Long-Term Sensitivity Analysis of Palmer Drought Severity Index (PDSI) through Uncertainty and Error Estimation from Plant Productivity and Biophysical Parameters

Abstract

An unprecedented number of wildfire events during 2019 throughout the Brazilian Amazon caught global attention, due to their massive extent and the associated loss in the Amazonian forest—an ecosystem on which the whole world depends. Such devastating wildfires in the Amazon has strongly hampered the global carbon cycle and significantly reduced forest productivity. In this study, we have quantified such loss of forest productivity in terms of gross primary productivity (GPP), applying a comparative approach using Google Earth Engine. A total of 12 wildfire spots have been identified based on the fire’s extension over the Brazilian Amazon, and we quantified the loss in productivity between 2018 and 2019. The Moderate Resolution Imaging Spectroradiometer (MODIS) GPP and MODIS burned area satellite imageries, with a revisit time of 8 days and 30 days, respectively, have been used for this study. We have observed that compared to 2018, the number of wildfire events increased during 2019. But such wildfire events did not hamper the natural annual trend of GPP of the Amazonian ecosystem. However, a significant drop in forest productivity in terms of GPP has been observed. Among all 11 observational sites were recorded with GPP loss, ranging from −18.88 gC m−2 yr−1 to −120.11 gC m−2 yr−1, except site number 3. Such drastic loss in GPP indicates that during 2019 fire events, all of these sites acted as carbon sources rather than carbon sink sites, which may hamper the global carbon cycle and terrestrial CO2 fluxes. Therefore, it is assumed that these findings will also fit for the other Amazonian wildfire sites, as well as for the tropical forest ecosystem as a whole. We hope this study will provide a significant contribution to global carbon cycle research, terrestrial ecosystem studies, sustainable forest management, and climate change in contemporary environmental sciences.

Comparison of different drought monitoring indices in different climatic conditions in Iran

“…Zuzulova and Vido (2018) also showed a strong correlation between drought indices from January to September in Slovakia, and Luo et al (2020) reported a positive correlation between NDVI and SPEI drought indices in parts of northern China with dry climates. Similar results were reported by Peled et al (2010), Choi et al (2013), andShen et al (2019) in northern China, as well as Wang et al (2020) and Ghosh et al (2021) in parts of Europe.…”