Remote sensing Penman-Monteith model to estimate catchment evapotranspiration considering the vegetation diversity

摘要

A new method for calculating evaporation is proposed, using the Penman-Monteith (P-M) model with remote sensing. This paper achieved the effective estimation to daily evapotranspiration in the Ziya river catchment by using the P-M model based on MODIS remote sensing leaf area index and respectively estimated plant transpiration and soil evaporation by using coefficient of soil evaporation. This model divided catchment into seven different sub-regions which are prairie, meadow, grass, shrub, broad-leaved forest, cultivated vegetation, and coniferous forest through thoroughly considering the vegetation diversity. Furthermore, optimizing and calibrating parameters based on each sub-region and analyzing spatio-temporal variation rules of the model main parameters which are coefficient of soil evaporation f and maximum stomatal conductance g (sx) . The results indicate that f and g (sx) calibrated by model are basically consistent with measured data and have obvious spatio-temporal distribution characteristics. The monthly average evapotranspiration value of simulation is 37.96 mm/mon which is close to the measured value with 33.66 mm/mon and the relative error of simulation results in each subregion are within 11 %, which illustrates that simulated values and measured values fit well and the precision of model is high. In addition, plant transpiration and soil evaporation account for about 84.64 and 15.36 % respectively in total evapotranspiration, which means the difference between values of them is large. What is more, this model can effectively estimate the green water resources in basin and provide effective technological support for water resources estimation.