A Vegetation Drought Stress Index Based On Solar-induced Chlorophyll Fluorescence

Drought events,which exbite an extremely negative impact on agriculture and socio-economic activities,have become more frequent due to global warming during recent decades.Sustained drought events can affect terrestrial ecological balances,reducing productivity of ecosystems sigificantly.Long-term drought can cause vegetation degradation because of the water stress,which leads to large-scale changes in vegetation physiological state.It is very important to understand the response of vegetation to water stress by monitoring large-scale drought events timely and accurately.The development of remote sensing technology has made it possible to monitor the physiological status of vegetation under drought conditions at global and reginal scales.The traditional remote sensing vegetation indices can measure the vegetation greenness and energy absorption,which can indirectly indicate the photosynthesis of vegetation.?s has been widely used in drought monitoring in many studies.However,the greenness-based vegetation indices cannot accurately capture the dynamic response of vegetation under different drought conditions.The newly obtained satellite solar-induced chlorophyll fluorescence is proved to be directly related to the photosynthesis efficiency of vegetation,which can more directly and accurately monitor the impact of drought events on vegetation.This paper uses solar-induced chlorophyll fluorescence data,vegetation indices data(?s),meteorological data,total water storage data from satellite GRACE,XCO2 data and drought indices data to monitor the droughts occurred in Southeast Asia,Central and Southern United States.This study aims to provide a method for better understanding of extreme climate events and the effects of drought on ecosystems.The main research contents and conclusions are as follows:(1)Using ?s,SIF and other climate data to detect the effects of 2015/16 El Nino-induced drought on the photosynthesis of crops and evergreen broadleaf forests in Southeast Asian.The results show that SIF is more sensitive to water stress than traditional ?s.Therefore,satellite SIF data can be used to predict vegetation response to water stress and high temperatures.SIF data is more suitable than vegetation index to be an indicator for characterizing and monitoring drought in tropical vegetated regions.In addition,SIF yield(SIFyield),which is eliminated the effects of radiation,response to drought becomes more pronounced,while changes on vegetation greenness may not be able to quickly reflect information of vegetation under drought conditions.But changes on fluorescence yield will respond quickly to water stress.Therefore,SIFyield can be a suitable indicator for monitoring changes in vegetation function during drought.(2)Based on the SIF data and XCO2 data,we find that carbon emissions increased in Southeast Asia in 2015 and 2016,indicating a strong negative correlation between XCO2 and SIF Satellite SIF data can indirectly reflect changes in regional CO2,especially when vegetation is under water stress.Water stress usually causes the stomatal closure of the vegetation,which can slow photosynthesis and reduce atmospheric CO2 absorption.Therefore,we can better understand the potential dynamic processes of CO2 by using satellite observations of SIF data.(3)SIFyieid is a suitable indicator for monitoring changes in vegetation function during drought.Therefore,this paper proposes a new remote sensing drought index SSTI,which linearly combined SIFyiedd,temperature condition index(TCI)and soil moisture index(SMCI).We evaluate the performance of the SSTI index in monitoring the drought in the Great Plains.We calculate the correlation between SSTI and the situ drought index and compare SSTI with other remote sensing drought indices in changes of spatial distribution.The study concludes that the SSTI index can monitor the drought extent and accurately analyze the drought severity.