Modeling net primary productivity of terrestrial ecosystems in the semi-arid climate of the Mongolian Plateau using LSWI-based CASA ecosystem model |
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| Institution: | 1. Institute of Soil and Water Conservation, Northwest A&F University, Yangling, Shaanxi 712100, China;2. Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling, Shaanxi 712100, China;3. The Global Change Research Institute, School of Life Sciences, Nanjing University, Nanjing 210093, China;4. The Center for Global Change & Earth Observations, Michigan State University, East Lansing 48823, USA;5. Department of Environmental Science, Faculty of Agricultural and Environment, the University of Sydney, Sydney 2006, Australia;1. College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China;2. School of Architecture and Design, Beijing Jiaotong University, Beijing 100044, China;3. Research School of Arid Environment & Climate Change, Lanzhou University, Lanzhou 730000, China;4. Ministry of Education Key Laboratory of Western China''s Environmental System, Lanzhou University, Lanzhou 730000, China;5. Collaborative Innovation Centre for Arid Environments and Climate Change, Lanzhou University, Lanzhou 730000, China |
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| Abstract: | Since the estimate of moisture stress coefficients (MSC) in the current Carnegie-Ames-Stanford-Approach (CASA) model still requires considerable inputs from ground meteorological data and many soil parameters, here we present a modified CASA model by introducing the land-surface water index (LSWI) and scaled precipitation to model the vegetation net primary productivity (NPP) in the arid and semiarid climate of the Mongolian Plateau. The field-observed NPP data and a previously proposed model (the Yu-CASA model) were used to evaluate the performance of our LSWI-based CASA model. The results show that the NPP predicted by both the LSWI-based CASA model and the Yu-CASA model showed good agreement with the observed NPP in the grassland ecosystems in the study area, with coefficients of determination of 0.717 and 0.714, respectively. The LSWI-based CASA model also performed comparably with the Yu-CASA model at both biome and per-pixel scales when keeping other inputs unchanged, with a difference of approximately 16 g C in the growing-season total NPP and an average value of 2.3 g C bias for each month. This indicates that, unlike an earlier method that estimated MSC based entirely on climatic variables or a soil moisture model, the method proposed here simplifies the model structure, reduces the need for ground measurements, and can provide results comparable with those from earlier models. The LSWI-based CASA model is potentially an alternative method for modelling NPP for a wide range of vegetation types in the Mongolian Plateau. |
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| Keywords: | Net primary productivity Land-surface water index CASA model Mongolian Plateau (semi-) Arid climate |
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