No abstract

The CO2 fertilization effect is a major source of uncertainty in crop models for future yield forecasts, but coordinated efforts to determine the mechanisms of this uncertainty have been lacking. Here, we studied causes of uncertainty among 16 crop models in predicting rice yield in response to elevated [CO2] (E-[CO2]) by comparison to free-air CO2 enrichment (FACE) and chamber experiments. The model ensemble reproduced the experimental results well. However, yield prediction in response to E-[CO2] varied significantly among the rice models. The variation was not random: models that overestimated at one experiment simulated greater yield enhancements at the others. The variation was not associated with model structure or magnitude of photosynthetic response to E-[CO2] but was significantly associated with the predictions of leaf area. This suggests that modelled secondary effects of E-[CO2] on morphological development, primarily leaf area, are the sources of model uncertainty. Rice morphological development is conservative to carbon acquisition. Uncertainty will be reduced by incorporating this conservative nature of the morphological response to E-[CO2] into the models. Nitrogen levels, particularly under limited situations, make the prediction more uncertain. Improving models to account for [CO2] × N interactions is necessary to better evaluate management practices under climate change.

The Lie-group approach to the perturbative renormalization group (RG) method is developed to obtain an asymptotic solutions of both autonomous and non-autonomous ordinary differential equations. Reduction of some partial differetial equations to typical RG equations is also achieved by this approach and a simple recipe for providing RG equations is presented.

Climate warming due to human activities will be accompanied by hydrological cycle changes. Economies, societies and ecosystems in south America are vulnerable to such water resource changes. Hence, water resource impact assessments for south America, and corresponding adaptation and mitigation policies, have attracted increased attention. However, substantial uncertainties remain in the current water resource assessments that are based on multiple coupled Atmosphere ocean General Circulation models. This uncertainty varies from significant wetting to catastrophic drying. By applying a statistical method, we characterized the uncertainty and identified global-scale metrics for measuring the reliability of water resource assessments in south America. Here, we show that, although the ensemble mean assessment suggested wetting across most of south America, the observational constraints indicate a higher probability of drying in the Amazon basin. Thus, over-reliance on the consensus of models can lead to inappropriate decision making.

Abstract:Highly accurate global polygonal drainage basin data (PDBD) was developed in this research. The PDBD was derived from digital elevation models (DEMs) at high-resolution (about 100 m-1 km) by automatic and non-automatic methods to suppress DEM errors which derive wrong PDBD. The automatic methods are 'stream burning' and 'ridge fencing', while the nonautomatic method is one which manually corrects DEM errors ('manual correction'). For the derivation of the PDBD, we collected and used geographic basin and river data published from governments, institutes, publishers, and water-related programs. The PDBD derived from the DEMs at high-resolution can represent the boundaries of the basins in detail, and precise geographic and topographic information can be thus derived. These features are helpful for regional and global analysis, assessment, and management with hydrological models in water-related studies. To assess the accuracy of the derived PDBD, we conducted two types of comparisons. Firstly, we geographically compared the derived PDBD with the collected basin data. The derived PDBD showed good geographic agreement with the collected basin data, and the geographic agreement of the derived PDBD was better than that of HYDRO1k. Secondly, we compared upstream areas and discharges based on the derived PDBD with the observed upstream areas and discharges. The upstream areas and discharges based on the derived PDBD showed good agreement with the observed upstream areas and discharges, and the agreement of the derived PDBD was better than that of HYDRO1k. These comparisons reveal that the derived PDBD are highly accurate and reliable. The derived PDBD are thus thought to offer the best information on the surface drainage of the earth.