAbstract. Irrigator Pro is a decision support tool for scheduling irrigation events in peanut. It was deployed in 1995 as a rule-based system using crop history, yield potential, soil type, in-season irrigation/rainfall and maximum/minimum soil temperature. As computing platforms have progressed from desktop personal computers to mobile web-based platforms, Irrigator Pro has been updated and is now deployed as a web-based program and an application for mobile devices. Irrigator Pro not only works for peanuts but has been modified to irrigate both corn and cotton. The irrigation decisions are now based on in-field soil water potential measurements in addition to the traditional checkbook with max/min soil temperatures. Users are individual growers, extension agents, and agronomic consultants. The objective of this manuscript is to document the initial development of Irrigator Pro as an expert system combining data and experiential knowledge and the progression from a checkbook-based decision support system to a hybrid system using observed weather data and soil moisture measurement. The background knowledge, equations, and thresholds for triggering irrigation recommendations are included. Keywords: Decision support system, Irrigation scheduling, Irrigator Pro, Mobile app, Peanut, Soil water potential.

New Approach to Improve the Soil Water Balance Method for Evapotranspiration Estimation

As an important component of the water budget, quantifying actual crop evapotranspiration (ET) will enable better planning, management, and allocation of the water resources. However, accurate ET measurement has always been a challenging task in agricultural water management. In the upper Midwest, where subsurface drainage is a common practice due to the shallow ground water depth and heavy clayey soil, ET measurement using traditional ground-based methods is more difficult. In this study, ET was measured using the eddy covariance (EC), Bowen ratio-energy balance (BREB), and soil water balance (SWB) methods during the 2018 corn growing season, and the results of the three methods were compared. To close the energy balance for the EC system, the residual method was used. For the SWB method, capillary rise was included in the ET estimation and was calculated using the measured soil water potential. The change of soil water content for ET estimation using the SWB method was calculated in four different ways, including daily average, 24:00–2:00 average, 24:00–4:00 average, and 4:00 measurement. Through the growing season, six observation periods (OPs) with no rainfall or minimal rainfall events were selected for comparisons among the three methods. The estimated latent heat flux (LE) by the EC system using the residual method showed a 29% overestimation compared to LE determined by the BREB system for the entire growing season. After excluding data taken in May and October, LE determined by the EC system was only 10% higher, indicating that the main difference between the two systems occurred during the early and late of the growing season. By considering all six OPs, a 6%–22% LE difference between the EC and the BREB systems was observed. Except during the early growing and late harvest seasons, both systems agreed well in LE estimation. The SWB method using the average soil water contents between 24:00 and 2:00 time period to calculate the daily capillary rise produced the best statistical fit when compared to the ET estimated by the BREB, with a root-mean-square error of 1.15. Therefore, measuring ET using the capillary rise from a shallow water table between 24:00 and 2:00 could improve the performance of the SWB methodology for ET measurement.

Convergent vegetation fog and dew water use in the Namib Desert

AbstractNonrainfall water inputs (e.g., fog and dew) are the least studied hydrological components in ecohydrology. The importance of nonrainfall waters on vegetation water status in arid ecosystems is receiving increasing attention. However, a clear understanding on how common plant water status benefits from nonrainfall waters, the impacts of different types of fog and dew events on vegetation water status, and the vegetation uptake mechanisms of nonrainfall waters is still lacking. In this study, we used concurrent leaf and soil water potential measurements from 3 years to investigate the species‐specific capacity to utilize moisture from fog and dew within the Namib Desert. Eight common plant species in the Namib Desert were selected. Our results showed that both fog and dew significantly increased soil water potential. Seven of the eight plant species studied responded to fog and dew events, although the magnitude of the response differed. Plants generally showed stronger responses to fog than to dew. Fog timing seemed to be an important factor determining vegetation response; for example, night fog did not affect plant water potential. We also found that Euclea pseudebenus and Faidherbia albida likely exploit fog moisture through foliar uptake. This study provides a first comprehensive assessment of the effects of nonrainfall waters on plant water status within the Namib Desert. Furthermore, this study highlights the importance of concurrent leaf and soil water potential measurements to identify the pathways of nonrainfall water use by desert vegetation. Our results fill a knowledge gap in dryland ecohydrology and have important implications for other drylands.

Influence of Drought on Foliar Water Uptake Capacity of Temperate Tree Species

Foliar water uptake (FWU) has been investigated in an increasing number of species from a variety of areas but has remained largely understudied in deciduous, temperate tree species from non-foggy regions. As leaf wetting events frequently occur in temperate regions, FWU might be more important than previously thought and should be investigated. As climate change progresses, the number of drought events is expected to increase, basically resulting in a decreasing number of leaf wetting events, which might make FWU a seemingly less important mechanism. However, the impact of drought on FWU might not be that unidirectional because drought will also cause a more negative tree water potential, which is expected to result in more FWU. It yet remains unclear whether drought results in a general increase or decrease in the amount of water absorbed by leaves. The main objectives of this study are, therefore: (i) to assess FWU-capacity in nine widely distributed key tree species from temperate regions, and (ii) to investigate the effect of drought on FWU in these species. Based on measurements of leaf and soil water potential and FWU-capacity, the effect of drought on FWU in temperate tree species was assessed. Eight out of nine temperate tree species were able to absorb water via their leaves. The amount of water absorbed by leaves and the response of this plant trait to drought were species-dependent, with a general increase in the amount of water absorbed as leaf water potential decreased. This relationship was less pronounced when using soil water potential as an independent variable. We were able to classify species according to their response in FWU to drought at the leaf level, but this classification changed when using drought at the soil level, and was driven by iso- and anisohydric behavior. FWU hence occurred in several key tree species from temperate regions, be it with some variability, which potentially allows these species to partly reduce the effects of drought stress. We recommend including this mechanism in future research regarding plant–water relations and to investigate the impact of different pathways used for FWU.

Dry season soil water potential maps of a 50 hectare tropical forest plot on Barro Colorado Island, Panama

Fine scale spatial variation in soil moisture influences plant performance, species distributions and diversity. However, detailed information on local soil moisture variation is scarce, particularly in species-rich tropical forests. We measured soil water potential and soil water content in the 50-ha Forest Dynamics Plot on Barro Colorado Island (BCI), Panama, one of the best-studied tropical forests in the world. We present maps of soil water potential for several dry season stages during a regular year and during an El Niño drought. Additionally, we provide code that allows users to create maps for specific dates. The maps can be combined with other freely available datasets such as long-term vegetation censuses (ranging from seeds to adult trees), data on other resources (e.g. light and nutrients) and remote sensing data (e.g. LiDAR and imaging spectroscopy). Users can study questions in various disciplines such as population and community ecology, plant physiology and hydrology under current and future climate conditions.

Where to monitor the soil-water potential for scheduling drip irrigation in Populus tomentosa plantations located on the North China Plain?

Determining the optimal tensiometer placement is crucial for scheduling irrigation based on soil water potential (SWP) in poplar plantations. However, such work has never been done. The stand-age effect on the tensiometer placement is still unknown, hindering the development of a dynamic irrigation regime. In a surface drip irrigated Populus tomentosa, short-rotation plantation on sandy loam soil, the variation of SWP at different positions [hereafter expressed in spatial coordinates (distance from dripper in cm, depth in cm)] within the soil wetting volume (WV), and the daily tree growth rates were continuously monitored in one growing season. Whereas, the transpiration and fine root distribution were measured in two growing seasons. The HYDRUS model was calibrated using soil water and transpiration data from one growing season and validated using data in another growing season. Then the model was applied to simulate sixty scenarios, which were combinations of different SWP measurement positions (ten scenarios), root distribution patterns (three scenarios; mainly using rooting depth as a proxy for trees at different ages), and irrigation thresholds (two scenarios). Based on the simulation results, we estimated the ratio of actual to potential transpiration (Ta/Tp) and irrigation efficiency (IE; calculated as (Ta/Tp)/irrigation amount) for each scenario. The absolute value of the mean relative difference of SWP was smaller at (15, 10) than at any other positions within the WV. The proportion of variation in growth (R2 = 0.294) and transpiration rates (R2 = 0.247) explained by root water-uptake was also highest at (15, 10). Fine roots concentrated on both sides of dripper as the trees grew bigger, with the maximal root density finally occurring at about (15, 10) and (−15, 10). Under the (−15, 10), (0, 10), (15, 10) and (0, 30) position scenarios, the Ta/Tp was at a high level relative to other scenarios, while the IE were at a middle level. As rooting depth increased, the ranks of different tensiometer positions in Ta/Tp and IE changed only a little, and Ta/Tp decreased slightly, implying the optimal placement should not vary with stand age. Therefore, tensiometer was recommended to place at 10 cm depth and about 15 cm distance from the dripper to schedule drip irrigation in different-aged P. tomentosa plantations on sandy loam soil. This will bring benefits to minimizing the use of irrigation water and maximizing production. Besides, the comprehensive approach used in this study can be adopted, when determining the optimal soil water measurement positions for scheduling irrigation for other plant species growing on other soil types.

Estimating Soil Water Retention Curve by Inverse Modelling from Combination of In Situ Dynamic Soil Water Content and Soil Potential Data

Soil water retention curves (SWRCs) are crucial for characterizing soil moisture dynamics, and are particularly relevant in the context of irrigation management. Inverse modelling is one of the methods used to parameterize models representing these curves, which are closest to the field reality. The objective of this study is to estimate the soil hydraulic properties through inverse modelling using the HYDRUS-1D code based on soil moisture and potential data acquired in the field. The in situ SWRCs acquired every 30 min are based on simultaneous soil water content and soil water potential measurements with 10HS and MPS-2 sensors, respectively, in five experimental fields. The fields were planted with drip-irrigated lettuces from February to March 2016 in the Chrey Bak catchment located in the Tonlé Sap Lake region, Cambodia. After calibration of the van Genuchten soil water retention model parameters, we used them to evaluate the performance of HYDRUS-1D to predict soil moisture dynamics in the studied fields. Water flow was reasonably well reproduced in all sites covering a range of soil types (loamy sand and loamy soil) with root mean square errors ranging from 0.02 to 0.03 cm3 cm−3.

Using germination prediction to inform seeding potential: II. comparison of germination predictions for cheatgrass and potential revegetation species in the Great Basin, USA

Germination models predict germination timing under seedbed water potential and temperature conditions. Using a wet thermal time model for germination prediction, we estimated progress toward germination (PTG) of 31 seedlots (10 species) as a function of hourly seedbed temperature (>0 °C) when soils were above a water potential of −1.5 MPa. Seasonally-summed progress toward germination with a value > 1 indicates that germination will occur for that season. We used near surface (1–3 cm) soil water potential and temperature measurements collected at 24 sites in the Great Basin to determine effects of site, season, and year on PTG. On tree encroached sites, we also determined effects of tree infilling phase at time of tree removal, removal method, and microsite on estimated PTG. Soils were wet and warm enough in early spring, late spring, and fall for PTG >1 indicating potential germination for most seedlots and species on most sites and years. Prescribed burning increased PTG as much as three times more than either tree cutting or mechanical shredding. Germination prediction could help to screen for plant materials adapted to specific sites or assess effects of seed additives or treatments that time germination to maximize seedling survival.

Parameterization of Root Water Uptake Models Considering Dynamic Root Distributions and Water Uptake Compensation

Core Ideas Parameters of different RWU models were optimized using data from a rhizotron facility. The same soil hydraulic properties were obtained for models considering RWU compensation. Feddes–Jarvis and Couvreur models predicted similar root‐system‐scale stress functions. The obtained RWU parameters were consistent with data reported in the literature. The models with compensation predicted similar total uptake but different local RWU. The spatiotemporal distribution of root water uptake (RWU) depends on the dynamics of the root distribution and compensatory uptake from wetter regions in the root zone. This work aimed to parameterize three RWU models with different representations of compensation: the Feddes–Jarvis model that uses an empirical function, the Feddes model without compensation, and the Couvreur model that is based on a physical description of water flow in the soil–root system. These models were implemented in HYDRUS‐1D, and soil hydraulic parameters were optimized by inverse modeling using soil water content and potential measurements and observations of root distributions of winter wheat (Triticum aestivum L.) in horizontally installed rhizotubes. Soil moisture was equally well predicted by the three models, and the soil hydraulic parameters optimized by the models with compensation were comparable. The obtained RWU parameters of the Feddes–Jarvis model were consistent with data reported in the literature, although the pressure heads h3l and h3h for lower and higher transpirations rates, respectively, could not be uniquely identified. Response surfaces of the objective function showed that the root‐related parameters of the Couvreur model could be identified using inverse modeling. Furthermore, these parameters were consistent with combined root architectural and hydraulic observations from the literature. The Feddes–Jarvis and Couvreur models simulated similar root‐system‐scale stress functions that link total RWU to the effective root zone water potential, suggesting that parameters may be transferable between the two models. Simulated RWU profiles differed due to different water redistribution by the root system, but the measurements were not sufficiently precise to observe this redistribution.

Assessing the Utility of Primed Acclimation for Improving Water Savings in Cotton using a Sensor‐Based Irrigation Scheduling System

This study addressed the potential of reduced prebloom irrigation, referred to as primed acclimation (PA), to increase agricultural water‐use efficiency (WUE) using a soil‐moisture‐based irrigation scheduling system in cotton (Gossypium hirsutum L.). To address this, a study was conducted near Camilla, GA, under a variable‐rate, center‐pivot irrigation system using a Watermark‐based automated soil moisture sensing approach to measure soil water potential (SWP) and impose varying irrigation scheduling treatments during the prebloom stage of development. Early season thresholds were −20 (Treatment 1), −40 (Treatment 2), −70 (Treatment 3), to −100 kPa (Treatment 4) prior to flowering. Reductions in prebloom irrigation of up to 17% were noted in this study for the driest thresholds (−100 kPa) with no reduction in lint yield relative to the −20 and −40 kPa thresholds. In some cases, prebloom irrigation was eliminated completely in the drier prebloom threshold treatments with no appreciable yield reductions. In rainfed treatments, episodic drought during flowering (2014) limited plant growth and node production, hastened cutout, decreased boll numbers per plant, produced a more compact boll distribution on the plant, and decreased yield and WUE relative to irrigated treatments. In contrast, season‐long rainfed treatments exhibited the highest WUE in 2015 (a wet season). The results of this study conclude that prebloom irrigation thresholds between −70 and −100 kPa appear to be viable for use in a sensor‐based PA irrigation scheduling system, whereas episodic drought coinciding with flowering represents a major threat to yield stability and WUE for cotton production in the southeastern United States.

Automatic plant-based water status monitoring in grapevine using an improved water transport and storage model

As all plants, grapevines (Vitis vinifera L.) need water to function properly. A certain level of drought stress might however be beneficial as it improves the composition of the grape. Earlier research has shown that differences in water status result in wines with different appearance, aroma, flavour and colour. Nevertheless, the level and timing is of utmost importance. Therefore, an adequate monitoring of the water status is crucial for improving grape (and wine) quality. It is internationally recognised that this should be based on plant measurements, because only then information is gained about the actual plant water status. Mechanistic models are promising for this purpose and allow a deeper understanding of the underlying mechanisms. In this study we use a dynamic water transport and storage model that links sap flow, or whole plant water consumption, and stem diameter variations in order to simulate stem water potential. This variable is considered as one of the best indicators for water status. We aimed at improving the model to perform well under both wet and pronounced dry conditions and evaluated it for real-time water status monitoring. To this end, the former constant flow resistance in the xylem has been replaced by a dynamic resistance depending on measured soil water potential and combines the resistance experienced in the soil, roots and stem. Furthermore, also the radial flow resistance (between xylem and storage tissues), originally implemented as a constant value, has been replaced by an equation. The improved model is able to accurately simulate the plant water status during both wet and pronounced dry conditions. The model seems very promising to apply as an automatic plant-based water status monitoring system and may be a tool to improve grape and wine quality.

Impact of irrigation on plant growth and development of white cabbage

It is widely known that an optimal irrigation water supply is a key to high horticultural productivity, efficient water use, and the reduction of off-site effects due to percolation of excess water. To promote better agronomic practices in irrigated horticulture, three different irrigation scheduling approaches based on soil water balance calculations, soil water potential measurements (sensor-based), and crop growth model simulations, were evaluated in a two-year field experiment. The experiments were conducted with white cabbage on a loamy sand soil near Dresden, Germany. The results show that sensor-based irrigation, at a soil water potential of −250hPa measured at a soil depth of 30cm, achieved high yields with moderate to low irrigation water inputs. Irrigation scheduling based on soil water balance calculations led to unproductive over-irrigation due to overestimated crop coefficients, which highlight the need for more accurate estimates of these coefficients. Simulation-based irrigation scheduling resulted in acceptable water productivities but can only be recommended to farmers to some extent because it requires a robust crop model calibration. Analysis of the plant development indicates that maintenance of field capacity until the end of head formation is favorable. Drought stress lead to reduced plant heights, leaf area indices and head yields. Furthermore, the results show that early drought stress effects can be compensated by an appropriate water supply in later growing stages.

Physiological and morphological responses of four different rice cultivars to soil water potential based deficit irrigation management strategies

This study was conducted to investigate the effects of six irrigation regimes on grain yield, yield attributes, water use efficiency, plant water status and antioxidant metabolite content of four rice varieties. We conducted a two year (dry seasons of 2014 and 2015) field experiment with four rice varieties (Apo, Annada, Satabdi and Naveen) and six irrigation schedules based on tensiometric measurement of soil water potential (SWP) with irrigation thresholds of −20 (SWP 1), −30 (SWP 2), −40 (SWP 3), −50 (SWP 4) and −60kPa (SWP 5), in addition to the traditional practice of growing flooded rice (CF). Among the six irrigation treatments, both grain yield and water input were lowest at SWP 5 and highest at CF. There was no significant difference in grain yield upto SWP 3 for Apo and Annada, whereas for Naveen and Satabdi the yield difference was non-significant up to SWP 2 as compared to CF. Reduced electrolyte leakage, root bleeding rate and increased concentration of proline, catalase and peroxidase contributed to tolerate the water deficit stress and higher grain yield in Apo and Annada varieties. The results indicated that adoption of water deficit irrigation strategy with an appropriate irrigation threshold and tolerant varieties can save water and increase water productivity. Rice genotypes having inherent capacity to produce higher amount of antioxidant metabolites in response to water deficit stress should be a primary target of breeding high yielding rice varieties for water deficit environments.

Dynamics of water uptake by maize on sloping farmland in a shallow Entisol in Southwest China

The water use patterns of maize grown in shallow soils remain poorly understood. To explore the water uptake dynamics of maize from a loamy Entisol with an average thickness of 40cm, excavation, isotopic tracer analysis and soil water potential measurements were combined to study the source of water used by maize. The differences between the δD of the water used by maize and the δD of the mobile soil water (MSW, the fraction of soil water with high mobility which can be easily replaced by the infiltrating rainwater) indicated that maize did not take up much MSW. The local meteoric evaporation line, the δD of the bulk soil water (BSW, total soil water including mobile and immobile soil water) and the soil water collected using a lysimeter were used in a model to calculate the isotopic compositions of different fractions of soil water and the proportion of immobile soil water (ImSW, the fraction of soil water with little mobility which was tightly bound to the soil particles). ImSW resulted from several heavy rains that occurred before the sampling. The primary water sources for maize varied temporally and spatially. Maize seedlings at the one-leaf stage used ImSW from 0 to 10cm soil depth; however, maize plants generally used more BSW from deeper soil layers when the roots reached greater depths. The ratios of MSW to ImSW were not equal between the maize stems and soil, with more ImSW in the maize stems, particularly during the seedling stage. This result invalidates the core concept of most watershed hydrology models and classical hypothesis in the isotopic models of general atmospheric circulation. The difference between the MSW and ImSW in the water cycle of the soil-plant-atmosphere continuum should be considered in the future studies of identifying the plant water sources and modeling hydrological processes.