KDF Search Results

Logging and mill residues are currently the largest sources of woody biomass for bioenergy in the US, but short-rotation woody crops (SRWCs) are expected to become a larger contributor to biomass production, primarily on lands marginal for food production. However, there are very few studies on the environmental effects of SRWCs, and most have been conducted at stand rather than at watershed scales.

Advanced biomass feedstocks tend to provide more non-fuel ecosystem goods and services (ES) than 1st-generation alternatives. We explore the idea that payment for non-fuel ES could facilitate market penetration of advanced biofuels by closing the profitability gap. As a specific example, we discuss the Mississippi-Atchafalaya River Basin (MARB), where 1st-generation bioenergy feedstocks (e.g., corn-grain) have been integrated into the agricultural landscape.

Join the U.S. Department of Energy’s Bioenergy Technologies Office on Dec. 6, 2018, at 1 p.m. CST for a webinar on “Biomass Production and Water Quality in the Mississippi River Basin.” In this webinar, Argonne National Laboratory and Oak Ridge National Laboratory will jointly present modeling and analyses of potential implications of biomass production on nutrients and sediments in each of the six tributaries of the Mississippi River Basin.

Model-data comparisons are always challenging, especially when working at a large spatial scale and evaluating multiple response variables. We implemented the Soil and Water Assessment Tool (SWAT) to simulate water quantity and quality for the Tennessee River Basin.

This dataset reports the pre-treatment hydrology and pre- and post-treatment water quality data from a watershed-scale experiment that is evaluating the effects of growing short-rotation loblolly pine for bioenergy on water quality and quantity in the southeastern U.S. The experiment is taking place on the Savannah River Site, near New Ellenton, South Carolina, USA.  Beginning in 2010, water quality and hydrology were measured for two years in 3 watersheds (R, B, C).

Global development of the biofuel sector is proceeding rapidly. Biofuel feedstock continues to be produced from a variety of agricultural and forestry resources. Large-scale feedstock production for biofuels could change the landscape structure and affect water quantity, water quality, and ecosystem services in positive or negative ways. With rapid advancements in computation technologies and science, field- and watershed-scale models have become a vital tool for quantifying water quality and ecosystem responses to bioenergy landscape and management practices.

Using the Soil and Water Assessment Tool (SWAT) for large-scale watershed modeling could be useful for evaluating the quality of the water in regions that are dominated by nonpoint sources in order to identify potential “hot spots” for which mitigating strategies could be further developed. An analysis of water quality under future scenarios in which changes in land use would be made to accommodate increased biofuel production was developed for the Missouri River Basin (MoRB) based on a SWAT model application.

There is an inextricable link between energy production and food/feed/fiber cultivation with available water resources. Currently in the United States, agriculture represents the largest sector of consumptivewater usemaking up 80.7%of the total. Electricity generation in the U.S. is projected to increase by 24 % in the next two decades and globally, the production of liquid transportation fuels are forecasted to triple over the next 25-years, having significant impacts on the import/export market and global economies.

Water consumption and water quality continue to be key factors affecting environmental sustainability in biofuel production. This review covers the findings from biofuel water analyses published over the past 2 years to underscore the progress made, and to highlight advancements in understanding the interactions among increased production and water demand, water resource availability, and potential changes in water quality. We focus on two key areas: water footprint assessment and watershed modeling.

The increasing demand for bioenergy crops presents our society with the opportunity to design more sustainable landscapes. We have created a Biomass Location for Optimal Sustainability Model (BLOSM) to test the hypothesis that landscape design of cellulosic bioenergy crop plantings may simultaneously improve water quality (i.e. decrease concentrations of sediment, total phosphorus, and total nitrogen) and increase profits for farmer-producers while achieving a feedstock-production goal.

ABSTRACT. Adding bioenergy to the U.S. energy portfolio requires long‐term profitability for bioenergy producers and long‐term protection of affected ecosystems. In this study, we present steps along the path toward evaluating both sides of the sustainability equation (production and environmental) for switchgrass (Panicum virgatum) using the Soil and Water Assessment Tool (SWAT). We modeled production of switchgrass and river flow using SWAT for current landscapes at a regional scale.

We quantify the emergence of biofuel markets and its impact on U.S. and world agriculture for the coming decade using the multi-market, multi-commodity international FAPRI (Food and Agricultural Policy Research Institute) model. The model incorporates the trade-offs between biofuel, feed, and food production and consumption and international feedback effects of the emergence through world commodity prices and trade.

This study presents the results of comparing land use estimates between three different data sets for the Upper Mississippi River Basin (UMRB). The comparisons were performed between the U.S. Department of Agriculture (USDA) Natural Resource Conservation Service (NRCS) National Resource Inventory (NRI), the U.S. Geological Survey (USGS) National Land Cover Data (NLCD) database, and a combined USDA National Agricultural Statistics Service (NASS) Agricultural Census – NLCD dataset created to support applications of the Hydrologic Unit Model for the U.S. (HUMUS).

Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution.

Land-use change models are used by researchers and professionals to explore the dynamics and drivers of land-use/land-cover change and to inform policies affecting such change. A broad array of models and modeling methods are available to researchers, and each type has certain advantages and disadvantages depending on the objective of the research. This report presents a review of different types of models as a means of exploring the functionality and ability of different approaches.

This paper presents an overview of multi-agent system models of land-use/cover change (MAS/LUCC models). This special class of LUCC models combines a cellular landscape model with agent-based representations of decisionmaking, integrating the two components through specification of interdependencies and feedbacks between agents and their environment. The authors review alternative LUCC modeling techniques and discuss the ways in which MAS/LUCC models may overcome some important limitations of existing techniques. We briefly review ongoing MAS/LUCC modeling efforts in four research areas.

Until recently, advanced very high-resolution radiometer (AVHRR) observations were the only viable source of data for global land cover mapping. While many useful insights have been gained from analyses based on AVHRR data, the availability of moderate resolution imaging spectroradiometer (MODIS) data with greatly improved spectral, spatial, geometric, and radiometric attributes provides significant new opportunities and challenges for remote sensing-based land cover mapping research.

This model was developed at Idaho National Laboratory and focuses on crop production. This model is an agricultural cultivation and production model, but can be used to estimate biomass crop yields.

Increasing demand for crop-based biofuels, in addition to other human drivers of land use, induces direct and indirect land use changes (LUC). Our system dynamics tool is intended to complement existing LUC modeling approaches and to improve the understanding of global LUC drivers and dynamics by allowing examination of global LUC under diverse scenarios and varying model assumptions. We report on a small subset of such analyses.