Modelling Soil Water Content in a Tomato Field: Proximal Gamma Ray Spectroscopy and Soil–Crop System Models (original) (raw)
Related papers
2018
Proximal gamma-ray spectroscopy recently emerged as a promising technique for non-stop monitoring of soil water content with possible applications in the field of precision farming. The potentialities of the method are investigated by means of Monte Carlo simulations applied to the reconstruction of gamma-ray spectra collected by a NaI scintillation detector permanently installed at an agricultural experimental site. A two steps simulation strategy based on a geometrical translational invariance is developed. The strengths of this approach are the reduction of computational time with respect to a direct source-detector simulation, the reconstruction of 40 K, 232 Th and 238 U fundamental spectra, the customization in relation to different experimental scenarios and the investigation of effects due to individual variables for sensitivity studies. The reliability of the simulation is effectively validated against an experimental measurement with known soil water content and radionuclides abundances. The relation between soil water content and gamma signal is theoretically derived and applied to a Monte Carlo synthetic calibration performed with the specific soil composition of the experimental site. Ready to use general formulae and simulated coefficients for the estimation of soil water content are also provided adopting standard soil compositions. Linear regressions between input and output soil water contents, inferred from simulated 40 K and 208 Tl gamma signals, provide excellent results demonstrating the capability of the proposed method in estimating soil water content with an average uncertainty < 1%.
Biomass water content effect on soil moisture assessment via proximal gamma-ray spectroscopy
Geoderma, 2019
Proximal gamma-ray spectroscopy supported by adequate calibration and correction for growing biomass is an effective field scale technique for a continuous monitoring of top soil water content dynamics to be potentially employed as a decision support tool for automatic irrigation scheduling. This study demonstrates that this approach has the potential to be one of the best space–time trade-off methods, representing a joining link between punctual and satellite fields of view. The inverse proportionality between soil moisture and gamma signal is theoretically derived taking into account a non-constant correction due to the presence of growing vegetation beneath the detector position. The gamma signal attenuation due to biomass is modelled with a Monte Carlo-based approach in terms of an equivalent water layer which thickness varies in time as the crop evolves during its life-cycle. The reliability and effectiveness of this approach is proved through a 7 months continuous acquisition of terrestrial gamma radiation in a 0.4 ha tomato (Solanum lycopersicum) test field. We demonstrate that a permanent gamma station installed at an agricultural field can reliably probe the water content of the top soil only if systematic effects due to the biomass shielding are properly accounted for. Biomass corrected experimental values of soil water content inferred from radiometric measurements are compared with gravimetric data acquired under different soil moisture levels, resulting in an average percentage relative discrepancy of about 3\% in bare soil condition and of 4\% during the vegetated period. The temporal evolution of corrected soil water content values exhibits a dynamic range coherent with the soil hydraulic properties in terms of wilting point, field capacity and saturation.
Agricultural Water Management, 2019
Accurate knowledge of soil hydraulic properties (K-θ-h) for the entire range of crop available water is essential for the prediction of soil water movement and related processes by mechanistic models, including the partitioning of surface energy fluxes into transpiration and evaporation and the dynamics of root water uptake, mandatory processes for adjustments of crop water use efficiency. We implemented an experimental and numerical protocol to obtain K-θ-h of eleven soils with a broad spectrum of texture and land use. Measurements of the soil water content during evaporation experiments using gamma-ray beam attenuation, a non-invasive technique, were adopted as an alternative approach to conventional measurements of the soil water pressure head. Inverse parameter optimization was performed using Hydrus-1D. The optimized K-θ-h functions were interpreted with respect to crop available water, where results calculated by a proposed "dynamic" method were compared with those determined using the conventional "static" criteria with standardized pressure heads. The evaporation experiment protocol allowed the determination of the K-θ-h relationships by inverse modeling from near-saturation to the dry range (∼ −150 m) with satisfactory accuracy. Soil water retention curves of the finetextured soils determined by the conventional method (pressure plates) deviated from those estimated by the inverse optimization near saturation and in the dry range, with the conventional method predicting larger water content values. In terms of crop available water, the "dynamic" method allowed incorporating system characteristics (atmospheric demand and crop properties) and K-θ-h in a process-based way, contrarily to the "static" method. Considering a specific scenario, for the fine-textured soils the "static" and "dynamic" approaches performed similarly, however, for the coarse-textured soils, they diverged significantly. No tendency could be revealed for crop water availability under different land uses, and, in general, crop available water for soils under forest use was very similar to their counterparts under agricultural use.
Advances in Water Resources, 2019
The global warming effects put in danger global water availability and make necessary todecrease water wastage, e.g., by monitoring global irrigation. Despite this, global irrigation information is scarce due to the absence of a solid estimation technique. In this study, we applied an innovative approach to retrieve irrigation water from high spatial and temporal resolution Soil Moisture (SM) data obtained from an advanced sensor based on Proximal Gamma-Ray (PGR) spectroscopy, in a field located in Emilia Romagna (Italy). The results show that SM is a key variable to obtain information about the amount of water applied to plants, with Pearson correlation between observed and estimated daily irrigation data ranges from 0.88 to 0.91 by using different calibration methodology. With the aim of reproducing the working conditions of satellites measuring soil moisture, we sub-sampled SM hourly time series at larger time steps. The results demonstrated that the methodology is still capable to perform the daily (weekly) irrigation estimation with Pearson Correlation around 0.6 (0.7) if the time step is not greater than 36 (48) hours.