Ecosystem services related to water supply are now a hot topic in ecology and hydrology. Here, water supply service in the Lancang River basin was evaluated using the newly developed model InVEST. We found the mean annual water supply in Lancang River basin is approximately 7.24E＋10 m3 y-1 with 23.87% from main stream and 76.13% from the tributaries. There is an increasing trend downstream. Grasslands and forests contribute 71.66% of the total water. A comparison of water supply capacity per unit area for ecosystems of different composition indicates that there is a decreasing trend from broad- leafed forest, mixed coniferous and broad-leafed forest, bamboo forest, coniferous forest, shrub forest and grassland. Two-thirds of the total water is provided by an area covering 40% of the total basin area. This study provides guidelines for the efficient management of water resources in the Lancang River basin.
Air temperature is an important climatological variable and is usually measured in meteorological stations.Accurate mapping of its spatial and temporal distribution is of great interest for various scientific disciplines,but low station density and complexity of the terrain usually lead to significant errors and unrepresentative spatial patterns over large areas.Fortunately the current studies have shown that the regression models can help overcome the problem with the help of time series remote sensing data.However,noise induced by cloud contamination and other atmospheric disturbances variability impedes the application of LST data.An improved Savizky-Golay（SG） algorithm based on the LST background library is used in this paper to reconstruct MODIS LST product.Data statistical analysis included 12 meteorological stations and 120 reconstructed MODIS LST images of the period from 2001 to 2010.The coefficient of correlations（R2） for 80% of the stations was higher than 0.5（below 0.5 for only 2 stations） which illustrated that there is a considerably close agreement between monthly mean TA（air temperature） and the reconstructed LST in the Lancang River basin.Comparing to the regression model for every month with only LST data,the regression model with LST and NDVI had higher R2 and RMSE.Finally,the LSTNDVI regression method was applied as an estimate model to produce distributed maps of air temperature with month intervals and 1 km spatial in the Lancang River basin of 2010.
