Estimating propagation probability from meteorological to ecological droughts using a hybrid machine learning-Copula method
- 1College of Water Resources and Architectural Engineering, Northwest A & F University, Yangling, Shaanxi, 712100, China
- 2Key Laboratory for Agricultural Soil and Water Engineering in Arid Area of Ministry of Education, Northwest A & F University, Yangling, Shaanxi, 712100, China
- 3College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225012, China
- 1College of Water Resources and Architectural Engineering, Northwest A & F University, Yangling, Shaanxi, 712100, China
- 2Key Laboratory for Agricultural Soil and Water Engineering in Arid Area of Ministry of Education, Northwest A & F University, Yangling, Shaanxi, 712100, China
- 3College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225012, China
Abstract. The impact of droughts on vegetation is essentially manifested as the transition of water shortage from the meteorological to ecological stages. Therefore, understanding the mechanism of drought propagation from meteorological to ecological drought is crucial for ecological conservation. This study proposes a method for calculating the probability of meteorological drought to trigger ecological drought at different magnitudes in Northwestern China. In this approach, meteorological and ecological drought events during 1982–2020 are identified using the three-dimensional identification method; the propagated drought events are extracted according to a certain spatio-temporal overlap rule; and propagation probability is calculated by coupling machine learning model and C-vine copula. The results indicate that: (1) 46 drought events are successfully paired by 130 meteorological and 184 ecological drought events during 1982–2020; ecological drought exhibits a longer duration, but smaller affected area and severity than meteorological drought; (2) Quadratic Discriminant Analysis (QDA) classifier performs the best among the 11 commonly used machine learning models which is combined with four-dimensional C-vine copula to construct drought propagation probability model; (3) the hybrid method considers more drought characteristics and more detailed propagation process which addresses the limited applicability of the traditional method to regions with large spatial extent.
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Tianliang Jiang et al.
Status: open (until 21 Jun 2022)
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RC1: 'Comment on hess-2022-78', Anonymous Referee #1, 29 Apr 2022
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General comments:
Drought risk is a common threat in many parts of the globe, and is expected to increase due to climate change and increasing pressure on water resources. However, meteorological drought does not necessarily imply ecological drought. The paper presents an innovative approach to study the relationship between these two types of droughts.
- Powerful machine learning approaches were applied. What were the degrees of freedom of the machine learning approaches? What is the ratio of the degrees of freedom over the rather small number of 81 meteorological drought events? According to Fig. 7 propagation probability is nearly exclusively determined by the severity of the meteorological drought which would meet common expectations. In contrast, any effect of duration or area is hardly discernible. Please compare the performance of the machine learning approaches to that of a multivariate linear regression.
- Please check the use of definite and indefinite articles and the use of plural “s”.
Details:
- 53-55: Who is “they”?
- 73-79: Section “2 Study area” comprises only 6 lines and should be merged with the subsequent section 3, or at least with section “3.1 Datasets”.
- 82-85: Verb is missing.
- 91: Use lowercase letter in “Root”.
- 98: Replace “deep phreatic buried depth” by “great depth to groundwater”.
- 112: Both “SEWDI” and “SEBS” need to be explained in a concise way. Referring to the Jiang et al. (2021) paper does not suffice.
- 124: Should be “three steps”, not “two steps”.
- 147: Delete “to”.
- 200: Do you mean “Johnson S_B distribution”?
- 224: What does “DS” mean?
- 265: Please explain “itau method”.
- 280-297: Section 5.1 should be either part of the methods or of the results section.
- 349-352: Verb is missing.
- Figure 3: I guess that the drought event numbers reflect chronological order, is that right? The colour scale indicates about the same meteorological-ecological drought event number for very different ecological and meteorological drought event numbers. E.g., green symbols show up for ecological drought event number 1-10, 30-50 and >150. How can that be? Is there something wrong with the colour coding of the symbols?
- Figure 7: In the figure caption correct “exceeding” to “exceed”.
Tianliang Jiang et al.
Tianliang Jiang et al.
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