Development of a random-forest-copula-factorial analysis (RFCFA) method for predicting propagation between meteorological and hydrological drought
In the context of global climate warming, the propagation of meteorological drought (MD) may aggravate the devastating impact of hydrological drought (HD) on water security and sustainable development. There are challenges in accurately predicting the propagation of drought and effectively quantifyi...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Science Press
2024-01-01
|
| Series: | National Science Open |
| Subjects: | |
| Online Access: | https://www.sciengine.com/doi/10.1360/nso/20230022 |
| _version_ | 1797348656742924288 |
|---|---|
| author | Wang Hao Li Yongping Huang Guohe Zhang Quan Ma Yuan Li Yangfeng |
| author_facet | Wang Hao Li Yongping Huang Guohe Zhang Quan Ma Yuan Li Yangfeng |
| author_sort | Wang Hao |
| collection | DOAJ |
| description | In the context of global climate warming, the propagation of meteorological drought (MD) may aggravate the devastating impact of hydrological drought (HD) on water security and sustainable development. There are challenges in accurately predicting the propagation of drought and effectively quantifying the effects of uncertainty, especially in data-deficient regions. In this study, a novel method called RFCFA is developed through integrating random forest (RF), copula, and factorial analysis (FA) into a general framework as well as applied to the Aral Sea Basin (a typical arid and data-scarce basin in Central Asia) under considering the impact of climate change. Several findings can be summarized: (1) the projected future drought propagation probability of ASB is 39.2%, which is about 8% higher than historical level; (2) drought propagation is mainly affected by mean climate condition, catchment characteristics (i.e., elevation, LUCC, and slope), and human activities (i.e., irrigation and reservoir operation); (3) the lower propagation probability in spring is expected under SSP1-2.6 due to increased snow meltwater, and the drought propagation probability in autumn is the highest (reaching 45.4%) under the influence of reservoir operation; (4) the combined effects of meteorological conditions and agricultural irrigation can lead to a higher probability of future propagation in the upper river basin in summer. Findings are valuable for predicting drought propagation risk, revealing main factors and inherent uncertainties, as well as providing support for drought management and disaster prevention. |
| first_indexed | 2024-03-08T12:09:01Z |
| format | Article |
| id | doaj.art-c11c4dd77e134062ba1f6df933a23adc |
| institution | Directory Open Access Journal |
| issn | 2097-1168 |
| language | English |
| last_indexed | 2024-03-08T12:09:01Z |
| publishDate | 2024-01-01 |
| publisher | Science Press |
| record_format | Article |
| series | National Science Open |
| spelling | doaj.art-c11c4dd77e134062ba1f6df933a23adc2024-01-23T03:11:56ZengScience PressNational Science Open2097-11682024-01-01310.1360/nso/20230022eb33e642Development of a random-forest-copula-factorial analysis (RFCFA) method for predicting propagation between meteorological and hydrological droughtWang Hao0Li Yongping1Huang Guohe2Zhang Quan3Ma Yuan4Li Yangfeng5["State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China"]["State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China","Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina Sask S4S 0A2, Canada"]["State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China","Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina Sask S4S 0A2, Canada"]["State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China"]["State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China"]["State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China"]In the context of global climate warming, the propagation of meteorological drought (MD) may aggravate the devastating impact of hydrological drought (HD) on water security and sustainable development. There are challenges in accurately predicting the propagation of drought and effectively quantifying the effects of uncertainty, especially in data-deficient regions. In this study, a novel method called RFCFA is developed through integrating random forest (RF), copula, and factorial analysis (FA) into a general framework as well as applied to the Aral Sea Basin (a typical arid and data-scarce basin in Central Asia) under considering the impact of climate change. Several findings can be summarized: (1) the projected future drought propagation probability of ASB is 39.2%, which is about 8% higher than historical level; (2) drought propagation is mainly affected by mean climate condition, catchment characteristics (i.e., elevation, LUCC, and slope), and human activities (i.e., irrigation and reservoir operation); (3) the lower propagation probability in spring is expected under SSP1-2.6 due to increased snow meltwater, and the drought propagation probability in autumn is the highest (reaching 45.4%) under the influence of reservoir operation; (4) the combined effects of meteorological conditions and agricultural irrigation can lead to a higher probability of future propagation in the upper river basin in summer. Findings are valuable for predicting drought propagation risk, revealing main factors and inherent uncertainties, as well as providing support for drought management and disaster prevention.https://www.sciengine.com/doi/10.1360/nso/20230022rought propagationrandom forestcopulafactorial analysisclimate changeAral Sea Basin |
| spellingShingle | Wang Hao Li Yongping Huang Guohe Zhang Quan Ma Yuan Li Yangfeng Development of a random-forest-copula-factorial analysis (RFCFA) method for predicting propagation between meteorological and hydrological drought National Science Open rought propagation random forest copula factorial analysis climate change Aral Sea Basin |
| title | Development of a random-forest-copula-factorial analysis (RFCFA) method for predicting propagation between meteorological and hydrological drought |
| title_full | Development of a random-forest-copula-factorial analysis (RFCFA) method for predicting propagation between meteorological and hydrological drought |
| title_fullStr | Development of a random-forest-copula-factorial analysis (RFCFA) method for predicting propagation between meteorological and hydrological drought |
| title_full_unstemmed | Development of a random-forest-copula-factorial analysis (RFCFA) method for predicting propagation between meteorological and hydrological drought |
| title_short | Development of a random-forest-copula-factorial analysis (RFCFA) method for predicting propagation between meteorological and hydrological drought |
| title_sort | development of a random forest copula factorial analysis rfcfa method for predicting propagation between meteorological and hydrological drought |
| topic | rought propagation random forest copula factorial analysis climate change Aral Sea Basin |
| url | https://www.sciengine.com/doi/10.1360/nso/20230022 |
| work_keys_str_mv | AT wanghao developmentofarandomforestcopulafactorialanalysisrfcfamethodforpredictingpropagationbetweenmeteorologicalandhydrologicaldrought AT liyongping developmentofarandomforestcopulafactorialanalysisrfcfamethodforpredictingpropagationbetweenmeteorologicalandhydrologicaldrought AT huangguohe developmentofarandomforestcopulafactorialanalysisrfcfamethodforpredictingpropagationbetweenmeteorologicalandhydrologicaldrought AT zhangquan developmentofarandomforestcopulafactorialanalysisrfcfamethodforpredictingpropagationbetweenmeteorologicalandhydrologicaldrought AT mayuan developmentofarandomforestcopulafactorialanalysisrfcfamethodforpredictingpropagationbetweenmeteorologicalandhydrologicaldrought AT liyangfeng developmentofarandomforestcopulafactorialanalysisrfcfamethodforpredictingpropagationbetweenmeteorologicalandhydrologicaldrought |