scholarly journals Temporal variation of soil moisture over the Wuding River basin assessed with an eco-hydrological model, in-situ observations and remote sensing

2009 ◽  
Vol 13 (7) ◽  
pp. 1375-1398 ◽  
Author(s):  
S. Liu ◽  
X. Mo ◽  
W. Zhao ◽  
V. Naeimi ◽  
D. Dai ◽  
...  
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Seasonal Pattern ◽  
Hydrological Process ◽  
Area Index ◽  
Significance Level ◽  
The Wuding River

Abstract. The change pattern and trend of soil moisture (SM) in the Wuding River basin, Loess Plateau, China is explored based on the simulated long-term SM data from 1956 to 2004 using an eco-hydrological process-based model, Vegetation Interface Processes model, VIP. In-situ SM observations together with a remotely sensed SM dataset retrieved by the Vienna University of Technology are used to validate the model. In the VIP model, climate-eco-hydrological (CEH) variables such as precipitation, air temperature and runoff observations and also simulated evapotranspiration (ET), leaf area index (LAI), and vegetation production are used to analyze the soil moisture evolution mechanism. The results show that the model is able to capture seasonal SM variations. The seasonal pattern, multi-year variation, standard deviation and coefficient of variation (CV) of SM at the daily, monthly and annual scale are well explained by CEH variables. The annual and inter-annual variability of SM is the lowest compared with that of other CEH variables. The trend analysis shows that SM is in decreasing tendency at α=0.01 level of significance, confirming the Northern Drying phenomenon. This trend can be well explained by the decreasing tendency of precipitation (α=0.1) and increasing tendency of temperature (α=0.01). The decreasing tendency of runoff has higher significance level (α=0.001). Because of SM's decreasing tendency, soil evaporation (ES) is also decreasing (α=0.05). The tendency of net radiation (Rn), evapotranspiration (ET), transpiration (EC), canopy intercept (EI) is not obvious. Net primary productivity (NPP), of which the significance level is lower than α=0.1, and gross primary productivity (GPP) at α=0.01 are in increasing tendency.

scholarly journals Temporal variation of soil moisture over the Wuding River Basin assessed with an eco-hydrological model, in-situ observations and remote sensing

2008 ◽  
Vol 5 (6) ◽  
pp. 3557-3604
Author(s):  
S. Liu ◽  
X. Mo ◽  
W. Zhao ◽  
V. Naeimi ◽  
D. Dai ◽  
...  
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Seasonal Pattern ◽  
Ecological Factors ◽  
Area Index ◽  
The Wuding River ◽  
Soil And Water ◽  
Integrative Management

Abstract. For integrative management of soil and water in the Wuding River basin, Loess plateau, China, where severe soil erosion damages are incurred, the ecohydrological behavior of the region is needed to be explored. In this study we focus on the evolution of soil moisture (SM) in the basin. Since there are only twelve years in-situ SM measurements available at two stations from 1992 to 2004, an eco-hydrological processes-based model (VIP, Vegetation Interface Processes model) is employed to simulate the long-term SM, evapotranspiration (ET), vegetation cover and production variation from 1956 to 2004, for the mechanical analysis of SM change. In-situ SM observations and a remotely sensed SM dataset retrieved by the Vienna University of Technology are used to validate the model. The results show that the model is able to capture seasonal SM variations. The seasonal pattern, multi-year variation, standard deviation and CV (coefficient of the variation) of SM at the daily, monthly and annual scale are well explained by the climatic and ecological factors such as precipitation, temperature, net radiation, evapotranspiration, and Leaf Area Index (LAI, denoted as LAI). The annual and inter-annual variability of SM is the lowest comparing with that for other 11-ecohydrological variables. The trend analysis shows that SM is in decreasing tendency at ∝=0.01 level of significance. Its significance is lower than that of runoff and that of temperature (∝=0.001), whereas higher than that of precipitation (∝=0.1). The products of these long-term SM data aim to help integrative management of soil and water resources.

scholarly journals Simulating Spatiotemporal Dynamics of Sichuan Grassland Net Primary Productivity Using the CASA Model and In Situ Observations

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Chuanjiang Tang ◽  
Xinyu Fu ◽  
Dong Jiang ◽  
Jingying Fu ◽  
Xinyue Zhang ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Alpine Meadow ◽  
Growth Period ◽  
Temporal Variations ◽  
Light Use Efficiency ◽  
Important Indicator ◽  
Casa Model ◽  
Use Efficiency

Net primary productivity (NPP) is an important indicator for grassland resource management and sustainable development. In this paper, the NPP of Sichuan grasslands was estimated by the Carnegie-Ames-Stanford Approach (CASA) model. The results were validated with in situ data. The overall precision reached 70%; alpine meadow had the highest precision at greater than 75%, among the three types of grasslands validated. The spatial and temporal variations of Sichuan grasslands were analyzed. The absorbed photosynthetic active radiation (APAR), light use efficiency (ε), and NPP of Sichuan grasslands peaked in August, which was a vigorous growth period during 2011. High values of APAR existed in the southwest regions in altitudes from 2000 m to 4000 m. Light use efficiency (ε) varied in the different types of grasslands. The Sichuan grassland NPP was mainly distributed in the region of 3000–5000 m altitude. The NPP of alpine meadow accounted for 50% of the total NPP of Sichuan grasslands.

scholarly journals A representation of the phosphorus cycle for ORCHIDEE (revision 3985)

2017 ◽  
Author(s):  
Daniel S. Goll ◽  
Nicolas Vuichard ◽  
Fabienne Maignan ◽  
Albert Jornet-Puig ◽  
Jordi Sardans ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Land Surface ◽  
Net Primary Productivity ◽  
Nutrient Content ◽  
Soil Development ◽  
Nutrient Concentrations ◽  
Surface Model ◽  
Phosphorus Cycle ◽  
Area Index ◽  
Leaf Level

Abstract. Land surface models rarely incorporate the terrestrial phosphorus cycle and its interactions with the carbon cycle, despite the extensive scientific debate about the importance of nitrogen and phosphorus supply for future land carbon uptake. We describe a representation of the terrestrial phosphorus cycle for the land surface model ORCHIDEE, and evaluate it with data from nutrient manipulation experiments along a soil formation chronosequence in Hawaii. ORCHIDEE accounts for influence of nutritional state of vegetation on tissue nutrient concentrations, photosynthesis, plant growth, biomass allocation, biochemical (phosphatase-mediated) mineralization and biological nitrogen fixation. Changes in nutrient content (quality) of litter affect the carbon use efficiency of decomposition and in return the nutrient availability to vegetation. The model explicitly accounts for root zone depletion of phosphorus as a function of root phosphorus uptake and phosphorus transport from soil to the root surface. The model captures the observed differences in the foliage stoichiometry of vegetation between an early (300yr) and a late stage (4.1 Myr) of soil development. The contrasting sensitivities of net primary productivity to the addition of either nitrogen, phosphorus or both among sites are in general reproduced by the model. As observed, the model simulates a preferential stimulation of leaf level productivity when nitrogen stress is alleviated, while leaf level productivity and leaf area index are stimulated equally when phosphorus stress is alleviated. The nutrient use efficiencies in the model are lower as observed primarily due to biases in the nutrient content and turnover of woody biomass. We conclude that ORCHIDEE is able to reproduce the shift from nitrogen to phosphorus limited net primary productivity along the soil development chronosequence, as well as the contrasting responses of net primary productivity to nutrient addition.

scholarly journals An Evaluation of the EnKF vs. EnOI and the Assimilation of SMAP, SMOS and ESA CCI Soil Moisture Data over the Contiguous US

2019 ◽  
Vol 11 (5) ◽  
pp. 478 ◽  
Author(s):  
Jostein Blyverket ◽  
Paul Hamer ◽  
Laurent Bertino ◽  
Clément Albergel ◽  
David Fairbairn ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Surface Soil ◽  
Open Loop ◽  
Surface Zone ◽  
Surface Soil Moisture ◽  
Atmospheric Forcing ◽  
Significance Level ◽  
Soil Moisture Data ◽  
In Situ Observations

A number of studies have shown that assimilation of satellite derived soil moisture using the ensemble Kalman Filter (EnKF) can improve soil moisture estimates, particularly for the surface zone. However, the EnKF is computationally expensive since an ensemble of model integrations have to be propagated forward in time. Here, assimilating satellite soil moisture data from the Soil Moisture Active Passive (SMAP) mission, we compare the EnKF with the computationally cheaper ensemble Optimal Interpolation (EnOI) method over the contiguous United States (CONUS). The background error–covariance in the EnOI is sampled in two ways: (i) by using the stochastic spread from an ensemble open-loop run, and (ii) sampling from the model spinup climatology. Our results indicate that the EnKF is only marginally superior to one version of the EnOI. Furthermore, the assimilation of SMAP data using the EnKF and EnOI is found to improve the surface zone correlation with in situ observations at a 95 % significance level. The EnKF assimilation of SMAP data is also found to improve root-zone correlation with independent in situ data at the same significance level; however this improvement is dependent on which in situ network we are validating against. We evaluate how the quality of the atmospheric forcing affects the analysis results by prescribing the land surface data assimilation system with either observation corrected or model derived precipitation. Surface zone correlation skill increases for the analysis using both the corrected and model derived precipitation, but only the latter shows an improvement at the 95 % significance level. The study also suggests that assimilation of satellite derived surface soil moisture using the EnOI can correct random errors in the atmospheric forcing and give an analysed surface soil moisture close to that of an open-loop run using observation derived precipitation. Importantly, this shows that estimates of soil moisture could be improved using a combination of assimilating SMAP using the computationally cheap EnOI while using model derived precipitation as forcing. Finally, we assimilate three different Level-2 satellite derived soil moisture products from the European Space Agency Climate Change Initiative (ESA CCI), SMAP and SMOS (Soil Moisture and Ocean Salinity) using the EnOI, and then compare the relative performance of the three resulting analyses against in situ soil moisture observations. In this comparison, we find that all three analyses offer improvements over an open-loop run when comparing to in situ observations. The assimilation of SMAP data is found to perform marginally better than the assimilation of SMOS data, while assimilation of the ESA CCI data shows the smallest improvement of the three analysis products.

scholarly journals The influence of Carboniferous palaeoatmospheres on plant function: an experimental and modelling assessment

1998 ◽  
Vol 353 (1365) ◽  
pp. 131-140 ◽  
Author(s):  
D. J. Beerling ◽  
F. I. Woodward ◽  
M. R. Lomas ◽  
M. A. Wills ◽  
W. P. Quick ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Soil Carbon ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Global Scale ◽  
Carbon Accumulation ◽  
Late Carboniferous ◽  
Atmospheric Composition ◽  
Area Index ◽  
The Impact

Geochemical models of atmospheric evolution predict that during the late Carboniferous, ca . 300 Ma, atmospheric oxygen and carbon dioxide concentrations were 35% and 0.03%, respectively. Both gases compete with each other for ribulose–1,5–bisphosphate carboxylase/oxygenase–the primary C–fixing enzyme in C 3 land plants: and the absolute concentrations and the ratio of the two in the atmosphere have the potential to strongly influence land–plant function. The Carboniferous therefore represents an era of potentially strong feedback between atmospheric composition and plant function. We assessed some implications of this ratio of atmospheric gases on plant function using experimental and modelling approaches. After six weeks growth at 35% O 2 and 0.03% carbon dioxide, no photosynthetic acclimation was observed in the woody species Betula pubescens and Hedera helix relative to those plants grown at 21% O 2 . Leaf photosynthetic rates were 29% lower in the high O 2 environment compared to the controls. A global–scale analysis of the impact of the late Carboniferous climate and atmospheric composition on vegetation function was determined by driving a process–based vegetation–biogeochemistry model with a Carboniferous global palaeoclimate simulated by the Universities Global Atmospheric Modelling Programme General Circulation Model. Global patterns of net primary productivity, leaf area index and soil carbon concentration for the equilibrium model solutions showed generally low values everywhere, compared with the present day, except for a central band in the northern land mass extension of Gondwana, where high values were predicted. The areas of high soil carbon accumulation closely match the known distribution of late Carboniferous coals. Sensitivity analysis with the model indicated that the increase in O 2 concentration from 21% to 35% reduced global net primary productivity by 18.7% or by 6.3 GtC yr –1 . Further work is required to collate and map at the global scale the distribution of vegetation types, and evidence for wildfires, for the late Carboniferous to test our predictions.

Spatiotemporal distribution of net primary productivity and its driving factors in the Nanliu River basin in the Beibu Gulf

2019 ◽  
Vol 39 (21) ◽  
Author(s):  
田义超 TIAN Yichao ◽  
黄远林 HUANG Yuanlin ◽  
张强 ZHANG Qiang ◽  
陶进 TAO Jin ◽  
张亚丽 ZHANG Yali ◽  
...  
Keyword(s):  
River Basin ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Driving Factors ◽  
Spatiotemporal Distribution ◽  
Beibu Gulf
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