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| Titel |
Risk identification of agricultural drought for sustainable Agroecosystems |
| VerfasserIn |
N. R. Dalezios, A. Blanta, N. V. Spyropoulos, A. M. Tarquis |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Sciences ; 14, no. 9 ; Nr. 14, no. 9 (2014-09-12), S.2435-2448 |
| Datensatznummer |
250118662
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| Publikation (Nr.) |
 copernicus.org/nhess-14-2435-2014.pdf |
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| Zusammenfassung |
| Drought is considered as one of the major natural hazards with a significant
impact on agriculture, environment, society and economy. Droughts affect
sustainability of agriculture and may result in environmental degradation of
a region, which is one of the factors contributing to the vulnerability of
agriculture. This paper addresses agrometeorological or agricultural drought
within the risk management framework. Risk management consists of risk
assessment, as well as a feedback on the adopted risk reduction measures.
And risk assessment comprises three distinct steps, namely risk
identification, risk estimation and risk evaluation. This paper deals with
risk identification of agricultural drought, which involves drought
quantification and monitoring, as well as statistical
inference. For the quantitative assessment of agricultural drought,
as well as the computation of spatiotemporal features, one of the most
reliable and widely used indices is applied, namely the vegetation health
index (VHI). The computation of VHI is based on satellite data of
temperature and the normalized difference vegetation index (NDVI). The
spatiotemporal features of drought, which are extracted from VHI, are areal
extent, onset and end time, duration and severity. In this paper, a 20-year
(1981–2001) time series of the National Oceanic and Atmospheric Administration/advanced very high resolution radiometer (NOAA/AVHRR) satellite data is used, where monthly
images of VHI are extracted. Application is implemented in Thessaly, which
is the major agricultural drought-prone region of Greece, characterized by
vulnerable agriculture. The results show that agricultural drought appears
every year during the warm season in the region. The severity of drought is
increasing from mild to extreme throughout the warm season, with peaks
appearing in the summer. Similarly, the areal extent of drought is also
increasing during the warm season, whereas the number of extreme drought
pixels is much less than those of mild to moderate drought throughout the
warm season. Finally, the areas with diachronic drought persistence can be
located. Drought early warning is developed using empirical functional
relationships of severity and areal extent. In particular, two second-order
polynomials are fitted, one for low and the other for high severity drought
classes, respectively. The two fitted curves offer a forecasting tool on a
monthly basis from May to October. The results of this drought risk
identification effort are considered quite satisfactory offering a
prognostic potential. The adopted remote-sensing data and methods have
proven very effective in delineating spatial variability and features in
drought quantification and monitoring. |
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