Assessment of a calibration procedure to estimate soil water content with Sentek Diviner 2000 capacitance probe

In irrigated systems, soil water content is a major factor determining plant growth. Irrigation scheduling criteria are often related to measurements of soil water content or matric potential. Strategies to manage irrigation can be used to optimize irrigation water use or to maximize crop yield and/or quality, in order to increase the net return for the farmer. Of course, whatever criterion is adopted to schedule irrigation and in particular when crop water stress conditions are considered, the accurate monitoring of the water content in the soil profile, could allow to verify the exact irrigation timing, defined according to the crop response to water stress. Currently many methods are available for determining soil water content on a volume basis (m3m-3) or a tension basis (MPa), as described by Robinson (2008). Recently, distributed fiber optic temperature measurement, has been assessed as a new technique for indirect and precise estimation of soil water contents. Over the past decade Frequency Domain Reflectometry (FDR) probes, allowing to measure the apparent dielectric constant of the soil (K), indirectly related to the volumetric water content (θv), have been improved, due to the good potentiality of capacitance based sensors to in situ measurements of soil water content. However, due to the high variability of K with soil minerals and dry plants tissues, it necessary to proceed to a specific calibration of the sensor for each soil (Baumhardt et al., 2000), even to take into account the effect of soil temperature, bulk density and water salinity (Al Ain et al., 2009). . According to Paltineanu and Starr (1997), the precision of the calibration equation, obtained with in situ measurements, mainly depends on the errors related to the sampling of the soil volume investigated by the sensor, that must be done accurately. For swelling/shrinking soils, the changes of soil bulk volume with water content cause modifications in the geometry of some if not all the soil pores, affecting the bulk density/water content relationship (Allbrook, 1992). Field experiments in shrinking-swelling clay soils evidenced that soil water content can be affect by errors of 20-30% if the soil shrinkage curve is not considered (Fares et al., 2004). The main objective of the paper was to propose a practical calibration procedure for FDR sensor using minilysimeter containing undisturbed soil, allowing to take in to account the possible variations of the bulk density with the soil water content. Moreover, the possibility of using disturbed soil samples for determining the sensor calibration curve was also investigated, in order to simplify the proposed methodology. Experiments were carried out on three different soil, two of which containing a percentage of clay higher than 40%, in order to compare the specific calibration curves with that suggested by the manufactures. The investigation showed how for swelling/shrinkage soils it is necessary the knowledge of the actual soil bulk density and also that using disturbed soil sample is not possible to consider the effects of the soil shrinkage consequent to the soil water content reductions

Discussion of “Laboratory and field calibration of the Diviner 2000 probe in two types of soil” by J. Haberland, PhD, R. Galvez, C. Kremer, PhD, and C. Carter.

The authors deal with the quite interesting and actual problem of Diviner 2000 capacitance probe calibration and present some field and laboratory data obtained on two different layers (0-0.26 cm and 0.26-0.50 cm) of the same soil profile, characterized by different textural class. The importance of site-specific calibration of sensors used to monitor soil or plant water status assumes a particular relevance in semi-arid environments where the application of precision irrigation represents an appropriate management strategy aimed to achieve high values of water use efficiency (Cammalleri et al., 2013). Moreover in clay soils, physical properties are strongly influenced by soil water content (Provenzano et al., 2013), so that the correct measurement of this variable plays a key role to increasing crop yield and preserving water. However, these discussers would focus on some significant points to be corrected in the manuscript and some others that AA. should have been specified in the methodology and considered in the final discussion, as following specified, for the benefit of potential readers. The need to install adequately the access tube, aimed to ensure the contact between the tube and the surrounding soil, is not only to avoid preferential flow of water down the walls of the tube, as considered in the paper, but also to reduce air gap around the tube and to avoid rough measurements of scaled frequency, used to estimate soil water contents, whose values depend on the mutual proportion of soil, water and air in the soil volume investigated by the sensor. With reference to the second part of eq. (2) it is necessary to precise that the function w(SF) correctly results

Farm scale application of EMI and FDR sensors to measuring and mapping soil water content

Soil water content (SWC) controls most water exchange processes within and between the soil-plants-atmosphere continuum and can therefore be considered as a practical variable for irrigation farmer choices. A better knowledge of spatial SWC patterns could improve farmer’s awareness about critical crop water status conditions and enhance their capacity to characterize their behavior at the field or farm scale. However, accurate soil moisture measurement across spatial and temporal scales is still a challenging task and, specifically at intermediate spatial (0.1–100 ha) and temporal (minutes to days) scales, a data gap remains that limits our understanding over reliability of the SWC spatial measurements and its practical applicability in irrigation scheduling. In this work we compare the integrated EM38 (Geonics Ltd. Canada) response, collected at different sensor positions above ground to that obtained by integrating the depth profile of volumetric SWC measured with Diviner 2000 (Sentek) in conjunction with the depth response function of the EM38 when operated in both horizontal and vertical dipole configurations. On a 1.0-ha Olive grove site in Sicliy (Italy), 200 data points were collected before and after irrigation or precipitation events following a systematic sampling grid with focused measurements around the tree. Inside two different zone of the field, characterized from different soil physical properties, two Diviner 2000 access tube (1.2 m) were installed and used for the EM38 calibration. After calibration, the work aimed to propose the combined use of the FDR and EMI sensors to measuring and mapping root zone soil water content. We found strong correlations (R2 = 0.66) between Diviner 2000 SWC averaged to a depth of 1.2 m and ECa from an EM38 held in the vertical mode above the soil surface. The site-specific relationship between FDR-based SWC and ECa was linear for the purposes of estimating SWC over the explored range of ECa monitored at field levels. Volumetric SWC changes in the root zone were observed by differencing the maps, where differences in the observed ECa are primarily the result of changes in soil water status. As with the data showed in the research, more structured patterns occur after wetting event, indicating the presence of subsurface flow or root water uptake paths. A vision for the future at hydrological watershed scale is to combine EMI measurements with FDR-based sensor networks, the last with the scope to constrain calibration of the EMI measurements

Evaluating the performance of reference evapotranspiration equations with scintillometer measurements under Mediterranean climate and effects on olive grove actual evapotranspiration estimated with FAO-56 water balance model

The concept of reference potranspiration is widely used to support water resource management in agriculture and for irrigation scheduling, especially under arid and semi-arid conditions. The Penman-Monteith standardized formulations, as suggested by ASCE and FAO-56 papers, are generally applied for accurate estimations of ETo, at hourly and daily scale. When detailed meteorological information are not available, several alternative and simplified equations, using a limited number of variables, have been proposed (Blaney-Criddle, HargreavesSamani, Turc, Makkinen and Pristley-Taylor). In this paper, scintillometer measurements collected for six month in 2005, on an experimental plot under “reference” conditions, were used to validate different ETo equations at hourly and daily scale. Experimental plot is located in a typical agricultural Mediterranean environment (Sicily, Italy), where olive groves is the dominant crop. As proved by other researches, the comparison confirmed the best agreement between estimated and measured fluxes corresponds to FAO-56 Penman-Monteith standardized equation, that was characterized by both the lowest average error and the minimum bias. However, the analysis also evidenced a quite good performance of Pristley-Taylor equation, that can be considered as a valid alternative to the more sophisticated PenmanMonteith method. The different ETo series, obtained by the considered simplified equations, were then used as input in the FAO-56 water balance model, in order to evaluate, for olive groves, the errors on estimated actual evapotranspiration ET. To this aim soil and crop model input parameters were settled by considering previous experimental researches already used to calibrate and validate the FAO-56 water balance model on olive groves, for the same study area. Also in this case, assuming as the true values of ET those obtained using the water balance coupled with Penman- Monteith ETo input values, the Priestley-Taylor equation, requiring a limited number of input meteorological data, was characterized by the best performance if compared to the other equations used to evaluate ETo. Under environments conditions similar to those considered therefore, according to the good performance associated to the Priestley-Tailor approach, FAO-56 model can allow realistic estimation of ET, even in absence of a full meteorological dataset

Adapting FAO-56 Spreadsheet Program to estimate olive orchard transpiration fluxes under soil water stress condition

In the Mediterranean environment, where the period of crops growth does not coincide with the rainy season, the crop is subject to water stress periods that may be amplified with improper irrigation management. Agro-hydrological models can be considered an economic and simple tool to optimize irrigation water use, mainly when water represents a limiting factor for crop production. In the last two decades, agro-hydrological physically based models have been developed to simulate mass and energy exchange processes in the soil-plant-atmosphere system (Feddes et al., 1978; Bastiaanssen et al., 2007). Unfortunately these models, although very reliable, as a consequence of the high number of required variables and the complex computational analysis, cannot often be used. Therefore, simplified agro-hydrological models may represent an useful and simple tool for practical irrigation scheduling. The main objective of the work is to assess, for an olive orchard, the suitability of FAO-56 spreadsheet agrohydrological model to estimate a long time series of field transpiration, soil water content and crop water stress dynamic. A modification of the spreadsheet is suggested in order to adapt the simulations to a crop tolerant to water stress. In particular, by implementing a new crop water stress function, actual transpiration fluxes and an ecophysiological stress indicator, i. e. the relative transpiration, are computed in order to evaluate a plant-based irrigation scheduling parameter. Validation of the proposed amendment is carried out by means of measured sap fluxes, measured on different plants and up-scaled to plot level. Spatial and temporal variability of soil water contents in the plot was measured, at several depths, using the Diviner 2000 capacitance probe (Sentek Environmental Technologies, 2000) and TDR-100 (Campbell scientific, Inc.) system. The detailed measurements of soil water content, allowed to explore the high spatial variability of soil water content due to the combined effect of the punctual irrigation and the non-uniform root density distribution. A further validation of the plant-based irrigation-timing indicator will be carried out by considering another ecophysiological stress variable like the predawn leaf water potential. Accuracy of the model output was assessed using the Mean Absolute Difference, the Root Mean Square Difference and the efficiency index of Nash and Sutcliffe. Experimental data, recorded during three years of field observation, allowed, with a great level of detail, to investigate on the dynamic of water fluxes from the soil to atmosphere as well as to validate the proposed amendment of the FAO-56 spreadsheet. The modified model simulated with a satisfactory approximation the measured values of average soil water content in the root zone, with error of estimation equal to about 2.0%. These differences can be considered acceptable for practical applications taking into account the intrinsic variability of the data especially in the soil moisture point measurements. An error less than 1 mm was calculated in the daily transpiration estimation. A good performance was observed in the estimation of the cumulate transpiration fluxes

Combining the FAO56 agrohydrological model and remote sensing data to assess water demand in a Sicilian irrigation district

Agricultural water use in irrigated areas plays a key role in the Mediterranean regions characterized by semi-arid climate and water shortage. In the face of optimizing irrigation water use, farmers must revise their irrigation practices to increase the drought resilience of agricultural systems and to avoid severe damages in agro-ecosystems. In this direction, during the last decades, the research has been focused on mathematical models to simulate the process of driving mass transport and energy exchanges in the Soil-Plant-Atmosphere system. The objective of the paper was to test the suitability of the combination of FAO56 agrohydrological model with remote sensing data retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) platform, to assess the spatiotemporal distributions of crop water requirement and to schedule irrigation in an irrigation district of the south-west of Sicily, Italy. The proposed approach allowed obtaining the spatiotemporal distributions of soil and crop parameters used in the FAO56 model implemented in a GIS environment to simulate the water balance, as well as to assess the actual irrigation strategy. The GIS database was organized to include soil and crop parameters, as well as the irrigation volumes actually delivered to each farmer; the latter data can be used not only as input for water balance to evaluate the efficiency of the actual irrigation strategies but also to identify different irrigation scheduling scenario obtained by the FAO56 procedure. The first application was carried out for the period 2014-2017, to identify a combination of irrigation scheduling parameters to be implemented in the model aimed at reproducing the ordinary strategy adopted by the farmers, based on the spatiotemporal variability of soil and climate forcings. When the model outputs were aggregated for single crop types, a fairly good agreement was found between simulated and actual seasonal irrigation volumes delivered either at the level of district and secondary units. Alternative scenarios of irrigation water distribution were then identified and analyzed, to provide irrigation technicians and policymakers a decision support tool to improve the efficiency of irrigation systems and to optimize the distribution based on the availability of water resources

Pre-stack full waveform inversion of ultra-high-frequency marine seismic reflection data

The full waveform inversion (FWI) of seismic reflection data aims to reconstruct a detailed physical properties model of the subsurface, fitting both the amplitude and the traveltime of the reflections generated at physical discontinuities in the propagation medium. Unlike reservoir-scale seismic exploration, where seismic inversion is a widely adopted remote characterization tool, ultrahigh-frequency (UHF, 0.2–4.0 kHz) multichannel marine reflection seismology is still most often limited to a qualitative interpretation of the reflections’ architecture. Here we propose an elastic FWI methodology, custom-tailored for pre-stack UHF marine data in vertically heterogeneous media to obtain a decimetric-scale distribution of P-impedance, density and Poisson’s ratio within the shallow subseabed sediments. We address the deterministic multiparameter inversion in a sequential fashion. The complex trace instantaneous phase is first inverted for the P-wave velocity to make up for the lack of low frequency in the data and reduce the nonlinearity of the problem. This is followed by a short-offset P-impedance optimization and a further step of full offset range Poisson’s ratio inversion. Provided that the seismogram contains wide reflection angles (>40°), we show that it is possible to invert for density and decompose a posteriori the relative contribution of P-wave velocity and density to the P-impedance. A broad range of synthetic tests is used to prove the potential of the methodology and highlights sensitivity issues specific to UHF seismic. An example application to real data is also presented. In the real case, trace normalization is applied to minimize the systematic error deriving from an inaccurate source wavelet estimation. The inverted model for the top 15 m of the subseabed agrees with the local lithological information and core-log data. Thus, we can obtain a detailed remote characterization of the shallow sediments using a multichannel sub-bottom profiler within a reasonable computing cost and with minimal pre-processing. This has the potential to reduce the need of extensive geotechnical coring campaigns

Experimental and numerical investigation of flow control on bluff bodies by passive ventilation

In this work, the so-called natural or passive ventilation drag reduction method is investigated experimentally and numerically. Passive ventilation is performed by directly connecting the high pressure region at the front of a body to the lower pressure in the near wake using a venting duct; in this manner, a net mass flux is established within the wake. In particular, in aerodynamic applications it appears suitable to attain a global reduction in the drag of a body moving in a fluid and a reduction in turbulence levels by means of a global modification of the body wake. Velocity field investigations using particle image velocimetry measurements and a Reynolds averaged numerical code are employed at moderately high Reynolds numbers to clarify the effectiveness of drag reduction on a vented bluff body. The numerical and experimental results agree qualitatively, but the amount of reduction for the vented body (about 10%) is underestimated numerically. The effectiveness of drag reduction has been proved both for smooth and rough (single strip) models. Direct balance measurements are used for comparisons

Assessing the performance of the Gaussian Process Regression algorithm to fill gaps in the time-series of daily actual evapotranspiration of different crops in temperate and continental zones using ground and remotely sensed data

The knowledge of crop evapotranspiration is crucial for several hydrological processes, including those related to the management of agricultural water sources. In particular, the estimations of actual evapotranspiration fluxes within fields are essential to managing irrigation strategies to save water and preserve water resources. Among the indirect methods to estimate actual evapotranspiration, ETa, the eddy covariance (EC) method allows to acquire continuous measurement of latent heat flux (LE). However, the time series of EC measurements are sometimes characterized by a lack of data due to the sensors' malfunctions. At this aim, Machine Learning (ML) techniques could represent a powerful tool to fill possible gaps in the time series. In this paper, the ML technique was applied using the Gaussian Process Regression (GPR) algorithm to fill gaps in daily actual evapotranspiration. The technique was tested in six different plots, two in Italy, three in the United States of America, and one in Canada, with different crops and climatic conditions in order to consider the suitability of the ML model in various contexts. For each site, the climate variables were not the same, therefore, the performance of the method was investigated on the basis of the available information. Initially, a comparison of ground and reanalysis data, where both databases were available, and between two different satellite products, when both databases were available, have been conducted. Then, the GPR model was tested. The mean and the covariance functions were set by considering a database of climate variables, soil water status measurements, and remotely sensed vegetation indices. Then, five different combinations of variables were analyzed to verify the suitability of the ML approach when limited input data are available or when the weather variables are replaced with reanalysis data. Cross-validation was used to assess the performance of the procedure. The model performances were assessed based on the statistical indicators: Root Mean Square Error (RMSE), coefficient of determination (R2), Mean Absolute Error (MAE), regression coefficient (b), and Nash-Sutcliffe efficiency coefficient (NSE). The quite high Nash Sutcliffe Efficiency (NSE) coefficient, and the root mean square error (RMSE) low values confirm the suitability of the proposed algorithm