Drought’s trends over continental Chile using climatic variables of water demand and supply, soil moisture, and vegetation productivity

Francisco Zambrano

francisco.zambrano@umayor.cl

Francisco Meza

fmeza@uc.cl

Nicolas Raab

nraab@uc.cl

Iongel Duran-Llacer

iongel.duran@umayor.cl

Motivation

• Global warming has increased the frequency and intensity of drought, according to the AR6 of the IPCC (Calvin et al. 2023).

• Calvin et al. (2023) suggests that rising temperatures will increase the extent, frequency, and severity of agricultural and ecological droughts.

• North-central Chile has faced a persistent precipitation deficit since 2010, defined as a megadrought (Garreaud et al. 2017).

Objective

We aim to assess across continental Chile:

1. short- to long-term temporal trends in multi-scalar drought indices of water demand, water supply, and soil moisture; and vegetation productivity;
2. the relationship of vegetation productivity with drought indices.

Study Area

Continental Chile

Land cover persistent surface area (>80%)
(2001-2022)

Note: Derived from MCD12Q1.061 (MODIS)

Data

Analysis

1) Trends analysis

• Significance of the trend: Non-parametric test of Mann-Kendall (Kendall 1975).
• Magnitude of the trend: Sen’s slope (Sen 1968).
  • Water demand and supply drought indices (SPI, SPEI, EDDI, and SSI) for 1981-2023
    
  • Vegetation productivity (zcNDVI) for 2000-2023 over the unchanged land cover.

2) Relationship of zcNDVI with drought indices

• Pixel-to-pixel correlation between the drought indices for short-term (1, 3, and 6 mnths) to long-term (12, 24, and 36 mnths) with zcNDVI..
• Resulting in two raster maps:
  
  1. values of the time scale that reached the maximum correlation per drought index and
     
  2. magnitude of the correlation (r).

Results: Trends in drought indices

Results: Trends in zcNDVI

Results: drought indices vs zcNDVI

Time-scales that reached the maximum r-squared

Coefficient of correlation (r)

Summary and outlook

Trends

• We found a significant trend toward decreasing water supply in most of the Chilean territory.

• The whole country showed an increase in water demand due to increasing temperatures.

• The magnitude of the trends become stronger for longer time scales.

• The change in vegetation productivity has been severe in the north-central part of the country.

Correlation of drought indices and zcNDVI

• The anomaly in soil moisture over 12 months is the main variable explaining the change in vegetation productivity (r-squared = ~0.5 in north-central Chile).

• The variation in AED appears to intensify the drought impact on vegetation productivity.

Outlook

• In future works, we will seek to analyze the interaction between drought trends (demand, supply, and soil moisture) and land cover changes.

Acknowledgment

The National Research and Development Agency of Chile (ANID) funded this work through the following projects:
- Drought Emergency FSEQ210022
- Fondecyt Regular N°121056
- Fondecyt de Inicación N°11190360
- Fondecyt Postdoctorado N°3230678

Thank you!

https://odes-chile.org/app/unidades
https://www.linkedin.com/company/odes-chile/
_odeschile
@odes_chile
francisco.zambrano@umayor.cl

References

Calvin, Katherine, Dipak Dasgupta, Gerhard Krinner, Aditi Mukherji, Peter W. Thorne, Christopher Trisos, José Romero, et al. 2023. “IPCC, 2023: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (Eds.)]. IPCC, Geneva, Switzerland.” Intergovernmental Panel on Climate Change (IPCC). https://www.ipcc.ch/report/ar6/syr/.

Garreaud, René, Camila Alvarez-Garreton, Jonathan Barichivich, Juan Pablo Boisier, Duncan Christie, Mauricio Galleguillos, Carlos LeQuesne, James McPhee, and Mauricio Zambrano-Bigiarini. 2017. “The 2010-2015 Mega Drought in Central Chile: Impacts on Regional Hydroclimate and Vegetation.” Hydrology and Earth System Sciences Discussions 2017: 1–37. https://doi.org/10.5194/hess-2017-191.

Kendall, Mann. 1975. Rank Correlation Methods (4th Ed. 2d impression). Griffin.

Sen, Pranab Kumar. 1968. “Estimates of the Regression Coefficient Based on Kendall’s Tau.” Journal of the American Statistical Association 63 (324): 1379–89. https://doi.org/10.1080/01621459.1968.10480934.