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Crop water requirements and crop coefficients for jute mallow (Corchorus olitorius L.) using the SIMDualKc model and assessing irrigation strategies for the Syrian Akkar region
Publication . Darouich, Hanaa; Karfoul, Razan; Ramos, Tiago B.; Moustafa, Ali; Shaheen, Baraa; Pereira, L.S.
Jute mallow (Corchorus olitorius L.) is an annual crop grown for human consumption of its nutritious leaves in
many regions of the world. Despite its importance for household food security and farmers’ income, reliable
information on the crop’s water requirements is still quite scarce. To overcome this knowledge gap, the irrigation
needs of jute mallow grown in the Akkar region in Syria were investigated. The analysis focused on a three-year
period (2017–2019) where the SIMDualKc model was calibrated and validated for simulating soil water contents
and computing the soil water balance in jute mallow plots irrigated with basin and drip methods. The model was
further used to determine the probabilities of the demand for irrigation water in scenarios considering different
crop season lengths, irrigation methods, and application depths over a longer period of 23 years (1998–2020).
The SIMDualKc model was able to simulate soil water contents measured in the field plots, returning root mean
square error values lower than 0.001 m3 m-3 and modeling efficiencies ranging from 0.358 to 0.812. The calibrated
basal (non-stressed) crop coefficients (Kcb) were 0.15, 0.95, and 0.95 for the initial (Kcb ini), mid-season
(Kcb mid), and end-season (Kcb end) stages, respectively. The crop was harvested twice per season, with the drip
treatments presenting the highest water productivity and economic indicators. In contrast, the basin treatment
resulted in substantial percolation losses, which affected yields and indicators. Although net irrigation requirements
showed a large variation for the extremes of the long-term weather time series, differences between
the years representing average water demand and those representing very high water demand were only found
for the drip irrigation scenarios. This study contributes to improving irrigation water management of jute mallow
in the Syrian Akkar region, and for the sustainability of local production systems
Exploring the Use of Vegetation Indices for Validating Crop Transpiration Fluxes Computed with the MOHID-Land Model. Application to Vineyard
Publication . Ramos, Tiago B.; Simionesei, Lucian; Oliveira, Ana R.; Neves, Ramiro; Darouich, Hanaa
The success of an irrigation decision support system (DSS) much depends on the reliability
of the information provided to farmers. Remote sensing data can expectably help validate that
information at the field scale. In this study, the MOHID-Land model, the core engine of the IrrigaSys
DSS, was used to simulate the soil water balance in an irrigated vineyard located in southern Portugal
during three growing seasons. Modeled actual basal crop coefficients and transpiration rates were
then compared with the corresponding estimates derived from the normalized difference vegetation
index (NDVI) computed from Sentinel-2 imagery. On one hand, the hydrological model was able
to successfully estimate the soil water balance during the monitored seasons, exposing the need for
improved irrigation schedules to minimize percolation losses. On the other hand, remote sensing
products found correspondence with model outputs despite the conceptual differences between
both approaches. With the necessary precautions, those products can be used to complement the
information provided to farmers for irrigation of vine crop, further contributing to the regular
validation of model estimates in the absence of field datasets
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Fundação para a Ciência e a Tecnologia
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6817 - DCRRNI ID
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157672