scholarly journals Evaluation of Clumping Effects on the Estimation of Global Terrestrial Evapotranspiration

2021 ◽  
Vol 13 (20) ◽  
pp. 4075
Author(s):  
Bin Chen ◽  
Xuehe Lu ◽  
Shaoqiang Wang ◽  
Jing M. Chen ◽  
Yang Liu ◽  
...  
Keyword(s):  
Random Distribution ◽  
Water Cycle ◽  
Terrestrial Ecosystems ◽  
Structural Parameter ◽  
Area Index ◽  
Global Water Cycle ◽  
Baseline Case ◽  
Clumping Index ◽  
Boreal Ecosystem ◽  
Boreal Ecosystem Productivity Simulator

In terrestrial ecosystems, leaves are aggregated into different spatial structures and their spatial distribution is non-random. Clumping index (CI) is a key canopy structural parameter, characterizing the extent to which leaf deviates from the random distribution. To assess leaf clumping effects on global terrestrial ET, we used a global leaf area index (LAI) map and the latest version of global CI product derived from MODIS BRDF data as well as the Boreal Ecosystem Productivity Simulator (BEPS) to estimate global terrestrial ET. The results show that global terrestrial ET in 2015 was 511.9 ± 70.1 mm yr−1 for Case I, where the true LAI and CI are used. Compared to this baseline case, (1) global terrestrial ET is overestimated by 4.7% for Case II where true LAI is used ignoring clumping; (2) global terrestrial ET is underestimated by 13.0% for Case III where effective LAI is used ignoring clumping. Among all plant functional types (PFTs), evergreen needleleaf forests were most affected by foliage clumping for ET estimation in Case II, because they are most clumped with the lowest CI. Deciduous broadleaf forests are affected by leaf clumping most in Case III because they have both high LAI and low CI compared to other PFTs. The leaf clumping effects on ET estimation in both Case II and Case III is robust to the errors in major input parameters. Thus, it is necessary to consider clumping effects in the simulation of global terrestrial ET, which has considerable implications for global water cycle research.

scholarly journals Impacts of droughts on carbon sequestration by China's terrestrial ecosystems from 2000 to 2011

2014 ◽  
Vol 11 (10) ◽  
pp. 2583-2599 ◽  
Author(s):  
Y. Liu ◽  
Y. Zhou ◽  
W. Ju ◽  
S. Wang ◽  
X. Wu ◽  
...  
Keyword(s):  
Carbon Sequestration ◽  
Ecosystem Respiration ◽  
Eastern China ◽  
Terrestrial Ecosystems ◽  
Northwest China ◽  
Central China ◽  
Ecosystem Productivity ◽  
Model Driven ◽  
Boreal Ecosystem ◽  
Boreal Ecosystem Productivity Simulator

Abstract. In recent years, China's terrestrial ecosystems have experienced frequent droughts. How these droughts have affected carbon sequestration by the terrestrial ecosystems is still unclear. In this study, the process-based Boreal Ecosystem Productivity Simulator (BEPS) model, driven by remotely sensed vegetation parameters, was employed to assess the effects of droughts on net ecosystem productivity (NEP) of terrestrial ecosystems in China from 2000 to 2011. Droughts of differing severity, as indicated by a standard precipitation index (SPI), hit terrestrial ecosystems in China extensively in 2001, 2006, 2009, and 2011. The national total annual NEP exhibited the slight decline of −11.3 Tg C yr−2 during the aforementioned years of extensive droughts. The NEP reduction ranged from 61.1 Tg C yr−1 to 168.8 Tg C yr−1. National and regional total NEP anomalies were correlated with the annual mean SPI, especially in Northwest China, North China, Central China, and Southwest China. The reductions in annual NEP in 2001 and 2011 might have been caused by a larger decrease in annual gross primary productivity (GPP) than in annual ecosystem respiration (ER). The reductions experienced in 2009 might be due to a decrease in annual GPP and an increase in annual ER, while reductions in 2006 could stem from a larger increase in ER than in GPP. The effects of droughts on NEP lagged up to 3–6 months, due to different responses of GPP and ER. In eastern China, where is humid and warm, droughts have predominant and short-term lagged influences on NEP. In western regions, cold and arid, the drought effects on NEP were relatively weaker but prone to lasting longer.

Net primary productivity following forest fire for Canadian ecoregions

2000 ◽  
Vol 30 (6) ◽  
pp. 939-947 ◽  
Author(s):  
B D Amiro ◽  
J M Chen ◽  
Jinjun Liu
Keyword(s):  
Primary Productivity ◽  
Forest Fires ◽  
Carbon Balance ◽  
Net Primary Productivity ◽  
Forest Carbon ◽  
Data Set ◽  
Area Index ◽  
Boreal Plains ◽  
Boreal Ecosystem ◽  
Boreal Ecosystem Productivity Simulator

Recent modelling results indicate that forest fires and other disturbances determine the magnitude of the Canadian forest carbon balance. The regeneration of post-fire vegetation is key to the recovery of net primary productivity (NPP) following fire. We geographically co-registered pixels classed using the Boreal Ecosystem Productivity Simulator, a process-based model with AVHRR (advanced very-high resolution radiometer) satellite estimates of leaf-area index and land cover type, with polygons from a recent database of large Canadian fires. NPP development with time since fire was derived for the first 15 years following the disturbance in the boreal and taiga ecozones. About 7 × 106 ha were analysed for over 500 fires occurring between 1980 and 1994. NPP increases linearly through this period, at rates that depend on ecoregion. A longer data set for the Boreal Plains ecozone of Alberta shows that NPP levels off at about 20-30 years and remains constant for 60 years. The NPP trajectories can be used as spatial averages to support models of forest carbon balance and succession through the most fire-prone regions of Canada.

scholarly journals Impacts of droughts on carbon sequestration by China's terrestrial ecosystems from 2000 to 2011

2013 ◽  
Vol 10 (11) ◽  
pp. 17469-17509 ◽  
Author(s):  
Y. B. Liu ◽  
Y. L. Zhou ◽  
W. M. Ju ◽  
S. Q. Wang ◽  
X. C. Wu ◽  
...  
Keyword(s):  
Carbon Sequestration ◽  
Terrestrial Ecosystems ◽  
Northwest China ◽  
Central China ◽  
Ecosystem Productivity ◽  
Model Driven ◽  
Lagged Effects ◽  
Vegetation Parameters ◽  
Boreal Ecosystem ◽  
Boreal Ecosystem Productivity Simulator

Abstract. In recent years, droughts have frequently hit China's terrestrial ecosystems. How these droughts affected carbon sequestration by China's terrestrial ecosystems is still unclear. In this study, the process-based Boreal Ecosystem Productivity Simulator (BEPS) model, driven by remotely sensed vegetation parameters, was employed to assess the effects of droughts on net ecosystem productivity (NEP) of terrestrial ecosystems in China for the period from 2000 to 2011. Different categories of droughts, as indicated by a standard precipitation index (SPI), extensively hit terrestrial ecosystems in China, particularly in 2001, 2006, 2009 and 2011. The national total NEP exhibited a slight decline of −11.3 Tg C yr−2 during the study period, mainly due to large reductions of NEP in typical drought-hit years 2001, 2006, 2009 and 2011, ranging from 61.1 Tg C yr−1 to 168.8 Tg C yr−1. National and regional total NEP anomalies were correlated with corresponding annual mean SPI, especially in Northwest China, North China, Central China, and Southwest China. In drought years, the reductions of NEP might be caused by a larger decrease in gross primary productivity (GPP) than in respiration (RE) (2001 and 2011), a decrease in GPP and an increase in RE (2009), or a larger increase in RE than in GPP (2006). Droughts had lagged effects of up to 3–6 months on NEP due to different reactions of GPP and RE to droughts. In east humid and warm parts of China, droughts have predominant and short-term lagged influences on NEP. In western cold and arid regions, the effects of droughts on NEP were relatively weaker and might last for a longer period of time.

The global water cycle and continental erosion during Phanerozoic time (570 my)

1989 ◽  
Vol 289 (4) ◽  
pp. 455-483 ◽  
Author(s):  
Y. Tardy ◽  
R. N'Kounkou ◽  
J.-L. Probst
Keyword(s):  
Water Cycle ◽  
Global Water Cycle ◽  
Continental Erosion ◽  
Global Water

scholarly journals Micropollutant-loaded powdered activated carbon released from waste water treatment plants: a risk for sediment-dwelling organisms?

2021 ◽  
Vol 33 (1) ◽  
Author(s):  
Marion Woermann ◽  
Julios Armand Kontchou ◽  
Bernd Sures
Keyword(s):  
Activated Carbon ◽  
Wastewater Treatment Plants ◽  
Water Cycle ◽  
Waste Water Treatment ◽  
Additional Treatment ◽  
Powdered Activated Carbon ◽  
Lumbriculus Variegatus ◽  
Negative Effects ◽  
Global Water Cycle ◽  
Receiving Waters

Abstract Background In order to protect aquatic environments and to reduce the presence of micropollutants in the global water cycle, wastewater treatment plants (WWTPs) often implement an additional treatment step. One of the most effective measures is the use of powdered activated carbon (PAC) as an adsorbent for micropollutants. This method provides sufficient elimination rates for several micropollutants and has been successfully employed in many WWTPs. Despite this success, there might be a drawback as the retention of the PAC in the WWTP can be challenging and losses of micropollutant-loaded PAC into the aquatic environment may occur. Upon emission, micropollutant-loaded PAC is expected to settle to the benthic zone of receiving waters, where sediment-dwelling organisms may ingest these particles. Therefore, the present study investigated possible adverse effects of micropollutant-loaded PAC from a WWTP as compared to unloaded (native) and diclofenac-loaded PAC on the sediment-dwelling annelid Lumbriculus variegatus. Results Native PAC induced the strongest effects on growth (measured as biomass) and reproduction of the annelids. The corresponding medium effective concentrations (EC50) were 1.7 g/kg and 1.8 g/kg, respectively. Diclofenac-loaded PAC showed lower effects with an EC50 of 2.5 g/kg for growth and EC50 of 3.0 g/kg for reproduction. Although tested at the same concentrations, the micropollutant-loaded PAC from the WWTP did not lead to obvious negative effects on the endpoints investigated for L.variegatus and only a slight trend of a reduced growth was detected. Conclusion We did not detect harmful effects on L. variegatus caused by the presence of MP-loaded PAC from a WWTP which gives an auspicious perspective for PAC as an advanced treatment option.

scholarly journals Transferability Intercomparison: An Opportunity for New Insight on the Global Water Cycle and Energy Budget

2007 ◽  
Vol 88 (3) ◽  
pp. 375-384 ◽  
Author(s):  
E. S. Takle ◽  
J. Roads ◽  
B. Rockel ◽  
W. J. Gutowski ◽  
R. W. Arritt ◽  
...  
Keyword(s):  
Energy Budget ◽  
Climate Models ◽  
Climate Model ◽  
Water Cycle ◽  
Regional Climate ◽  
Climate Conditions ◽  
Continental Scale ◽  
Global Water Cycle ◽  
Wide Range ◽  
Global Water

A new approach, called transferability intercomparisons, is described for advancing both understanding and modeling of the global water cycle and energy budget. Under this approach, individual regional climate models perform simulations with all modeling parameters and parameterizations held constant over a specific period on several prescribed domains representing different climatic regions. The transferability framework goes beyond previous regional climate model intercomparisons to provide a global method for testing and improving model parameterizations by constraining the simulations within analyzed boundaries for several domains. Transferability intercomparisons expose the limits of our current regional modeling capacity by examining model accuracy on a wide range of climate conditions and realizations. Intercomparison of these individual model experiments provides a means for evaluating strengths and weaknesses of models outside their “home domains” (domain of development and testing). Reference sites that are conducting coordinated measurements under the continental-scale experiments under the Global Energy and Water Cycle Experiment (GEWEX) Hydrometeorology Panel provide data for evaluation of model abilities to simulate specific features of the water and energy cycles. A systematic intercomparison across models and domains more clearly exposes collective biases in the modeling process. By isolating particular regions and processes, regional model transferability intercomparisons can more effectively explore the spatial and temporal heterogeneity of predictability. A general improvement of model ability to simulate diverse climates will provide more confidence that models used for future climate scenarios might be able to simulate conditions on a particular domain that are beyond the range of previously observed climates.

How forests change transit times of transpiration, evaporation and streamflow – a modeling approach

2021 ◽  
Author(s):  
Ingo Heidbüchel ◽  
Jie Yang ◽  
Jan H. Fleckenstein
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Water Cycle ◽  
Rooting Depth ◽  
Water Fluxes ◽  
Area Index ◽  
Transit Times ◽  
Physically Based ◽  
Forested Areas ◽  
The Individual

<p>In a recent paper we investigated how different catchment and climate properties influence transit time distributions. This was done by employing a physically-based spatially explicit 3D model in a virtual catchment running many different scenarios with different combinations of catchment and climate properties. We found that the velocity distribution of water fluxes through a catchment is more sensitive to certain properties while other factors appear less relevant. Now we expanded the approach by adding vegetation to the model and thus introducing new hydrologic processes (transpiration and evaporation) to the simulated water cycle. On the one hand we wanted to know how these new processes would influence transit times of the water fluxes to the stream, on the other hand we were interested in how exactly differences in the vegetation itself (e.g. rooting depth and leaf area index) would alter the various flux velocities (including transit times of transpiration and evaporation). It was very interesting to observe that streamflow in forested areas appeared to become older on average. We also found that transpiration was generally younger if the vegetation had shallower roots and/or a larger leaf area index. The biggest difference in the age of evaporation was detected for different amounts of subsequent precipitation (evaporation was generally younger in a wetter climate). In conclusion, we found that forests influence the age of the different water fluxes within a catchment. According to our results the overall hydrologic cycle is decelerated when adding vegetation to a model that otherwise only simulates evaporation.</p><p>Still, in order to make meaningful predictions on the age of hydrologic fluxes, it is not constructive to single out specific catchment and climate properties. The multitude of influences from different parameters makes it very challenging to find rules and underlying principles in the integrated catchment response. Therefore it is necessary to look at the individual parameters and their potential interactions and interdependencies in a bottom-up approach.</p>

Self-validating deep learning of continental hydrology through satellite gravimetry and altimetry

2021 ◽  
Author(s):  
Christopher Irrgang ◽  
Jan Saynisch-Wagner ◽  
Robert Dill ◽  
Eva Boergens ◽  
Maik Thomas
Keyword(s):  
Neural Network ◽  
Satellite Altimetry ◽  
Water Cycle ◽  
Global Water Cycle ◽  
Network Training ◽  
The Neural Network ◽  
Continental Hydrology ◽  
Terrestrial Water ◽  
Combine Machine ◽  
Groundwater Basins

<p>Space-borne observations of terrestrial water storage (TWS) are an essential ingredient for understanding the Earth's global water cycle, its susceptibility to climate change, and for risk assessments of ecosystems, agriculture, and water management. However, the complex distribution of water masses in rivers, lakes, or groundwater basins remains elusive in coarse-resolution gravimetry observations. We combine machine learning, numerical modeling, and satellite altimetry to build and train a downscaling neural network that recovers simulated TWS from synthetic space-borne gravity observations. The neural network is designed to adapt and validate its training progress by considering independent satellite altimetry records. We show that the neural network can accurately derive TWS anomalies in 2019 after being trained over the years 2003 to 2018. Specifically for validated regions in the Amazonas, we highlight that the neural network can outperform the numerical hydrology model used in the network training.</p><p>https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020GL089258</p>

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