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14 <br /> Aa The Economic Importance of Water in Kansas <br /> Figure 2 summarizes the estimated GSP losses by study area arising from GMD3's constrained water <br /> scenario in CY2062. This suggests that in percentage terms, Area 3 could lose 52.2%of GSP in CY2062 as <br /> a result of GMD3's estimated reduction in water availability. However,the hardest hit area in percentage <br /> terms could be Area 2. This latter area consists of 5 counties—Greeley, Lane,Scott,Wallace,and Wichita. <br /> Area 2's estimated $1.4 billion loss in GSP in CY2062 due to GMD3's reduced water availability scenario <br /> equates to a 66.2% loss in the area's GSP in that year. <br /> Figure 2: Estimated GSP Losses by Area in CY2062 <br /> Area 1 ®1.11111.111111 38.0% <br /> Area 2 66.2% <br /> Area 3 52.2% <br /> Area 4 9.3% <br /> Area 5 9.5% <br /> Area 6 0.0% <br /> Area 7 0.0% <br /> All 7 Areas 10.1% <br /> 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% <br /> Source:Apparet Analytics <br /> Table 4 estimates the total statewide GSP losses at a sectoral level in the State of Kansas, compared to a <br /> Business as Usual (BAU) scenario in which water availability is unconstrained. The GSP estimates <br /> encompass direct, indirect, and induced losses. The sectors are categorized according to the North <br /> American Industry Classification System (NAICS).11 An explanation of the categories of business activity <br /> included within each NAICS sector is provided in Appendix A. <br /> Two private sector establishment categories are each estimated to contribute over$3 billion less to GSP <br /> (2015 $) in the State of Kansas if the best available regional data provided for CY2062 holds true. These <br /> sectors are Agriculture, Forestry, Fishing and Hunting; and Real Estate and Rental. Five additional public <br /> 11 NAICS is the standard used by Federal statistical agencies to classify business establishments for the purpose of collecting, <br /> analyzing,and publishing statistical data related to the U.S.business economy. <br /> 9 <br /> Apparet Analytics 2015 <br />