Soil Water Content Measurements Research Articles

Linking an agro-meteorological model and a water cloud model for estimating soil water content over wheat fields

Agricultural drought has great impact on crop yields. Soil water content can directly reflect the degree of agricultural drought. The Water Cloud Model (WCM) is a vegetation contribution model which has been widely used in soil water content retrieval over vegetated areas. However, when optical remote sensing images are absent or are of a poor quality due to cloud cover and haze, the WCM parameters, describing the characteristics of vegetation layer, are hard to obtain. In order to effectively retrieve the soil water content over wheat fields, an agro-meteorological model, Simple Algorithm For Yield estimate (SAFY) model, was introduced to simulate the daily values of the WCM parameters during the whole winter wheat growth stages. Firstly, the leaf area index (LAI), retrieved from two Sentinel-2 (high-resolution optical) satellite images, was used to calibrate the parameters of the SAFY model in the Guanzhong Plain, PR China. The calibrated SAFY model was applied to simulate daily LAI. Then, Sentinel-1 backscatter coefficient, average ground measured soil water content from a depth of 0–12 cm and the simulated LAI were used to calibrate the WCM parameters to retrieve soil water content. In a final step, the soil water content retrieval results were validated at rain-fed and irrigated sampling sites, respectively. The SAFY model simulates the LAI of the Sentinel-1 sensing dates and uses it as an accurate vegetation description parameter for the WCM, which effectively solves the problem that the vegetation description parameter in the WCM cannot accurately describe the surface vegetation state at the time of radar satellite passing territory due to the Sentinel-1 and Sentinel-2 data in the study area cannot be acquired on the same day, and thus improving the accuracy of the WCM soil water content retrieval. For all sampling sites, the soil water content retrieval results have a satisfactory overall accuracy, and the soil water content retrieval results from rain-fed sampling sites have better accuracy than those from irrigated sampling sites. The soil water content retrieval results at the harvesting stage of winter wheat have the best accuracy among the three field experiments (R2 = 0.66; RMSE = 2.24%), followed by the tillering stage (R2 = 0.56; RMSE = 2.56%) and jointing stage (R2 = 0.36; RMSE = 2.74%). These results indicated that the combination of SAFY model and WCM can effectively retrieve the soil water content at different growth stages of winter wheat in the absence of optical remotely sensed images, and can provide significant benefit for soil water content retrieval over agricultural fields at the regional scale.

Modelling non‐stationary water ages in a tropical rainforest: A preliminary spatially distributed assessment

AbstractPristine tropical forests play a critical role in regional and global climate systems. For a better understanding of the eco‐hydrology of tropical “evergreen” vegetation, it is essential to know the partitioning of water into transpiration and evaporation, runoff and associated water ages. For this purpose, we evaluated how topography and vegetation influence water flux and age dynamics at high temporal (hourly) and spatial (10 m) resolution using the Spatially Distributed Tracer‐Aided Rainfall‐Runoff model for the tropics (STARRtropics). The model was applied in a tropical rainforest catchment (3.2 km2) where data were collected biweekly to monthly and during intensive monitoring campaigns from January 2013 to July 2018. The STARRtropicsmodel was further developed, incorporating an isotope mass balance for evapotranspiration partitioning into transpiration and evaporation. Results exhibited a rapid streamflow response to rainfall inputs (water and isotopes) with limited mixing and a largely time‐invariant baseflow isotope composition. Simulated soil water storage showed a transient response to rainfall inputs with a seasonal component directly resembling the streamflow dynamics which was independently evaluated using soil water content measurements. High transpiration fluxes (max 7 mm/day) were linked to lower slope gradients, deeper soils and greater leaf area index. Overall water partitioning resulted in 65% of the actual evapotranspiration being driven by vegetation with high transpiration rates over the drier months compared to the wet season. Time scales of water age were highly variable, ranging from hours to a few years. Stream water ages were conceptualized as a mixture of younger soil water and slightly older, deeper soil water and shallow groundwater with a maximum age of roughly 2 years during drought conditions (722 days). The simulated soil water ages ranged from hours to 162 days and for shallow groundwater up to 1,200 days. Despite the model assumptions, experimental challenges and data limitation, this preliminary spatially distributed model study enhances knowledge about the water ages and overall young water dominance in a tropical rainforest with little influence of deeper and older groundwater.

Field Measurements of Soil Water Content at Shallow Depths for Landslide Monitoring

Monitoring changes in soil saturation is important for slope stability analyses. Soil moisture capacitive sensors have recently been developed; their response time is extremely fast, they require little maintenance, and they are relatively inexpensive. The use of low-cost sensors in landslide areas can allow the monitoring of large territories, but appropriate calibration is required. Installation in the field and the setting up of the monitoring network also require attention. In the ALCOTRA AD-VITAM project, the University of Genoa is involved in the development of a system, called LAMP, for the monitoring, analysis and forecasting of slides triggered by rainfalls. Multiple installations (along vertical alignments) of WaterScout sensors are placed in the nodes of the monitoring network. They provide real-time water content profiles in the shallow layers (typically in the upper meter) of a slope. With particular reference to these measurements, the present paper describes the reliability analysis of the instruments, the operations related to the sensor calibration and the installation phases for the monitoring networks. Finally, some of the data coming from a node, belonging to one of the five monitoring networks, are reported.

A novel spectroscopy-based method using monopole antenna for measuring soil water content

Soil water content measurement is indispensable to precision agriculture. A novel soil water content measuring method based on frequency scanning is proposed in this research. The measuring system consists of a monopole antenna to emit and receive electromagnetic waves as well as a network analyzer. The soil equivalent circuit model is presented and its spectroscopy is obtained by comparing incident and reflected waves. The results indicate that the resonance frequency shifts towards the low frequency region as soil moisture increases, therefore soil water content can be obtained simply by detecting resonance frequency. The linear fitting curve has a determination coefficient of 0.9834 and a root mean square error of 1.4%. The measuring range from 5.0% to 37.4% is wide enough for actual agricultural production. The method offers a productive solution for soil water content measurement and provides an idea to sense other soil characteristics.

Hammond Hill Research Catchment: Supporting hydrologic investigations of rooting zone and vegetation water dynamics under climate change

AbstractThe Hammond Hill Research Catchment (HH) is a small (120 ha), temperate, second order tributary to Six Mile Creek, Cayuga Lake, and the Great Lakes (42.42°, −76.32°). The HH has been monitored since January 2017 for the purpose of understanding how recent infiltration mixes with antecedent soil water on hillslope forest floors and the spatial and temporal patterns of Root Water Uptake (RWU) by temperate northeastern US tree species (eastern hemlock [Tsuga canadensis], American beech [Fagus grandifolia], and sugar maple [Acer saccharum]). These data are informing us about the hydrologic consequences of anticipated tree species composition change and supporting the development of more refined ecohydrological models. The glaciated catchment is underlain by a shallow confining siltstone layer (1–1.5 m depth) and densely covered with an approximately 60 year old regrowth mixed species forest of hemlock, beech, and other deciduous tree species common to the northeastern US. Current datasets from the HH include precipitation snow water equivalent, discharge, and associated isotopic water compositions, δ2H & δ18O. Measurements of (top 10 cm) soil water content, as well as bulk soil water and hemlock and beech xylem isotopic compositions are made at several locations across a topographic wetness gradient. The near‐term role of the HH is to support an understanding of the environmental and ecological drivers of plant RWU competition. All data from the HH are publicly available.

Spatio‐temporal variability of multi‐layer soil water at a hillslope scale in the critical zone of the Chinese Loess Plateau

AbstractUnderstanding the spatio‐temporal variability of soil water content (SWC) in the Critical Zone (CZ) is essential to balance plant‐water benefits and to enhance the ability to monitor and predict drought. In current study, the spatial variability and temporal stability of multi‐layer SWC to a depth of 500 cm (35 soil layers) at 27 sampling sites were evaluated at a hillslope scale. A total of 64 SWC measurements were obtained from 28 March, 2017 to 23 December, 2018. We hypothesized the existence of a “special point” that is temporally stable both in horizontal direction (which means different layers) and in vertical direction (which means different profiles). We found a clear seasonal dynamic pattern of mean SWC for all sites in the 0–500 cm profile, with SWC varying from 4.0 to 24.8%. In the horizontal layer, both the 130‐cm and 140‐cm layers contained a maximum number of temporal stability sites (N = 4) which all located at H11, H13, H14 and H26. In the vertical profile, H19 was the most stable site, followed by H10 and H26, with 15, 10 and 6 stable layers, respectively. The decreasing order of SWC temporal stability was 200–500 cm, 0–500 cm and 0–200 cm, which means the temporal stability of SWC in 0–500 cm profile was more dependent on the 0–200 cm sub‐profile. At a three‐dimension scale, the most temporal stability layer and site was 180‐cm of H1 and H21 of 220‐cm, which confirmed our hypothesis. This study provides an accurate description of SWC spatio‐temporal variation at the hillslope scale, which is helpful for addressing eco‐hydrological models and water management issues in the Earth's CZs.

Thermo–time domain reflectometry method: Advances in monitoring in situ soil bulk density

AbstractSoil bulk density (ρb) is a critical parameter for describing soil structure and physical processes, yet traditional methods are unable to capture spatial and temporal changes in ρb. Recently the thermo–time domain reflectometry (thermo‐TDR) technique has been applied to determine in situ ρb on the basis of soil thermal property and water content measurements. Here, we present theory, instrumentation, procedures, and comments for monitoring in situ ρb with the thermo‐TDR sensor. We conclude that the thermo‐TDR sensor offers a useful tool for determining ρb continuously and nondestructively.

Characterizing the exudation of water and pollutants from soil into streams during soil-thawing period

The objectives of this study were to characterize the exudation of water and pollutants from soil into streams during soil-thawing periods, and to investigate the impacts of hydrological and pollution transport processes in soil, and energy entering soil on the exudation. Field experiments were conducted to measure soil water content and concentrations of ammonia nitrogen (NH4+-N), nitrate nitrogen (NO3−-N), and soluble phosphorus (SP) in four closed catchments containing paddy or corn fields, along with the exudation of water and pollutants from soil into streams (i.e., flow rate and pollution fluxes at catchment outlets). The amount of dissolved pollutants from soil particles was the key factor affecting pollution exudation into streams during soil-thawing periods. Water exudation directly affected pollution exudation; when the former was >1.24 × 10−3 m3 s−1 km−2, the pollutant mass in the water reached maximum and changes in its concentration were primarily attributed to water exudation. When water exudation was 1.08 × 10−3–1.24 × 10−3 m3 s−1 km−2, the dissolved pollutant mass from soil decreased with water exudation. The influence of pollutant transport processes on pollution exudation became more significant when water exudation was <1.08 × 10−3 m3 s−1 km−2. Relative concentrations of pollutants in corn-dominated catchments were higher than those in the paddy-dominated catchment, suggesting that pollution exudation was most attributable to water exudation in paddies and to the pollution source in corn fields. Energy entering the soil accelerated the fragmentation of soil aggregates and enhanced the N transformation and SP solubility, further increasing pollution exudation.

Porous‐fiber module increases infiltration and reduces runoff

AbstractThe porous‐fiber module (PFM) is an advanced product used for rainfall regulation and storage. Most studies focus on the characteristics of its constituent material while ignoring the impacts of PFM application on infiltration and runoff. In this study, several factors were comprehensively considered in the field control simulated rainfall experiments conducted on bare land, including two types of rainfall intensities, four PFM volumes, and two arrangements of the PFM, to evaluate the impacts. The experiments consisted of measuring soil water content variation, surface runoff of each treatment plot, and the cumulative infiltration obtained by water balance. The results demonstrated that the effect of PFM volume on infiltration and runoff was much greater than that of the PFM arrangement. The addition of PFM could improve the water‐holding capacity of soil; this effect initially strengthened and subsequently weakened with the increase in the PFM volume. The PFM embedding increased the cumulative infiltration of the experimental plots by 5.1–79.2%, delayed the runoff start time by 0–20 min, weakened the peak by 13.6–51.1%, and reduced the runoff‐yielding amount by 11.23–62.53%, compared with those of the control plot. These effects were enhanced as PFM volume increased. An empirical formula, presented as the theoretical influence of PFM volume on the product of the cumulative infiltration multiplied by the Philip model derived by the control plot, was further established for simulating the infiltration process with various PFM volumes.

Growing-season soil microbial respiration response to long-term no tillage and spring ridge tillage

No tillage (NT) and spring ridge tillage (SRT) are two common applications of conservation tillage. Although conservation tillage is known to exert major control over soil microbial respiration (SMR), the growing-season SMR response to these two applications remains elusive. In order to better understand the influence of conservation tillage practices, this experiment was conducted in an experimental field using NT and SRT for 17 years. In situ measurements of SMR, soil temperature and soil water content (SWC) were performed. Soil samples were collected to analyze soil porosity, soil microbial biomass (SMB) and soil enzymatic activities. Results show that the two conservation tillage systems had a significant difference (p 0.05). Despite SRT increasing the proportion of micro-porosities and meso-porosities, the soil macro-porosities for NT were 7.37% higher than that of SRT, which resulted in higher bacteria and fungi in NT. Owing to SRT damaged the hypha, which had disadvantage in soil microbe protection. Inversely, less soil disturbance was a unique advantage in NT, which was in favor of improving soil macro-pores and SWC. Redundancy analyses (RDA) showed SMR was positively correlated with soil macro-pores, SMB and SWC. Furthermore, the Pearson correlation test indicated that SMB and soil enzymatic activities did not have a significant correlation (p>0.05). This study results suggest that SRT is more conducive to carbon sequestration compared with NT in cropland. Keywords: no tillage, spring ridge tillage, soil microbial respiration, microbial biomass, soil porosity, soil enzymatic activity DOI: 10.25165/j.ijabe.20201304.5587 Citation: Wang G, Jia H L, Zhuang J, Glatzel S, Bennett J M, Zhu Y C. Growing-season soil microbial respiration response to long-term no tillage and spring ridge tillage. Int J Agric & Biol Eng, 2020; 13(4): 143–150.

A modelling approach to discriminate contributions of soil hydrological properties and slope gradient to water stress in Mediterranean vineyards

Grapevine is a widespread crop for grape and wine production, often cultivated on hilly areas. Moderate vine water stress plays an important role in determining high-quality viticulture. However, a precise quantification of the effect of hydraulic properties and slope gradient on hilly soil water balance and consequently on vine stress has not yet been addressed in the literature. The slope-gradient effect is generally taken for granted, without providing experiments validating such a qualitative assumption. We tested the hypothesis that soil hydraulic properties play a greater role than slope gradient in driving soil water status and vine stress. In two consecutive years, we studied an “Aglianico” vineyard grown along a 90 m slope, with up-slope soil having lower water holding capacity than down-slope. Up-slope vines were more stressed, as shown by lower leaf water potential, stomatal conductance, leaf CO2 assimilation and leaf area index, than down-slope vines.Water flow was simulated by using the Hydrus (2D/3D) model, calibrated and validated towards a two-year set of soil water content measurements. Significantly lower soil pressure head and higher transpiration occurred in the up- than the down-slope site.A viable procedure was developed to separate the effects of soil hydraulic properties and slope gradient by modelling soil water balance and therefore vine transpiration with and without the slope gradient. The simulations indicated that the difference in seasonal relative transpiration of 8% in 2011 and 5% in 2012 between the two sites was due to their differing soil hydraulic properties, and that the slope gradient had no contribution to this variation.

An improved approach to estimating the infiltration characteristics in surface irrigation systems.

The most common methods for estimating the infiltration function are measurements through a double-ring infiltrometer (DRI) and empirical models. Infiltration data always exhibit different kinds of scatter, which affect the accuracy of the estimated infiltration function. This study presents a new methodology to calibrate the infiltration function. The suggested approach is based on combining the DRI method with the changes in the measured soil water content. Furrow irrigation experiments were conducted to estimate the infiltration function using different methods and to investigate the effect of data scatter on the reliability of the estimated infiltration function. Furrow elevations were observed, and for each irrigation event advance times, recession times, and inflow rates were observed. The infiltration depths were measured as a function of the change in the soil water content before and after irrigation event. Infiltration parameters were estimated using DRI treatment, empirical model (Kostiakov model), and suggested approach. Measured and simulated infiltration depths using the described methods were compared. The results show that the infiltration depths estimated using a DRI were lower than the observed infiltration depths, while the infiltration depths estimated using the empirical model were higher than the observed infiltration depths. The results indicate that the infiltration function estimated using the recommended approach was more accurate and reasonable than the infiltration function estimated using the DRI, and empirical (Kostiakov model) methods. In addition, the proposed approach can reduce the required measurements during the irrigation event, and can also reduce the potential scatter in the estimated infiltration function that results from soil variability and measurement errors.

Estimating the macroscopic capillary length from Beerkan infiltration experiments and its impact on saturated soil hydraulic conductivity predictions

The macroscopic capillary length, λc, is a fundamental soil parameter expressing the relative importance of the capillary over gravity forces during water movement in unsaturated soil. In this investigation, we propose a simple field method for estimating λc using only a single-ring infiltration experiment of the Beerkan type and measurements of initial and saturated soil water contents. We assumed that the intercept of the linear regression fitted to the steady-state portion of the experimental infiltration curve could be used as a reliable predictor of λc. This hypothesis was validated by assessing the proposed calculation approach using both analytical and field data. The analytical validation demonstrated that the proposed method was able to provide reliable λc estimates over a wide range of soil textural characteristics and initial soil water contents. The field testing was performed on a large database including 433 Beerkan infiltration experiments, with the 99% of the experiments yielding realistic λc values. The generated λc values were then used in conjunction with four different methods for estimating saturated soil hydraulic conductivity, Ks. Estimated Ks values were close to those generated by a reference method, with relative error < 25% in nearly all cases. By comparison, assuming constant or soil-dependent λc values caused relative errors in Ks of up to 600%. Altogether, the proposed method constitutes an easy solution for estimating λc, which can improve our ability to estimate Ks in the field.

Remote-Sensing-Based Water Balance for Monitoring of Evapotranspiration and Water Stress of a Mediterranean Oak–Grass Savanna

Mediterranean oak savannas (known as dehesas in Spain) are exposed to numerous threats from natural and economic causes. A close monitoring of the use of water resources and the status of the vegetation in these ecosystems can be useful tools for maintaining the production of ecological services. This study explores the estimation of evapotranspiration (ET) and water stress over a dehesa by integrating remotely sensed data into a water balance using the FAO-56 approach (VI-ETo model). Special attention is paid to the different phenology and contribution to the system’s hydrology of the two main canopy layers of the system (tree + grass). The results showed that the model accurately reproduced the dynamics of the water consumed by the vegetation, with RMSE of 0.47 mm day−1 and low biases for both, the whole system and the grass layer, when compared with flux tower measurements. The ET/ETo ratio helped to identify periods of water stress, confirmed for the grassland by measured soil water content. The modeling scheme and Sentinel-2 temporal resolution allowed the reproduction of fast and isolated ET pulses, important for understanding the hydrologic behavior of the system, confirming the adequacy of this sensor for monitoring grasslands water dynamics.

Comparison of soil water content estimation equations using ground penetrating radar

Soil water content has an important impact on many fundamental biophysical processes. The quantification of soil water content is necessary for different applications, ranging from large-scale calibration of global-scale climate models to field and catchment scale monitoring in hydrology and agriculture. Many techniques are available today for measuring soil water content, ranging from point scale soil water content sensors to global scale, active and passive, microwave satellites. Geophysical methods are important methods, used for several decades, to measure soil water content at different scales. Among these methods, ground penetrating radar has been shown to be one of the most reliable and promising ones. Soil water content measurement using ground penetrating radar requires the application of parametric equations that will convert the measured dielectric permittivity to water content. While several studies have been performed to test equations for soil water content sensors such as time domain reflectometry, a few studies have been performed to test different formulae for application to ground penetrating radar. In this study, we compare available formulae for converting dielectric permittivity obtained from detailed laboratory scale measurement of reflected waves using ground penetrating radar. Four soils covering a wide range of textures were used and the measured soil water contents were compared with values obtained from gravimetric measurements. Results showed that the dielectric mixing model of Roth et al. (1990) provided the best fit for individual soil textural classes, except for sandy soils. However, for all data combined the dielectric mixing model performed much better with significant difference in coefficient and determination and root mean square error. Empirical equations developed from calibration of time domain reflectometry performed poorly when applied to estimation of soil water content obtained from ground penetrating radar. Differences in sample volume, frequency of operation and data analysis between ground penetrating radar and time domain reflectometry, suggest to use more flexible and robust electromagnetic mixing formulae, allowing for incorporating the dielectric properties of constituents materials and geometrical features of the media. Sensitivity analysis was then performed to provide detailed information for the most accurate application of the selected dielectric model. Sensitivity analysis showed that the geometric parameter α and the dielectric permittivity of the solid phase ∊s are the two most sensitive parameters, determining important variations in the estimation of soil water content. Based on these results, these two parameters are suggested as fitting parameters, to be selected if the model is fitted to data. Otherwise, the model can be successfully used without calibration, as presented in this study, by using α = 0.5 (as also suggested by the authors) and ∊s = 4, which is an average value for soil minerals.

Application of SALTMED and HYDRUS-1D models for simulations of soil water content and soil salinity in controlled groundwater depth

Salinization is a gradual process that should be monitored. Modelling is a suitable alternative technique that saves time and cost for the field monitoring. But the performance of the models should be evaluated using the measured data. Therefore, the aim of this study was to evaluate and compare the SALTMED and HYDRUS-1D models using the measured soil water content, soil salinity and wheat yield data under different levels of saline irrigation water and groundwater depth. The field experiment was conducted in 2013 and in this research three controlled groundwater depths, i.e., 60 (CD60), 80 (CD80) and 100 (CD100) cm and two salinity levels of irrigation water, i.e., 4 (EC4) and 8 (EC8) dS/m were used in a complete randomized design with three replications. Soil water content and soil salinity were measured in soil profile and compared with the predicted values by the SALTMED and HYDRUS-1D models. Calibrations of the SALTMED and HYDRUS-1D models were carried out using the measured data under EC4-CD100 treatment and the data of the other treatments were used for validation. The statistical parameters including normalized root mean square error (NRMSE) and degree of agreement (d) showed that the values for predicting soil water content and soil salinity were more accurate in the HYDRUS-1D model than in the SALTMED model. The NRMSE and d values of the HYDRUS-1D model were 9.6% and 0.64 for the predicted soil water content and 6.2% and 0.98 for the predicted soil salinity, respectively. These indices of the SALTMED model were 10.6% and 0.81 for the predicted soil water content and 11.0% and 0.97 for the predicted soil salinity, respectively. According to the NRMSE and d values for the predicted wheat yield (9.8% and 0.91, respectively) and dry matter (2.9% and 0.99, respectively), we concluded that the SALTMED model predicted the wheat yield and dry matter accurately.

Relationships between soil water content, evapotranspiration, and irrigation measurements in a California drip-irrigated Pinot noir vineyard

The Central Valley of California relies on irrigation for crop production, but water resources, particularly groundwater, have reached a critical state due to extended drought periods and overuse by irrigated agriculture. The purpose of the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) project is to improve efficiency in vineyard irrigation through field measurements and modeling efforts using remote sensing. In this study, we analyze multi-year timeseries of ground-based soil moisture and evapotranspiration (ET) measurements collected during GRAPEX to identify patterns that may inform future irrigation recommendations based on remotely sensed ET. The study focuses on field data collected in two adjacent Pinot noir vineyards near Lodi, CA from 2013 to 2017. The data used for this analysis are reference evapotranspiration (ETref), actual evapotranspiration (ETa), mean daytime soil water content (SWC) measured to a depth of 90 cm, precipitation, and irrigation. The relationship between SWC and the ratio of ETa/ETref (used as a soil moisture proxy indicator) changes throughout the spring and summer months due to advancing phenological stages and management practices. In early spring, when the interrow cover crop is the primary source of ET, ETa is strongly correlated with SWC. As the vine canopy grows in, the strong correlation breaks down as the vines begin to access to water beyond the depth of the soil moisture sensors. As the soil profile dries out during the summer, the correlation between ETa and SWC once again emerges as the vines become strongly dependent on irrigation. The dynamic interaction between the upper and lower root zone profile and evaporative demand means that the key to understanding vineyard water status using relatively shallow SWC observations is to use them in conjunction with ETa data, so that when both SWC and ETa timeseries are highly correlated vine water status is well defined. This suggests, delaying the initiation of irrigation during the period of rapid vine growth until a clear relationship between SWC and ETa emerges would both reduce the total amount of water used and give the grower more control over vine growth and grape quality affected by water status.

A macroscopic soil-water transport model to simulate root water uptake in the presence of water and disease stress

Macroscopic modeling approaches based on the solution of the Richards equation with root water uptake (RWU) as a sink term can help in understanding soil-water-plant interactions within the rhizosphere. However, these models currently cannot capture the differences in RWU attributed to variations in plant health. Errors in simulating RWU from unhealthy plants are significant when disease-causing fungus inhibits water uptake rather than other usually considered plant stresses. We developed RWU reduction functions to simulate plant transpiration under combined water and disease stress conditions using linear and non-linear response models. The developed functions were implemented in the numerical model HYDRUS (2D/3D) to simulate water uptake from a root system in a radially symmetrical flow domain. Field experiments were conducted in the Vidarbha region of central India for one crop cycle on four citrus trees with varying disease intensities (healthy to severely diseased). The proposed model was rigorously tested by comparing its results with measured soil water contents and plant transpiration fluxes under various water and disease limiting conditions. Error in simulating RWU fluxes from unhealthy trees by ignoring the disease stress factor was found to be significant (15% for slightly diseased to 26% for the severely diseased tree). Parameters of the spatial root distribution and the disease stress response functions were optimized for each scenario using a genetic algorithm approach. Our results indicate that calibration targets to validate uptake reduction functions should be chosen cautiously based on the dominant stress experienced by the plant root system.

A modified soil water content measurement technique using actively heated fiber optic sensor

Abstract Soil water content measurement is critical in practical engineering. The actively heated fiber Bragg grating optic sensor (FBGS) has great potential of multi-point measurement for soil water content measurement in field. In this study, the effect of heating time on the measurement accuracy is discussed, and modifications are made for actively heated fiber optic (AHFO) sensors. The results demonstrate that if an integration data analysis method is used, the accuracy and reliability of soil water content measurement with AHFO sensors will be improved. Both a short fiber length and a short-term heating pattern are effective and can help to reduce soil disturbance. With the proposed integration method, a short heating time is guaranteed for measuring the soil water content. Such improvements will reduce the thermal disturbance to soil sample and improve the reliability of measurement.

Limitations in Validating Derived Soil Water Content from Thermal/Optical Measurements Using the Simplified Triangle Method

We assess the validity of the surface moisture availability parameter (Mo) derived from satellite-based optical/thermal measurements using the simplified triangle method. First, we show that Mo values obtained from the simplified triangle method agree closely with those generated from a soil/vegetation/atmosphere/transfer (SVAT) model for scenes over a field site at the Allahabad district, India. Next, we compared Mo values from the simplified triangle method for these same overpass scenes with surface soil water content measured at depths of 5 and 15 cm at this field site. Although a very weak correlation exists between remotely sensed values of Mo for the full scenes and measured soil water content measured at both depths, correlations increasingly improve for the 5 cm samples (but not for the 15 cm samples) as pixels were limited to increasingly smaller vegetation fractions. We conclude that the simplified triangle method would yield reasonable values of Mo and demonstrate good agreement with ground measurements, provided that validation is limited to pixels with little or no vegetation and to soil depths of 5 cm or less.