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Daccache, A.; Ciurana, J.S.; Diaz, J.A.R.; Knox, J.W. |
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Title |
Water and energy footprint of irrigated agriculture in the Mediterranean region |
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Journal Article |
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Year |
2014 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
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Volume |
9 |
Issue |
12 |
Pages  |
124014 |
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Keywords |
food security; CO2 emissions; nexus; water productivity; water resources; climate-change; southern spain; management; impacts; deficit; grids |
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Abstract |
Irrigated agriculture constitutes the largest consumer of freshwater in the Mediterranean region and provides a major source of income and employment for rural livelihoods. However, increasing droughts and water scarcity have highlighted concerns regarding the environmental sustainability of agriculture in the region. An integrated assessment combining a gridded water balance model with a geodatabase and GIS has been developed and used to assess the water demand and energy footprint of irrigated production in the region. Modelled outputs were linked with crop yield and water resources data to estimate water (m(3) kg(-1)) and energy (CO2 kg(-1)) productivity and identify vulnerable areas or `hotspots’. For a selected key crops in the region, irrigation accounts for 61 km(3) yr(-1) of water abstraction and 1.78 Gt CO2 emissions yr-1, with most emissions from sunflower (73 kg CO2/t) and cotton (60 kg CO2/t) production. Wheat is a major strategic crop in the region and was estimated to have a water productivity of 1000 tMm(-3) and emissions of 31 kg CO2/t. Irrigation modernization would save around 8 km(3) of water but would correspondingly increase CO2 emissions by around +135\%. Shifting from rain-fed to irrigated production would increase irrigation demand to 166 km(3) yr(-1) (+137\%) whilst CO2 emissions would rise by +270\%. The study has major policy implications for understanding the water-energy-food nexus in the region and the trade-offs between strategies to save water, reduce CO2 emissions and/or intensify food production. |
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1748-9326 |
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CropM, ft_macsur |
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no |
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MA @ admin @ |
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4747 |
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Schauberger, B.; Rolinski, S.; Müller, C. |
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Title |
A network-based approach for semi-quantitative knowledge mining and its application to yield variability |
Type |
Journal Article |
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Year |
2016 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
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Volume |
11 |
Issue |
12 |
Pages |
123001 |
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Keywords |
yield variability; crop models; interaction network; plant process; wheat; maize; rice; Global Food Security; Climate-Change; Crop Production; Stress Tolerance; Wheat Yields; Heat-Stress; Temperature Variability; Environmental-Factors; United-States; Elevated CO2 |
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Abstract |
Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. Asystematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields. |
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2017-04-07 |
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1748-9326 |
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Review |
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CropM, ft_macsur |
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MA @ admin @ |
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4942 |
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Tao, F.; Palosuo, T.; Roetter, R.P.; Hernandez Diaz-Ambrona, C.G.; Ines Minguez, M.; Semenov, M.A.; Kersebaum, K.C.; Cammarano, D.; Specka, X.; Nendel, C.; Srivastava, A.K.; Ewert, F.; Padovan, G.; Ferrise, R.; Martre, P.; Rodriguez, L.; Ruiz-Ramos, M.; Gaiser, T.; Hohn, J.G.; Salo, T.; Dibari, C.; Schulman, A.H. |
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Title |
Why do crop models diverge substantially in climate impact projections? A comprehensive analysis based on eight barley crop models |
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Journal Article |
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Year |
2020 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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281 |
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107851 |
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Keywords |
agriculture; climate change; crop growth simulation; impact; model; improvement; uncertainty; air CO2 enrichment; elevated CO2; wheat growth; nitrogen dynamics; simulation-models; field experiment; atmospheric CO2; rice phenology; temperature; uncertainty |
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Robust projections of climate impact on crop growth and productivity by crop models are key to designing effective adaptations to cope with future climate risk. However, current crop models diverge strongly in their climate impact projections. Previous studies tried to compare or improve crop models regarding the impact of one single climate variable. However, this approach is insufficient, considering that crop growth and yield are affected by the interactive impacts of multiple climate change factors and multiple interrelated biophysical processes. Here, a new comprehensive analysis was conducted to look holistically at the reasons why crop models diverge substantially in climate impact projections and to investigate which biophysical processes and knowledge gaps are key factors affecting this uncertainty and should be given the highest priorities for improvement. First, eight barley models and eight climate projections for the 2050s were applied to investigate the uncertainty from crop model structure in climate impact projections for barley growth and yield at two sites: Jokioinen, Finland (Boreal) and Lleida, Spain (Mediterranean). Sensitivity analyses were then conducted on the responses of major crop processes to major climatic variables including temperature, precipitation, irradiation, and CO2, as well as their interactions, for each of the eight crop models. The results showed that the temperature and CO2 relationships in the models were the major sources of the large discrepancies among the models in climate impact projections. In particular, the impacts of increases in temperature and CO2 on leaf area development were identified as the major causes for the large uncertainty in simulating changes in evapotranspiration, above-ground biomass, and grain yield. Our findings highlight that advancements in understanding the basic processes and thresholds by which climate warming and CO2 increases will affect leaf area development, crop evapotranspiration, photosynthesis, and grain formation in contrasting environments are needed for modeling their impacts. |
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2020-06-08 |
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CropM, ft_macsur |
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MA @ admin @ |
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5232 |
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Yang, H.; Dobbie, S.; Ramirez-Villegas, J.; Feng, K.; Challinor, A.J.; Chen, B.; Gao, Y.; Lee, L.; Yin, Y.; Sun, L.; Watson, J.; Koehler, A.-K.; Fan, T.; Ghosh, S. |
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Title |
Potential negative consequences of geoengineering on crop production: A study of Indian groundnut |
Type |
Journal Article |
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Year |
2016 |
Publication |
Geophysical Research Letters |
Abbreviated Journal |
Geophys. Res. Let. |
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Volume |
43 |
Issue |
22 |
Pages |
11786-11795 |
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Keywords |
Mangrove Tidal Creek; Land-Ocean Boundary; Carbon-Dioxide; Organic-Matter; River Estuary; European Estuaries; CO2 Fluxes; NE Coast; Water; Bay; fCO(2) (water); air-water CO2 flux; Hugli Estuary; Matla Estuary; Blue Carbon; source of CO2 |
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Geoengineering has been proposed to stabilize global temperature, but its impacts on crop production and stability are not fully understood. A few case studies suggest that certain crops are likely to benefit from solar dimming geoengineering, yet we show that geoengineering is projected to have detrimental effects for groundnut. Using an ensemble of crop-climate model simulations, we illustrate that groundnut yields in India undergo a statistically significant decrease of up to 20% as a result of solar dimming geoengineering relative to RCP4.5. It is somewhat reassuring, however, to find that after a sustained period of 50 years of geoengineering crop yields return to the nongeoengineered values within a few years once the intervention is ceased. |
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2017-01-20 |
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0094-8276 |
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CropM, ft_MACSUR |
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MA @ admin @ |
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4936 |
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Kim, D.-G.; Thomas, A.D.; Pelster, D.; Rosenstock, T.S.; Sanz-Cobena, A. |
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Title |
Greenhouse gas emissions from natural ecosystems and agricultural lands in sub-Saharan Africa: synthesis of available data and suggestions for further research |
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Journal Article |
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Year |
2016 |
Publication |
Biogeosciences |
Abbreviated Journal |
Biogeosciences |
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Volume |
13 |
Issue |
16 |
Pages |
4789-4809 |
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nitrous-oxide emissions; soil CO2 efflux; N2O emissions; carbon-dioxide; agroforestry residues; improved-fallow; disturbance gradient; fertilizer; nitrogen; sampling frequency; gaseous emissions |
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This paper summarizes currently available data on greenhouse gas (GHG) emissions from African natural ecosystems and agricultural lands. The available data are used to synthesize current understanding of the drivers of change in GHG emissions, outline the knowledge gaps, and suggest future directions and strategies for GHG emission research. GHG emission data were collected from 75 studies conducted in 22 countries (n = 244) in sub-Saharan Africa (SSA). Carbon dioxide (CO2) emissions were by far the largest contributor to GHG emissions and global warming potential (GWP) in SSA natural terrestrial systems. CO2 emissions ranged from 3.3 to 57.0 Mg CO2 ha(-1) yr(-1), methane (CH4) emissions ranged from -4.8 to 3.5 kg ha(-1) yr(-1) (-0.16 to 0.12 Mg CO2 equivalent (eq.) ha(-1) yr(-1)), and nitrous oxide (N2O) emissions ranged from -0.1 to 13.7 kg ha(-1) yr(-1) (-0.03 to 4.1 Mg CO2 eq. ha(-1) yr(-1)). Soil physical and chemical properties, rewetting, vegetation type, forest management, and land-use changes were all found to be important factors affecting soil GHG emissions from natural terrestrial systems. In aquatic systems, CO2 was the largest contributor to total GHG emissions, ranging from 5.7 to 232.0 Mg CO2 ha(-1) yr(-1), followed by -26.3 to 2741.9 kgCH(4) ha(-1) yr(-1) (-0.89 to 93.2 Mg CO2 eq. ha(-1) yr(-1)) and 0.2 to 3.5 kg N2O ha(-1) yr(-1) (0.06 to 1.0 Mg CO2 eq. ha(-1) yr(-1)). Rates of all GHG emissions from aquatic systems were affected by type, location, hydrological characteristics, and water quality. In croplands, soil GHG emissions were also dominated by CO2, ranging from 1.7 to 141.2 Mg CO2 ha(-1) yr(-1), with -1.3 to 66.7 kgCH(4) ha(-1) yr(-1) (-0.04 to 2.3 Mg CO2 eq. ha(-1) yr(-1)) and 0.05 to 112.0 kg N2O ha(-1) yr(-1) (0.015 to 33.4 Mg CO2 eq. ha(-1) yr(-1)). N2O emission factors (EFs) ranged from 0.01 to 4.1 %. Incorporation of crop residues or manure with inorganic fertilizers invariably resulted in significant changes in GHG emissions, but results were inconsistent as the magnitude and direction of changes were differed by gas. Soil GHG emissions from vegetable gardens ranged from 73.3 to 132.0 Mg CO2 ha(-1) yr(-1) and 53.4 to 177.6 kg N2O ha(-1) yr(-1) (15.9 to 52.9 Mg CO2 eq. ha(-1) yr(-1)) and N2O EFs ranged from 3 to 4 %. Soil CO2 and N2O emissions from agroforestry were 38.6 Mg CO2 ha(-1) yr(-1) and 0.2 to 26.7 kg N2O ha(-1) yr(-1) (0.06 to 8.0 Mg CO2 eq. ha(-1) yr(-1)), respectively. Improving fallow with nitrogen (N)-fixing trees led to increased CO2 and N2O emissions compared to conventional croplands. The type and quality of plant residue in the fallow is an important control on how CO2 and N2O emissions are affected. Throughout agricultural lands, N2O emissions slowly increased with N inputs below 150 kg N ha(-1) yr(-1) and increased exponentially with N application rates up to 300 kg N ha(-1) yr(-1). The lowest yield-scaled N2O emissions were reported with N application rates ranging between 100 and 150 kg N ha(-1). Overall, total CO2 eq. emissions from SSA natural ecosystems and agricultural lands were 56.9 +/- 12.7 x 10(9) Mg CO2 eq. yr(-1) with natural ecosystems and agricultural lands contributing 76.3 and 23.7 %, respectively. Additional GHG emission measurements are urgently required to reduce uncertainty on annual GHG emissions from the different land uses and identify major control factors and mitigation options for low-emission development. A common strategy for addressing this data gap may include identifying priorities for data acquisition, utilizing appropriate technologies, and involving international networks and collaboration. |
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2016-10-18 |
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1726-4170 |
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CropM, ft_macsur |
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MA @ admin @ |
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4687 |
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