In Northeast Thailand, the climate change has resulted in erratic rainfall and tem- perature patterns. The region has experienced both periods of drought and seasonal floods with the increasing severity. This study in...In Northeast Thailand, the climate change has resulted in erratic rainfall and tem- perature patterns. The region has experienced both periods of drought and seasonal floods with the increasing severity. This study investigated the seasonal variation of vegetation greenness based on the Normalized Difference Vegetation Index （NDVI） in major land cover types in the region. An assessment of the relationship between climate patterns and vegeta- tion conditions observed from NDVI was made. NDVI data were collected from year 2001 to 2009 using multi-temporal Terra MODIS Vegetation Indices Product （MOD13Q1）. NDVI pro- files were developed to measure vegetation dynamics and variation according to land cover types. Meteorological information, i.e. rainfall and temperature, for a 30 year time span from 1980 to 2009 was analyzed for their patterns. Furthermore, the data taken from the period of 2001-2009, were digitally encoded into GIS database and the spatial patterns of monthly rainfall and temperature maps were generated based on kriging technique. The results showed a decreasing trend in NDVI values for both deciduous and evergreen forests. The highest productivity and biomass were observed in dry evergreen forests and the lowest in paddy fields. Temperature was found to be increasing slightly from 1980 to 2009 while no significant trends in rainfall amounts were observed. In dry evergreen forest, NDVI was not correlated with rainfall but was significant negatively correlated with temperature. These re- sults indicated that the overall productivity in dry evergreen forest was affected by increasing temperatures. A vegetation greenness model was developed from correlations between NDVI and meteorological data using linear regression. The model could be used to observe the change in vegetation greenness and dynamics affected by temperature and rainfall.展开更多
Vegetation information is seldom considered in lumped conceptual rainfall-runoff models.This paper uses two modified rainfall-runoff models,the Xinanjiang-ET and SIMHYD-ET models in which vegetation leaf area index is...Vegetation information is seldom considered in lumped conceptual rainfall-runoff models.This paper uses two modified rainfall-runoff models,the Xinanjiang-ET and SIMHYD-ET models in which vegetation leaf area index is incorporated,to investigate impacts of vegetation change and climate variability on streamflow in a Southern Australian catchment,the Crawford River experimental catchment,where Tasmanian blue gum plantations were introduced gradually from 1998 till 2005.The Xinanjiang-ET and SIMHYD-ET models incorporate remotely-sensed leaf area index(LAI) data obtained from the Advanced Very High Resolution Radiometer(AVHRR) on board NOAA polar orbiting satellites.Compared to the original versions,the Xinanjiang-ET and SIMHYD-ET models show marginal improvements in runoff simulations in the pre-plantation period(1882-1997).The calibrated Xinanjaing-ET and SIMHYD-ET models are then used to simulate plantation impact on streamflow in the post-plantation period.The total change in streamflow between the pre-plantation and post-plantation periods is 32.4 mm/a.The modelling results from the two models show that plantation reduces streamflow by 20.5 mm/a,and climate variability reduces streamflow by 11.9 mm/a.These results suggest that increase in plantations can reduce streamflow substantially,even more than climate variability.展开更多
基金supported by the Faculty of Engineering and the Higher Education Research Promotion and National Research University Project of ThailandOffice of the Higher Education Commission and the Faculty of Engineering,Khon Kaen University,Thailand
文摘In Northeast Thailand, the climate change has resulted in erratic rainfall and tem- perature patterns. The region has experienced both periods of drought and seasonal floods with the increasing severity. This study investigated the seasonal variation of vegetation greenness based on the Normalized Difference Vegetation Index （NDVI） in major land cover types in the region. An assessment of the relationship between climate patterns and vegeta- tion conditions observed from NDVI was made. NDVI data were collected from year 2001 to 2009 using multi-temporal Terra MODIS Vegetation Indices Product （MOD13Q1）. NDVI pro- files were developed to measure vegetation dynamics and variation according to land cover types. Meteorological information, i.e. rainfall and temperature, for a 30 year time span from 1980 to 2009 was analyzed for their patterns. Furthermore, the data taken from the period of 2001-2009, were digitally encoded into GIS database and the spatial patterns of monthly rainfall and temperature maps were generated based on kriging technique. The results showed a decreasing trend in NDVI values for both deciduous and evergreen forests. The highest productivity and biomass were observed in dry evergreen forests and the lowest in paddy fields. Temperature was found to be increasing slightly from 1980 to 2009 while no significant trends in rainfall amounts were observed. In dry evergreen forest, NDVI was not correlated with rainfall but was significant negatively correlated with temperature. These re- sults indicated that the overall productivity in dry evergreen forest was affected by increasing temperatures. A vegetation greenness model was developed from correlations between NDVI and meteorological data using linear regression. The model could be used to observe the change in vegetation greenness and dynamics affected by temperature and rainfall.
文摘Vegetation information is seldom considered in lumped conceptual rainfall-runoff models.This paper uses two modified rainfall-runoff models,the Xinanjiang-ET and SIMHYD-ET models in which vegetation leaf area index is incorporated,to investigate impacts of vegetation change and climate variability on streamflow in a Southern Australian catchment,the Crawford River experimental catchment,where Tasmanian blue gum plantations were introduced gradually from 1998 till 2005.The Xinanjiang-ET and SIMHYD-ET models incorporate remotely-sensed leaf area index(LAI) data obtained from the Advanced Very High Resolution Radiometer(AVHRR) on board NOAA polar orbiting satellites.Compared to the original versions,the Xinanjiang-ET and SIMHYD-ET models show marginal improvements in runoff simulations in the pre-plantation period(1882-1997).The calibrated Xinanjaing-ET and SIMHYD-ET models are then used to simulate plantation impact on streamflow in the post-plantation period.The total change in streamflow between the pre-plantation and post-plantation periods is 32.4 mm/a.The modelling results from the two models show that plantation reduces streamflow by 20.5 mm/a,and climate variability reduces streamflow by 11.9 mm/a.These results suggest that increase in plantations can reduce streamflow substantially,even more than climate variability.
