Electrical resistivity tomography for spatiotemporal variations of soil moisture in a precision irrigation experiment

Soil moisture temporal variations play a key role in the hydrological processes occurring in the unsaturated zone, which are critical for annual crop yields. The electrical resistivity tomography technique was applied in a field cultivated with cotton in northern Greece, thereby investigating its potential to serve as a reliable soil moisture-monitoring tool for precision irrigation in highly heterogeneous, clay-rich soils. Repeated surface resistivity measurements were made along two plant lines combined with soil water content measurements conducted with a reference gravimetric method and an electromagnetic sensor. Resistivity pseudo-sections were inverted to produce 2D resistivity models, and time-lapse inversion algorithms were also used, to better calculate the temporal changes in subsurface soil resistivity. The results showed clear spatial and temporal changes in resistivity transects in accordance with rainfall/irrigation and dry periods. The soil resistivity data exhibited a power model relationship with gravimetric soil moisture point measurements and a fair correlation with electromagnetic sensor profiles

Operational precise irrigation for cotton cultivation through the coupling of meteorological and crop growth models.

In this paper, we tested the operational capacity of an interoperable model coupling system for the irrigation scheduling (IMCIS) at an experimental cotton (Gossypium hirsutum L.) field in Northern Greece. IMCIS comprises a meteorological model (TAPM), downscaled at field level, and a water-driven cultivation tool (AquaCrop), to optimize irrigation and enhance crop growth and yield. Both models were evaluated through on-site observations of meteorological variables, soil moisture levels and canopy cover progress. Based on irrigation management (deficit, precise and farmer’s practice) and method (drip and sprinkler), the field was divided into six sub-plots. Prognostic meteorological model results exhibited satisfactory agreement in most parameters affecting ETo, simulating adequately the soil water balance. Precipitation events were fairly predicted, although rainfall depths needed further adjustment. Soil water content levels computed by the crop growth model followed the trend of soil humidity measurements, while the canopy cover patterns and the seed cotton yield were well predicted, especially at the drip irrigated plots. Overall, the system exhibited robustness and good predicting ability for crop water needs, based on local evapotranspiration forecasts and crop phenological stages. The comparison of yield and irrigation levels at all sub-plots revealed that drip irrigation under IMCIS guidance could achieve the same yield levels as traditional farmer’s practice, utilizing approximately 32% less water, thus raising water productivity up to 0.96 kg/m3.N/