Analyzing Driving Factors of Drought in Growing Season in the Inner Mongolia Based on Geodetector and GWR Models

Round 1

Reviewer 1 Report

The article is interesting, as it deals with the spatial distribution of drought and identify influencing factors on drought at Inner Mongolia though SPEI. The methodology is very comprehensive and the results are encouraging towards a new direction of drought monitoring studies.

As the paper stands, right now it needs some minor improvements. The criticism I have are listed below

 1)      I think the results can be presented a bit better. You can identify instances where the Drought Index (SPEI) fails. Are there any particular commonalities where the fails/succeeds? That would be useful to the readers.

 

 2)      I have read some other drought assessment papers, which consider human activities as another impact factor, but this paper does not. The authors should make a clear explanation in this direction.

 3)      The limitation of this work could be added.

Author Response

Response 1:

         In this paper, the Thornthwaite method was used for the calculation of PET parameters of SPEI, which is characterized by the need for fewer parameters, but the disadvantage is that it may not be suitable for environments with insufficient water evaporation like the southeastern United States and Middle East areas when compared with other methods such as the Penman formula and Hargreaves-Samani method. Therefore, the study area excluded Alxa and its surrounding areas where extreme droughts occurred frequently (Figure 1a).

 

References are as follows:

1.Xu, C.Y.; Singh, V.P. Evaluation and generalization of temperature-based methods for calculating evaporation. Hydrol. Process. 2001, 15, 305-19. https://doi.org/10.1002/hyp.119.

2. Jiao, D.D.; Ji, X.B.; Jin, B.W.; Zhao L.W; Zhang J.L. Comparison of Different Methods for Estimating Potential Evaporation in an Arid Environment. Plateau Meteorology. 2018, 37, 1002-16. https://doi.org/10.7522/j.issn.1000－0534.2018.00048.
3. Lu, J.; Sun, G.; McNulty, S. G.; Amatya, D.M. A comparison of six potential evapotranspiration methods for regional use in the southeastern United States. JAWRA Journal of the American Water Resources Association. 2005, 41(3), 621-633. https://doi.org/10.1111/j.1752-1688.2005.tb03759.x
4. Van der Schrier, G.; Jones, P. D.; Briffa, K. R. The sensitivity of the PDSI to the Thornthwaite and Penman‐Monteith parameterizations for potential evapotranspiration. Journal of Geophysical Research: Atmospheres. 2011, 116(D3). https://doi.org/10.1029/2010JD015001

 

Point 2: I have read some other drought assessment papers, which consider human activities as another impact factor, but this paper does not. The authors should make a clear explanation in this direction.   

Response 2:

         This paper introduces three factors related to human activities, DTC, LUCC, and AOPD [line 234]. Among them, DTC and AOPD are less explanatory to SPEI [line 322], and LUCC is more explanatory to SPEI at an altitude of 800-1300m. It is likely to be affected by scientific irrigation, closing mountains for afforestation, and overgrazing [line 496-501]. In addition, other factors (GDP, CO₂ emissions, etc.) are likely to contribute to drought. Further will likely introduce.

 

Point 3: The limitation of this work could be added.?

Response 3:

         Limitations of this work can include:

1. It is insufficient to use meteorological data for less than 20 years to carry out long-term analysis. Time series and SPEI changes in different periods help us to better reveal the driving factors for drought.
2. The analysis of drought-driven results in the whole Inner Mongolia region has a strong macroscopic nature, and future research at further detailed scales will help to quantify the drought conditions and causes in the study area, especially in the eastern Inner Mongolia and western Inner Mongolia.
3. The above content has been added to the Outlook section in paper.

Reviewer 2 Report

The authors quantitatively characterized mode, scope, and intensity of changes in SPEI caused by drought-influencing factors such as weather, water, topography, soil and human activities using Geodetector and Geographically Weighted Regression (GWR) models. The result show that air temperature, precipitation, elevation, and distance to rivers are main controlling factors in drought change, and the factor interactions showed nonlinear enhancement. The explanation the interaction between the main controlling factors is important. However, the selected drought index SPEI is a typical meteorological drought based on precipitation and air temperature. I do not understand the current conclusion especially in term of social factors. In addition, the authors did not employ remote sensing technology for data mining. I suggest the editors reject the MS.

Author Response

In this paper, in terms of the influence of social factors on SPEI, DTC, LUCC and AOPD were selected as the potential social factors affecting SPEI [line 234]. Figure 5 and Figure 7a based on the changes in q values, aiming to dynamically describe the changes in the explanatory power of each factor to the SPEI. In addition, we believe that the exploration of driving forces based on spatiotemporal heterogeneity is an important research direction in remote sensing Geoscience Analysis.

Reviewer 3 Report

 

A novel work, based on spatial distribution of drought and identifing influencing factors on drought around Inner Mongolia (China). Drought driving factors are presenting and  quantitative indicators of drought, combined with the best management practices that could be applied in the area. 

The main question has been well addressed by the research The topic is original and relevant It has an added value considering to the used novel methodology The improvements that could be done by the authors is to try to apply the used methodologies to other areas with similar climatic characteristics (arid and semi-arid) The conclusions are satisfactory, and they answer the posed arguments and questions The references section, need an improvement, so that the results to be more representative globally from other areas as well, with similar climatic characteristics, as already mentioned English language needs a review from a native speaker

The paper has to be enriched with case studies from other semi-arid and arid areas worlwide, like the Meditteranean and Middle East areas. Moreover, some Water Management Models and Techniques need to be mentioned. So the reference section needs to be improved with some releavant proposed works: 

 

Psilovikos A., 1999. Optimum Management of Groundwater Resources. Comparison and evaluation with Linear and Non-Linear Programming Models. PhD Thesis, Aristotle University of Thessaloniki, Dept. of Rural & Surveying Engineering, 254 p.

Karam Alsafadi, Nadhir Al-Ansari, Ali Mokhtar, Safwan Mohamed, Agmed Elbeltagi, Saad Sh Sammen, Shuoben Bi, 2022. An evapotranspiration deficit-based drought index to detect variability of terrestrial carbon productivity in the Middle East. Environ. Res. Lett., Vol 17, No 1, 014051.

 

 

Author Response

Thank you for your good suggestions, we have completed English review. Also we have read and cited the following additional references:

1. Drumond, A.; Gimeno, L.; Nieto, R.; Trigo, R.M.; Vicente-Serrano, S.M. Drought episodes in the climatological sinks of the Mediterranean moisture source: The role of moisture transport. Global and Planetary Change, 151,4-14.https://doi.org/10.1016/j.gloplacha.2016.12.004.
2. Psilovikos, A.; Tzimopoulos C. Comparison of quadratic and non-linear programming (QP and NLP) optimization models in groundwater management. Journal of Hydroinformatics, 2004, 6(3): 175-185. https://doi.org/10.2166/hydro.2004.0014.
3. Alsafadi, K.; Al-Ansari, N.; Mokhtar, A.; Mohammed, S.; Elbeltagi, A.; Sammen, S.; Bi, S. An evapotranspiration deficit-based drought index to detect variability of terrestrial carbon productivity in the Middle East. Environmental Research Letters, 2022, 17(1): 014051. https://doi.org/10.1088/1748-9326/ac4765.
4. Dregne H E. Desertification of arid lands. Physics of desertification. 1986, 4-34. https://doi.org/10.1007/978-94-009-4388-9_2.
5. Julich, S.; Moorcroft, M.; Feger, K.; van-Tol, J. The impact of overgrazing on water fluxes in a semi-arid watershed–The suitability of watershed scale modeling in a data scarce area. Journal of Hydrology: Regional Studies, 2022, 43: 101178. https://doi.org/10.1016/j.ejrh.2022.101178.

Round 2

Reviewer 2 Report

I think the paper is acceptable in present form.

Reviewer 3 Report

Accepted in its present form, after the corrections which took place by the authors.