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Author Dass, P.; Müller, C.; Brovkin, V.; Cramer, W. url  doi
openurl 
  Title Can bioenergy cropping compensate high carbon emissions from large-scale deforestation of high latitudes Type Journal Article
  Year 2013 Publication Earth System Dynamics Abbreviated Journal (down) Earth System Dynamics  
  Volume 4 Issue 2 Pages 409-424  
  Keywords land-use change; global vegetation model; soil carbon; climate-change; surface albedo; cover changes; snow cover; remind-r; forest; productivity  
  Abstract Numerous studies have concluded that deforestation of the high latitudes result in a global cooling. This is mainly because of the increased albedo of deforested land which dominates over other biogeophysical and biogeochemical mechanisms in the energy balance. This dominance, however, may be due to an underestimation of the biogeochemical response, as carbon emissions are typically at or below the lower end of estimates. Here, we use the dynamic global vegetation model LPJmL for a better estimate of the carbon cycle under such large-scale deforestation. These studies are purely theoretical in order to understand the role of vegetation in the energy balance and the earth system. They must not be mistaken as possible mitigation options, because of the devastating effects on pristine ecosystems. For realistic assumptions of land suitability, the total emissions computed in this study are higher than that of previous studies assessing the effects of boreal deforestation. The warming due to biogeochemical effects ranges from 0.12 to 0.32 degrees C, depending on the climate sensitivity. Using LPJmL to assess the mitigation potential of bioenergy plantations in the suitable areas of the deforested region, we find that the global biophysical bioenergy potential is 68.1 +/- 5.6 EJ yr(-1) of primary energy at the end of the 21st century in the most plausible scenario. The avoided combustion of fossil fuels over the time frame of this experiment would lead to further cooling. However, since the carbon debt caused by the cumulative emissions is not repaid by the end of the 21st century, the global temperatures would increase by 0.04 to 0.11 degrees C. The carbon dynamics in the high latitudes especially with respect to permafrost dynamics and long-term carbon losses, require additional attention in the role for the Earth’s carbon and energy budget.  
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  Corporate Author Thesis  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2190-4987 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial 4486  
Permanent link to this record
 

 
Author Lorite, I.J.; García-Vila, M.; Santos, C.; Ruiz-Ramos, M.; Fereres, E. url  doi
openurl 
  Title AquaData and AquaGIS: Two computer utilities for temporal and spatial simulations of water-limited yield with AquaCrop Type Journal Article
  Year 2013 Publication Computers and Electronics in Agriculture Abbreviated Journal (down) Computers and Electronics in Agriculture  
  Volume 96 Issue Pages 227-237  
  Keywords software tool; aquacrop; crop simulation model; geographic information system; spatial aggregation; fao crop model; irrigation management; iberian peninsula; southern spain; climate models; impacts; program; europe; system  
  Abstract The crop simulation model AquaCrop, recently developed by FAO can be used for a wide range of purposes. However, in its present form, its use over large areas or for applications that require a large number of simulations runs (e.g., long-term analysis), is not practical without developing software to facilitate such applications. Two tools for managing the inputs and outputs of AquaCrop, named AquaData and AquaGIS, have been developed for this purpose and are presented here. Both software utilities have been programmed in Delphi v. 5 and in addition, AquaGIS requires the Geographic Information System (GIS) programming tool MapObjects. These utilities allow the efficient management of input and output files, along with a GIS module to develop spatial analysis and effect spatial visualization of the results, facilitating knowledge dissemination. A sample of application of the utilities is given here, as an AquaCrop simulation analysis of impact of climate change on wheat yield in Southern Spain, which requires extensive input data preparation and output processing. The use of AquaCrop without the two utilities would have required approximately 1000 h of work, while the utilization of AquaData and AquaGIS reduced that time by more than 99%. Furthermore, the use of GIS, made it possible to perform a spatial analysis of the results, thus providing a new option to extend the use of the AquaCrop model to scales requiring spatial and temporal analyses. (C) 2013 Elsevier B.V. All rights reserved.  
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  Corporate Author Thesis  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0168-1699 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial 4609  
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Author Mansouri, M.; Dumont, B.; Destain, M.-F. url  doi
openurl 
  Title Modeling and prediction of nonlinear environmental system using Bayesian methods Type Journal Article
  Year 2013 Publication Computers and Electronics in Agriculture Abbreviated Journal (down) Computers and Electronics in Agriculture  
  Volume 92 Issue Pages 16-31  
  Keywords state and parameter estimation; variational filter; particle filter; extended kalman filter; nonlinear environmental system; leaf area index and soil moisture model; extended kalman filter; state-space models; parameter-estimation; particle filters; navigation; tutorial; tracking  
  Abstract An environmental dynamic system is usually modeled as a nonlinear system described by a set of nonlinear ODEs. A central challenge in computational modeling of environmental systems is the determination of the model parameters. In these cases, estimating these variables or parameters from other easily obtained measurements can be extremely useful. This work addresses the problem of monitoring and modeling a leaf area index and soil moisture model (LSM) using state estimation. The performances of various conventional and state-of-the-art state estimation techniques are compared when they are utilized to achieve this objective. These techniques include the extended Kalman filter (EKF), particle filter (PF), and the more recently developed technique variational filter (VF). Specifically, two comparative studies are performed. In the first comparative study, the state variables (the leaf-area index LAI, the volumetric water content of the soil layer 1, HUR1 and the volumetric water content of the soil layer 2, HUR2) are estimated from noisy measurements of these variables, and the various estimation techniques are compared by computing the estimation root mean square error (RMSE) with respect to the noise-free data. In the second comparative study, the state variables as well as the model parameters are simultaneously estimated. In this case, in addition to comparing the performances of the various state estimation techniques, the effect of number of estimated model parameters on the accuracy and convergence of these techniques are also assessed. The results of both comparative studies show that the PF provides a higher accuracy than the EKF, which is due to the limited ability of the EKF to handle highly nonlinear processes. The results also show that the VF provides a significant improvement over the PF because, unlike the PF which depends on the choice of sampling distribution used to estimate the posterior distribution, the VF yields an optimum choice of the sampling distribution, which also accounts for the observed data. The results of the second comparative study show that, for all techniques, estimating more model parameters affects the estimation accuracy as well as the convergence of the estimated states and parameters. However, the VF can still provide both convergence as well as accuracy related advantages over other estimation methods. (C) 2013 Elsevier B.V. All rights reserved.  
  Address  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0168-1699 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial 4495  
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Author Semenov, M.A.; Pilkington-Bennett, S.; Calanca, P. url  doi
openurl 
  Title Validation of ELPIS 1980-2010 baseline scenarios using the observed European Climate Assessment data set Type Journal Article
  Year 2013 Publication Climate Research Abbreviated Journal (down) Clim. Res.  
  Volume 57 Issue 1 Pages 1-9  
  Keywords climate change; impact assessment; downscaling; lars-wg; stochastic weather generators; diverse canadian climates; lars-wg; aafc-wg; radiation; impacts  
  Abstract Local-scale daily climate scenarios are required for assessment of climate change impacts. ELPIS is a repository of local-scale climate scenarios for Europe, which are based on the LARS-WG weather generator and future projections from 2 multi-model ensembles, CMIP3 and EU-ENSEMBLES. In ELPIS, the site parameters for the 1980-2010 baseline scenarios were estimated by LARS-WG using daily weather from the European Crop Growth Monitoring System (CGMS) used in many European agricultural assessment studies. The objective of this paper was to compare ELPIS baseline scenarios with observed daily weather obtained independently from the European Climate Assessment (ECA) data set. Several statistical tests were used to compare distributions of climatic variables derived from ECA-observed daily weather and ELPIS-generated baseline scenarios. About 30% of selected sites have a difference in altitude of > 50 m compared with the CGMS grid-cell altitude that was selected to represent agricultural land within a grid-cell. Differences in altitude can explain significant Kolmogorov-Smirnov test (KS-test) results for distribution of daily temperature and in t-tests for temperature monthly means, because of the well-known negative correlation between temperature and elevation. For daily precipitation, the KS-test showed little difference between generated and observed data; however, the more sensitive t-test showed significant results for the sites where altitude differences were large. Approximately 11% of sites showed small positive or negative bias in monthly solar radiation, although 86% sites showed > 3 significant t-test results for monthly means. These results can be explained by differences in conversion of sunshine hours to solar radiation used in CGMS and LARS-WG. We conclude that, considering the limitations above, ELPIS baseline scenarios are suitable for agricultural impact assessments in Europe.  
  Address 2016-10-31  
  Corporate Author Thesis  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0936-577x 1616-1572 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4812  
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Author Müller, C. doi  openurl
  Title African lessons on climate change risks for agriculture Type Journal Article
  Year 2013 Publication Annual Review of Nutrition Abbreviated Journal (down) Ann. Rev. Nutr.  
  Volume 33 Issue 1 Pages 395-411  
  Keywords Africa/epidemiology; *Climate Change/economics; Crops, Agricultural/economics/*growth & development; Diet/adverse effects/economics; Forecasting; *Global Health/economics/trends; Humans; Malnutrition/economics/epidemiology/prevention & control; *Models, Theoretical; Risk; Soil/chemistry; Water Resources/economics  
  Abstract Climate change impact assessments on agriculture are subject to large uncertainties, as demonstrated in the present review of recent studies for Africa. There are multiple reasons for differences in projections, including uncertainties in greenhouse gas emissions and patterns of climate change; assumptions on future management, aggregation, and spatial extent; and methodological differences. Still, all projections agree that climate change poses a significant risk to African agriculture. Most projections also see the possibility of increasing agricultural production under climate change, especially if suitable adaptation measures are assumed. Climate change is not the only projected pressure on African agriculture, which struggles to meet demand today and may need to feed an additional one billion individuals by 2050. Development strategies are urgently needed, but they will need to consider future climate change and its inherent uncertainties. Science needs to show how existing synergies between climate change adaptation and development can be exploited.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0199-9885 1545-4312 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial 4496  
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