A remote sensing-based net primary productivity model for semi-arid grasslands: model description and validation

This paper presents a production efficiency model (PEM) of regional net primary productivity parameterized with remote sensing information, and tests it for inner Mongolia semi-arid grassland. The model uses the concept of light use efficiency (LUE) that solar radiation is absorbed by plants to provide energy for photosynthesis, while change of air temperature, plant-water deficits and respiration reduce the efficiency of light usage, and the model is modified to better represent regional environmental characteristics of the semi-arid grasslands on a month time step. In this study, high quality weather and field data were introduced to calibrate model parameters, and the ratio of aboveground biomass and underground biomass was regarded as a constant. Accuracy of model products, such as leaf area index (LAI), aboveground biomass and aboveground NPP, was assessed by comparing them with field measurement. Aboveground NPP simulated has good linear relation with the measured (R²=0.9698), and the absolute error of estimates is mostly less than 11% for no grazing and moderate grazing areas. Moreover, the model was used to evaluate aboveground NPP in response to water, temperature and grazing pressure. Results show that the response is consistent with the actual environmental and climatic condition of semi-arid grassland, the water-stress is the main reason of the decrease in light use efficiency, and grazing pressure can not be neglected especially for overgrazing areas.