Using satellite vegetation and compound topographic indices to map highly erodible cropland buffers for cellulosic biofuel crop developments in eastern Nebraska, USA

Abstract

"Using satellite vegetation and compound topographic indices to maphighly erodible cropland buffers for cellulosic biofuel cropdevelopments in eastern Nebraska, USA" (2016). USGS Staff --Published Research. 903. http://digitalcommons.unl.edu/usgsstaffpub/903 Ecological Indicators 60 (2016) [64][65][66][67][68][69][70] Contents lists available at ScienceDirect Ecological Indicators j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / e c o l i n d Cultivating annual row crops in high topographic relief waterway buffers has negative environmental effects and can be environmentally unsustainable. Growing perennial grasses such as switchgrass (Panicum virgatum L.) for biomass (e.g., cellulosic biofuel feedstocks) instead of annual row crops in these high relief waterway buffers can improve local environmental conditions (e.g., reduce soil erosion and improve water quality through lower use of fertilizers and pesticides) and ecosystem services (e.g., minimize drought and flood impacts on production; improve wildlife habitat, plant vigor, and nitrogen retention due to post-senescence harvest for cellulosic biofuels; and serve as carbon sinks). The main objectives of this study are to: (1) identify cropland areas with high topographic relief (high runoff potentials) and high switchgrass productivity potential in eastern Nebraska that may be suitable for growing switchgrass, and (2) estimate the total switchgrass production gain from the potential biofuel areas. Results indicate that about 140,000 hectares of waterway buffers in eastern Nebraska are suitable for switchgrass development and the total annual estimated switchgrass biomass production for these suitable areas is approximately 1.2 million metric tons. The resulting map delineates high topographic relief croplands and provides useful information to land managers and biofuel plant investors to make optimal land use decisions regarding biofuel crop development and ecosystem service optimization in eastern Nebraska.

Mapping cropland waterway buffers for switchgrass development in the eastern Great Plains, USA

“…The identified biofuel potential areas in the EGP are nearly 11.7 times larger than the biofuel potential areas identified in eastern Nebraska (1400 km 2 , c . 1.9% of the total study area) in our previous study (Gu & Wylie, ). The total annual estimated switchgrass biomass production gain for these suitable areas is approximately 15 million metric tons, which is about 12.5 times higher than the switchgrass production estimated from eastern Nebraska ( c .…”

“…d) based on NLCD 2011 and the USGS irrigation map (switchgrass economics are not expected to be able to cover the additional costs of irrigation). Calculate the mean CTI value (CTI mean ) within a 5 × 5 pixel window (150 m × 150 m) for each pixel. Map the high‐topographic‐relief waterway buffers based on (i) CTI > (1.2 × CTI mean ) and (ii) 12 < CTI < 20. Water bodies (e.g., lakes) and extremely high CTI regions associated with larger streams and rivers were excluded from the waterway buffer map as the small rivulets or streamlets are to be targeted for potential switchgrass conversion (Gu & Wylie, ). Remove pixels from the identified waterway buffers if they are (i) irrigated cropland pixels or (ii) unproductive switchgrass pixels (i.e., switchgrass GSN < 0.5) based on the switchgrass productivity map. Exclude pixels within the Sand Hills ecoregion from the identified biofuel potential areas to avoid any undesirable land use change (i.e., avoid sand dune activation). Estimate the total switchgrass biofuel potential areas in the EGP and the potential total switchgrass biomass productivity gain (Gu & Wylie, ) from the biofuel potential areas in the EGP. Compare the EGP study results with the results from the previous Nebraska study. Generate a 250‐m switchgrass biomass productivity potential map for the EGP to visualize the results. A switchgrass productivity uncertainty map for the EGP region was generated based on our previous study result (Gu et al ., ).…”

“…3 Map the high-topographic-relief waterway buffers based on (i) CTI > (1.2 9 CTI mean ) and (ii) 12 < CTI < 20. Water bodies (e.g., lakes) and extremely high CTI regions associated with larger streams and rivers were excluded from the waterway buffer map as the small rivulets or streamlets are to be targeted for potential switchgrass conversion (Gu & Wylie, 2016). 4 Remove pixels from the identified waterway buffers if they are (i) irrigated cropland pixels or (ii) unproductive switchgrass pixels (i.e., switchgrass GSN < 0.5) based on the switchgrass productivity map.…”

“…Growing perennial grasses such as switchgrass for biofuel in riparian zones, stream waterway buffers, and highly erodible cropland areas has been proposed and investigated (Sanderson et al, 2001;Mersie et al, 2006;Sanderson, 2008;Dominguez-Faus et al, 2009;Koh et al, 2009;Powers et al, 2010; http://www.mda.state.mn.us/pro tecting/conservation/practices/waterway.aspx). Gu & Wylie (2016) developed an approach that combined 30m hydrological data (i.e., US Geological Survey [USGS] Compound Topographic Index) and switchgrass biomass productivity potential information to map highly erodible waterway buffers that might be suitable for switchgrass development. This method was applied to a small pilot study area (eastern Nebraska) for demonstration and illustration (Gu & Wylie, 2016).…”

Mapping marginal croplands suitable for cellulosic feedstock crops in the Great Plains, United States

“…Based on the previous study results, switchgrass has higher biomass production than most grassland species; therefore, the total estimated switchgrass biomass productivity gain from the identified biofuel potential areas in the GP was assumed to be double that of the total estimated grassland biomass productivity (Vogel et al ., ; Fike et al ., ; Mclaughlin et al ., ; Kiniry et al ., ; Jager et al ., ; Schmer et al ., ; Wullschleger et al ., ; Anderson‐Teixeira et al ., ; Behrman et al ., ; Tulbure et al ., ; Bonin & Lal, ; Gu & Wylie, ).…”