Probabilistic model of the relationship between ENSO and the occurrence of agricultural droughts in southern Peru
DOI:
https://doi.org/10.54139/revinguc.v28i1.13Keywords:
ENSO, probabilistic model, agricultural drought, copula functionsAbstract
In the article, the information on rainfall in the Province of Candarave, located in southern Peru, is analyzed and contrasted with different indices of the ENSO phenomenon to define whether there is influence of this phenomenon on the dry seasons in the region and build a probabilistic model using copula functions. The EMI (El Niño Modoki Index), ONI (Oceanic Niño Index), TNI (Trans-Niño Index), ICEN (Coastal El Niño Index), and the temperature anomalies ENSO34 (from zone
34) and ENSO 1 +2 (from zone 1 + 2) were analyzed and correlated with the three-month standardized precipitation index, SPI3, usually taken as an indicator of the occurrence of agricultural droughts. The results show that there is an association between the SPI3 index and the EMI, ENSO34, TNI and ONI indices at a significance level of 5 %. The goodness-of-fit analysis shows that the Gumbel-type copula is the most representative of the phenomenon being evaluated; therefore, the corresponding probabilistic model was built. The results allow inferring at a probabilistic level the possible occurrence of agricultural droughts based on the occurrence of the ENSO phenomenon.
Downloads
References
Intergovernmental Panel on Climate Change, "Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects." Cambridge University, Cambridge, United Kingdom and New York, NY, USA, Reporte Técnico, 2014.
F. Vega, "Variabilidad espacio-temporal de las sequías en el Perú y el peligro asociado al Fenómeno del Niño. ," Tesis para optar el grado de Magister Scientiae en recursos hídricos, Universidad Nacional Agraria La Molina. , Lima, Perú, 2018.
C. Knutson, "Methods and Tools for Drought Analysis and Management," Eos, vol. 89, no. 22, 2018. https://doi.org/10.1029/2008EO220013
G. Salvadori, C. De Michele, N. Kottegoda, and R. Rosso, Extremes in Nature: An approach using Copulas. Springer Netherlands, 2007. https://doi.org/10.1007/1-4020-4415-1
L. Santos, I. Cordery, and I. Iacovides, Coping with Water ScarcityAddressing the Challenges. Springer, Dordrecht, 2009.
SENAMHI, "Análisis de riesgo de sequias en el Sur del Perú." Ministetrio del Ambiente del Perú, Reporte Técnico, 2016.
INEI, Perú: Migraciones Internas. Lima. INEI, 2009.
A. AghaKouchak, "Entropy-copula in hydrology and climatology," Journal of Hydrometeorology, vol. 15, no. 6, pp.2176-2189, 2014. https://doi.org/10.1175/JHM-D-13-0207.1
L. Rü¨schendorf, Mathematical Risk AnalysisDependence, Risk Bounds, Optimal Allocations and Portfolios. Springer Berlin Heidelberg, 2013, ch. Copulas, Sklar's Theorem, and Distributional Transform. https://doi.org/10.1007/978-3-642-33590-7_1
B. Rayens and R. Nelsen, "An Introduction to Copulas by Roger B. Nelsen," Technometrics, vol. 42, no. 3, p. 317, 2000. https://doi.org/10.2307/1271100
M. Azam, S. Maeng, H. Kim, and A. Murtazaev, "Copula-Based Stochastic Simulation for Regional Drought Risk Assessment in South Korea," Water, vol. 10, no. 4, p. 359, 2018. https://doi.org/10.3390/w10040359
L. Hangshing and P. Dabral, "Multivariate Frequency Analysis of Meteorological Drought Using Copula." Water Resources Management, vol. 32, pp. 1741-1758, 2018. https://doi.org/10.1007/s11269-018-1901-0
F. Serinaldi, B. Bonaccorso, A. Cancelliere, and S. Grimaldi, "Probabilistic characterization of drought properties through copulas," Physics and Chemistry of the Earth Parts A/B/C, vol. 34, no. 10, pp. 596-605, 2009. https://doi.org/10.1016/j.pce.2008.09.004
K. Xu, D. Yang, X. Xu, and H. Lei, "Copula based drought frequency analysis considering the spatio-temporal variability in Southwest China," Journal of Hidrology, vol. 527, pp. 630-640, 2015. https://doi.org/10.1016/j.jhydrol.2015.05.030
J. Cabrera and J. Mejía, "Relationship between drought occurrence and ENSO in Southern Peru: a copulas analysis," in 38th IAHR World Congress-"Water: Connecting the World", Panama, 2019.
D. A. Wilhite and M. Glantz, "Understanding the drought phenomenon: The role of definitions," Water International, vol. 10, no. 3, pp. 111-120, 1985. https://doi.org/10.1080/02508068508686328
T. Mckee, N. Doesken, and J. Kleist, "The relationship of drought frequency and duration to time scales." in Eighth Conference on Applied Climatology, Anaheim, California, 1993, pp. 17-22.
L. Nkemdirim, Encyclopedia of Atmospheric Sciences, 2nd ed. Academic Press, 2015, ch. HYDROLOGY, FLOODS AND DROUGHTS | Palmer Drought Severity Index, pp. 224-231. https://doi.org/10.1016/B978-0-12-382225-3.00299-1
A. Cancelliere, G. Di Mauro, B. Bonaccorso, and G. Rossi, "Drought forecasting using the Standardized Precipitation Index," Water Resources Management, vol. 2, no. 5, pp. 801-819, 2007. https://doi.org/10.1007/s11269-006-9062-y
A. Cancelliere and J. Salas, "Drought length properties for periodic-stochastic hydrologic data," Water Resources Research, vol. 40, no. 2, 2004. https://doi.org/10.1029/2002WR001750
M. Sadegh, E. Ragno, and A. AghaKouchak, "Multivariate Copula Analysis Toolbox (MvCAT): Describing dependence and underlying uncertainty using a Bayesian framework," Water Resources Research, vol. 56, no. 6, pp. 5166-5183, 2017. https://doi.org/10.1002/2016WR020242
C. Genest, B. Rémillard, and D. Beaudoin, "Goodness-of-fit tests for copulas: a review and a power study," Insurance: Mathematics and Economics, vol. 44, no. 2, pp. 199-213, 2009. https://doi.org/10.1016/j.insmatheco.2007.10.005
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
