Abstract
Palmer Drought Severity Index (PDSI) is the most effective and well-acknowledged drought severity index that particularly determines the long-term drought conditions over the forest and other terrestrial ecosystems. However, the sensitivity of PDSI has not been explored yet based on productivity (i.e., Gross Primary Productivity (GPP)), biophysical parameters (i.e., biomass—Leaf Area Index (LAI) and Enhanced Vegetation Index (EVI) and greenness content—Normalized Difference Vegetation Index (NDVI)), and absorbed solar radiation by plants (i.e., fraction of Absorbed Solar Radiation (fAPAR)) over a humid-subtropical forest ecosystem. In this study, the sensitivity of the PDSI was analyzed through uncertainty and error estimation modeling from long-term (2015–2019) MODIS GPP and reflectance data using Google Earth Engine (GEE) over a humid-subtropical forest region of Arunachal Pradesh, India. It was experimentally observed that EVI was the most sensitive parameter to the PDSI in long-run observation based on a low uncertainty (2.39–3.01%) and error (0.07–0.12) compared to the other parameters. Besides, EVI had a strong agreement with PDSI compared to GPP, NDVI, LAI, and fAPAR, where the Pearson’s r ranged from −0.87 to −0.63, except 2015. Hence, it is stated that EVI is the simple, effective, and most complementary indicator for assessing the PDSI over the forest regions of a tropical ecosystem. This study showed that EVI might be a promising tool for effectively evaluating long-term drought impacts on the forest ecosystem that indicates the actual water deficit-induced stress conditions.
Highlights
Drought is the dryness condition of the environment that creates ecological stress due to lack of precipitation and shortages in water supply for plant growth
Based on the long-term analysis from this experimental study over the sub-tropical forest region of the Arunachal Pradesh state of India, it was observed that EVI was the most sensitive parameter to Palmer Drought Severity Index (PDSI) in a long-term observation based on promising correlation, low uncertainty, and low error, where most of the existing studies on drought severity showed a high sensitivity of GPP and NDVI
It is stated that EVI is the simple, effective, and most complementary indicator for assessing PDSI over forest regions of a tropical ecosystem
Summary
Drought is the dryness condition of the environment that creates ecological stress due to lack of precipitation and shortages in water supply for plant growth. The Palmer Drought Severity Index (PDSI) [1] is one of the most effective, well-acknowledged, and widely used drought severity index that determines the long-term drought conditions over the forest and other terrestrial ecosystems. The PDSI is based on the demand and supply concept of the water balance model, taking consideration precipitation deficit and includes local temperature and soil moisture anomalies to assess relative dryness [2]. Several studies were already conducted on the application of PDSI, the sensitivity of PDSI has not been explored yet based on productivity 2020, 1, Firstpage-Lastpage; doi: FOR PEER REVIEW www.mdpi.com/journal/environsciproc Proc. 2020, 1, Firstpage-Lastpage; doi: FOR PEER REVIEW www.mdpi.com/journal/environsciproc
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call