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Kotikot, Susan M.

Publications and source records attributed to Kotikot, Susan M..

Spatial–Temporal Patterns of Historical, Near-Term, and Projected Drought in the Conterminous United States

Major droughts in the United States have heavily impacted the hydrologic system, negatively effecting energy and food production. Improved understanding of historical drought is critical for accurate forecasts. Data from global climate models (GCMs), commonly used to assess drought, cannot effectively evaluate local patterns because of their low spatial scale. This research leverages downscaled (~4 km grid spacing) temperature and precipitation estimates from nine GCMs’ data under the business-as-usual scenario (Representative Concentration Pathway 8.5) to examine drought patterns. Drought severity is estimated using the Palmer Drought Severity Index (PDSI) with the Thornthwaite evapotranspiration method. The specific objectives were (1) To reproduce historical (1966–2005) drought and calculate near-term to future (2011–2050) drought patterns over the conterminous USA. (2) To uncover the local variability of spatial drought patterns in California between 2012 and 2018 using a network-based approach. Our estimates of land proportions affected by drought agree with the known historical drought events of the mid-1960s, late 1970s to early 1980s, early 2000s, and between 2012 and 2015. Network analysis showed heterogeneity in spatial drought patterns in California, indicating local variability of drought occurrence. The high spatial scale at which the analysis was performed allowed us to uncover significant local differences in drought patterns. This is critical for highlighting possible weak systems that could inform adaptation strategies such as in the energy and agricultural sectors.

54 ENVIRONMENTAL SCIENCES↗

Planning green infrastructure placement based on projected precipitation data

Continued urbanization has led to tremendous changes on the landscape. These changes have exacerbated the effects of extreme climatic events such as flooding because of constrained water infiltration and increased surface flow. Typical runoff control measures involve sophisticated gray infrastructure that guide excess surface flow into storage and disposal sites. In a dynamic climate system, these measures are not sustainable since they cannot be easily modified to accommodate large volumes of runoff. Green Infrastructure (GI) is an adaptable technique that can be used to minimize runoff, in addition to offering an array of additional benefits (urban heat regulation, aesthetics, improved air quality etc.). Strategic placement of GI is key to achieving maximum utility. While physical site characteristics play a major role in determining suitable GI placement sites, knowledge of future precipitation patterns is crucial to ensure successful flood mitigation. Here, suitable GI sites within the city of Knoxville, Tennessee, were determined based on potential impact of an extreme flood event as indicated by site characteristics. Then, the relative potential likelihood of a flood event was determined based on projected precipitation data and knowledge of existing flood zones. By combining potential impact with likelihood information, low, medium, and high priority GI implementation sites were established. Results indicate that high priority sites are in the central parts of the city with priority decreasing outward. The GI prioritization scheme presented here, offers valuable guidance to city planners and policy makers who wish to exploit the GI approach for flood mitigation.

54 ENVIRONMENTAL SCIENCES↗

The Economic Accessibility of CO2 Sequestration through Bioenergy with Carbon Capture and Storage (BECCS) in the US

Bioenergy with carbon capture and storage (BECCS) is one strategy to remove CO2 from the atmosphere. To assess the potential scale and cost of CO2 sequestration from BECCS in the US, this analysis models carbon sequestration net of supply chain emissions and costs of biomass production, delivery, power generation, and CO2 capture and sequestration in saline formations. The analysis includes two biomass supply scenarios (near-term and long-term), two biomass logistics scenarios (conventional and pelletized), and two generation technologies (pulverized combustion and integrated gasification combined cycle). Results show marginal cost per tonne CO2 (accounting for costs of electricity and CO2 emissions of reference power generation scenarios) as a function of CO2 sequestered (simulating capture of up to 90% of total CO2 sequestration potential) and associated spatial distribution of resources and generation locations for the array of scenario options. Under a near-term scenario using up to 206 million tonnes per year of biomass, up to 181 million tonnes CO2 can be sequestered annually at scenario-average costs ranging from $62 to $137 per tonne CO2; under a long-term scenario using up to 740 million tonnes per year of biomass, up to 737 million tonnes CO2 can be sequestered annually at scenario-average costs ranging from $42 to $92 per tonne CO2. These estimates of CO2 sequestration potential may be reduced if future competing demand reduces resource availability or may be increased if displaced emissions from conventional power sources are included. Results suggest there are large-scale opportunities to implement BECCS at moderate cost in the US, particularly in the Midwest, Plains States, and Texas.

09 BIOMASS FUELS↗

Data and interactive visualization for "The economic accessibility of CO2 sequestration through bioenergy with carbon capture and sequestration (BECCS) in the US" submitted to the journal "Land", 2020

Detailed outputs and interactive visualization to accompany the manuscript titled "The economic accessibility of CO2 sequestration through bioenergy with carbon capture and sequestration (BECCS) in the US" submitted to the journal "Land" in 2020. https://public.tableau.com/profile/billion.ton.2016#!/vizhome/ORNLBECCS2020/CO2EMITANDCAPTURE2

Langholtz, Matthew↗

Mapping Threats to Agriculture in East Africa: Performance of MODIS Derived LST for Frost Identification in Kenya's Tea Plantations

Increased prevalence of weather related hazards in eastern Africa including drought, floods, hail and frost threatening agricultural productivity. Kenya is heavily dependent on agriculture for economic growth (FAO 2013); (1) Agriculture contributed 23.5% and 21.5% of GDP in 2009 and 2010 respectively, (2) Employment to half a million households of smallholders and 150,000 on large tea estates. Tea growing in Kenya depends on stability of the weather; (1) Weather is unpredictable, (2) Frost has contributed 30% of tea leaf losses, (3) Drought has contributed 14-30%, (4) The losses are experienced between January and march - frost and dry season.

remote sensing↗