| 1. |
- Xing, Xiuli, et al.
(författare)
-
Modeling China's terrestrial ecosystem gross primary productivity with BEPS model : Parameter sensitivity analysis and model calibration
- 2023
-
Ingår i: Agricultural and Forest Meteorology. - 0168-1923. ; 343
-
Tidskriftsartikel (refereegranskat)abstract
- Terrestrial ecosystems are the largest sink for carbon, and their ecosystem gross primary productivity (GPP) regulates variations in atmospheric carbon dioxide (CO2) concentrations. Current process-based ecosystem models used for estimating GPP are subject to large uncertainties due to poorly constrained parameter values. In this study, we implemented a global sensitivity analysis (GSA) on parameters in the Boreal Ecosystem Productivity Simulator (BEPS) considering the parameters’ second-order impacts. We also applied the generalized likelihood estimation (GLUE) method, which is flexible for a multi-parameter calibration, to optimize the GPP simulation by BEPS for 10 sites covering 7 plant functional types (PFT) over China. Our optimized results significantly reduced the uncertainty of the simulated GPP over all the sites by 17 % to 82 % and showed that the GPP is sensitive to not only the photosynthesis-related parameters but also the parameters related to the soil water uptake as well as to the energy balance. The optimized GPP across South China showed that the mix forest, shrub, and grass have a higher GPP and are more controlled by the soil water availability. This study showed that the GLUE method together with the GSA scheme could constrain the ecosystem model well when simulating GPP across multiple ecosystems and provide a reasonable estimate of the spatial and temporal distribution of the ecosystem GPP over China. We call for more observations from more sites, as well as data on plant traits, to be collected in China in order to better constrain ecosystem carbon cycle modeling and understand its response to climate change.
|
|
| 2. |
- He, Wei, et al.
(författare)
-
China's Terrestrial Carbon Sink Over 2010–2015 Constrained by Satellite Observations of Atmospheric CO2 and Land Surface Variables
- 2022
-
Ingår i: Journal of Geophysical Research: Biogeosciences. - 2169-8953. ; 127:2
-
Tidskriftsartikel (refereegranskat)abstract
- The magnitude and distribution of China's terrestrial carbon sink remain uncertain due to insufficient constraints at large scales, whereby satellite data offer great potential for reducing the uncertainty. Here, we present two carbon sink estimates for China constrained either by satellite CO2 column concentrations (XCO2) within the Global Carbon Assimilation System or by remotely sensed soil moisture and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) in addition to in situ CO2 observations within the Carbon Cycle Data Assimilation System. They point to a moderate size of carbon sinks of 0.34 ± 0.14 (mean ± unc.) and 0.43 ± 0.09 PgC/yr during 2010–2015, which are supported by an inventory-based estimate for forest and soil carbon sink (0.26 PgC/yr) and fall in the range of contemporary ensemble atmospheric inversions (0.25–0.48 PgC/yr). They also agree reasonably well on interannual variations, which reflect the carbon sink anomalies induced by regional droughts in southwest China. Furthermore, their spatial distributions are broadly consistent that of the forest inventory-based estimate, indicating that the largest carbon sinks locate in central and eastern China. Their estimates for forest carbon sink coincide fairly well with the inventory-based estimate across different regions, especially when aggregated to the north and south of China. Although enhanced recently by afforestation, China's carbon sink was also significantly weakened by regional droughts, which were often not fully represented in previous in situ CO2-based inversions due to insufficient observations. Our results suggest that satellite-based atmospheric CO2 and land surface observations are vital in characterizing terrestrial net carbon fluxes at regional scales.
|
|
| 3. |
- Chen, Haorui, et al.
(författare)
-
Forecasting the human and climate impacts on groundwater resources in the irrigated agricultural region of North China Plain
- 2023
-
Ingår i: Hydrological Processes. - : Wiley. - 0885-6087 .- 1099-1085. ; 37:3
-
Tidskriftsartikel (refereegranskat)abstract
- Climate change has caused significant impacts on water resource redistribution around the world and posed a great threat in the last several decades due to intensive human activities. The impacts of human water use and management on regional water resources remain unclear as they are intertwined with the impacts of climate change. In this study, we disentangled the impact of climate-induced human activities on groundwater resources in a typical region of the semi-arid North China Plain based on a process-oriented groundwater modelling approach accounting for climate-human-groundwater interactions. We found that the climate-induced human effect is amplified in water resources management ('amplifying effect') for our study region under future climate scenarios. We specifically derived a tipping point for annual precipitation of 350 mm, below which the climate-induced human activities on groundwater withdrawal will cause significant 'amplifying effect' on groundwater depletion. Furthermore, we explored the different pumping scenarios under various climate conditions and investigated the pumping thresholds, which the pumping amount should not exceed (4 x 10(7) m(3)) in order to control future groundwater level depletion. Our results highlight that it is critical to implement adaptive water use practices, such as water-saving irrigation technologies in the semi-arid regions, in order to mitigate the negative impacts of groundwater overexploitation, particularly when annual precipitation is anomalously low.
|
|
| 4. |
- Wu, Mousong, et al.
(författare)
-
Regional Responses of Vegetation Productivity to the Two Phases of ENSO
- 2024
-
Ingår i: Geophysical Research Letters. - 0094-8276. ; 51:8
-
Tidskriftsartikel (refereegranskat)abstract
- The two phases of El-Niño-Southern Oscillation (ENSO) influence both regional and global terrestrial vegetation productivity on inter-annual scales. However, the major drivers for the regional vegetation productivity and their controlling strengths during different phases of ENSO remain unclear. We herein disentangled the impacts of two phases of ENSO on regional carbon cycle using multiple data sets. We found that soil moisture predominantly accounts for ∼40% of the variability in regional vegetation productivity during ENSO events. Our results showed that the satellite-derived vegetation productivity proxies, gross primary productivity from data-driven models (FLUXCOM) and observation-constrained ecosystem model (Carbon Cycle Data Assimilation System) generally agree in depicting the contribution of soil moisture and air temperature in modulating regional vegetation productivity. However, the ensemble of weakly constrained ecosystem models exhibits non-negligible discrepancies in the roles of vapor pressure deficit and radiation over extra-tropics. This study highlights the significance of water in regulating regional vegetation productivity during ENSO.
|
|
| 5. |
- Xing, Xiuli, et al.
(författare)
-
Soil Moisture Assimilation Improves Terrestrial Biosphere Model GPP Responses to Sub-Annual Drought at Continental Scale
- 2023
-
Ingår i: Remote Sensing. - : MDPI AG. - 2072-4292. ; 15:3
-
Tidskriftsartikel (refereegranskat)abstract
- Due to the substantial gross exchange fluxes with the atmosphere, the terrestrial carbon cycle plays a significant role in the global carbon budget. Drought commonly affects terrestrial carbon absorption negatively. Terrestrial biosphere models exhibit significant uncertainties in capturing the carbon flux response to drought, which have an impact on estimates of the global carbon budget. Through plant physiological processes, soil moisture tightly regulates the carbon cycle in the environment. Therefore, accurate observations of soil moisture may enhance the modeling of carbon fluxes in a model–data fusion framework. We employ the Carbon Cycle Data Assimilation System (CCDAS) to assimilate 36-year satellite-derived surface soil moisture observations in combination with flask samples of atmospheric CO2 concentrations. We find that, compared to the default model, the performance of optimized net ecosystem productivity (NEP) and gross primary productivity (GPP) has increased with the RMSEs reduced by 1.62 gC/m2/month and 10.84 gC/m2/month, which indicates the added value of the ESA-CCI soil moisture observations as a constraint on the terrestrial carbon cycle. Additionally, the combination of soil moisture and CO2 concentration in this study improves the representation of inter-annual variability of terrestrial carbon fluxes as well as the atmospheric CO2 growth rate. We thereby investigate the ability of the optimized GPP in responding to drought by comparing continentally aggregated GPP with the drought index. The assimilation of surface soil moisture has been shown to efficiently capture the influences of the sub-annual (≤9 months drought durations) and large-scale (e.g., regional to continental scales) droughts on GPP. This study highlights the significant potential of satellite soil moisture for constraining inter-annual models of the terrestrial biosphere’s carbon cycle and for illustrating how GPP responds to drought at a continental scale.
|
|
