In this study an innovative approach for investigating the accumulated meteorological effects on cotton production during the growing season is presented. The quantification of the meteorological effects is based on the incorporation of the Bhalme and Mooley Drought Index (BMDI) methodology into the Vegetation Condition Index (VCI) extracted by NOAA/AVHRR data. The resulted Bhalme and Mooley Vegetation Condition Index (BMVCI) uses the same scale as the Z-Index of the Palmer Drought Severity Index (PDSI) for drought monitoring. The study area consists of the country of Greece. Eighteen years of NOAA/AVHRR data are examined and processed with the BMVCI to examine the unfavourable conditions for cotton production. For the validation of BMVCI an empirical relationship between the cotton production and the BMVCI values is derived. The method is developed based on the first sixteen years time series data and validated utilizing the following two years. The resultant high correlation coefficient and the approximation of the production for the validated years refer to very favourable results and confirms the usefulness of this integrated methodological approach as an effective tool to assess cotton production in Greece.
The use of actual evapotranspiration derived by satellite data at watershed scale in water balance modelling of forested mountainous watersheds is studied. Mean monthly maximum composites of the Normalized Difference Vegetation Index (NDVI), derived from the National Oceanic and Atmospheric Administration’s (NOAA) / Advanced Very High Resolution Radiometer (AVHRR) were correlated with monthly actual evapotranspiration rates estimated by a water balance model. The water balance model was applied to three mountainous and forested watersheds of Central Thessaly in Greece and the actual basin-wide evapotranspiration was estimated using two methods for the estimation of basin wide precipitation and two methods of potential evapotranspiration. The derived values of actual evapotranspiration were then correlated to NDVI data, and the developed equations were validated temporally and spatially. The actual evapotranspiration estimates, derived from NDVI and used in the water balance model, resulted in equally accurate simulations of monthly runoff when compared with the simulations acquired from the classical application of water balance model.