Articles | Volume 27, issue 2
https://doi.org/10.5194/hess-27-559-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-27-559-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Estimating propagation probability from meteorological to ecological droughts using a hybrid machine learning copula method
Tianliang Jiang
College of Water Resources and Architectural Engineering, Northwest A & F University, Yangling, Shaanxi 712100, China
Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Northwest A & F University, Yangling, Shaanxi 712100, China
College of Water Resources and Architectural Engineering, Northwest A & F University, Yangling, Shaanxi 712100, China
Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Northwest A & F University, Yangling, Shaanxi 712100, China
Gengxi Zhang
College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, China
Te Zhang
College of Water Resources and Architectural Engineering, Northwest A & F University, Yangling, Shaanxi 712100, China
Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Northwest A & F University, Yangling, Shaanxi 712100, China
Haijiang Wu
College of Water Resources and Architectural Engineering, Northwest A & F University, Yangling, Shaanxi 712100, China
Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Northwest A & F University, Yangling, Shaanxi 712100, China
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Huimin Wang, Gengxi Zhang, Shuyu Zhang, Xiaoling Su, Songbai Song, Lijie Shi, Kai Feng, and Xiaolei Fu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-217, https://doi.org/10.5194/hess-2022-217, 2022
Manuscript not accepted for further review
Short summary
Short summary
A significant increasing trend of compound dry and hot events has been reported in many regions under global warming. However, most of the proposed indices are based on monthly meteorological data and cannot monitor short-term events timely. This study proposes a novel daily-scale compound dry and hot index by jointing daily drought index and heat index. This index can detect spatial evolutions of dry and hot conditions and reflects vegetation losses, indicating its applicability.
Haijiang Wu, Xiaoling Su, Vijay P. Singh, Te Zhang, Jixia Qi, and Shengzhi Huang
Hydrol. Earth Syst. Sci., 26, 3847–3861, https://doi.org/10.5194/hess-26-3847-2022, https://doi.org/10.5194/hess-26-3847-2022, 2022
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Agricultural drought forecasting lies at the core of overall drought risk management and is critical for food security and drought early warning. Using three-dimensional scenarios, we attempted to compare the agricultural drought forecast performance of a canonical vine copula (3C-vine) model and meta-Gaussian (MG) model over China. The findings show that the 3C-vine model exhibits more skill than the MG model when using 1– to 3-month lead times for forecasting agricultural drought.
Zheng Liang, Xiaoling Su, and Kai Feng
Nat. Hazards Earth Syst. Sci., 21, 1323–1335, https://doi.org/10.5194/nhess-21-1323-2021, https://doi.org/10.5194/nhess-21-1323-2021, 2021
Short summary
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In view of the shortage of data in alpine mountainous areas and the difficulty of a single drought index to reflect all the characteristics of drought, this paper constructs a comprehensive drought index (MAHDI) based on the SWAT model and the empirical Kendall distribution function, which connects multiple drought elements. The results show that MAHDI can simultaneously characterize meteorological, agricultural and hydrological drought and has strong applicability and comprehensiveness.
Related subject area
Subject: Ecohydrology | Techniques and Approaches: Stochastic approaches
Detecting dominant changes in irregularly sampled multivariate water quality data sets
Probabilistic inference of ecohydrological parameters using observations from point to satellite scales
An integrated probabilistic assessment to analyse stochasticity of soil erosion in different restoration vegetation types
Christian Lehr, Ralf Dannowski, Thomas Kalettka, Christoph Merz, Boris Schröder, Jörg Steidl, and Gunnar Lischeid
Hydrol. Earth Syst. Sci., 22, 4401–4424, https://doi.org/10.5194/hess-22-4401-2018, https://doi.org/10.5194/hess-22-4401-2018, 2018
Short summary
Short summary
We suggested and tested an exploratory approach for the detection of dominant changes in multivariate water quality data sets with irregular sampling in space and time. The approach is especially recommended for the exploratory assessment of existing long-term low-frequency multivariate water quality monitoring data.
Maoya Bassiouni, Chad W. Higgins, Christopher J. Still, and Stephen P. Good
Hydrol. Earth Syst. Sci., 22, 3229–3243, https://doi.org/10.5194/hess-22-3229-2018, https://doi.org/10.5194/hess-22-3229-2018, 2018
Ji Zhou, Bojie Fu, Guangyao Gao, Yihe Lü, and Shuai Wang
Hydrol. Earth Syst. Sci., 21, 1491–1514, https://doi.org/10.5194/hess-21-1491-2017, https://doi.org/10.5194/hess-21-1491-2017, 2017
Short summary
Short summary
We constructed an integrated probabilistic assessment to describe, simulate and evaluate the stochasticity of soil erosion in restoration vegetation in the Loess Plateau. We found that morphological structures in vegetation are the source of different stochasticities of soil erosion, and proved that the Poisson model is fit for predicting erosion stochasticity. This assessment could be an important complement to develop restoration strategies to improve understanding of stochasticity of erosion.
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Short summary
A hybrid method is developed for calculating the propagation probability of meteorological to ecological drought at different levels. Drought events are identified from a three-dimensional perspective. A spatial and temporal overlap rule is developed for extracting propagated drought events.
A hybrid method is developed for calculating the propagation probability of meteorological to...