Assessment of vegetation drought using MODIS derived VCI and CHIRPS precipitation data: Case study in Taung Kyune reserved forest in Myanmar

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1 7th International Conference on Sustainable Energy and Environment (SEE 18): 8-3 November 18, Bangkok, Thailand Assessment of vegetation drought using MODIS derived VCI and CHIRPS precipitation data: Case study in Taung Kyune reserved forest in Myanmar Kyu Kyu Sein 1,, Amnat Chidthaisong 1,,*, Uday Pimple 1, 1 The Joint Graduate School of Energy and Environment King Mongkut s University of Technology Thonburi (JGSEE KMUTT), Bangkok, Thailand. Center for Energy Technology and Environment, Ministry of Education, Bangkok, Thailand. Abstract: Drought is projected to be intensified under future climate change. It affects on forest ecosystem services including carbon exchange process, and leads to increase greenhouse gases in the atmosphere. Developing effective monitoring system is one of the options among many to cope with the adverse impacts of droughts. The present study analyses the correlations between MODIS derived Vegetation Condition Index (VCI) through Normalized Vegetation Index (NDVI), and Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data to understand the response of tropical forest in Myanmar to meteorological drought during the period 31. The was computed at different time steps of 1,3,6,9, and 1 months using monthly CHIRPS data. The VCI was correlated to the and it was observed that response of VCI is most strongly correlated with 3-month and 6-month. The results indicate that, the area was severely affected by drought in the year 1 with of -1.87, while extreme wet year in 11 with of during study period. As a result, it is preliminary concluded that VCI and CHIRPS are well correlated and could provide near real time information on vegetation stress, and VCI could give future indicator of occurrence and severity of drought affected areas. Keywords: Vegetation Drought; MODIS; VCI; ; Taung Kyune; Myanmar * Corresponding author. Tel.: , Fax: address: amnat_c@jgsee.kmutt.ac.th 1. Introduction Drought is a natural phenomenon and recurring climate events mostly linked to the deficiency of precipitation relative to reference condition. Under global climate change, it is projected to be intensified and more severe, which will impact on many forest systems and associated ecosystem disturbances such as insects, diseases, forest die-off, forest fire, and tree mortality (Allen et al., 1; IPCC, 7). Previous studies (VanMantgem et al., 9; Wang et al., 1; Zhang et al., 13) reported that growing threats to carbon sinks have unexpectedly increased in the past decades as a result of tree mortality caused by rising temperatures and increasing drought throughout the world. Therefore, the need for suitable assessment of drought impacts and monitoring becomes critically important. Drought intensity, duration, and extent can be monitored using various station-based and satellitebased drought indices. Drought indices such as the Palmer Drought Severity Index (PDSI), or the Standardized Precipitation Index () have been used to monitor and assess drought (Domenikiotis and Dalezios, ). Among them, is a useful index to monitor meteorological drought which can be determined drought severity levels and better distinguish between abnormal wetness and dryness than the PDSI (Thavorntam et al., 15). Beside the station-based drought indices, drought impact on vegetation has been observed through satellite-based drought indices, such as Normalized Difference Vegetation Index (NDVI), and the Vegetation Condition Index (VCI). NDVI has been widely used for identifying vegetation conditions such as healthy and un-healthy vegetation while VCI was used to detect the vegetation condition from extremely condition to optimal conditions (Tucker, 1979; Kogan, 1995). Moreover, the correlation between vegetation drought and meteorological drought was proved to better capturing the spatiotemporal variations of drought impact on vegetation (Jain et al., 9; Vicente-Serrano, 7). Myanmar has been experienced an increase in prevalence of drought events. The moderate intensity of drought years was frequent in 198s and 199s while severe droughts have increased in frequency from 199 to. Such severe drought diminished water resources and impacts on the 3

2 7th International Conference on Sustainable Energy and Environment (SEE 18): 8-3 November 18, Bangkok, Thailand agricultural fields as well as forest degradation in the year 1 (NECC, 1). Thus, there is a need to make an effort to monitor drought for the preparedness and mitigation which can help the decision makers to reduce the effect of drought in agricultural and forest ecosystem. Therefore, this study tries to assess forest response to drought and correlation between satellite drought and meteorological drought which can be used for drought monitoring in Myanmar.. Methodology.1 Study area Taung Kyune reserved forest area is situated in Patheingyi Township, Mandalay, northeast of dry zone area in Myanmar. This region is dry for the most of the year except the rainy season, and exhibits a semi-arid climate. Rainfall in this region occurs mainly during May to October followed by a prolonged dry period between November to April with annual mean rainfall between 5 mm to 8 mm. The average temperature range is 15ºC to ºC with the highest temperature usually occurs in April. The elevation ranges between 1 m to 168 m with rocky soil type. Forest in this area is dry upper mixed deciduous forest with the area coverage of 3,36 Acre (13,381.7 ha). In recent years, environmental deterioration has become significant in this region due to speedy deforestation contributed by agriculture expansion, grazing and excessive cutting for fuel wood and wood supplies.. Data used Moderate Resolution Imaging Spectroradiometer (MODIS) of surface reflectance 8 Day L3 Global 5m (MOD9Q1) and Global 5m (MOD9A1) for the period 31, and Climate Hazards group InfraRed Precipitation with Stations (CHIRPS) of were used to derived correlations between MODIS VCI and precipitation..3 Methods MODIS pre-processing steps of cloud mask extraction, cloud removing and replacing, and median smoothing were applied for all images using method by Hoan and Ryutaro (13). Tung Kyune Reserved Forest area was extracted from Land use map that was collected from the Forest Department of Myanmar. Normalized Difference Vegetation Indices (NDVI) is one of the most widely used vegetation indices and that were used as input data of this study (Tucker, 1979). Time series NDVI for 31 is calculated as the normalizing of the spectral reflectance of the near infrared (NIR) and visible (RED) channel using the following (Tucker, 1979); NDVI = NIR RED NIR+RED Eq. (1) Vegetation Condition Index (VCI) through NDVI was computed to monitor forest dynamics due to water stress using the formula below (Kogan and Sullivan, 1993); VCI = NDVI j NDVI min NDVI max NDVI min 1 Eq. () where, NDVI max and NDVI min represent time series maximum and minimum NDVI of each pixel a nd NDVI j represents the current NDVI. VCI range is between -1% and higher VCI values corres -ponds to a favourable moisture condition and represent as healthy vegetation. Standardized Precipitation Index () developed by Mckee et al. (1993) was used to monitor meteorological drought for different time-steps (one month;-1, three month; -3, six month; -6, nine month; -9, and twelve month; -1) using monthly aggregated Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) data. In addition, the Pearson s correlation coefficient was used to measure the linear correlation between satellite drought (VCI) and meteorological drought () in order to find out the driving forces of vegetation changes (Guo et al., 1). 33

3 th International Conference on Sustainable Energy and Environment (SEE 18): 8-3 November 18, Bangkok, Thailand 3. Results and discussion The yearly precipitation pattern shows that the study area has received highest precipitation in 11. The trend also observed that moderate to severe drought occurred in 3 and 1, the entire study area suffered with drought. In other years 6, 7, 8, 11, 1, and 13 were drought free, as moderate to very wet conditions. The rest of the years,, 5, 9, and 1 as normal. The severe drought was observed in the year 1 with value -1.87, while extreme wet in 11 with of (Fig. 1) month- VCI Fig. 1 Time series of VCI (green line) and 1-month (blue bar) at study area (31) The VCI fluctuations in forest area is mainly due to fluctuations in precipitation amounts, and the yearly trends of VCI and CHIRPS precipitation data suggested that the forest in the study area had been faced with moderate to extreme drought in 1, with the lowest VCI range of 9.8%. The VCI value increased and reached maximum value between % in 6, 7, and 8, 11 that indicated the similar pattern of increased in precipitation amount. VCI trend was dramatically fluctuated with the same upward and downward trends of. The historical results of climate analysis show two consecutive drought years in 91 (Fig. 1). Thus, VCI values were significant dropped in 1 which could be the effects of insufficient precipitation amount in 9. Therefore, VCI is likely to be dependent on the existing soil moisture conditions and well correlated with multiple time-steps of. As long as the precipitation increased, the VCI range towards increased trend in 11. In facts, the forest in study area was under a prolonged dry condition through the whole year in 1 whereas healthy condition of forest in 11 was observed. Fig. presents the annual average of VCI range in Taung Kyune reserved forest area during the period 31. The spatial VCI distribution confirm that in the year 5, 9, 1, 13, and 1 almost all parts of the study area were affected by drought condition with VCI less than % were demarcated (Fig. c, g, h, k, and l). According to the ENSO index, the year 1, 5, 9, and 1 were considered as El Niño years, which affect extreme to light drought in the whole study area, and VCI were observed worst condition. Among them, 1 was strongest El Niño, the VCI range 7-58 % and no greenest pixels in the whole study area were observed (Fig. h). Time (a) (b) (c) (d) (e) (f) (g) (h) (i) (j) (k) (l) Fig. Spatial temporal variation of annual VCI in Taung Kyune Reserved Forest Area (31) 3

4 7th International Conference on Sustainable Energy and Environment (SEE 18): 8-3 November 18, Bangkok, Thailand Fig. 3 illustrates the correlations between VCI with multiple time-steps. VCI has the strongest significant correlations (p<.1) with 3-month and 6-month, and the weakness at 1-month time-steps across all indices. The calculated result of r value in 6-month (r =.33, p <.1) was noticeable higher than 3-month (r =.9, p<.1) (Fig. 3b and c). The 1-month could have only a minor impact on vegetation properties compared with the other time-steps. Generally, there are much stronger relationships between the VCI and 6-month in this region as the highest coefficients of determination more than 6% of the variance in the VCI. Thus, the use of MODIS VCI and different time-steps of could be a good indicator for monitoring of drought conditions. 1month- 3month- (a) (b) (c) 6month- r =.165 (p=.7) (d) 9month- - r =.9 (p<.1) r =.3 (p<.1) month- (e) - r =.1 (p=.3) r =.139 (p=.9) Fig. 3 Correlation between VCI with values at different time-steps; (a) 1-month, (b) 3-month, (c) 6-month, (d) 9-month, and (e) 1-month. All the correlation are significant at 95% confidence level.. Conclusion The results from this study indicate that the VCI and different time-steps (1-month, 3-month, 6- month, 9-month, 1-mongh) of derived CHIRPS are well correlated. The VCI had the strongest significant correlation with the highest R values in 6-month time-steps. Thus, the use of MODIS VCI and 6-month can be a good indicator for monitoring of drought conditions Moreover, the analysis also showed that this area had faced with three extreme drought conditions in 1989, 1998, and 1. It could be further concluded that VCI and CHIRPS could provide near real time information of drought monitoring on vegetation stress conditions of this region in Myanmar. However, more analysis on relationship with other climate factors and different topographic conditions are needed to improve drought monitoring and assessments. Acknowledgement The authors wish to acknowledge the supports of the project Analysis of historical forest carbon changes in Myanmar and Thailand and the contribution of climate variability and extreme events funded by USAID and National Science Foundation (NSF) USA under Partnerships for Enhanced Engagement in Research (PEER) program. The authors also would like to express their deepest gratitude to the Forest Department, Nay Pyi Taw, and Myanmar for providing landuse/ landcover data of Myanmar. 35

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