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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Water Management and Systems Research » Research » Publications at this Location » Publication #302217
Title: Landuse and agricultural management practice web-service (LAMPS) for agroecosystem modeling and conservation planning

Author
item KIPKA, HOLM - Colorad0 State University
item DAVID, OLAF - Colorad0 State University
item Green, Timothy
item GARCIA, LUIS - Colorad0 State University
item Ascough Ii, James
item ROJAS, KEN - Natural Resources Conservation Service (NRCS, USDA)
item MAZDAK, ARABI - Colorad0 State University

Submitted to: Soil and Water Conservation Society Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 7/27/2014
Publication Date: 7/30/2014
Citation: Kipka, H., O. David, T.R. Green, L. Garcia, J.C. Ascough II, K.W. Rojas, and M. Arabi. 2014. Landuse and agricultural management practice web-Service (LAMPS) for agroecosystem modeling and conservation planning. Proc. 2014 Soil and Water Conservation Society Meeting, July 27-30, Lombard, Illinois. pp. 89.

Interpretive Summary: Agroecosystem models and conservation planning tools require spatially and temporally explicit input data about agricultural management operations. The USDA Natural Resources Conservation Service is developing a Land Management and Operation Database (LMOD) which contains potential model input, but LMOD does not provide high-resolution spatial data. LAMPS complements LMOD data with 30-m resolution spatial information from the CropScape web service provided by the USDA National Agricultural Statistics Service (NASS). Here, we demonstrate spatial data provisioning to the AgroEcoSystem-Watershed (AgES-W) model implemented under the Object Modeling System. LAMPS determines the dominant crop for each year and area by calculating a crop confidence index from CropScape accuracy values. LAMPS identifies irrigated and non-irrigated crops using geo-spatial irrigation data provided by the USGS. It then detects a sequence of main crops and matches the crop sequence to available crop rotation information and all associated management tillage operation information obtained from LMOD. Finally, LAMPS generates required management input files for the AgES-W model over the desired simulation period. Previously LAMPS was evaluated using ground observations of crop type on a farm in Colorado. Here, LAMPS will be demonstrated and evaluated on a watershed in Iowa.

Technical Abstract: Agroecosystem models and conservation planning tools require spatially and temporally explicit input data about agricultural management operations. The USDA Natural Resources Conservation Service is developing a Land Management and Operation Database (LMOD) which contains potential model input, however LMOD does not provide high-resolution spatial data. LAMPS complements LMOD data with spatial information by using a 30 meters resolution geo-spatial data source, the CropScape web service from the USDA National Agricultural Statistics Service (NASS). NASS contains a remote sensing based raster Crop Data Layer (CDL) for a specific year and a spatial Area of Interest (AOI). Here, we demonstrate spatial data provisioning to the component-based AgroEcoSystem-Watershed (AgES-W) model implemented under the Object Modeling System. AgES-W simulates hydrological responses, water quality, and agronomic processes across spatially distributed and interconnected hydrological response units (HRUs). Land use inputs are required for each HRU across a watershed. LAMPS queries the annual crop information from CropScape web service for the AOI and for available CDL years. LAMPS selects the dominant crop by calculating a crop confidence index within each HRU using CropScape provided accuracy values. LAMPS also identifies irrigated and non-irrigated crops using geo-spatial irrigation data provided by the USGS. It then detects a sequence of main crops for every HRU and matches the crop sequence to available crop rotation information and all associated management tillage operation information obtained from LMOD. Finally, LAMPS generates required management input files for the AgES-W model over the desired simulation period. Previously LAMPS was evaluated using ground observations of crop type on a farm in Colorado. Here, LAMPS will be demonstrated and evaluated on a watershed in Iowa.