Pronounced Increases in Future Soil Erosion and Sediment Deposition as Influenced by Freeze-Thaw Cycles in the Upper Mississippi River Basin.

Soil erosion and sediment deposition are relevant to multiple important ecosystem services essential for natural and human systems. The present study aims to project future soil erosion and sediment deposition in the Upper Mississippi River Basin (UMRB) using climate projections by five Global Circulation Models (GCMs) under the Representative Concentrations Pathway (RCP) 8.5 scenario. To understand the importance of freeze-thaw cycles (FTCs) for soil erosion and sediment deposition estimation with climate change, this study compared two Soil and Water Assessment Tool (SWAT) models with different representations of the FTCs, with the standard SWAT using a simple regression method and SWAT-FT employing a physically based method. Modeling results show that future climate change can pronouncedly intensify soil erosion and increase sediment deposition, and the impacts are sensitive to how FTCs are represented in the model. The standard SWAT projected an increase in soil erosion by nearly 40% by the end of the 21st century, which is much lower than the projected over 65% increase in soil erosion by SWAT-FT. For sediment deposition, the projected percent changes by the standard SWAT and SWAT-FT also deviate from each other (i.e., about 70% by the standard SWAT vs about 120% by SWAT-FT). Overall, these results demonstrate the important roles of FTCs in projecting future soil erosion and sediment deposition and underline the need to consider the effects of conservation practices on FTCs to realistically assess the effectiveness of those measures.

SWAT ungauged: Water quality modeling in the Upper Mississippi River Basin.

Improving model performance in ungauged basins has been a chronic challenge in watershed model application to understand and assess water quality impacts of agricultural conservation practices, land use change, and climate adaptation measures in large river basins. Here, we evaluate a modified version of SWAT2012 (referred to as SWAT-EC hereafter), which integrates an energy balanced soil temperature module (STM) and the CENTRUY-based soil organic matter algorithm, for simulating water quality parameters in the Upper Mississippi River Basin (UMRB), and compare it against the original SWAT2012. Model evaluation was performed for simulating streamflow, sediment, and nitrate-N (NO3-N) and total nitrogen (TN) loadings at three stations near the outlets of UMRB. The model comparison was conducted without parameter calibration in order to assess their performance under ungauged conditions. The results indicate that SWAT-EC outperformed SWAT2012 for stream flow and NO3-N and TN loading simulation on both monthly and annual scales. For sediment, SWAT-EC performed better than SWAT2012 on a monthly time step basis, but no noticeable improvement was found at the annual scale. In addition, the performance of the uncalibrated SWAT-EC was comparable to other calibrated SWAT models reported in previous publications with respect to sediment and NO3-N loadings. These findings highlight the importance of advancing process representation in physically-based models to improve model credibility, particularly in ungauged basins.

Nitrate loading projection is sensitive to freeze-thaw cycle representation.

Climate change can have substantial impacts on nitrogen runoff, which is a major cause of eutrophication, harmful algal blooms, and hypoxia in freshwaters and coastal regions. We examined responses of nitrate loading to climate change in the Upper Mississippi River Basin (UMRB) with an enhanced Soil and Water Assessment Tool with physically based Freeze-Thaw cycle representation (SWAT-FT), as compared with the original SWAT model that employs an empirical equation. Driven by future climate projections from five General Circulation Models (GCMs) from 1960 to 2099 under the Representative Concentrations Pathways (RCP) 8.5 scenario, we analyzed changes in riverine nitrate loadings, as well as terrestrial surface and subsurface contributions of the UMRB in the 21st century relative to the baseline period of 1960-1999. By the end of the 21st century, the original SWAT model predicted about a 50% increase in riverine nitrate loadings which is nearly twice as much as that estimated by SWAT-FT (ca. 25%). Such a large difference in projected nitrate changes can potentially mislead mitigation strategies that aim to reduce nitrogen runoff from the UMRB. Further analysis shows that the difference between the original SWAT model and SWAT-FT led to substantial discrepancies in the spatial distribution of surface and subsurface nitrate loadings in the UMRB. In general, SWAT-FT predicted more nitrate leaching for northwestern parts of the UMRB which are more sensitive to freeze-thaw cycle, mainly because SWAT-FT simulated less frequent frozen soils. This study highlights the importance of using physically based freeze-thaw cycle representation in water quality modeling. Design of future nitrogen runoff reduction strategies should include careful assessment of effects that land management has on the freeze-thaw cycles to provide reliable projection of water quality under climate change.

Combining the effects of increased atmospheric carbon dioxide on protein, iron, and zinc availability and projected climate change on global diets: a modelling study.

BACKGROUND: Increasing atmospheric concentrations of carbon dioxide (CO2) affect global nutrition via effects on agricultural productivity and nutrient content of food crops. We combined these effects with economic projections to estimate net changes in nutrient availability between 2010 and 2050. METHODS: In this modelling study, we used the International Model for Policy Analysis of Agricultural Commodities and Trade to project per capita availability of protein, iron, and zinc in 2050. We used estimated changes in productivity of individual agricultural commodities to model effects on production, trade, prices, and consumption under moderate and high greenhouse gas emission scenarios. Two independent sources of data, which used different methodologies to determine the effect of increased atmospheric CO2 on different key crops, were combined with the modelled food supply results to estimate future nutrient availability. FINDINGS: Although technological change, market responses, and the effects of CO2 fertilisation on yield are projected to increase global availability of dietary protein, iron, and zinc, these increases are moderated by negative effects of climate change affecting productivity and carbon penalties on nutrient content. The carbon nutrient penalty results in decreases in the global availability of dietary protein of 4·1%, iron of 2·8%, and zinc of 2·5% as calculated using one dataset, and decreases in global availability of dietary protein of 2·9%, iron of 3·9%, and zinc of 3·4% using the other dataset. The combined effects of projected increases in atmospheric CO2 (ie, carbon nutrient penalty, CO2 fertilisation, and climate effects on productivity) will decrease growth in the global availability of nutrients by 19·5% for protein, 14·4% for iron, and 14·6% for zinc relative to expected technology and market gains by 2050. The many countries that currently have high levels of nutrient deficiency would continue to be disproportionately affected. INTERPRETATION: This approach is an improvement in estimating future global food security by simultaneously projecting climate change effects on crop productivity and changes in nutrient content under increased concentrations of CO2, which accounts for a much larger effect on nutrient availability than CO2 fertilisation. Regardless of the scenario used to project future consumption patterns, the net effect of increasing concentrations of atmospheric CO2 will slow progress in decreasing global nutrient deficiencies. FUNDING: US Environmental Protection Agency, Consultative Group on International Agricultural Research (CIGAR) Research Program on Policies, Institutions and Markets (PIM), and the CGIAR Research Program on Climate Change and Food Security (CCAFS).

DISTRIBUTIONAL IMPLICATIONS OF A NATIONAL CO2 TAX IN THE U.S. ACROSS INCOME CLASSES AND REGIONS: A MULTI-MODEL OVERVIEW.

This paper presents a multi-model assessment of the distributional impacts of carbon pricing. A set of harmonized representative CO2 taxes and tax revenue recycling schemes is implemented in five large-scale economy-wide general equilibrium models. Recycling schemes include various combinations of uniform transfers to households and labor and capital income tax reductions. Particular focus is put on equity - the distribution of impacts across household incomes - and efficiency, evaluated in terms of household welfare. Despite important differences in the assumptions underlying the models, we find general agreement regarding the ranking of recycling schemes in terms of both efficiency and equity. All models identify a clear trade-off between efficient but regressive capital tax reductions and progressive but costly uniform transfers to households; all agree upon the inferiority of labor tax reductions in terms of welfare efficiency; and all agree that different combinations of capital tax reductions and household transfers can be used to balance efficiency and distributional concerns. A subset of the models go further and find that equity concerns, particularly regarding the impact of the tax on low income households, can be alleviated without sacrificing much of the double-dividend benefits offered by capital tax rebates. There is, however, less agreement regarding the progressivity of CO2 taxation net of revenue recycling. Regionally, the models agree that abatement and welfare impacts will vary considerably across regions of the U.S. and generally agree on their broad geographical distribution. There is, however, little agreement regarding the regions which would profit more from the various recycling schemes.

THE IMPACT OF CARBON TAXATION AND REVENUE RECYCLING ON U.S. INDUSTRIES.

This paper provides a detailed, cross-model analysis and discussion of the implications of carbon tax scenarios on changes in sectoral output, energy production and consumption and the competitiveness of the United States' economy. Our analysis focuses on the broad patterns apparent across models in both qualitative and quantitative terms at the sector level, with a focus on energy-intensive, trade-exposed sectors. We identify how variations in carbon tax trajectories and different options for using the revenue from the tax drive these results.

Evaluating the effects of climate change on US agricultural systems: sensitivity to regional impact and trade expansion scenarios.

Agriculture is one of the sectors that is expected to be most significantly impacted by climate change. There has been considerable interest in assessing these impacts and many recent studies investigating agricultural impacts for individual countries and regions using an array of models. However, the great majority of existing studies explore impacts on a country or region of interest without explicitly accounting for impacts on the rest of the world. This approach can bias the results of impact assessments for agriculture given the importance of global trade in this sector. Due to potential impacts on relative competitiveness, international trade, global supply, and prices, the net impacts of climate change on the agricultural sector in each region depend not only on productivity impacts within that region, but on how climate change impacts agricultural productivity throughout the world. In this study, we apply a global model of agriculture and forestry to evaluate climate change impacts on US agriculture with and without accounting for climate change impacts in the rest of the world. In addition, we examine scenarios where trade is expanded to explore the implications for regional allocation of production, trade volumes, and prices. To our knowledge, this is one of the only attempts to explicitly quantify the relative importance of accounting for global climate change when conducting regional assessments of climate change impacts. The results of our analyses reveal substantial differences in estimated impacts on the US agricultural sector when accounting for global impacts vs. US-only impacts, particularly for commodities where the United States has a smaller share of global production. In addition, we find that freer trade can play an important role in helping to buffer regional productivity shocks.