A recent study has proposed and tested a semi-empirical method to estimate crop irrigation based on a water balance logic and Sentinel-2 Multi Spectral Instrument (MSI) NDVI imagery. The current ...paper aims at extending the same approach to the analysis of the main irrigation patterns occurred in Tuscany (Central Italy) during the 2000-2019 period. This operation was made possible by feeding the irrigation water (IW) estimation method with 250-m spatial resolution Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI images. The results of this operation were first assessed versus various reference datasets available for the region; next, the annual maps of IW estimated for the 20 study years were analyzed at province scale in conjunction with relevant agricultural statistics. The use of MODIS in place of MSI images reduces the IW estimation accuracy irregularly at local scale, depending on the size and spatial arrangement of irrigated and non-irrigated fields; the reduction in accuracy is, however, marginal over relatively large areas. Irrigated crops are decreasing throughout most Tuscany provinces, while they are increasing in the most southern and driest province. The possible reasons and implications of these findings are finally discussed in relation to the main environmental issues affecting the region.
Aridity and drought, which are determined by climatic and temporary water scarcity, respectively, are important limiting factors for plant gross primary production. These phenomena are commonly ...assessed and/or monitored by means of weather indices, most of which are based on observations of precipitation and potential evapotranspiration. The estimation of such indices over large areas can be carried out using multiple datasets, i.e., those derived from weather stations, satellite images, and ground radars. The possibility of using interpolated or remotely sensed datasets in place of ground measurements was currently investigated for Tuscany, a region in Central Italy, showing complex and heterogeneous environmental features. The former weather datasets were first evaluated versus corresponding ground measurements. Next, the basic weather variables were combined and cumulated over 30–60 days to yield synthetic indicators of water deficit, which were assessed in the same way. Finally, these indicators were evaluated to predict the soil water conditions of a meadow and an olive grove during the 2021 summer period. The results obtained indicate that the use of the multi-source weather datasets induces only a minor deterioration of the water stress indicators and is therefore efficient to monitor the water status of different ecosystems with high spatial (200 m) and temporal (daily) details.
Crop irrigation uses more than 70% of the world's water, and thus, improving irrigation efficiency is decisive to sustain the food demand from a fast-growing world population. This objective may be ...accomplished by cultivating more water-efficient crop species and/or through the application of efficient irrigation systems, which includes the implementation of a suitable method for precise scheduling. At the farm level, irrigation is generally scheduled based on the grower's experience or on the determination of soil water balance (weather-based method). An alternative approach entails the measurement of soil water status. Expensive and sophisticated root zone sensors (RZS), such as neutron probes, are available for the use of soil and plant scientists, while cheap and practical devices are needed for irrigation management in commercial crops. The paper illustrates the main features of RZS' (for both soil moisture and salinity) marketed for the irrigation industry and discusses how such sensors may be integrated in a wireless network for computer-controlled irrigation and used for innovative irrigation strategies, such as deficit or dual-water irrigation. The paper also consider the main results of recent or current research works conducted by the authors in Tuscany (Italy) on the irrigation management of container-grown ornamental plants, which is an important agricultural sector in Italy.
Relative soil water content (RSWC) is widely used to characterize the impact of water stress (WS) on vegetation. In bi-layer ecosystems, such as olive groves, this impact must be primarily estimated ...for the tree component, which, having greater rooting depth, responds more slowly to WS than understory grass. This complicates the application of methods for RSWC prediction, which must be properly adapted to consider the deeper soil layer influential on olive trees. The current study investigates the modification of a recently proposed RSWC simulation method based on a combination of meteorological and satellite-derived normalized difference vegetation index (NDVI) data. The application of the method to an olive grove in Central Italy requires the estimation of both weather and NDVI contributions affecting solely olive trees, which is carried out through the use of appropriate data processing techniques. The RSWC estimates obtained reasonably reproduce the ground RSWC observations referred to the 1 m soil layer, which are representative of the WS affecting olive trees (r
2
= 0.795, RMSE = 0.15 and MBE = −0.09). The limits and prospects of this method are finally discussed with particular reference to the possible integration of the RSWC estimates within more complex ecosystem models.
Recent studies have demonstrated that the soil water content (SWC) of Mediterranean ecosystems can be simulated by combining ground data and remote sensing observations of Normalized Difference ...Vegetation Index (NDVI). The application of this approach in heterogeneous and fragmented areas, however, requires the use of spatio-temporal fusion (STF) methods to properly account for the actual NDVI variability of the examined ecosystems. One of these methods, which was specifically developed to produce annual NDVI data series in Mediterranean regions, is currently applied to MODIS and TM/ETM+ images taken over a highly fragmented green urban area in Florence (Central Italy). The performances of this STF method, called SEVIS, are indirectly evaluated by comparing local SWC measurements to simulations driven by the original (MODIS) and fused (MODIS+TM/ETM+) NDVI datasets. The results obtained confirm the critical dependence of the applied SWC simulation strategy on the efficient accounting for the actual NDVI evolution of the observed ecosystem. In particular, the use of the fused NDVI dataset corrects almost completely for the strong SWC underestimation produced by the original MODIS images during the summer dry period, significantly improving all accuracy statistics (r
2
from 0.564 to 0.855, RMSE from 0.101 to 0.044 cm
3
cm
−3
and MBE from −0.046 to 0.000 cm
3
cm
−3
).
The estimation of site water budget is important in Mediterranean areas, where it represents a crucial factor affecting the quantity and quality of traditional crop production. This is particularly ...the case for spatially fragmented, multi-layer agricultural ecosystems such as olive groves, which are traditional cultivations of the Mediterranean basin. The current paper aims at demonstrating the effectiveness of spatialized meteorological data and remote sensing techniques to estimate the actual evapotranspiration (ETA) and the soil water content (SWC) of an olive orchard in Central Italy. The relatively small size of this orchard (about 0.1 ha) and its two-layer structure (i.e., olive trees and grasses) require the integration of remotely sensed data with different spatial and temporal resolutions (Terra-MODIS, Landsat 8-OLI and Ikonos). These data are used to drive a recently proposed water balance method (NDVI-Cws) and predict ETA and then site SWC, which are assessed through comparison with sap flow and soil wetness measurements taken in 2013. The results obtained indicate the importance of integrating satellite imageries having different spatio-temporal properties in order to properly characterize the examined olive orchard. More generally, the experimental evidences support the possibility of using widely available remotely sensed and ancillary datasets for the operational estimation of ETA and SWC in olive tree cultivation systems.
Actual evapotranspiration (ETA) is a major term of site water balance whose knowledge is essential for numerous purposes. The classical ETA estimation approach based on the use of multitemporal crop ...coefficients (Kc) cannot be applied in water-limited environments without proper correction. Such correction can be theoretically obtained by means of soil water content (SWC) measurements, which, however, are affected by several drawbacks, due to both their technical and operational characteristics. The current paper proposes a method to normalize annual SWC datasets and integrate them in an ETA estimation procedure suitable for monitoring both agricultural and natural Mediterranean ecosystems. Differently from previous approaches, the SWC normalization is obtained using data-specific information, which renders the new method mostly insensitive to the mentioned problems. The method is first described and then applied in three case studies representative of different Mediterranean ecosystems (i.e., grassland, coniferous, and deciduous forests). The results are evaluated versus latent heat measurements taken by eddy covariance flux towers. Satisfactory accuracy is obtained in all three case studies, with advantages and limitations which are discussed in the final concluding sections.
Crop irrigation should be properly monitored to plan the use of land water resources and their repartition among competing activities. Appropriate statistical approaches can be applied to infer the ...irrigation water (IW) supplied over a cropped area relying on ground observations and the outputs of calibrated crop development models. The collection of such reference samples over relatively large areas and multiyear periods, however, is often hampered by practical problems that limit the possibility of obtaining precise estimates of the IW actually supplied. One of the possible ways to overcome these issues and increase the precision of the IW observations is through a regression correction versus wall-to-wall IW covariates obtained from remotely sensed images. Specifically, the correction of the reference IW observations can be performed using mapped IW estimates yielded by the combination of meteorological data and Sentinel-2 NDVI images. This strategy was tested in a 10 × 10 km
2
agricultural area in Southern Tuscany (Central Italy) during 2018–2022. The high correlations found between the reference and remotely sensed IW values allowed us to obtain satisfactory results for all years. The regression corrections applied had very high relative efficiencies (> 30) and notably enhanced the IW precisions obtained from the reference samples. The dynamics of the corrected IW observations were finally analysed versus the possible drivers, yielding useful indications for the management of local water resources.
•An operational method is presented to predict relative soil water content (RSWC).•The method works without requiring specific information on soil features.•Tests are made versus continuous and ...spatially distributed SWC measurements.•The RSWC estimates obtained are similar to those of a simplified soil water balance.
Recent investigations have supported the possibility of predicting soil water content (SWC) through a simplified soil water balance (WB) model fed with remotely sensed actual evapotranspiration (ETa) estimates. This approach, however, requires information on main soil features (i.e. depth, wilting point, field capacity) which are generally difficult to retrieve over large regions. The current paper proposes an alternative model which directly predicts SWC relying on the same logic of the recently proposed ETa estimation method, i.e. the combination of meteorological and normalized difference vegetation index (NDVI) datasets. The theoretical bases of the old and new SWC estimation methods are first described. Both methods are then applied in Central Italy using ancillary and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data having a spatial resolution of 250 m; the outputs obtained are assessed versus SWC measurements taken both continuously and instantaneously. In the former case three ecosystems are analyzed (i.e. the grassland of Amplero and the forests of Barbialla and Amiata), where SWC was measured by probes during three different years (2003, 2012 and 2018, respectively). The latter experiment concerns 362 sample sites where SWC gravimetric measurements were taken during a similar time span (2000–2018). In both cases SWC is first normalized into relative SWC (RSWC), which is more directly influential on vegetation conditions. The results of both experiments indicate that the two simulation methods perform similarly when the former is driven by adequate information on soil features. The main limitations of the two simulation approaches are due to the spatial resolution mismatch between SWC measurements and estimates, which has a relatively minor impact on the first three homogeneous areas but is decisive for the other sampled sites. In general, the new simulation method is capable of predicting RSWC with relatively high spatial and temporal resolution without the use of specific soil information.
Conventional meteorological data and remotely sensed Normalized Difference Vegetation Index (NDVI) images can be proficiently combined to predict actual evapotranspiration (ET
A
) on different ...spatial and temporal scales. Up to now, however, the operational application of this approach in heterogeneous Mediterranean regions has found difficulty due to the insufficient spatial resolution of satellite sensors having high acquisition frequency (i.e. 250 m of Terra/Aqua Moderate Resolution Imaging Spectroradiometer, MODIS). The current study investigates the advantages brought for this objective by the recent availability of NDVI data taken from the Sentinel-2 MultiSpectral Instrument (MSI), which has a spatial resolution of 10 m. The investigation has been performed in two Mediterranean areas characterized by different spatio-temporal variability of vegetation cover. The first is a mountain coniferous forest, where such variability is low, while the second is a relatively small (around 10 ha) irrigated tomato field surrounded by other annual crops showing diversified growing cycles. An ET
A
estimation method based on NDVI data is applied in the two study areas and its performances are evaluated against ground references obtained through the elaboration of site measurements (i.e. meteorological, soil water content, and crop coefficient observations). The advantage of using MSI over MODIS NDVI images is marginal in the first case study, while is evident in the second. More particularly, such advantage is outstanding when the remote sensing method is applied in an operational mode, i.e. without using the information on the water supplied to the tomato crop by irrigation. This confirms that the utility of higher spatial resolution data is dependent not only on the fragmentation of the observed landscapes but also on the synchronicity of major vegetation growing cycles, which is influenced by both environmental and human-induced factors.
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