the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Monitoring the combined effects of drought and salinity stress on crops using remote sensing
- 1Institute of Environmental Sciences (CML), Leiden University, Box 9518, 2300 RA Leiden, the Netherlands
- 2Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, 1090 GE Amsterdam, the Netherlands
- 3Lifewatch ERIC, vLab & Innovation Centre, 1090 GE Amsterdam, the Netherlands
- 1Institute of Environmental Sciences (CML), Leiden University, Box 9518, 2300 RA Leiden, the Netherlands
- 2Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, 1090 GE Amsterdam, the Netherlands
- 3Lifewatch ERIC, vLab & Innovation Centre, 1090 GE Amsterdam, the Netherlands
Abstract. Global sustainable agricultural systems are under threat, due to projected increases of co-occurring drought and salinity with climate change. Combined effects of drought and salinity on agricultural crops have traditionally been evaluated in small-scale experimental studies. As such the need exists for large scale studies that increase our understanding and assessment of the combined impacts in agricultural practice in real life scenarios. This study aims to provide a new approach to estimate and compare the impacts of drought, salinity and their combination on crop traits at large spatial (138.74 km2) and temporal extents in the Netherlands using remote sensing observations. Specifically, for both maize and potato, we calculated five functional traits from Sentinel-2 observations, namely: leaf area index (LAI), the fraction of absorbed photosynthetically active radiation (FAPAR), the fraction of vegetation cover (FVC), leaf chlorophyll content (Cab) and leaf water content (Cw). Individual and combined effects of the stresses on the seasonal dynamics in crop traits were determined using both one-way and two-way ANOVAs. We found that both stresses (individual and co-occurring) affected the functional traits of both crops significantly (with R2 ranging from 0.326 to 0.796), though with stronger sensitivities to drought than to salinity. While we found exacerbating effects within co-occurrent stresses, the impact-level depended strongly on the moment in the growing season. For both crops, LAI, FAPAR and FVC dropped the most under severe drought stress conditions. The patterns for Cab and Cw were more inhibited by co-occurring drought and salinity. Consequently, our study constitutes a way towards evaluating drought and salinity impacts in agriculture with the possibility of potential large-scale application for a sustainable food security.
Wen Wen et al.
Status: final response (author comments only)
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RC1: 'Comment on hess-2022-50', Anonymous Referee #1, 21 Mar 2022
The combined effect of drought and salinity on crops is very important for food security under global change background. Remote sensing shows its advantage for large-scale applications. This paper used the sentinel-2 satellite data to conduct an analysis in this regard. The findings are interesting. I have the following major concerns:
Major:
1) Irrigation can mitigate the drought effect to a large extent. I would like to know how irrigation has influenced the analysis. There is no information reported in this regard.
2) Five different indicators were used to depict the health condition of different crops. I am wondering how the stress factors influence the final yield. Is it possible to have some discussion in this regard?Moreover, please find below some minor comments:
Line 33, more deeply challenged.
Line 37, delete ‘of’ and ‘more than’
Lines 83-90, why was SPEI selected as the drought indicator rather than the others? What is the RD_new projection? Where are the precipitation and PET data from?
Lines 124-129, Include some information about Sentinel-2 in the data description although it was pointed out in Fig. 1.
Line 145, why was the biomass effect removed? Is this contradictory to the Cab*LAI and Cw*LAI at Line 142?
Line 151, What do you mean by ‘due to the unbalance in the occurrence of stress conditions‘?
Lines 163-173, More explanations are needed to illustrate the connotations of different indicators in the ANOVA analysis, to increase the readability. Probably this can be supplemented in the methodology section.
Line 200, Add some information for the different letters indicating the significance level.
Line 220 and Line 244, It was concluded at Line 220 that there is no additive effect for drought and salinity. Is it in contradiction to the severe effect of the co-occurrence of drought and salinity?
Line 257, why was the drought effect mitigated? Please add more explanations.
Line 278, ‘Considering the additional’, remove the comma. Change ‘promising’ to ‘probable’.
Line 283, ‘In addition to facilitating the evaluation…’
Line 285, distinctively
Line 288, understand
Line 289, as compared to
Line 291, In this respect
Line 292, the transpiration demand normally refers to the atmospheric demand, like VPD and incoming radiation. What do you mean here?Please check the English writing more carefully to enhance the readability.
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- AC1: 'Reply on RC1', Wen Wen, 19 Apr 2022
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RC2: 'Comment on hess-2022-50', Anonymous Referee #2, 23 Mar 2022
Drought and salinity are considered to be the two main factors limiting crop productivity. Remote sensing enables the assessment of the impacts of extremes on crops, but it is seldomly used in the study of compound effects of drought and salinity stress. The novelty of this study is to assess the impacts of drought, salinity, and their combination on crop traits using multiple remote sensing observations and explore their relationships with stress timings and drought levels. The manuscript makes a contribution to the assessment of compound extremes’ impacts using remote sensing and the writing is well organized. I suggest this manuscript should be accepted by HESS after minor revisions.
Specific comments:
- In this study, only the 2018 case over the Netherlands was analyzed, are the conclusions robust? As the available data range from 2004 to 2018, are there any else cases to verify the conclusions? If there is no more cases, it is better to add the name of this case in the title.
- Add a map of the crop distribution over the study region.
- Line 89-90: The standard deviation of SPEI is 1 (Vicente-Serrano et al 2010), why do you define drought when SPEI is less than -321?
- The captions of Table 1, figure 3, and figure 4 should be described in detail, e.g. what are MD, MS, SS, ab, and abc short for in fig. 3?
- As figures 3-4 show the values of crop traits from May to September, it is better to show their standardized anomalies compared with climatology, which enables the comparison between different timings.
- What is the best explanation of the different responses among the five crop traits to such stresses?Â
- AC2: 'Reply on RC2', Wen Wen, 19 Apr 2022
Wen Wen et al.
Wen Wen et al.
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