کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
4464670 1313841 2016 10 صفحه PDF ندارد دانلود رایگان
عنوان انگلیسی مقاله
Modeling net primary productivity of terrestrial ecosystems in the semi-arid climate of the Mongolian Plateau using LSWI-based CASA ecosystem model
ترجمه فارسی عنوان
مدل سازی بهره وری اولیه خالص از اکوسیستم های زمینی در آب و هوای نیمه خشک از فلات مغولستان با استفاده از مدل اکوسیستم CASA مبتنی بر LSWI
کلمات کلیدی
بهره وری اولیه خالص؛ شاخص آب زمین سطح؛ مدل CASA. فلات مغولستان؛ آب و هوای (نیمه)خشک
Net primary productivity; Land-surface water index; CASA model; Mongolian Plateau; (semi-) Arid climate
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات کامپیوتر در علوم زمین
چکیده انگلیسی


• We presented a new method to estimate the moisture stress coefficient in the early CASA model.
• The improved method can achieve a comparable result of NPP with results from the early CASA model and ground measured NPP.
• The estimate of moisture stress coefficient in the proposed model was strongly simplified and more direct way compared to the early model.

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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Applied Earth Observation and Geoinformation - Volume 46, April 2016, Pages 84–93
نویسندگان
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