Articles | Volume 26, issue 17
https://doi.org/10.5194/hess-26-4537-2022
© Author(s) 2022. 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-26-4537-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Sep 2022
Research article |
| 13 Sep 2022
| 13 Sep 2022
Monitoring the combined effects of drought and salinity stress on crops using remote sensing in the Netherlands
Institute of Environmental Sciences (CML), Leiden University, Box
9518, 2300 RA Leiden, the Netherlands
Joris Timmermans
Institute of Environmental Sciences (CML), Leiden University, Box
9518, 2300 RA Leiden, the Netherlands
Institute for Biodiversity and Ecosystem Dynamics, University of
Amsterdam, 1090 GE Amsterdam, the Netherlands
Lifewatch ERIC, vLab & Innovation Centre, 1090 GE Amsterdam, the
Netherlands
Qi Chen
Institute of Environmental Sciences (CML), Leiden University, Box
9518, 2300 RA Leiden, the Netherlands
Peter M. van Bodegom
Institute of Environmental Sciences (CML), Leiden University, Box
9518, 2300 RA Leiden, the Netherlands
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Cited articles
Asner, G. P., Scurlock, J. M. O., and Hicke, J. A.: Global synthesis of
leaf area index observations: Implications for ecological and remote sensing
studies, Global Ecol. Biogeogr., 12, 191–205, https://doi.org/10.1046/j.1466-822X.2003.00026.x, 2003.
Ayers, R. S. and Westcot, D. W.: Water quality for agriculture, Food and Agriculture Organization of the United Nations Rome, https://www.waterboards.ca.gov/water_issues/programs/tmdl/records/state_board/1985/ref2648.pdf (last access: 9 September 2022), 1985.
Azad, N., Rezayian, M., Hassanpour, H., Niknam, V., and Ebrahimzadeh, H.:
Physiological mechanism of salicylic acid in mentha pulegium l. Under
salinity and drought stress, Braz. J. Bot., 44, 359–369,
https://doi.org/10.1007/s40415-021-00706-y, 2021.
Bernstein, L. and Ayers, A.: Salt tolerance of cabbage and broccoli, United
States Salinity Laboratory Report to Collaborators, Riverside, CA, 39, 1949.
Boussetta, S., Balsamo, G., Beljaars, A., Kral, T., and Jarlan, L.: Impact
of a satellite-derived leaf area index monthly climatology in a global
numerical weather prediction model, Int. J. Remote Sens., 34, 3520–3542,
https://doi.org/10.1080/01431161.2012.716543, 2012.
Bowman, W. D.: The relationship between leaf water status, gas-exchange, and
spectral reflectance in cotton leaves, Remote Sens. Environ., 30, 249–255,
https://doi.org/10.1016/0034-4257(89)90066-7, 1989.
Broekhuizen, A.: Storm duurt dagen, droogte duurt maanden,
https://www.rijkswaterstaat.nl/nieuws/archief/2018/08/storm-duurt-dagen-droogte-duurt-maanden (last access: 14 September 2021), 2018.
Chen, Q., Timmermans, J., Wen, W., and van Bodegom, P. M.: A multi-metric
assessment of drought vulnerability across different vegetation types using
high-resolution remote sensing, Sci. Total Environ., 832, 154970, https://doi.org/10.1016/j.scitotenv.2022.154970, 2022.
Ciais, P., Reichstein, M., Viovy, N., Granier, A., Ogée, J., Allard, V.,
Aubinet, M., Buchmann, N., Bernhofer, C., Carrara, A., Chevallier, F., De
Noblet, N., Friend, A. D., Friedlingstein, P., Grünwald, T., Heinesch,
B., Keronen, P., Knohl, A., Krinner, G., Loustau, D., Manca, G., Matteucci,
G., Miglietta, F., Ourcival, J. M., Papale, D., Pilegaard, K., Rambal, S.,
Seufert, G., Soussana, J. F., Sanz, M. J., Schulze, E. D., Vesala, T., and
Valentini, R.: Europe-wide reduction in primary productivity caused by the
heat and drought in 2003, Nature, 437, 529–533,
https://doi.org/10.1038/nature03972, 2005.
Copernicus: Copernicus sentinel-2 data, Copernicus [data set], https://scihub.copernicus.eu/ (last access: 20 May 2021), 2018.
Corwin, D. L.: Climate change impacts on soil salinity in agricultural
areas, Eur. J. Soil Sci., 72, 842–862,
https://doi.org/10.1111/ejss.13010, 2020.
Croft, H., Chen, J. M., Luo, X., Bartlett, P., Chen, B., and Staebler, R.
M.: Leaf chlorophyll content as a proxy for leaf photosynthetic capacity,
Glob. Change Biol., 23, 3513–3524, https://doi.org/10.1111/gcb.13599, 2017.
Daryanto, S., Wang, L., and Jacinthe, P. A.: Global synthesis of drought
effects on maize and wheat production, PLoS One, 11, e0156362,
https://doi.org/10.1371/journal.pone.0156362, 2016a.
Daryanto, S., Wang, L. X., and Jacinthe, P. A.: Drought effects on root and
tuber production: A meta-analysis, Agr. Water Manage., 176, 122–131,
https://doi.org/10.1016/j.agwat.2016.05.019, 2016b.
Daryanto, S., Wang, L. X., and Jacinthe, P. A.: Global synthesis of drought
effects on cereal, legume, tuber and root crops production: A review, Agr.
Water Manage., 179, 18–33, https://doi.org/10.1016/j.agwat.2016.04.022, 2017.
Deb, P., Moradkhani, H., Han, X., Abbaszadeh, P., and Xu, L.: Assessing
irrigation mitigating drought impacts on crop yields with an integrated
modeling framework, J. Hydrol., 609, 127760,
https://doi.org/10.1016/j.jhydrol.2022.127760, 2022.
Delsman, J. R., Oude Essink, G. H. P., Huizer, S., Bootsma, H., Mulder, T., Zitman, P., and Romero Verastegui, B.: Actualisatie zout in het nhi – toolbox nhi zoet-zout modellering en landelijk model, Nederlands Hydrologisch Instrumentarium (NHI) [data set], https://doi.org/10.13140/RG.2.2.17077.09447, 2020.
Dente, L., Satalino, G., Mattia, F., and Rinaldi, M.: Assimilation of leaf
area index derived from asar and meris data into ceres-wheat model to map
wheat yield, Remote Sens. Environ., 112, 1395–1407,
https://doi.org/10.1016/j.rse.2007.05.023, 2008.
Doraiswamy, P. C., Sinclair, T. R., Hollinger, S., Akhmedov, B., Stern, A.,
and Prueger, J.: Application of modis derived parameters for regional crop
yield assessment, Remote Sens. Environ., 97, 192–202,
https://doi.org/10.1016/j.rse.2005.03.015, 2005.
Efimova, M. V., Kolomeichuk, L. V., Boyko, E. V., Malofii, M. K.,
Vidershpan, A. N., Plyusnin, I. N., Golovatskaya, I. F., Murgan, O. K., and
Kuznetsov, V. V.: Physiological mechanisms of solanum tuberosum l. Plants'
tolerance to chloride salinity, Russ. J. Plant Physl., 65, 394–403,
https://doi.org/10.1134/S1021443718030020, 2018.
ESA: Sentinel-2 user handbook, https://sentinel.esa.int/documents/247904/685211/sentinel-2_user_handbook (last access: 6 April 2022), 2015.
Fang, H., Baret, F., Plummer, S., and Schaepman-Strub, G.: An overview of
global leaf area index (lai): Methods, products, validation, and
applications, Rev. Geophys., 57, 739–799,
https://doi.org/10.1029/2018RG000608, 2019.
FAO, IFAD, UNICEF, WFP and WHO: The state of food security
and nutrition in the world 2020, Transforming food systems for affordable healthy diets, FAO, Rome, https://doi.org/10.4060/ca9692en, 2020.
Fatima, A., Hussain, S., Hussain, S., Ali, B., Ashraf, U., Zulfiqar, U.,
Aslam, Z., Al-Robai, S. A., Alzahrani, F. O., Hano, C., and El-Esawi, M. A.:
Differential morphophysiological, biochemical, and molecular responses of
maize hybrids to salinity and alkalinity stresses, Agronomy, 11, 1150,
https://doi.org/10.3390/agronomy11061150, 2021.
Gerhards, M., Schlerf, M., Mallick, K., and Udelhoven, T.: Challenges and
future perspectives of multi-/hyperspectral thermal infrared remote sensing
for crop water-stress detection: A review, Remote Sens., 11, 1240–1264,
https://doi.org/10.3390/rs11101240, 2019.
Ghimire, B., Timsina, D., and Nepal, J.: Analysis of chlorophyll content and
its correlation with yield attributing traits on early varieties of maize
(zea mays l.), J. Maize Res. Dev., 1, 134–145,
https://doi.org/10.3126/jmrd.v1i1.14251, 2015.
Ghosh, S. C., Asanuma, K., Kusutani, A., and Toyota, M.: Effect of salt stress on some chemical components and yield of potato, Soil Sci. Plant Nutr., 47, 467–475, https://doi.org/10.1080/00380768.2001.10408411, 2001.
Gitelson, A. A., Vina, A., Ciganda, V., Rundquist, D. C., and Arkebauer, T.
J.: Remote estimation of canopy chlorophyll content in crops, Geophys. Res.
Lett., 32, L08403, https://doi.org/10.1029/2005GL022688, 2005.
Godfray, H. C., Beddington, J. R., Crute, I. R., Haddad, L., Lawrence, D.,
Muir, J. F., Pretty, J., Robinson, S., Thomas, S. M., and Toulmin, C.: Food
security: The challenge of feeding 9 billion people, Science, 327, 812–818,
https://doi.org/10.1126/science.1185383, 2010.
Harfi, M. E., Hanine, H., Rizki, H., Latrache, H., and Nabloussi, A.: Effect
of drought and salt stresses on germination and early seedling growth of
different color-seeds of sesame (sesamum indicum), Int. J. Agr. Biol., 18,
1088–1094, https://doi.org/10.17957/ijab/15.0145, 2016.
Homolova, L., Maenovsky, Z., Clevers, J. G. P. W., Garcia-Santos, G., and
Schaeprnan, M. E.: Review of optical-based remote sensing for plant trait
mapping, Ecol. Complex., 15, 1–16,
https://doi.org/10.1016/j.ecocom.2013.06.003, 2013.
Hu, Q., Yang, J., Xu, B., Huang, J., Memon, M. S., Yin, G., Zeng, Y., Zhao,
J., and Liu, K.: Evaluation of global decametric-resolution lai, fapar and
fvc estimates derived from sentinel-2 imagery, Remote Sens., 12, 912,
https://doi.org/10.3390/rs12060912, 2020.
Huang, J., Wang, H., Dai, Q., and Han, D.: Analysis of ndvi data for crop
identification and yield estimation, IEEE J. Sel. Top. Appl., 7, 4374–4384,
https://doi.org/10.1109/JSTARS.2014.2334332, 2014.
Hussain, T., Koyro, H. W., Zhang, W., Liu, X., Gul, B., and Liu, X.: Low
salinity improves photosynthetic performance in panicum antidotale under
drought stress, Front. Plant Sci., 11, 481,
https://doi.org/10.3389/fpls.2020.00481, 2020.
Ionita, M., Tallaksen, L. M., Kingston, D. G., Stagge, J. H., Laaha, G., Van Lanen, H. A. J., Scholz, P., Chelcea, S. M., and Haslinger, K.: The European 2015 drought from a climatological perspective, Hydrol. Earth Syst. Sci., 21, 1397–1419, https://doi.org/10.5194/hess-21-1397-2017, 2017.
Ivanov, V.: Main principles of fruit crop salt resistance determination,
Pochvovedenie, 4, 78–85, 1970.
Jarlan, L., Balsamo, G., Lafont, S., Beljaars, A., Calvet, J. C., and
Mougin, E.: Analysis of leaf area index in the ecmwf land surface model and
impact on latent heat and carbon fluxes: Application to west africa, J.
Geophys. Res.-Atmos., 113, D24117,
https://doi.org/10.1029/2007jd009370, 2008.
Jefferies, R.: Physiology of crop response to drought, in: Potato ecology and modelling of crops under conditions limiting growth, edited by: Haverkort, A. J. and MacKerron, D. K. L., Springer, 61–74, https://doi.org/10.1007/978-94-011-0051-9, 1995.
Jones, E. and van Vliet, M. T. H.: Drought impacts on river salinity in the
southern us: Implications for water scarcity, Sci. Total Environ., 644,
844–853, https://doi.org/10.1016/j.scitotenv.2018.06.373, 2018.
Kriston-Vizi, J., Umeda, M., and Miyamoto, K.: Assessment of the water
status of mandarin and peach canopies using visible multispectral imagery,
Biosyst. Eng., 100, 338–345,
https://doi.org/10.1016/j.biosystemseng.2008.04.001, 2008.
Levy, D.: The response of potatoes (solunum tuberosum l.) to salinity: Plant growth and tuber yields in the arid desert of israel, Ann. Appl. Biol., 120, 547–555, https://doi.org/10.1111/j.1744-7348.1992.tb04914.x, 1992.
Liang, S. and Wang, J.: fraction of absorbed photosynthetically active radiation, chap. 11, in: Advanced remote sensing (second edition), edited by: Liang, S., and Wang, J., Academic Press, 447–476, https://doi.org/10.1016/B978-0-12-815826-5.00011-8, 2020.
Liao, Q., Gu, S. J., Kang, S. Z., Du, T. S., Tong, L., Wood, J. D., and
Ding, R. S.: Mild water and salt stress improve water use efficiency by
decreasing stomatal conductance via osmotic adjustment in field maize, Sci.
Total Environ., 805, 150364,
https://doi.org/10.1016/j.scitotenv.2021.150364, 2022.
López-Lozano, R., Duveiller, G., Seguini, L., Meroni, M.,
García-Condado, S., Hooker, J., Leo, O., and Baruth, B.: Towards
regional grain yield forecasting with 1km-resolution eo biophysical
products: Strengths and limitations at pan-european level, Agr. Forest
Meteorol., 206, 12–32, https://doi.org/10.1016/j.agrformet.2015.02.021, 2015.
Lu, J., Carbone, G. J., Huang, X., Lackstrom, K., and Gao, P.: Mapping the
sensitivity of agriculture to drought and estimating the effect of
irrigation in the united states, 1950–2016, Agr. For. Meteorol., 292–293,
108124, https://doi.org/10.1016/j.agrformet.2020.108124, 2020.
Mahmood, U., Hussain, S., Hussain, S., Ali, B., Ashraf, U., Zamir, S.,
Al-Robai, S. A., Alzahrani, F. O., Hano, C., and El-Esawi, M. A.:
Morpho-physio-biochemical and molecular responses of maize hybrids to
salinity and waterlogging during stress and recovery phase, Plants (Basel),
10, 1345, https://doi.org/10.3390/plants10071345, 2021.
Masante, D. and Vogt, J.: Drought in central-northern europe-august 2018, Report of JRC European Drought Observatory (EDO), https://edo.jrc.ec.europa.eu/documents/news/EDODroughtNews201808_Central_North_Europe.pdf (last access: 26 October 2021), 2018.
McKee, T. B., Doesken, N. J., and Kleist, J.: The relationship of drought frequency and duration to time scales, Proceedings of the 8th Conference on Applied Climatology, California, the United States, 17–22 January 1993, 179–183, 1993
Mi, N., Cai, F., Zhang, Y. S., Ji, R. P., Zhang, S. J., and Wang, Y.:
Differential responses of maize yield to drought at vegetative and
reproductive stages, Plant Soil Environ., 64, 260–267,
https://doi.org/10.17221/141/2018-Pse, 2018.
Ministerie van Economische Zaken en Klimaat: Basisregistratie gewaspercelen (brp), Publieke Dienstverlening Op de Kaart (PDOK) [data set], https://www.pdok.nl/introductie/-/article/basisregistratie-gewaspercelen-brp- (last access: 1 June 2021), 2018.
Mkhabela, M. S., Bullock, P., Raj, S., Wang, S., and Yang, Y.: Crop yield
forecasting on the canadian prairies using modis ndvi data, Agr. Forest
Meteorol., 151, 385–393,
https://doi.org/10.1016/j.agrformet.2010.11.012, 2011.
Mulder, M., Hack-ten Broeke, M., Bartholomeus, R., van Dam, J., Heinen, M., van Bakel, J., Walvoort, D., Kroes, J., Hoving, I., and Holshof, G.: Waterwijzer landbouw: Instrumentarium voor kwantificeren van effecten van waterbeheer en klimaat op landbouwproductie, 2018-48, Stowa, https://edepot.wur.nl/464525 (last accss: 29 November 2021), 2018.
Ors, S. and Suarez, D. L.: Spinach biomass yield and physiological response
to interactive salinity and water stress, Agr. Water Manage., 190, 31–41,
https://doi.org/10.1016/j.agwat.2017.05.003, 2017.
Patane, C., Saita, A., and Sortino, O.: Comparative effects of salt and
water stress on seed germination and early embryo growth in two cultivars of
sweet sorghum, J. Agron. Crop Sci., 199, 30–37,
https://doi.org/10.1111/j.1439-037X.2012.00531.x, 2013.
de Louw, P., Kaandorp, V., Massop, H., and Veldhuizen, A.: Beregening: Deltafact, Amersfoort, Stowa, https://edepot.wur.nl/535694 (last access: 29 November 2021), 2020.
Richter, K., Rischbeck, P., Eitzinger, J., Schneider, W., Suppan, F., and
Weihs, P.: Plant growth monitoring and potential drought risk assessment by
means of earth observation data, Int. J. Remote Sens., 29, 4943–4960, https://doi.org/10.1080/01431160802036268, 2008.
Rozema, J. and Flowers, T.: Ecology. Crops for a salinized world, Science,
322, 1478–1480, https://doi.org/10.1126/science.1168572, 2008.
Sayar, R., Bchini, H., Mosbahi, M., and Khemira, H.: Response of durum wheat
(triticum durum desf.) growth to salt and drought stresses, Czech J. Genet.
Plant. Breed., 46, 54–63, https://doi.org/10.17221/85/2009-CJGPB, 2010.
Schittenhelm, S., Sourell, H., and Lopmeier, F. J.: Drought resistance of
potato cultivars with contrasting canopy architecture, Eur. J. Agron., 24,
193–202, https://doi.org/10.1016/j.eja.2005.05.004, 2006.
Schwalm, C. R., Anderegg, W. R. L., Michalak, A. M., Fisher, J. B., Biondi,
F., Koch, G., Litvak, M., Ogle, K., Shaw, J. D., Wolf, A., Huntzinger, D.
N., Schaefer, K., Cook, R., Wei, Y., Fang, Y., Hayes, D., Huang, M., Jain,
A., and Tian, H.: Global patterns of drought recovery, Nature, 548, 202–205,
https://doi.org/10.1038/nature23021, 2017.
Shinozaki, K., Uemura, M., Bailey-Serres, J., Bray, E., and Weretilnyk, E.: Responses to abiotic stress, in: Biochemistry and molecular biology of plants, edited by: Buchanan, B. B., Gruissem, W., and Jones, R. L., Wiley Blackwell, 1051–1100, ISBN 978-0-470-71422-5, 2015.
Steidle Neto, A. J., Lopes, D. d. C., Silva, T. G. F. d., Ferreira, S. O.,
and Grossi, J. A. S.: Estimation of leaf water content in sunflower under
drought conditions by means of spectral reflectance, Eng. Agric. Environ.
Food, 10, 104–108, https://doi.org/10.1016/j.eaef.2016.11.006,
2017.
Stuyt, L. C. P. M., Blom-Zandstra, M., and Kselik, R. A. L.: Inventarisatie en analyse zouttolerantie van landbouwgewassen op basis van bestaande gegevens, Wageningen environmental research rapport, Wageningen Environmental Research, https://doi.org/10.18174/391931, 2016.
Sun, L., Gao, F., Anderson, M. C., Kustas, W. P., Alsina, M. M., Sanchez,
L., Sams, B., McKee, L., Dulaney, W., White, W. A., Alfieri, J. G., Prueger,
J. H., Melton, F., and Post, K.: Daily mapping of 30 m lai and ndvi for
grape yield prediction in california vineyards, Remote Sens., 9, 317, https://doi.org/10.3390/rs9040317, 2017.
Tao, H., Borth, H., Fraedrich, K., Su, B., and Zhu, X.: Drought and wetness
variability in the tarim river basin and connection to large-scale
atmospheric circulation, Int. J. Climatol., 34, 2678–2684, https://doi.org/10.1002/joc.3867, 2014.
Tokarz, B., Wójtowicz, T., Makowski, W., Jędrzejczyk, R. J., and
Tokarz, K. M.: What is the difference between the response of grass pea
(lathyrus sativus l.) to salinity and drought stress? – a physiological
study, Agronomy, 10, 833, https://doi.org/10.3390/agronomy10060833, 2020.
Trenberth, K. E., Dai, A., van der Schrier, G., Jones, P. D., Barichivich,
J., Briffa, K. R., and Sheffield, J.: Global warming and changes in drought,
Nat. Clim. Change, 4, 17–22, https://doi.org/10.1038/nclimate2067, 2013.
Tucker, C. J.: Red and photographic infrared linear combinations for
monitoring vegetation, Remote Sens. Environ., 8, 127–150, https://doi.org/10.1016/0034-4257(79)90013-0, 1979.
Vannoppen, A., Gobin, A., Kotova, L., Top, S., De Cruz, L., Viksna, A.,
Aniskevich, S., Bobylev, L., Buntemeyer, L., Caluwaerts, S., De Troch, R.,
Gnatiuk, N., Hamdi, R., Reca Remedio, A., Sakalli, A., Van De Vyver, H., Van
Schaeybroeck, B., and Termonia, P.: Wheat yield estimation from ndvi and
regional climate models in latvia, Remote Sens., 12, 2206, https://doi.org/10.3390/rs12142206, 2020.
van Straten, G., Bruning, B., de Vos, A. C., González, A. P., Rozema,
J., and van Bodegom, P. M.: Estimating cultivar-specific salt tolerance
model parameters from multi-annual field tests for identification of salt
tolerant potato cultivars, Agr. Water Manage., 252, 106902, https://doi.org/10.1016/j.agwat.2021.106902, 2021.
Vereecken, H., Weihermuller, L., Jonard, F., and Montzka, C.:
Characterization of crop canopies and water stress related phenomena using
microwave remote sensing methods: A review, Vadose Zone J., 11,
vzj2011.0138ra, https://doi.org/10.2136/vzj2011.0138ra, 2012.
Wagg, C., Hann, S., Kupriyanovich, Y., and Li, S.: Timing of short period
water stress determines potato plant growth, yield and tuber quality, Agr.
Water Manage., 247, 106731, https://doi.org/10.1016/j.agwat.2020.106731,
2021.
Wang, J. L., Huang, X. J., Zhong, T. Y., and Chen, Z. G.: Climate change
impacts and adaptation for saline agriculture in north jiangsu province,
china, Environ. Sci. Policy, 25, 83–93, https://doi.org/10.1016/j.envsci.2012.07.011, 2013.
Weiss, M., and Baret, F.: S2toolbox level 2 products: Lai, fapar, fcover, version 1.1, ESA Contract nr 4000110612/14/I-BG, 52, https://step.esa.int/docs/extra/ATBD_S2ToolBox_L2B_V1.1.pdf (last access: 2 February 2022), 2016.
Weiss, M., Jacob, F., and Duveiller, G.: Remote sensing for agricultural
applications: A meta-review, Remote Sens. Environ., 236, 111402, https://doi.org/10.1016/j.rse.2019.111402, 2020.
Wen, W., Timmermans, J., Chen, Q., and van Bodegom, P. M.: A review of
remote sensing challenges for food security with respect to salinity and
drought threats, Remote Sens., 13, 6, https://doi.org/10.3390/rs13010006, 2020.
Wengert, M., Piepho, H. P., Astor, T., Grass, R., Wijesingha, J., and
Wachendorf, M.: Assessing spatial variability of barley whole crop biomass
yield and leaf area index in silvoarable agroforestry systems using
uav-borne remote sensing, Remote Sens., 13, 2751, https://doi.org/10.3390/rs13142751, 2021.
Wright, I. J., Reich, P. B., and Westoby, M.: Least-cost input mixtures of
water and nitrogen for photosynthesis, Am. Nat., 161, 98–111, https://doi.org/10.1086/344920, 2003.
Yang, L., Jia, K., Liang, S., Liu, M., Wei, X., Yao, Y., Zhang, X., and Liu,
D.: Spatio-temporal analysis and uncertainty of fractional vegetation cover
change over northern china during 2001–2012 based on multiple vegetation
data sets, Remote Sens., 10, 549, https://doi.org/10.3390/rs10040549, 2018.
Zhang, F. and Zhou, G.: Estimation of canopy water content by means of
hyperspectral indices based on drought stress gradient experiments of maize
in the north plain china, Remote Sens., 7, 15203–15223, https://doi.org/10.3390/rs71115203, 2015.
Zhang, F., Zhou, G. S., and Nilsson, C.: Remote estimation of the fraction
of absorbed photosynthetically active radiation for a maize canopy in
northeast china, J. Plant Ecol., 8, 429–435, https://doi.org/10.1093/jpe/rtu027, 2015.
Zhang, H., Han, M., Comas, L. H., DeJonge, K. C., Gleason, S. M., Trout, T.
J., and Ma, L.: Response of maize yield components to growth stage-based
deficit irrigation, Agron. J., 111, 3244–3252, https://doi.org/10.2134/agronj2019.03.0214, 2019.
Zhang, L., Chen, B., Zhang, G., Li, J., Wang, Y., Meng, Y., and Zhou, Z.:
Effect of soil salinity, soil drought, and their combined action on the
biochemical characteristics of cotton roots, Acta Physiol. Plant, 35,
3167–3179, https://doi.org/10.1007/s11738-013-1350-6, 2013.
Zhu, X., Wang, T. J., Skidmore, A. K., Darvishzadeh, R., Niemann, K. O., and
Liu, J.: Canopy leaf water content estimated using terrestrial lidar, Agric.
For. Meteorol., 232, 152–162, https://doi.org/10.1016/j.agrformet.2016.08.016, 2017.
Short summary
A novel approach for evaluating individual and combined impacts of drought and salinity in real-life settings is proposed using Sentinel-2. We found that crop responses to drought and salinity differ between growth stages. Compared to salinity, crop growth is most strongly affected by drought stress and is, in general, further exacerbated when co-occurring with salinity stress. Our approach facilitates a way to monitor crop health under multiple stresses with potential large-scale applications.
A novel approach for evaluating individual and combined impacts of drought and salinity in...
