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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Research Project #420992


Location: Hydrology and Remote Sensing Laboratory

2012 Annual Report

1a. Objectives (from AD-416):
1. Enhance the current decision support system tools to determine the level of crop residue and biomass needed to maintain economic viability, protect soil carbon, minimize soil erosion, and enhance water quality. 2. Integrate remote sensing data and products in to the DSS to scale-up model from fields to watersheds and regions. 3. Evaluate the DSS with data from on-going CEAP and REAP watershed studies over a range of soil and climate gradient across the U.S. Croplands.

1b. Approach (from AD-416):
Application of the EPIC decision support system developed at HSRL, the SWAT water quality model for assessing the impacts of post harvest crop residue removal on soil erosion, soil carbon management and soil water quality. Model parameters derived from remote sensing will provide the spatial component to enhance the site-specific decisions regarding soil and crop management at the local level.

3. Progress Report:
The current escalation of energy costs has emphasized the need to seek alternative sources of renewable energy. Development of biofuel from corn, soybeans, and other non-grain crops may contribute to shifts in conservation programs promoted by USDA and lead to accelerated soil erosion and environmental degradation. Proper and timely management of soil and crop resources enhance the ability of the soil to produce food, feed, fiber, and fuel. The primary study site is the South Fork watershed of the Iowa River which contains some of central Iowa’s most productive land. Crop residue cover and remotely sensed imagery were acquired in 2009-2011 and will be used to assess soil tillage intensity in the spring and fall for the watershed. Crop biomass data and remotely sensed imagery were acquired at maturity in 2009 and 2010 and will be used to calibrate and test the crop models. Work is underway to integrate these data and products into a suite of decision support tools and to scale-up from a few fields to the entire watershed. This project offers a systematic solution to provide decision support tools for short and long-term strategies that will benefit the end-users for resource management and conservation practices.

4. Accomplishments