摘要:利用CASA模型估算植被净初级生产力（NPP）应用广泛，但其精度仍然有待提高。基于地理因子回归方法（AMMRR）和地表水分指数（LSWI）对CASA模型的两个关键参数：温度胁迫系数和水分胁迫系数进行校正，再估算NPP并分析了校正对植被NPP及各因子与NPP关系的影响。研究表明：（1）校正能有效提高CASA模型的估算精度，校正后NPP总量为34.29 TgC/a，原CASA模型高估了0.23 TgC/a。（2）研究不仅可以校正地形对NPP的影响，还可以校正平坦地形下人类活动区NPP的影响；在高海拔、地形起伏较大的区域以及人类活动地区，校正对NPP估算影响较大，绿洲区原模型存在高估。（3）校正对生长季的影响大于非生长季；坡度对NPP影响较大，坡度越大原模型高估越多；校正前高估了阳坡NPP，低估了阴坡NPP。



Abstract:The CASA model is widely used in estimating vegetation net primary productivity (NPP), but its accuracy needs to be improved. Based on the geographical factor regression method (AMMRR) and land surface water index (LSWI), this study aimed to correct the temperature stress coefficient and water stress coefficient, two key parameters of CASA model. Next, we continued to estimate NPP and analyze the effect of the correction on vegetation and on the relationship between NPP and other factors. Results showed that:(1) The correction could effectively improve the estimation accuracy of the CASA model. The amount of corrected NPP was 34.29 TgC/a, but the original NPP was 34.52 TgC/a; therefore, the NPP of the original model was overestimated by 0.23 TgC/a. (2) This method can not only correct the influence of terrain on NPP, but also corrects the impact of human activities areas on NPP under flat terrain. In areas with high altitude, large topographic relief, as well as in human activities areas, the correction had a large impact on NPP estimation, and the original model of the oasis area was overvalued. (3) The effect of correction on growth season was greater than that during the non-growth season. Slope had a substantial influence on NPP, and the higher the slope was, the greater the overestimation of the original model. Before correction, sunny slope NPP values were overestimated, whereas, the shady slope NPP values were underestimated.





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