Data di Pubblicazione:
2017
Abstract:
The Mediterranean water resources are almost fully exploited in many areas and the impacts
on water scarcity are projected to multiply under climate change. The most effective mean to
save water appear to be through the adoption of carefully managed irrigation strategies. Plant
indicators enable the grower to use the plant directly for clues as to when irrigate. These
indicators could be obtained through the use of remote sensing that is widely involved in
numerous disciplines such as agriculture. Remote sensing is one of the solutions that can
significantly contribute to providing a timely and accurate imagery of the agricultural sector.
The main objective of this study is to compare satellite and ground-based sensing techniques
as tools describing the variations of crop stress related indices under different water regimes
(case of durum wheat). The experimental layout was established in Policoro (Matera) located
in Southern Italy about 3 km far from the Ionian coast. The growing season was from
February to June 2015 with three distinguished water management practices (rain-fed, 50%
and 100% of irrigation requirements). The Landsat 8 images and ground-based sensing data
were acquired regularly in April, May and June together with plant physiological parameters.
The overall results indicated no significant differences of both biomass and yield among the
irrigation regimes. This could be explained by the abundant precipitation (205 mm) which
limited the needs for irrigation. Correlated to the leaf gas exchange parameters, Water Index
(WI), CWSI_Jackson and CWSI_Alves and Pereira performed better than CWSI_Idso. Water
Deficit Index (WDI) was found strongly related to plant water status, than Crop Water Stress
Index (CWSI) with average R² of 0.96 in respect to 0.57 (CWSI_Idso). High correlation
appear to be evident for satellite and ground-based derived WDI regressions (R²=0.81).
Nevertheless, the satellite data could provide reasonable indications about the crop status
when other means of measurement are missing.
Tipologia CRIS:
04.02 Abstract in Atti di convegno
Keywords:
irrigation; water deficit; remote sensing
Elenco autori:
Albrizio, Rossella; Cantore, Vito
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