Soil Water Content Measurements Research Articles

The Cycles agroecosystem model: Fundamentals, testing, and applications

Models of the soil–plant-atmosphere continuum are repositories of knowledge and gears in analytical and decision support tools applied to agroecosystems. In this paper, we present the Cycles agroecosystem model theory along with test cases and applications. Cycles combines innovations for simulating soil hydrology and biogeochemistry, including carbon and nitrogen saturation theory, with a modular software architecture. These elements enable simulating monoculture or polyculture crop sequences and associated management practices, containerizing for applications that require high-performance computing, and data assimilation at runtime. A comparison of simulated and measured daily evapotranspiration (ET) obtained with the eddy covariance method for maize (Zea mays L.) and shrub willow (Salix spp.) shows that Cycles represents well meteorological and vegetation controls of ET (root mean square error or RMSE = 0.75 mm d-1). Cycles accurately simulated differences of 150 mm in growing season ET between these two plant communities. Comparisons of modeled versus measured soil water content under soybean (Glycine max [L.] Merr.) in southeastern Pennsylvania for six soil layers at 0.1-m increments show accurate representation of water depletion and recharge (RMSE of 0.027–0.011 m3 m−3). Simulations of growth and nitrogen uptake of wheat (Triticum aestivum L.) in eastern Washington also highlight the model’s skill simulating processes that affect water and nutrient fluxes simultaneously. To highlight Cycles’ suitability for incorporation in high performance computing applications, we present a coupling of Cycles with an autonomous crop sequence builder (Cycles-A) in the Chesapeake Bay watershed. This system automatically identified areas for double cropping and selected the optimum combination of annual crops across the watershed. The Cycles model innovations and agroecosystem framing continue advancing the premise of making models not only dynamic knowledge repositories but useful tools for research and landscape management.

Development and in situ application of actively heated fiber Bragg grating cable for soil water content measurement

The actively heated fiber-optic (AHFO) technology has emerged as a frontier and hotspot in soil water content measurement, offering advantages such as easy installation, large-scale distributed measurement capability, and resistance to electromagnetic interference. However, current AHFO water content sensors fail to simultaneously achieve high precision, applicability for deep soil, and automated real-time monitoring, thereby limiting their development and application. Therefore, this study introduces a novel actively heated fiber Bragg grating (AH-FBG) cable. Laboratory tests were conducted to assess the heating uniformity of the AH-FBG cable and to establish the temperature characteristic value (Tt) – soil water content (θ) calibration formula for water content measurement. Subsequently, AH-FBG cables were deployed for in situ soil water content monitoring in a test pit on the Loess Plateau. Through two-year monitoring data verified the accuracy of the AH-FBG cable and elucidated the spatiotemporal distribution of in situ loess water content. Laboratory results demonstrated superior heating uniformity of AH-FBG cable, with a Tt standard deviation of approximately 0.3 °C. In the field, the AH-FBG cable exhibited excellent performance in soil water content measurement, achieving a high accuracy of 0.023 cm3/cm3. Further analysis revealed that the θ fluctuation predominantly occurred within a 10 m depth from the soil surface, with an overall upward trend over the two-year monitoring period; the response of shallow θ to precipitation was significant but exhibited increasing hysteresis with depth; frequent precipitation significantly enhanced water infiltration depth. This study provides technical guidance for high-precision, quasi-distributed, automated and real-time water content measurement of deep soil.

Rainfall-Groundwater Table Fluctuations Impact on Root Zone Soil Water Simulated in Upflow for Crop Production Planning in Obio Akpa Watershed, Nigeria

The non-predictability of rainfall-groundwater table relationships in the ungauged Obio Akpa watershed has rubbished remedial measures against seasonal crop losses. This study utilizes ten years (2011-2020) climate data obtained from the study area to predict the seasonal rainfall-groundwater table variations and simulate the effects on crop root zone using Upflow model. Twelve wells monitored monthly, characterized the seasonal behaviour of the Groundwater Table (GT). Gravimetric direct measurements of soil water contents were the inputs to UPFLOW model used to simulate the seasonal responses of GT to rainfall. Correlation-regression analysis was used to obtain a prediction equation of GT responses to rainfall. Results showed that in the month of April, the mean rainfall of 230mm induced GT rise of 1.35m (35%) from 3.85m in March to 2.50m in April. The effect on the soil water properties included a corresponding increase of 1.8 vol.% (10.7%) in field capacity at equilibrium with the water table in the preceding month. Mean soil water condition remained optimal at 15.9 vol.% with the GT at 1.5m below the root zone. In September and October when 1859mm and 2129mm of the mean annual rainfall was received, the water table increased by 72% and 74% respectively, and field capacity in equilibrium with the GT increased to 34.9 vol.%. causing GT inundation of the root zone (RZ) and deficit aeration in 74% of the RZ respectively. In November, with reduced rainfall amount and decreased input to groundwater, only 16% of the RZ was in deficit aeration. UPFLOW simulations of the annual soil water regime showed the months of September, October and November as high GT months suitable for planting and harvesting of only shallow rooted, short maturity crops. This knowledge will guide effective water resources and crop management in the watershed.

Effect of Biomass Water Dynamics in Cosmic-Ray Neutron Sensor Observations: A Long-Term Analysis of Maize-Soybean Rotation in Nebraska.

Precise soil water content (SWC) measurement is crucial for effective water resource management. This study utilizes the Cosmic-Ray Neutron Sensor (CRNS) for area-averaged SWC measurements, emphasizing the need to consider all hydrogen sources, including time-variable plant biomass and water content. Near Mead, Nebraska, three field sites (CSP1, CSP2, and CSP3) growing a maize-soybean rotation were monitored for 5 (CSP1 and CSP2) and 13 (CSP3) years. Data collection included destructive biomass water equivalent (BWE) biweekly sampling, epithermal neutron counts, atmospheric meteorological variables, and point-scale SWC from a sparse time domain reflectometry (TDR) network (four locations and five depths). In 2023, dense gravimetric SWC surveys were collected eight (CSP1 and CSP2) and nine (CSP3) times over the growing season (April to October). The N0 parameter exhibited a linear relationship with BWE, suggesting that a straightforward vegetation correction factor may be suitable (fb). Results from the 2023 gravimetric surveys and long-term TDR data indicated a neutron count rate reduction of about 1% for every 1 kg m-2 (or mm of water) increase in BWE. This reduction factor aligns with existing shorter-term row crop studies but nearly doubles the value previously reported for forests. This long-term study contributes insights into the vegetation correction factor for CRNS, helping resolve a long-standing issue within the CRNS community.

Customizing pyfao56 for evapotranspiration estimation and irrigation scheduling at the Limited Irrigation Research Farm (LIRF), Greeley, Colorado

Estimation of evapotranspiration (ET, the water used by soil evaporation and plant transpiration) and soil water depletion (Dr, the amount of water to bring the soil water in the root zone to field capacity) are critical in irrigation water management. The open-source Python-based crop ET and water balance modeling package named “pyfao56” was originally developed based on the dual crop coefficient approach as described in the Food and Agricultural Organization of the United Nations, Irrigation and Drainage Paper No. 56 (FAO-56). The package later expanded on the seminal FAO-56 document to consider various options relevant to ET and water balance modeling, including both short (grass) and tall (alfalfa) reference crops, optional discretization of variable soil layers based on field capacity, and interpretation of readily available water (RAW) and Dr based on both a dynamic (growing) root zone and maximum root zone. The package requires two input data objects; the “Parameters” class defines variables affecting soil water balance and ET and the “Weather” class specifies relevant meteorological data. Other optional input data objects include the “Irrigation” class for irrigation events, the “Soil_Profile: class for defining stratified soil layer data, and the “Update” class for assimilation of measured data. Additional tools are available for estimating and forecasting standardized reference ET (ETref), providing seasonal water balance summaries, computing goodness-of-fit statistics between measured and modeled values, and visualizing time series plots of daily Dr, ET, and crop coefficients. The current pyfao56 release (v1.2.1) was incorporated into a customized workflow for specific use at the USDA-ARS Limited Irrigation Research Farm (LIRF) in Greeley, Colorado, and named the LIRF Implementation of Pyfao56 (LIRFIP). Field data from 2023 full and limited irrigation field trials were used to demonstrate the functionality of LIRFIP and its customizations and integration of pyfao56 into the LIRF workflow. Specific customizations included use of pyfao56 “customload” functions to input data from various sources, including weather from an on-site micrometerological station (using the application programming interface (API) developed by the maintainers of the Colorado Agricultural Meteorological (CoAgMet) weather station network), irrigation events (via a shared Google docs sheet), field capacity values by plot and soil layer (via an Excel spreadsheet), and measured soil water content as well as basal crop coefficient (Kcb) calculated from fractional canopy cover (fc) (via an SQLite database). To evaluate multiple research plots, LIRFIP was designed to iterate simulations from multiple instances of pyfao56 and to produce customized output summary files and interactive hypertext markup language (html) graphs as an aid for irrigation management decisions for LIRF field trials. This study demonstrated pyfao56 as a useful, flexible, customizable, and repeatable ET-based water balance model by showcasing its integration within a specific computational workflow for irrigation management field research at LIRF. The approach serves as an example for pyfao56 integration in other water management tools as conceived by water managers, researchers, and practitioners worldwide.

Soil-Specific Calibration Using Plate Compression Filling Technique and Monitoring Soil Biomass Degradation Based on Dielectric Properties

Accurate estimation of soil water content (SWC) is crucial for effective irrigation management and maximizing crop yields. Although dielectric property-based SWC measurements are widely used, their accuracy is still affected by soil variability, soil–sensor contact, and other factors, making the development of convenient and accurate soil-specific calibration methods a major challenge. This study aims to propose a plate compression filling technique for soil-specific calibrations and to monitor the extent of soil biomass degradation using dielectric properties. Before and after biodegradation, dielectric measurements of quartz sand and silt loam were made at seven different water contents with three different filling techniques. A third-order polynomial fitting equation explaining the dependence of the dielectric constant on the volumetric water content was obtained using the least-squares method. The suggested plate compression filling method has a maximum mean bias error (MBE) of less than 0.5%, according to experimental results. Depending on the water content, silt loam’s dielectric characteristics change significantly before and after biodegradation. The best water content, measured in gravimetric units, to encourage the decomposition of biomass was discovered to be 24%. It has been demonstrated that the plate compression filling method serves as a simple, convenient, and accurate alternative to the uniform compaction method, while the dielectric method is a reliable indicator for evaluating biomass degradation. This exploration provides valuable insights into the complex relationship between SWC, biomass degradation, and soil dielectric properties.

Dual-Frequency Soil Moisture Meter Method for Simultaneous Estimation of Soil Moisture and Conductivity.

The measurement of soil water content is a very important factor in plant cultivation, both from an economic and ecological point of view. Proper estimation of moisture content not only allows for proper yields but can also contribute to ecologically appropriate use of fresh water, of which the world's resources are limited. It is important, for example, that the moisture content in the root area of plants is optimal for their growth, while over-watering can result in losses in the form of water, which seeps below the root layer and is lost. The novel, inexpensive electronic meter for measuring soil moisture is presented in the article. The meter, based on a capacitive method, uses an optimization algorithm to calculate soil electrical permeability and a simplified new formula between soil electrical permeability and volumetric moisture content. Moreover, by using two high-frequency signals for measurements, it is possible not only to estimate moisture content but also soil conductivity. Both readings obtained from the meter not only allow for rational management of crop optimization for economic reasons but are also important for environmental protection. In addition, the inexpensive meter, based on the principle of operation presented, can be made as an IoT module, which allows for its wide application.

Evaluating the Efficiency of Field Oven for Quick Measurement of Gravimetric Soil Water Content

Evaluating the Efficiency of Field Oven for Quick Measurement of Gravimetric Soil Water Content

Combined 2D- and 3D ERT monitoring as a geophysical tool for investigating spatial and temporal soil moisture fluctuations in a pine-beech forest

As climate change continues, forests are increasingly suffering from drought stress, which is leading to widespread forest dieback, but also to increased mortality of individual trees. In this regard, the impact of small-scale differences in water availability on individual trees has not yet been sufficiently studied to determine possible responses of different tree species to future droughts. Since conventional soil moisture monitoring and sampling methods only consider single points or small volumes, Electrical Resistivity Tomography (ERT) is becoming increasingly important to cover a larger survey area and to detect small-scale heterogeneities with regard to soil properties and soil moisture.The current study describes the application of a combined two- and three-dimensional geoelectrical monitoring approach with daily measurements over two years (May 2021 – April 2023) in a forest ecosystem in Lower Franconia (northwestern Bavaria, Germany), which is strongly affected by climate change. Soil water content, soil matric potential, throughfall, and stem flow are also measured at the forest site as well as precipitation at an adjacent forest clearing.The seasonally (long-term) and precipitation-driven (short-term) temporal change of soil resistivity is correlated strongly with the measured soil water content and matric potential. The applied 3D-ERT approach also allowed a first three-dimensional monitoring of the subsurface below a European beech located in the middle of the measuring grid with a daily resolution. The corresponding results also provide first indications that besides soil moisture changes also chemical processes in the subsurface may influence temporal resistivity changes in the soil of forest sites.The results of this study show that daily 3D-ERT is very suitable for investigating small-scale as well as short- and long-term variations in soil moisture, which is becoming increasingly important for understanding the causal relationships considering tree mortality and the subsurface.

Recent Advances in Dielectric Properties-Based Soil Water Content Measurements

Dielectric properties are crucial in understanding the behavior of water within soil, particularly the soil water content (SWC), as they measure a material’s ability to store an electric charge and are influenced by water and other minerals in the soil. However, a comprehensive review paper is needed that synthesizes the latest developments in this field, identifies the key challenges and limitations, and outlines future research directions. In addition, various factors, such as soil salinity, temperature, texture, probing space, installation gap, density, clay content, sampling volume, and environmental factors, influence the measurement of the dielectric permittivity of the soil. Therefore, this review aims to address the research gap by critically analyzing the current state-of-the-art dielectric properties-based methods for SWC measurements. The motivation for this review is the increasing importance of precise SWC data for various applications such as agriculture, environmental monitoring, and hydrological studies. We examine time domain reflectometry (TDR), frequency domain reflectometry (FDR), ground-penetrating radar (GPR), remote sensing (RS), and capacitance, which are accurate and cost-effective, enabling real-time water resource management and soil health understanding through measuring the travel time of electromagnetic waves in soil and the reflection coefficient of these waves. SWC can be estimated using various approaches, such as TDR, FDR, GPR, and microwave-based techniques. These methods are made possible by increasing the dielectric permittivity and loss factor with SWC. The available dielectric properties are further synthesized on the basis of mathematical models relating apparent permittivity to water content, providing an updated understanding of their development, applications, and monitoring. It also analyzes recent mathematical calibration models, applications, algorithms, challenges, and trends in dielectric permittivity methods for estimating SWC. By consolidating recent advances and highlighting the remaining challenges, this review article aims to guide researchers and practitioners toward more effective strategies for SWC measurements.

Response of the TEROS 12 Soil Moisture Sensor under Different Soils and Variable Electrical Conductivity.

In this work, the performance of the TEROS 12 electromagnetic sensor, which measures volumetric soil water content (θ), bulk soil electrical conductivity (σb), and temperature, is examined for a number of different soils, different θ and different levels of the electrical conductivity of the soil solution (ECW) under laboratory conditions. For the above reason, a prototype device was developed including a low-cost microcontroller and suitable adaptation circuits for the aforementioned sensor. Six characteristic porous media were examined in a θ range from air drying to saturation, while four different solutions of increasing Electrical Conductivity (ECw) from 0.28 dS/m to approximately 10 dS/m were used in four of these porous media. It was found that TEROS 12 apparent dielectric permittivity (εa) readings were lower than that of Topp's permittivity-water content relationship, especially at higher soil water content values in the coarse porous bodies. The differences are observed in sand (S), sandy loam (SL) and loam (L), at this order. The results suggested that the relationship between experimentally measured soil water content (θm) and εa0.5 was strongly linear (0.869 < R2 < 0.989), but the linearity of the relation θm-εa0.5 decreases with the increase in bulk EC (σb) of the soil. The most accurate results were provided by the multipoint calibration method (CAL), as evaluated with the root mean square error (RMSE). Also, it was found that εa degrades substantially at values of σb less than 2.5 dS/m while εa returns to near 80 at higher values. Regarding the relation εa-σb, it seems that it is strongly linear and that its slope depends on the pore water electrical conductivity (σp) and the soil type.

Spatial and Temporal Distribution of Soil Moisture in Maize Using Frequency Domain Reflectometry Sensor

Field experiment was conducted during kharif 2018, rabi 2018-19 and kharif 2019 at Department of Soil Water Engineering, Dr. NTR College of Agricultural Engineering, Bapatla, Andhra Pradesh to study the spatial and temporal distribution of soil moisture in maize using FDR sensor.The experiment was laid out in split plot design consisting of three irrigation levels (0.6 ETc (I1), 0.8 ETc (I2) and 1.0 ETc (I3)) and four nitrogen levels consisting of fertigation levels (80% RDN (N1), 100% RDN (N2), 120% RDN (N3) and Manual application (N4) on sandy clay loam soil. Water requirement of the maize crop was calculated on the daily basis by using CROPWAT 8.0. Frequency Domain Reflectometry (FDR) Sensor was used to measure soil moisture data by installing 34 access tubes up to a depth of 100 cm with an interval of 10 cm from the soil surface and measured soil water content during crop period. Soil moisture was evaluated for 2.0 lph emitter discharges at 3h after irrigation, 6h after irrigation, 24h after irrigation at emitter, 15 cm from emitter, 30 cm from emitter and 45 cm from emitter for soil moisture in the soil for arriving the best irrigation strategy. The soil water distribution under all drip irrigation treatments indicated that it was relatively high near the dripper and decreased as the distance from the dripper point increased.

Effects of hillslope aspect on erosion rate of alpine meadows in the Three-River Headwater Region, China

Soil erosion causes serious grassland degradation in the Three-River Headwater Region (TRHR) of the Qinghai-Tibet Plateau. Identifying source areas of erosion is important, including understanding the influences of hillslope aspect on soil erosion. However, the effect of hillslope aspect on soil erosion is a much-debated process, wherein contrasting results were previously reported. We hypothesized that aspect-induced differences in environmental variables will be related to differences in erosion magnitude and spatial pattern, and that these differences will impact soil physiochemical characteristics as well. To test this hypothesis, soil samples were collected at conjoined south- and north-facing hillslopes along elevational profiles in a small watershed in Yushu County, with measurements of soil water content (SWC), soil organic carbon (SOC), soil organic matter (SOM), soil particle size distribution, soil total nitrogen (STN) and phosphorus (STP). Soil erosion rate was estimated using 137Cs technology. The results showed that soil erosion rates of the two hillslopes ranged from 0.073 to 10.83 t ha-1 yr-1, and were 3 times greater on the south-facing hillslope. Soil water content ranged from 7.6% to 76.8% on the two hillslopes with lower values on the south-facing hillslope due to the greater solar radiation. By Spearman correlation analysis and path analysis, we concluded that lower soil water content on the south-facing hillslope restricts vegetation growth, and hence resulting in greater soil erosion under the case where vegetation growth is dominantly controlled by water availability. Greater soil erosion on the south-facing hillslope caused greater surficial accumulation of coarser materials and greater loss of soil nutrients, which are expected to complicate the hydrological erosion process. Moreover, the downslope increased soil erosion rate should be fully considered in conservation practices. These results will improve our understanding of the interaction and feedback mechanisms between soil characteristics, vegetation function, and soil erosion in the TRHR.

Technical Note: Revisiting the general calibration of cosmic-ray neutron sensors to estimate soil water content

Abstract. Cosmic-ray neutron sensing (CRNS) is becoming increasingly popular for monitoring soil water content (SWC). To retrieve SWC from observed neutron intensities, local measurements of SWC are typically required to calibrate a location-specific parameter, N0, in the corresponding transfer function. In this study, we develop a generalized conversion function that explicitly takes into account the different factors that govern local neutron intensity. Thus, the parameter N0 becomes location independent, i.e. generally applicable. We demonstrate the feasibility of such a “general calibration function” by analysing 75 CRNS sites from four recently published datasets. Given the choice between the two calibration strategies – local or general – users will wonder which one is preferable. To answer this question, we estimated the resulting uncertainty in the SWC by means of error propagation. While the uncertainty in the local calibration depends on both the local reference SWC itself and its error, the uncertainty in the general calibration is mainly governed by the errors in vegetation biomass and soil bulk density. Our results suggest that a local calibration – generally considered best practice – might often not be the best option. In order to support the decision which calibration strategy – local or general – is actually preferable in the user-specific application context, we provide an interactive online tool that assesses the uncertainty in both options (https://cosmic-sense.github.io/local-or-global, last access: 23 February 2024).

Water Uptake Characteristics of Stipa bungeana Trin: Affected by Subsidence in the Coal Mining Areas of Northwest China

Revealing the water use pattern of plants influenced by coal-mining-caused land subsidence is crucial to understand plant–water interactions and guide ecological restoration. However, available information on herbaceous plants, the dominant species in most arid and semi-arid regions with abundant coal resources, remains inadequate. We investigated the water use patterns of Stipa bungeana Trin. by measuring soil water content, root distribution, and stable isotopes of hydrogen (δ2H) and oxygen (δ18O) of soil water and plant stem water both before and after a rainfall event. The results revealed that prior to rainfall, both areas exhibited a low soil water content with no discernible difference in soil drought. However, the soil waters δ2H and δ18O were found to be more enriched at varying depths within the subsidence area, indicating a heightened level of soil evaporation. Both soil water content and soil water isotopic composition responded sensitively to rainfall, with rainfall primarily replenishing the shallow layer (0–20 cm), thereby reflecting an infiltration mode dominated by piston flow. More water seeped into deeper soil layers in the subsidence area compared to the non-subsidence area, with more preferential flow. Before rainfall, the sources of plant water uptake were consistent both at shallow and deep soil layers, implying that the proportion of water uptake gradually decreased with increasing depth. After rainfall, the sources of plant water uptake differed slightly between the two soil layers. The plants in non-subsidence and subsidence areas dominantly extracted soil water at depths greater than 10 cm and 20 cm, respectively. The root system in the subsidence area was more developed than that in the non-subsidence area. Plant water uptake was primarily influenced by the spatial distribution of roots, as well as the post-rainfall water distribution, regardless of whether they were in the subsidence area or not. Although land subsidence affected soil water transport, the water uptake pattern of Stipa bungeana Trin. was similar before and after rainfall, indicating the adaptive growth of plants through their roots in the subsidence area. The high adaptability of herbs such as Stipa bungeana Trin. makes them a viable option for vegetation restoration in subsidence areas. This study has significant implications for evaluating plant–water relationships in subsidence areas due to coal mining, thereby providing a fundamental basis and valuable reference for ecological restoration and management strategies within such affected regions.

Assessing capacitance soil moisture sensor probes’ ability to sense nitrogen, phosphorus, and potassium using volumetric ion content

Accurate and near real-time volumetric soil water and volumetric ion content (VIC) measurements can both inform precise irrigation scheduling and aid in fertilizer management applications in cropping systems. To assist in the monitoring of these measurements, capacitance-based soil moisture probes are used in agricultural best management practice (BMP) programs. However, the ability of these sensors to detect nutrients in the soil sourced from fertilizers is not well understood. The objective of this study was to evaluate the sensitivity of a capacitance-based soil moisture probe in detecting Nitrogen (N), Phosphorous (P), and Potassium (K) movement in the soil. To achieve this, a laboratory-based setup was established using pure sand soil cores. Raw soil moisture and VIC probe readings from the cores were contrasted across multiple N, P, and K rates. The N treatments applied were rates of 0, 112, 168, and 224 kg/ha; for P, were 0, 3.76, and 37.6 kg/ha, and for K were 0, 1.02, 1.53, and 2.04 kg/ha. Each nutrient was evaluated separately using a randomized complete block design experiment with three replications for N and K, and 5 replications for P. The impact of each nutrient rate on the sensitivity of VIC readings was determined by evaluating differences in three points of the time series, including the observed maximum point, inflection point, and convergence value as well as the time of occurrence of those points over a 24-hour period. These points were assessed at depths 5, 15, 25, 35, 45, and 55 cm. The findings of this study highlight the capacitance-based soil moisture probes’ responsiveness to changes in all K rates at most depths. However, its sensitivity to changes in N and P rates is comparatively lower. The results obtained in this study can be used to develop fertilizer management protocols that utilize K movement as the baseline to indirectly assess N and P, while helping to inform those who currently use the probe which nutrients the probe may be detecting. The probes’ readings could be incorporated into decision support systems for irrigation and nutrient management and improve control systems for precision water and nutrient management.

SOIL PHYSICAL QUALITY INDICES OF MINING-INDUCED DISTURBANCES IN SOIL WITHIN THE LOESS REGION OF WESTERN CHINA

Soil sampling and in situ measurements were conducted at 24 locations at three time points from May 2015 to April 2016. The statistical analysis showed that the variabilities of soil water content and soil penetration were moderate, while particle size and soil saturated hydraulic conductivity varied considerably. Rainfall before measurements contributed positively to the mean soil water content and negatively to particle size. This was mainly due to the soil aggregates and large soil particles being broken into smaller particles from rain splash. The detached small-sized soil particles could coalesce into larger-sized ones and even soil aggregates. Stressors in zones differ, resulting in variations between soil physical quality indices. The point-to-point comparisons indicated that the mean measured soil water content and soil saturated hydraulic conductivity were similar, if the measurements for these two indices were conducted under similar weather conditions during the same period between years. The investigation on the relationships among soil physical quality indices showed a negative relationship between the measured soil water content and soil saturated hydraulic conductivity. A positive correlation was also found between soil particle size and soil saturated hydraulic conductivity. Lower soil strength resulted in higher soil saturated hydraulic conductivity.

A method for measuring soil water content based on principal component analysis.

Principal component analysis (PCA) has been applied in many aspects. To address the problem of measuring water content in soil, this paper proposes a method to measure soil water content based on the PCA. We used PCA to reduce the dimension of the data and processed the soil amplitude ratio frequency response spectra. First, we designed the measuring device and measured the soil amplitude ratio frequency response data of different water content, then we used the PCA to extract features from the frequency response spectra of different water contents, established a relationship model of soil water content, and finally, we solved the model, the maximum error between the calculation results and the actual water content was no more than 0.85%. Subsequently, we carried out experimental verification, and we measured six kinds of soil with known water content by this method. The experimental results showed that the maximum error did not exceed 1.16%, and the average error was 0.71%. Thus, the proposed method can provide a useful way of measuring soil water content.

Using phenology to unravel differential soil water use and productivity in a semiarid savanna

AbstractSavannas are water‐limited ecosystems characterized by two dominant plant types: trees and an understory primarily made up grass. Different phenology and root structures of these plant types complicate how savanna primary productivity responds to changes in water availability. We tested the hypothesis that productivity in savannas is controlled by the temporal and vertical distribution of soil water content (SWC) and differences in growing season length of understory and tree plant functional types. To quantify the relationship between tree, understory, and savanna‐wide phenology and productivity, we used PhenoCam and satellite observations surrounding an eddy covariance tower at a semiarid savanna site in Arizona, USA. We distinguished between SWC across two different depth intervals (shallow, &lt;0–30 cm and deep, &gt;30–100 cm). We found that tree greenness increased with SWC at both depths, while understory greenness was only sensitive to the shallower SWC measurements. Onset of ecosystem dormancy, estimated from satellite observations close to the eddy covariance tower, explained more variability in annual gross primary productivity (GPP) than in other phenometrics. Higher SWC led to an extended growing season, caused by delayed dormancy in trees, but the understory showed no evidence of delayed dormancy in wetter periods. We infer that the timing of ecosystem scale dormancy, driven by trees, is important in understanding changes in a savanna's GPP. These findings highlight the important effects of rainfall during the winter. These findings suggest that savanna GPP is conditional on different responses to moisture availability in each of the dominant vegetation components.

Evaluation of canopy fraction-based vegetation indices, derived from multispectral UAV imagery, to map water status variability in a commercial vineyard

AbstractWater stress is a major factor affecting grapevine yield and quality. Standard methods for measuring water stress, such as midday stem water potential (ΨSWP), are laborious and time-consuming for intra-block variability mapping. In this study, we investigate water status variability within a 2.42-ha commercial Cabernet Sauvignon block with a standard vertical trellis system, using remote sensing (RS) tools, specifically canopy fraction-based vegetation indices (VIs) derived from multispectral unmanned aerial vehicle (UAV) imagery, as well as standard reference methods to evaluate soil and plant water status. A total of 31 target vines were monitored for ΨSWP during the whole growing season. The highest variability was at véraison when the highest atmospheric demand occurred. The ΨSWP variability present in the block was contrasted with soil water content (SWC) measurements, showing similar patterns. With spatial and temporal water stress variability confirmed for the block, the relationship between the ΨSWP measured in the field and fraction-based VIs obtained from multispectral UAV data was analysed. Four UAV flights were obtained, and five different VIs were evaluated per target vine across the vineyard. The VI correlation to ΨSWP was further evaluated by comparing VI obtained from canopy fraction (VIcanopy) versus the mean (VImean). It was found that using canopy fraction-based VIs did not significantly improve the correlation with ΨSWP (NDVIcanopyr = 0.57 and NDVImeanr = 0.53), however fractional cover (fcover) did seem to show a similar trend to plant water stress with decreasing canopy size corresponding with water stress classes. A subset of 14 target vines were further evaluated to evaluate if additional parameters (maximum temperature, relative humidity (RH), vapour pressure deficit, SWC and fractional cover) could serve as potential water stress indicators for future mapping. Results showed that the integration of NDVIcanopy and NDREmean with additional information could be used as an indicator for mapping water stress variability within a block.