Meteorological Drought Assessment and Prediction in Association with Combination of Atmospheric Circulations and Meteorological Parameters via Rule Based Models

The development of data-driven models in conjunction with the advances in technologies regarded as remote sensing in generating recorded data from satellites has guided water management studies towards using these technologies, especially in the regions dealing with drought, like the Lake Urmia basi...

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Main Authors: Ercan Kahya, Mohammad Taghi Sattari, Hashem Rostamzadeh, Fatemeh Shaker Sureh
Format: Article
Language:English
Published: Ankara University 2024-01-01
Series:Journal of Agricultural Sciences
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Online Access:https://dergipark.org.tr/tr/download/article-file/2229914
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author Ercan Kahya
Mohammad Taghi Sattari
Hashem Rostamzadeh
Fatemeh Shaker Sureh
author_facet Ercan Kahya
Mohammad Taghi Sattari
Hashem Rostamzadeh
Fatemeh Shaker Sureh
author_sort Ercan Kahya
collection DOAJ
description The development of data-driven models in conjunction with the advances in technologies regarded as remote sensing in generating recorded data from satellites has guided water management studies towards using these technologies, especially in the regions dealing with drought, like the Lake Urmia basin, Iran. In this basin, the agricultural sector has been exposed to dryness due to a decrease in rainfall and uncontrolled water consumption. In the last decade, many studies have tried to brighten this arena of water knowledge. However, the relationship between meteorological variables and atmospheric circulation with the meteorological drought of Lake Urmia had never been determined. The relationship between meteorological variables and atmospheric circulation with Lake Urmia's meteorological drought has been determined. This study calculated Standardized Precipitation Evapotranspiration Index (SPEI) values based on meteorological variables. Then a combination of the meteorological variables and atmospheric circulation values was considered a data mining model input for estimating the droughts. The series of the SPEI values for 3-, 6-, 9-, 12-, 24-, and 48-month time scales were obtained during 1988-2016. In this study, both the M5 Tree model and Associate Rules were used to predict and analyze the meteorological drought at six synoptic stations in the basin, considering both the atmospheric circulations (North Atlantic Oscillation (NAO), Southern Oscillation Index (SOI), Mediterranean Oscillation Index of Gibraltar-Israel (Mogi), Mediterranean Oscillation Index of Algiers-Cairo (MOac), Western Mediterranean Oscillation Index (WEMO), Mediterranean, Red, Black, Caspian, and Persian Gulf SSTs) and the meteorological variables (lagged relative humidity, evapotranspiration, average temperature, minimum-maximum temperature, and pressure). The results showed that using a combination of the atmospheric circulation indices and meteorological variables in the models increases the model's accuracy and improves the results in a long-term period. The best result in the study of drought in the Lake Urmia basin is related to SPEI48 (R = 0.85, RMSE = 0.08, MAE = 0.11), and in the association rules, the value of the lifting index of the best rule is 1.32. Although both approaches provided acceptable results, the M5 Tree model had a comparative advantage due to simple and practical linear relationships.
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publishDate 2024-01-01
publisher Ankara University
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series Journal of Agricultural Sciences
spelling doaj-art-c3d8bc8fafe54bf392afcabea39ce0262025-08-20T03:23:11ZengAnkara UniversityJournal of Agricultural Sciences1300-75802148-92972024-01-01301617810.15832/ankutbd.106748645Meteorological Drought Assessment and Prediction in Association with Combination of Atmospheric Circulations and Meteorological Parameters via Rule Based ModelsErcan Kahya0Mohammad Taghi Sattari1Hashem Rostamzadeh2Fatemeh Shaker Sureh3İSTANBUL TEKNİK ÜNİVERSİTESİUniversity of TabrizUniversity of TabrizTarbiat Modares UniversityThe development of data-driven models in conjunction with the advances in technologies regarded as remote sensing in generating recorded data from satellites has guided water management studies towards using these technologies, especially in the regions dealing with drought, like the Lake Urmia basin, Iran. In this basin, the agricultural sector has been exposed to dryness due to a decrease in rainfall and uncontrolled water consumption. In the last decade, many studies have tried to brighten this arena of water knowledge. However, the relationship between meteorological variables and atmospheric circulation with the meteorological drought of Lake Urmia had never been determined. The relationship between meteorological variables and atmospheric circulation with Lake Urmia's meteorological drought has been determined. This study calculated Standardized Precipitation Evapotranspiration Index (SPEI) values based on meteorological variables. Then a combination of the meteorological variables and atmospheric circulation values was considered a data mining model input for estimating the droughts. The series of the SPEI values for 3-, 6-, 9-, 12-, 24-, and 48-month time scales were obtained during 1988-2016. In this study, both the M5 Tree model and Associate Rules were used to predict and analyze the meteorological drought at six synoptic stations in the basin, considering both the atmospheric circulations (North Atlantic Oscillation (NAO), Southern Oscillation Index (SOI), Mediterranean Oscillation Index of Gibraltar-Israel (Mogi), Mediterranean Oscillation Index of Algiers-Cairo (MOac), Western Mediterranean Oscillation Index (WEMO), Mediterranean, Red, Black, Caspian, and Persian Gulf SSTs) and the meteorological variables (lagged relative humidity, evapotranspiration, average temperature, minimum-maximum temperature, and pressure). The results showed that using a combination of the atmospheric circulation indices and meteorological variables in the models increases the model's accuracy and improves the results in a long-term period. The best result in the study of drought in the Lake Urmia basin is related to SPEI48 (R = 0.85, RMSE = 0.08, MAE = 0.11), and in the association rules, the value of the lifting index of the best rule is 1.32. Although both approaches provided acceptable results, the M5 Tree model had a comparative advantage due to simple and practical linear relationships.https://dergipark.org.tr/tr/download/article-file/2229914speithe urmia lake basinm5 tree modelassociate rulesiran
spellingShingle Ercan Kahya
Mohammad Taghi Sattari
Hashem Rostamzadeh
Fatemeh Shaker Sureh
Meteorological Drought Assessment and Prediction in Association with Combination of Atmospheric Circulations and Meteorological Parameters via Rule Based Models
Journal of Agricultural Sciences
spei
the urmia lake basin
m5 tree model
associate rules
iran
title Meteorological Drought Assessment and Prediction in Association with Combination of Atmospheric Circulations and Meteorological Parameters via Rule Based Models
title_full Meteorological Drought Assessment and Prediction in Association with Combination of Atmospheric Circulations and Meteorological Parameters via Rule Based Models
title_fullStr Meteorological Drought Assessment and Prediction in Association with Combination of Atmospheric Circulations and Meteorological Parameters via Rule Based Models
title_full_unstemmed Meteorological Drought Assessment and Prediction in Association with Combination of Atmospheric Circulations and Meteorological Parameters via Rule Based Models
title_short Meteorological Drought Assessment and Prediction in Association with Combination of Atmospheric Circulations and Meteorological Parameters via Rule Based Models
title_sort meteorological drought assessment and prediction in association with combination of atmospheric circulations and meteorological parameters via rule based models
topic spei
the urmia lake basin
m5 tree model
associate rules
iran
url https://dergipark.org.tr/tr/download/article-file/2229914
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AT hashemrostamzadeh meteorologicaldroughtassessmentandpredictioninassociationwithcombinationofatmosphericcirculationsandmeteorologicalparametersviarulebasedmodels
AT fatemehshakersureh meteorologicaldroughtassessmentandpredictioninassociationwithcombinationofatmosphericcirculationsandmeteorologicalparametersviarulebasedmodels