Gross primary production-coupled evapotranspiration in the global arid and semi-arid regions based on the NIRv index
文献类型：期刊论文
| 作者 | Su, Yanxin4; Gan, Guojing3; Bu, Jingyi2; Yuan, Mengjia4; Ma, Hongyu4; Liu, Xianghe4; Zhang, Yongqiang4; Gao, Yanchun |
| 刊名 | JOURNAL OF HYDROLOGY
 |
| 出版日期 | 2024-11-01 |
| 卷号 | 643页码:132012 |
| 关键词 | Arid and semi-arid regions NIRv Evapotranspiration Gross primary production |
| DOI | 10.1016/j.jhydrol.2024.132012 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | In arid and semi-arid regions, accurate estimates of global primary productivity (GPP) and evapotranspiration (ET) are critical for understanding and managing water and carbon cycling in these fragile ecosystems. In this study, an improved ET-photosynthesis model (PT-JPL-GPP) was used to optimize GPP and ET estimates in these ecosystems by introducing the near infrared reflectance index (NIRv). NIRv, an indicator of the light use efficiency of vegetation, was integrated into the PT-JPL model. Compared to the original PT-JPL and existing remote sensing models, this PT-JPL-GPP model displayed a higher correlation (R-2 = 0.73) and lower BIAS (-19.57 %) for GPP estimation. ET estimates were also noticeably improved, the R2 increased by 0.03(SN-Dhr) to 0.16(USSRC), and the Root Mean Square Error (RMSE) reduced by 0.57 mm/month (SN-Dhr) to 4.64 mm/month (USSRC). Particularly at the GRA site, the R-2 was increased from 0.63 to 0.74, and the RMSE and bias was decreased by 1.25 mm/month and 10.51 %, respectively. The PT-JPL-GPP model was comparable with GLEAM, VPM, MOD17, MOD16, and PML-V2 models. The PT-JPL-GPP model exhibits a lower root mean square error and higher correlation for estimating GPP, compared to the VPM, MOD17, and PML-V2 models. The PT-JPL-GPP model outperformed PT-JPL, MOD16 models for estimating ET, but was slightly poorer than GLEAM and PML-V2 models. Our results highlight the merits of NIRv for improving GPP and ET estimates. |
| WOS关键词 | LAND-SURFACE TEMPERATURE ; LATENT-HEAT FLUX ; WATER-RESOURCES MANAGEMENT ; NET PRIMARY PRODUCTION ; SENSITIVITY-ANALYSIS ; HYDROLOGICAL CYCLE ; TIME-SERIES ; MODEL ; SOIL ; EVAPORATION |
| WOS研究方向 | Engineering ; Geology ; Water Resources |
| WOS记录号 | WOS:001319829300001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/207953]  |
| 专题 | 陆地水循环及地表过程院重点实验室_外文论文 |
| 通讯作者 | Gao, Yanchun |
| 作者单位 | 1.Univ New Hampshire, Earth Syst Res Ctr, Inst Study Earth Oceans & Space, Durham, NH 03824 USA 2.Chinese Acad Sci, Nanjing Inst Geog & Limnol, Key Lab Lake & Watershed Sci Water Secur, Nanjing 210008, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Su, Yanxin,Gan, Guojing,Bu, Jingyi,et al. Gross primary production-coupled evapotranspiration in the global arid and semi-arid regions based on the NIRv index[J]. JOURNAL OF HYDROLOGY,2024,643:132012. |
| APA | Su, Yanxin.,Gan, Guojing.,Bu, Jingyi.,Yuan, Mengjia.,Ma, Hongyu.,...&Gao, Yanchun.(2024).Gross primary production-coupled evapotranspiration in the global arid and semi-arid regions based on the NIRv index.JOURNAL OF HYDROLOGY,643,132012. |
| MLA | Su, Yanxin,et al."Gross primary production-coupled evapotranspiration in the global arid and semi-arid regions based on the NIRv index".JOURNAL OF HYDROLOGY 643(2024):132012. |
入库方式： OAI收割
来源：地理科学与资源研究所
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