Journal Publications

Note: *Identifies students and # for postdocs advised and supervised by Dr. Sami Khanal as ‘major advisor’.

2026

• Devnath, B., Khanal, S., Shah, A., and Reza, T. 2026. Nutrient Recovery from Co-Hydrothermal Carbonization of Animal Manures: Synergistic Effects on Hydrochar Properties and Agronomic Potential. Waste Management 213 (2026), 115391.

2025

• *Dhakal, S., Shah, A., and Khanal, S. 2025. Monitoring Historical Waste Coal Piles Using Image Classification and Change Detection Algorithms on Satellite Images. Remote Sensing 17(17), 3041.
• Ansari, A., Timilsina, A. P., Shah, A., Manandhar, A., and Khanal, S. 2025. Switchgrass for abandoned mine lands reclamation: A SWAT-based hydrological and water quality assessment. Agricultural Water Management 318 (2025) 109730.
• Hu, T., Zhang, X., Khanal, S., and Zhao, K. 2025. Beyond radiation use efficiency: A mechanistic biochemical photosynthesis model for crop growth simulation and agroecosystem modeling.  Computers and Electronics in Agriculture, 233, 110199.
• Waltz, L., Katari, S., Hong, C., Anup, A., Colbert, J., Potlapally, A., Dill, T., Porter, C., Engle, J., Stewart, C., Subramoni, H., Machiraju, R., Ortez, O., Lindsey, L., Nandi, A., and Khanal, S. 2025. Cyberinfrastructure for Machine Learning Applications in Agriculture: Experiences, Analysis, and Vision. International Society of Precision Agriculture, 7, 1496066.

2024

• Van Roekel, J., Khanal, S., Karhoff, S., Lindsey, L., Haden, R., Timilsina, A., Bevers, N., Shahrokhi, M., Ortez, O. 2024. Impact of Cereal Rye Cover Crops on Yield and Environmental Outcomes: A Field-Scale Approach. ASA, CSSA, SSSA International Annual Meeting.
• Katari, S., Venkatesh, S., Stewart, C., and Khanal, S. 2024. Integrating Automated Labeling Framework for Enhancing Deep Learning Models to Count Corn Plants Using UAS Imagery. Sensors, 24, no. 19: 6467.
• Bevers, N., Ohlson, E., KC, K., Jones, M., and Khanal, S. 2024. Sugarcane Mosaic Virus Detection in Maize Using UAS Multispectral Imagery. Remote Sensing, 16, no. 17: 3296.
• Park, J., Khanal, S., Zhao, K., and Byun, K. 2024. Remote Sensing of Chlorophyll-a and Water Quality over Inland Lakes: How to Alleviate Geo-Location Error and Temporal Discrepancy in Model Training. Remote Sensing, 16, no. 15: 2761.
• Devnath, B.,  Khanal, S., Shah, A., and Reza, T. 2024. Influence of Hydrothermal Carbonization (HTC) Temperature on Hydrochar and Process Liquid for Poultry, Swine, and Dairy Manure. Environments, 11, no. 7: 150.
• KC, K., Romanko, M., Perrault, A. et al. On-farm cereal rye biomass estimation using machine learning on images from an unmanned aerial system. 2024. Precision Agric, 25, 2198–2225.
• Joshi, N., Park, J., Zhao, K., Londo, A., and Khanal, S. 2024. Monitoring Harmful Algal Blooms and Water Quality Using Sentinel-3 OLCI Satellite Imagery with Machine Learning. Remote Sensing,16, no. 13: 2444.
• Waltz, L., Katari, S., Dill, T., Porter, C., Ortez, O., Lindsey, L., Nandi, A., and Khanal, S. 2024. A Growth Stage Centric Approach to Field Scale Yield Estimation for Corn Leveraging Machine Learning Methods From Multimodal Data. 16th International Conference on Precision Agriculture.
• Timilsina, A., Steinbeck, G., Shah, A., and Khanal, S. 2024. Assessing the Multifaceted Tradeoffs of Agricultural Conservation Practices on Ecosystem Services in the Midwest U.S. Sustainability, 16, no. 13: 5622.
• Hu, T., Zhang, X., Khanal, S., Wilson, R., Leng, G., Toman, E., Wang, X., Li, Y., and Zhao, K. Climate change impacts on crop yields: A review of empirical findings, statistical crop models, and machine learning methods. 2024. Environmental Modelling & Software, Volume 179, 106119. ISSN 1364-8152.
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2023

• Wong, T., Lyon, S., Khanal, S., and Zhao, K. 2023. Grain size estimation in fluvial gravel bars using uncrewed aerial vehicles: A comparison between methods based on imagery and topography. Earth Surface Processes and Landforms.
• Mousavi-Avval, S.H., Khanal, S., and Shah, A. 2023. Assessment of potential pennycress availability and suitable sites for sustainable aviation fuel refineries in Ohio. Sustainability.
• Varga, M., Csukas, B., Khanal, S., and Bakshi, B. 2023. Lessons from the biosphere for the anthroposphere: Analysis of recycling structures of conservational measures. Resources, Conservation and Recycling, 192, 106919.
• *KC, K., and Khanal, S. 2023. Agricultural productivity and water quality tradeoffs of winter cover crops at a landscape scale through the lens of remote sensing. Journal of Environmental Management, 330, 117212.

2022

• *Bhattarai, A., *Steinbeck, G., Grant, B., Kalcic, M., King, K., Smith, W., *Xu, N., Deng, J., and Khanal, S. 2022. Development of a calibration approach using DNDC and PEST for improving estimates of management impacts on water and nutrient dynamics in an agricultural system. Environmental Modelling and Software, 157, 105494.
• Zappernick, N., Nedunuri, K.V., Islam, K.R., Khanal, S., Worley, T., Laki, S.L., and Shah, A. 2022. Techno-economic analysis of a recirculating tilapia-lettuce aquaponics system. Journal of Cleaner Production, 365, 132753.
• Allred, B., Martinez, L., Khanal, S., Sawyer, A.H., and Rouse, G. 2022. Subsurface drainage outlet detection in ditches and streams with UAV thermal infrared imagery: Preliminary research. Agricultural Water Management, 271, 107737.
• *Zhang, Z., Khanal, S., Raudenbush, A., Tilmon, K., and Stewart, C. 2022. Assessing the efficacy of machine learning techniques to characterize soybean defoliation from unmanned aerial vehicles. Computers and Electronics in Agriculture, 193, 106682.

2021

• Lee, K., Khanal, S., and Bakshi, B. 2021. Techno-ecologically synergistic food-energy-water systems can meet human and ecosystem needs. Energy & Environmental Science, 7(14), 3700-3716.
• *KC, K., Zhao, K., Romanko, M., and Khanal, S. 2021. Assessment of the spatial and temporal patterns of cover crops using remote sensing. Remote Sensing, 13(14), 2689.
• Khanal, S., Klopfenstein, A., *KC, K., Ramarao, V., Fulton, J., Douridas, N., and Shearer, S. 2021. Assessing the impact of agricultural field traffic on corn grain yield using remote sensing and machine learning. Soil and Tillage Research, 208.

2020

• Khanal, S., *KC, K., Fulton, J.P., Shearer, S., and Ozkan, E. 2020. Remote Sensing in Agriculture-Accomplishments, Limitations, and Opportunities. Remote Sensing, 12 (22).
• *Zhang, Z., Boubin, J., Stewart, C., and Khanal, S. 2020. Whole-field reinforcement learning: A fully autonomous aerial scouting method for precision agriculture. Sensors, 20(22).

2019

• Boubin, J., Chumley, J., Stewart, C., and Khanal, S. 2019. Autonomic Computing Challenges in Fully Autonomous Precision Agriculture. IEEE International Conference on Autonomic Computing (ICAC), Umea, Sweden, 2019, pp. 11-17.

2018

• Khanal, S., Fulton, J., Klopfenstein, A., Douridas, N., and Shearer, S. 2018. Integration of high-resolution remotely sensed data and machine learning techniques for spatial prediction of soil properties and corn yield. Computers and Electronics in Agriculture, 153, 213-225.
• Khanal, S., Fulton, J., Douridas, N., Klopfenstein, A., and Shearer, S. 2018. Integrating aerial images for in-season nitrogen management in a corn field. Computers and Electronics in Agriculture, 148, 121-131.
• Khanal, S., Lal, R., Kharel, G., and Fulton, J. 2018. Identification and classification of critical soil and water conservation areas in the Muskingum River basin in Ohio. Journal of Soil and Water Conservation, 73 (2), 213-226.
• Vasco-Correa, J., Khanal, S., Manandhar, A., and Shah, A. 2018. Anaerobic digestion for bioenergy production: Global status, environmental and techno-economic implications, and government policies. Bioresource Technology, 247, 1015-1026.

2017

• Khanal, S., Fulton, J., and Shearer, S. 2017. An overview of current and potential applications of thermal remote sensing in precision agriculture. Computers and Electronics in Agriculture, 139, 22-32.
• Shah, A., Darr, M., Khanal, S., and Lal, R. 2017. A techno-environmental overview of a corn stover biomass feedstock supply chain for cellulosic biorefineries. Biofuels, 8 (1), 59-69.
• Khanal, S., Fulton, J., Shah, A., Klopfenstein, A., Douridas, N., and Shearer, S. 2017. Economics of in-season nitrogen management practices for corn production. Agricultural Research and Technology: Open Access Journal 5(2), 555660.

2014

• Khanal, S., Anex, R.P., Anderson, C.J., and Herzmann, D.E. 2014. Streamflow impacts of biofuel policy-driven landscape change. PLOS One, 9 (10).
• Khanal, S., Anex, R.P., Gelder, B.K., and Wolter, C. 2014. Nitrogen balance in Iowa and the implications of corn-stover harvesting. Agriculture Ecosystems & Environment, 183, 21-30.
• Janowiak, M. K., Iverson, L. R., Khanal, S. et al. 2014. Forest ecosystem vulnerability assessment and synthesis for northern Wisconsin and western Upper Michigan: a report from the Northwoods Climate Change Response Framework project. General Technical Report. NRS-136. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station, 1-247.

2013

• Khanal, S., Anex, R.P., Anderson, C.J., Herzmann, D.E., and Jha, M.K. 2013. Implications of biofuel policy‐driven land cover change for rainfall erosivity and soil erosion in the United States. GCB Bioenergy, 5(6), 713-722.
• Khanal, S., Ambinakudige, S., and Rodgers, J. 2013. A GIS analysis of the spatial relation between evapotranspiration and pan evaporation in the United States. Water International, 38(3), 353-360.

2012

• Khanal, S., Anex, R.P., Gelder, B.K., Dixon, P., and Caragea, P. 2012. Cropping pattern choice with proximity to ethanol production and animal feeding operations. Biofuels, Bioproducts and Biorefining, 6(4), 431-443.
• Shah, A., Darr, M.J., Medic, D., Anex, R.P., Khanal, S., and Maski, D. 2012. Techno‐economic analysis of a production‐scale torrefaction system for cellulosic biomass upgrading. Biofuels, Bioproducts and Biorefining, 6(1), 45-57.
• Khanal, S. 2012. Assessment of the Environmental Impacts of Agricultural Practices in Biofuels Production Systems (Order No. 3547570). Available from Agricultural & Environmental Science Collection; Dissertations & Theses @ Big Ten Academic Alliance; ProQuest Dissertations & Theses A&I; ProQuest Dissertations & Theses Global. (1269161272).

2010

• Ambinakudige, S., and Khanal, S. 2010. Assessment of Impacts of Hurricane Katrina on Net Primary Productivity in Mississippi. Earth Interactions, 14,1-12.
• Ambinakudige, S., Choi, J., & Khanal, S. 2010. A comparative analysis of CBERS-2 CCD and LANDSAT-TM satellite images in vegetation mapping. Revista Brasileira de Cartografia, 63(1).

2009

• Khanal, S. 2009. Estimation of aboveground terrestrial net primary productivity and analysis of its spatial and temporal trends in the conterminous United States from 1997 to 2007 using NASA – CASA model (Order No. 1470494). Available from ProQuest Dissertations & Theses A&I; ProQuest Dissertations & Theses Global. (304938906).

2003

• Ambinakudige, S., Choi, J., & Khanal, S. 2009. A comparative analysis of CBERS and LANDSAT data. In American Society for Photogrammetry and Remote Sensing Annual Conference 2009, ASPRS 2009 (pp. 31-36).