the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 29 Oct 2024
Historical changes in drought characteristics and its impact on vegetation cover over Madagascar
Abstract. Drought has become one of the most devastating natural hazards in recent decades causing severe vegetation degradation. This study aims to analyze the spatiotemporal characteristics of drought (duration, frequency, severity, intensity) over Madagascar during 1981–2022. In addition, it evaluates the relationship between the Standardized Precipitation Index (SPI) and the Normalized Difference Vegetation Index (NDVI) during 2000–2022, representing the impact of drought on vegetation over the studied area. Drought assessment was computed on SPI-3, SPI-6, and SPI-12 timescales, accompanied by seasonal and annual analyses. While the NDVI-SPI relationships were performed through the analysis of vegetation changes based on specific selected SPI time-periods and the correlation analysis. The findings reveal that drought events have become more consecutive during the most recent past (2017 to 2022) and intensified over the southern part of the country. Links between the drought occurrence and vegetation changes are confirmed: the occurrences of continuous negative values of seasonal and annual SPI increase vegetation losses, and the existence of smaller negative values of the wet season SPI relates to more vegetation degradation during the wet season. The correlation between NDVI and SPI emphasizes the NDVI-SPI relationship found with statistical significance, especially over southern Madagascar. These findings are crucial for complementing other climatic factors that influence Madagascar’s vegetation besides drought.
- Preprint
(2543 KB) - Metadata XML
-
Supplement
(1935 KB) - BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Comment on nhess-2024-191', Anonymous Referee #1, 01 Dec 2024
The manuscript discusses the impact of droughts on vegetation in Madagascar through the analysis of the relationships between the SPI and NDVI. Spatiotemporal characteristics of droughts were performed for the period 1981-2022, while the relationships between the indices were analysed over the time span of 2000-2022. Drought duration, frequency, severity and intensity were investigated. The topic and idea are important and interesting. In my opinion, the manuscript can be published after some corrections, which I assess as something between minor and major.
The manuscript is written in the correct language; however, in some parts, the sentences are very similar, which makes the text a bit humdrum (section discussing the spatial patterns).
The interpretation of the results in the section “Spatial analysis of drought characteristics (Duration, Frequency, 220 Intensity, and Severity)” is poor - limited to the very general description of the figures. In the case of drought characteristics, one general sentence describes each of the characteristics and says no more than the index is higher or lower. After reading this section, no clear information remains in one's mind. The section lacks the interpretation of the charts. It can also be due to the language style, like - Drought intensity shows the occurrence of moderate drought during the dry season. A sentence like “during dry season moderate droughts dominated” would be more direct and more transparent.
The Division into the 3 regions – the justification of the Madagascar division into the three regions differing in the precipitation and vegetation conditions is convincing, however, the borders are like those made by the ruler. In nature, there are no such straight borders. Moreover, it would be informative if Fig.1 included the grids for precipitation data used in this study and some information on precipitation and air temperature in these regions to provide their differences.
Precipitation Data. The manuscript is based on model data, which usually differs from the station data. Two different data sources were used and the data from these sources probably differ. Several questions arise concerning these data. Were those data just combined – what about the differences between the sources? Why are two datasets used? It is not explained. What is the resolution of the data? How much do they differ from station data? Randriatsara et al. (2022b) stated that the databases performed well for 1983-2015 while the manuscript uses the data for 1981-2022. What about the 1981 and 1982? Please refer to these questions.
Please extend the section regarding SPI. Deliver more information on how the SPIs were calculated. It will make catching the difference between the further SPI figures easier.
Fig. 1. Colours in the legend (colour scale) should be inverted. Usually, brown is used for high altitudes, and green is used for low elevations.
lines 102-104: due to the shift of the convergence zone (?) – please check the expression with respect to the verb. It seems that “shift” (or other similar word) is lacking in the sentence.
line 172: It should be “the sum of months with SPI<1” instead of “the sum of SPI values <-1” – please check it.
Fig.2. – Please shift the shaded bels to the background of the figure so that they ....
Section Regional values of monthly SPI-3, SPI-6 and SPI-12 – the description of the fig. 2-3 is very scarce. In the case of Fig. 3, there is only one very general statement in the text that there were more occurrences of moderate and severe drought events over the R1 than the 195 R2 and R3, especially in the recent decade. There is much more interesting information in these figures... Please interpret these figures in more detail, not only focusing on the recent years.
Lines 197-198: However, it is worth mentioning that based on SPI -12 all the regions experienced simultaneous drought in the years 1991, 2006, 2017, and 2021b – I can identify 7 common dry periods in this figure.
Lines 203-204: The temporal development of dry season SPI in Fig. 5B exhibits almost the same patterns in all three regions – I can see the similarities until 2007, but later the patterns are different (?), aren’t they?
Fig 6 – I am unsure if my impression is correct because there is no clear information on how the indices were calculated. Still, It seems that the differences in the duration for SPI-3, SPI-6 and SPI-12 are due to the method of calculations. If so, should the colour scale for these figures be the same?
line 221-222: “... (up to 26 months in the southern R1 region (Fig. 6c) ...” – bracket is missing.
line 236-237: “Drought intensity shows the occurrence of moderate drought during the dry season ...” Does it mean moderate drought dominated? Please make the sentence more informative, particularly “show the occurrence”.
line 233: “Drought intensity shows the occurrence of moderate drought during the dry season...” – Please deliver some numbers ...
Does Fig. 6 show the average values of duration, frequency, severity and intensity? Please include this information in the capture.
The citations in lines 247-252 (copied below) indicate that no changes in droughts occurred in the study area. It is unclear that the authors' intention was to focus on the drought-driving factors. Please rewrite the sentences to drive the reader’s attention to the factors.
“According to Harrington et al. (2022), based on a combination of observations and climate modeling, the likelihood of poor rains experienced over the southern part of Madagascar was not found significantly increased due to human-caused climate change since it is overwhelmed by natural variability. However, a perceptible change in drought will 250 emerge over the region if anthropogenic activities increase the global mean temperatures by more than 2 °C above preindustrial levels (IPCC 2021; Harrington et al., 2022).”
Please explain the abbreviations of IOD, SIOD also, SST, and ENSO, although the last two are commonly used.
line 285-286: “The anomaly of NDVI at the end of the Event-I (Fig. 7d) shows that the area with negative values has extended with an increased amplitude of up to -0.2 compared to the beginning of the event (Fig. 7a).” Difficult to understand, particularly when it goes to amplitude. What is meant by amplitude here? The same in line 352 – negative amplitude? How can amplitude be negative? Amplitude has its particular meaning.
line 371: Is the decrease in NDVI for R1 statistically significant?
lines 391-392: The correlation coefficients are very low. Regarding the large number of pixels are these relationships really so valid? In the further part of the manuscript, it is extended, but the statement of the existence of the relationships should be weaker in this sentence.
Conclusions also include a kind of discussion. This discussion is interesting and valuable; however, it does not agree with the title of the section. I have some trouble with the structure because the discussion is also included in the particular sections... My advice is just to skip the discussion in the conclusions and include the results arising from your analysis. In such a case, shift the discussion parts to the results. The second possibility is to modify the section title to Discussion and Conclusions, which is also not the best solution (discussion is also included in the results). If none of the other reviewers raised that problem, skip this comment.
Citation: https://doi.org/10.5194/nhess-2024-191-RC1 -
RC2: 'Comment on nhess-2024-191', Anonymous Referee #2, 16 Dec 2024
Review of ‘Historical changes in drought characteristics and its impact on vegetation cover over Madagascar’
I read the manuscript of Randriatsara et al with interest. Here, the author’s analyse spatio-temporal characteristics of droughts over Madagascar, together with MODIS based NDVI. They show that the occurrence and intensity of droughts increased over the southern region, and that, especially over this region, there is a relationship between the SPI and NDVI.
The paper is clearly written and the impact of droughts on vegetation is a very relevant topic. I do have a few concerns regarding the analyses, and I believe that some of the conclusions are not supported by the current methodology or the (non-quantitative) description of the results. I will list my concerns below with suggestions to improve the methodology.
I have two concerns regarding the analyses of NDVI differences and NDVI time series.
1) The NDVI difference is calculated against a reference year (2001). Although the text mentions that 2001 was a relatively normal period, it appears to follow a severely dry period in R2 and R3. And any non-normal month during 2001 would lead to false conclusions about the NDVI difference later in the manuscript. Therefore, I recommend to calculate the NDVI anomaly relative to the monthly mean NDVI of the whole time series.
2) There is a trend in NDVI values for R1 for certain months. The manuscript mentions that this is related to climate change and natural variability (could rising CO2 concentrations also be one?). This means that the results presented in for example Fig. 9, L354 – 359, are (at least partly) the result of this decreasing trend, rather than the drought events itself. Detrending of the NDVI time series could possibly be used to separate the drought related effects from the negative trend effects. How does this negative trend impact the correlation results presented in for example Fig. 11 and Fig. S6?The NDVI anomalies in Fig. 7 – 9 are difficult to interpret without a reference value. What is the normal variation (or change) that one finds? Would it be an option to compare the values and changes to the 5 – 95% interval from all years? Furthermore, for Fig 7, the beginning and ending of the dry period might not reflect the worse drought period or the strongest vegetation response. I would recommend to compare the mean NDVI anomaly for the selected drought period with the normal anomaly that is found during this period.
L280 – 283: How are the start and end of the drought events determined? And how sensitive are the results in Fig 7 to the selection of the start and end of the drought event?Generally, the manuscript would benefit from more quantitative statements. I give three examples. 1. L190 – L191 “The SPI-3 (Fig. 2) shows that the occurrence of moderate to severe drought events (i.e. SPI values between -1 and -1.99) in the recent decade are more frequent over the southern region (R1) than over the western (R2) and eastern (R3) regions”. What is more frequent? Is this a significant change? Because I count a similar number of drought events in each region. 2. L228 – L229: “It is worth mentioning that for all the drought characteristics for all the three timescales, the magnitudes are higher over the southern region, especially for SPI-12, compared to the rest of the area”. Based on the figure, I do not agree with this statement, but if this is relevant, it would be good to have the corresponding values in a table. 3. L233 – 234: “Drought appears less frequent during the dry season, compared to the wet season”. What is less frequent? And ‘appears’; does this mean that there is a statistically significant difference?
Fig 11 and Fig S6 represents the correlation between the NDVI and SPI. Are these monthly mean values? I have the impression that this figure is comparing seasonality in NDVI with anomalies in precipitation; most of the variation along the x-axis is the effect of seasonality, while the magnitude of the drought effect is much smaller. I would recommend to do this analyses with NDVI anomaly values, rather than absolute NDVI values.
Minor points
The study links the SPI (index for precipitation drought) to NDVI (agricultural droughts). However, vegetation is not affected by a lack of rainfall, it ‘cares about’ the vapour pressure deficit and the amount of water in the root zone. Agricultural droughts have a stronger link with soil moisture availability. However, precipitation data has a better availability, compared to soil moisture data, and therefore, the SPI (or SPEI) is a frequently used index for studying agricultural droughts. I recommend to add a bit of introduction or discussion on the processes linking drought, SPI, vegetation, and NDVI.
I find the overview of drought characteristics in 2.3.3 very clear. It would be helpful for the reader to add that these drought characteristics are calculated for the three considered timescales (SPI3, SPI6, SPI12, and for the seasonal and annual). I do have two questions regarding these calculations. Is the Number_Timesteps lower for the seasonal and annual timescale? For Fig 6d-f: I do not understand what the drought duration of 4 or 9 months means for these seasonal and annual time scale. Could this be explained in the text?
For Eq. 1: the NDVI is usually calculated with specifically the Red part of the visible spectrum. Did you also use the wavelength of Red light to calculate the NDVI or all visible light?
L148: The website refers to Version 6, while you mention that version 6.1 was used.
Citation: https://doi.org/10.5194/nhess-2024-191-RC2
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 140 | 26 | 7 | 173 | 14 | 3 | 5 |
- HTML: 140
- PDF: 26
- XML: 7
- Total: 173
- Supplement: 14
- BibTeX: 3
- EndNote: 5
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1