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University of North Dakota | Geography - Academia.edu
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u-borderColorGrayLight u-borderRight1"><a href="https://und.academia.edu/"><span class="u-linkUnstyled u-tcGrayDarkest">University of North Dakota</span></a></span><h1 class="u-m0x u-fw300 u-fs24 u-displayInline">Geography</h1></div><div class="u-floatRight u-mt1x"></div></div></div></div></div><div class="TabbedNavigation"><div class="container"><div class="row"><div class="col-xs-12 clearfix"><ul class="nav u-m0x u-p0x list-inline"><li class="u-floatLeft u-pr5x u-mr5x u-borderColorGrayLight u-borderRight1"><a href="https://und.academia.edu/"><span><i class="fa fa-arrow-left"></i> All Departments</span></a></li><li class="u-floatLeft active"><a href="https://und.academia.edu/Departments/Geography/Documents">22 Papers</a></li><li class="u-floatLeft"><a href="https://und.academia.edu/Departments/Geography">18 Researchers</a></li></ul></div></div></div></div><div class="container"><div class="row"><div class="col-xs-12"><div class="u-displayFlex"><div class="u-flexGrow1"><div 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itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="138386" href="https://und.academia.edu/BradleyRundquist">Bradley Rundquist</a><script data-card-contents-for-user="138386" type="text/json">{"id":138386,"first_name":"Bradley","last_name":"Rundquist","domain_name":"und","page_name":"BradleyRundquist","display_name":"Bradley Rundquist","profile_url":"https://und.academia.edu/BradleyRundquist","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_54833622 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="54833622"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 54833622, container: ".js-paper-rank-work_54833622", }); });</script></li><li class="js-percentile-work_54833622 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span 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{"id":54833622,"title":"Remote Detection of Prairie Pothole Ponds in the Devils Lake Basin, North Dakota","created_at":"2021-10-02T06:33:13.772-07:00","owner_id":138386,"url":"https://www.academia.edu/54833622/Remote_Detection_of_Prairie_Pothole_Ponds_in_the_Devils_Lake_Basin_North_Dakota","slug":"Remote_Detection_of_Prairie_Pothole_Ponds_in_the_Devils_Lake_Basin_North_Dakota","dom_id":"work_54833622","summary":null,"publication":"GIScience \u0026 Remote Sensing","publication_with_fallback":"GIScience \u0026 Remote 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Rundquist","profile_url":"https://und.academia.edu/BradleyRundquist","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":204014,"name":"North Dakota","url":"https://www.academia.edu/Documents/in/North_Dakota","nofollow":false}],"publication_year":2005,"publication_year_with_fallback":2005,"paper_rank":null,"all_time_views":5,"active_discussion":{}}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_54833623" data-work_id="54833623" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/54833623/Geographic_distributions_of_motor_neuron_disease_mortality_and_well_water_use_in_U_S_counties">Geographic distributions of motor neuron disease mortality and well water use in U.S. counties</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">We recently reported that U.S. mortality rates for motor neuron disease (MND) at the level of the state are associated with well water use. However, data at the state level may not accurately reflect data at the individual level. We... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_54833623" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">We recently reported that U.S. mortality rates for motor neuron disease (MND) at the level of the state are associated with well water use. However, data at the state level may not accurately reflect data at the individual level. We therefore examined the association between MND mortality and well water use utilizing data from smaller geographic units that may better reflect exposure and disease at the individual level. We used data on age-adjusted MND mortality rates at the level of the county, obtained from the CDC, and corresponding data on the prevalence of well water use, obtained from the U.S. Geological Survey. Data were analyzed by multivariate linear regression and by Getis-Ord Gi*, a measure of spatial clustering. Age-adjusted mortality rates for MND in 923 U.S. counties were significantly correlated with the prevalence of well water (p &lt; 0.0001). &#39;Hot spots&#39; of MND mortality were significantly associated with &#39;hot spots&#39; of well water use (p &lt; 0.0005...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/54833623" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="92059c9eea061ab5235c0d8ed957f977" rel="nofollow" data-download="{"attachment_id":71004465,"asset_id":54833623,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/71004465/download_file?st=MTczMjczNjg4Niw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="138386" href="https://und.academia.edu/BradleyRundquist">Bradley Rundquist</a><script data-card-contents-for-user="138386" type="text/json">{"id":138386,"first_name":"Bradley","last_name":"Rundquist","domain_name":"und","page_name":"BradleyRundquist","display_name":"Bradley Rundquist","profile_url":"https://und.academia.edu/BradleyRundquist","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_54833623 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="54833623"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 54833623, container: ".js-paper-rank-work_54833623", }); 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$(".js-view-count[data-work-id=54833623]").text(description); $(".js-view-count-work_54833623").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_54833623").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="54833623"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i> <a class="InlineList-item-text u-positionRelative">5</a> </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="42973" href="https://www.academia.edu/Documents/in/Amyotrophic_Lateral_Sclerosis">Amyotrophic Lateral Sclerosis</a>, <script data-card-contents-for-ri="42973" type="text/json">{"id":42973,"name":"Amyotrophic Lateral Sclerosis","url":"https://www.academia.edu/Documents/in/Amyotrophic_Lateral_Sclerosis","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="64055" href="https://www.academia.edu/Documents/in/Water_Supply">Water Supply</a>, <script data-card-contents-for-ri="64055" type="text/json">{"id":64055,"name":"Water Supply","url":"https://www.academia.edu/Documents/in/Water_Supply","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="98134" href="https://www.academia.edu/Documents/in/United_States">United States</a>, <script data-card-contents-for-ri="98134" type="text/json">{"id":98134,"name":"United States","url":"https://www.academia.edu/Documents/in/United_States","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="289330" href="https://www.academia.edu/Documents/in/Prevalence">Prevalence</a><script data-card-contents-for-ri="289330" type="text/json">{"id":289330,"name":"Prevalence","url":"https://www.academia.edu/Documents/in/Prevalence","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=54833623]'), work: {"id":54833623,"title":"Geographic distributions of motor neuron disease mortality and well water use in U.S. counties","created_at":"2021-10-02T06:33:13.854-07:00","owner_id":138386,"url":"https://www.academia.edu/54833623/Geographic_distributions_of_motor_neuron_disease_mortality_and_well_water_use_in_U_S_counties","slug":"Geographic_distributions_of_motor_neuron_disease_mortality_and_well_water_use_in_U_S_counties","dom_id":"work_54833623","summary":"We recently reported that U.S. mortality rates for motor neuron disease (MND) at the level of the state are associated with well water use. However, data at the state level may not accurately reflect data at the individual level. We therefore examined the association between MND mortality and well water use utilizing data from smaller geographic units that may better reflect exposure and disease at the individual level. We used data on age-adjusted MND mortality rates at the level of the county, obtained from the CDC, and corresponding data on the prevalence of well water use, obtained from the U.S. Geological Survey. Data were analyzed by multivariate linear regression and by Getis-Ord Gi*, a measure of spatial clustering. Age-adjusted mortality rates for MND in 923 U.S. counties were significantly correlated with the prevalence of well water (p \u0026lt; 0.0001). \u0026#39;Hot spots\u0026#39; of MND mortality were significantly associated with \u0026#39;hot spots\u0026#39; of well water use (p \u0026lt; 0.0005...","publication":"Amyotrophic lateral sclerosis \u0026 frontotemporal degeneration","publication_with_fallback":"Amyotrophic lateral sclerosis \u0026 frontotemporal degeneration","downloadable_attachments":[{"id":71004465,"asset_id":54833623,"asset_type":"Work","always_allow_download":false,"scribd_thumbnail_url":"https://attachments.academia-assets.com/71004465/thumbnails/1.jpg","download_url":"https://d1wqtxts1xzle7.cloudfront.net/71004465/21678421.2016-libre.pdf?1633205993=\u0026response-content-disposition=attachment%3B+filename%3DGeographic_distributions_of_motor_neuron.pdf\u0026Expires=1732740486\u0026Signature=b2W8OP7hpsxXCWgKwzMSXEinkoBlexRKxGtOJVVdOn9bOh5mzpfpibtemjiUV02TjMVqZuV5AY4C2T9s~z9Hllcd~gw4qnrmTD~MVe-KDBnnDZIdsQCJ-j5v8uNFa7VMG5uk9lRXX4pzghWYharXZZhMFWUlLh-Un5nt91wT9bX8C~-1KQftgX02flQUalUf0kJ85uE5j1rN5iwE~s9IhRthKM5~hpBcihVmdoss40Pwh4KxVGiZw9~pyztcnLEVNaSpdDrypv7acv790DY36A29iN1uzyHYrOEOaH0w-R8aWgpwFVbO0CNWILd1cmzpnC3Q9aljNJMRrIzj4qdxjQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA","download_file_url":"https://www.academia.edu/attachments/71004465/download_file?st=MTczMjczNjg4Niw4LjIyMi4yMDguMTQ2&","full_thumbnail_url":"https://0.academia-photos.com/attachment_thumbnails/71004465/mini_magick20211002-1618-115rk1d.png?1633181689"}],"downloadable_attachments_with_full_thumbnails":[{"id":71004465,"asset_id":54833623,"asset_type":"Work","always_allow_download":false,"scribd_thumbnail_url":"https://attachments.academia-assets.com/71004465/thumbnails/1.jpg","download_url":"https://d1wqtxts1xzle7.cloudfront.net/71004465/21678421.2016-libre.pdf?1633205993=\u0026response-content-disposition=attachment%3B+filename%3DGeographic_distributions_of_motor_neuron.pdf\u0026Expires=1732740486\u0026Signature=b2W8OP7hpsxXCWgKwzMSXEinkoBlexRKxGtOJVVdOn9bOh5mzpfpibtemjiUV02TjMVqZuV5AY4C2T9s~z9Hllcd~gw4qnrmTD~MVe-KDBnnDZIdsQCJ-j5v8uNFa7VMG5uk9lRXX4pzghWYharXZZhMFWUlLh-Un5nt91wT9bX8C~-1KQftgX02flQUalUf0kJ85uE5j1rN5iwE~s9IhRthKM5~hpBcihVmdoss40Pwh4KxVGiZw9~pyztcnLEVNaSpdDrypv7acv790DY36A29iN1uzyHYrOEOaH0w-R8aWgpwFVbO0CNWILd1cmzpnC3Q9aljNJMRrIzj4qdxjQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA","download_file_url":"https://www.academia.edu/attachments/71004465/download_file?st=MTczMjczNjg4Niw4LjIyMi4yMDguMTQ2&","full_thumbnail_url":"https://0.academia-photos.com/attachment_thumbnails/71004465/mini_magick20211002-1618-115rk1d.png?1633181689"}],"has_pdf":true,"has_fulltext":true,"page_count":6,"ordered_authors":[{"id":138386,"first_name":"Bradley","last_name":"Rundquist","domain_name":"und","page_name":"BradleyRundquist","display_name":"Bradley Rundquist","profile_url":"https://und.academia.edu/BradleyRundquist","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":42973,"name":"Amyotrophic Lateral Sclerosis","url":"https://www.academia.edu/Documents/in/Amyotrophic_Lateral_Sclerosis","nofollow":false},{"id":64055,"name":"Water Supply","url":"https://www.academia.edu/Documents/in/Water_Supply","nofollow":false},{"id":98134,"name":"United States","url":"https://www.academia.edu/Documents/in/United_States","nofollow":false},{"id":289330,"name":"Prevalence","url":"https://www.academia.edu/Documents/in/Prevalence","nofollow":false},{"id":3995201,"name":"Motor neuron disease","url":"https://www.academia.edu/Documents/in/Motor_neuron_disease"}],"publication_year":2016,"publication_year_with_fallback":2016,"paper_rank":null,"all_time_views":4,"active_discussion":{}}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_54833625" data-work_id="54833625" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/54833625/County_level_incidence_rates_of_chronic_lymphocytic_leukemia_are_associated_with_residential_radon_levels">County level incidence rates of chronic lymphocytic leukemia are associated with residential radon levels</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Aim: We previously reported that incidence rates for chronic lymphocytic leukemia (CLL) among US states are significantly correlated with levels of residential radon (RR). Because these correlations could be influenced by confounding... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_54833625" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Aim: We previously reported that incidence rates for chronic lymphocytic leukemia (CLL) among US states are significantly correlated with levels of residential radon (RR). Because these correlations could be influenced by confounding and/or misclassification among large geographic units, we reinvestigated them using smaller geographic units that better reflect exposure and disease at the individual level. Methods: We examined the relationships between CLL and RR per county in 478 counties with publicly-available data. Results: After adjustment for ultraviolet radiation, a possible risk factor for CLL, county rates for CLL and RR were significantly correlated among males and females both together and separately (p </div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/54833625" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="968ee2d55890ef980bfeb6cc05debf44" rel="nofollow" data-download="{"attachment_id":71004475,"asset_id":54833625,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/71004475/download_file?st=MTczMjczNjg4Niw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="138386" href="https://und.academia.edu/BradleyRundquist">Bradley Rundquist</a><script data-card-contents-for-user="138386" type="text/json">{"id":138386,"first_name":"Bradley","last_name":"Rundquist","domain_name":"und","page_name":"BradleyRundquist","display_name":"Bradley Rundquist","profile_url":"https://und.academia.edu/BradleyRundquist","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_54833625 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="54833625"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 54833625, container: ".js-paper-rank-work_54833625", }); 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$(".js-view-count[data-work-id=54833625]").text(description); $(".js-view-count-work_54833625").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_54833625").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="54833625"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i> <a class="InlineList-item-text u-positionRelative">5</a> </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="98134" href="https://www.academia.edu/Documents/in/United_States">United States</a>, <script data-card-contents-for-ri="98134" type="text/json">{"id":98134,"name":"United States","url":"https://www.academia.edu/Documents/in/United_States","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="174502" href="https://www.academia.edu/Documents/in/Incidence">Incidence</a>, <script data-card-contents-for-ri="174502" type="text/json">{"id":174502,"name":"Incidence","url":"https://www.academia.edu/Documents/in/Incidence","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="225942" href="https://www.academia.edu/Documents/in/Radon">Radon</a>, <script data-card-contents-for-ri="225942" type="text/json">{"id":225942,"name":"Radon","url":"https://www.academia.edu/Documents/in/Radon","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1312021" href="https://www.academia.edu/Documents/in/Environmental_Exposure">Environmental Exposure</a><script data-card-contents-for-ri="1312021" type="text/json">{"id":1312021,"name":"Environmental Exposure","url":"https://www.academia.edu/Documents/in/Environmental_Exposure","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=54833625]'), work: {"id":54833625,"title":"County level incidence rates of chronic lymphocytic leukemia are associated with residential radon levels","created_at":"2021-10-02T06:33:13.944-07:00","owner_id":138386,"url":"https://www.academia.edu/54833625/County_level_incidence_rates_of_chronic_lymphocytic_leukemia_are_associated_with_residential_radon_levels","slug":"County_level_incidence_rates_of_chronic_lymphocytic_leukemia_are_associated_with_residential_radon_levels","dom_id":"work_54833625","summary":"Aim: We previously reported that incidence rates for chronic lymphocytic leukemia (CLL) among US states are significantly correlated with levels of residential radon (RR). Because these correlations could be influenced by confounding and/or misclassification among large geographic units, we reinvestigated them using smaller geographic units that better reflect exposure and disease at the individual level. Methods: We examined the relationships between CLL and RR per county in 478 counties with publicly-available data. Results: After adjustment for ultraviolet radiation, a possible risk factor for CLL, county rates for CLL and RR were significantly correlated among males and females both together and separately (p ","publication":"Future Oncology","publication_with_fallback":"Future Oncology","downloadable_attachments":[{"id":71004475,"asset_id":54833625,"asset_type":"Work","always_allow_download":false,"scribd_thumbnail_url":"https://attachments.academia-assets.com/71004475/thumbnails/1.jpg","download_url":"https://d1wqtxts1xzle7.cloudfront.net/71004475/52449bb4e5d3ceaac0ad2735d1571e458c95-libre.pdf?1633205991=\u0026response-content-disposition=attachment%3B+filename%3DCounty_level_incidence_rates_of_chronic.pdf\u0026Expires=1732740486\u0026Signature=WFThRRtRSZGoRQg5evJfaEs1UaS3rWFdAxE1vLaKjxMWN1PrzkHA9uMXZVRg43UBAGu37SsNeTs~VHZMdcZmfufB7Y3TT2bv0msD32km0kebRKbydlsr9cf1BHT3zQUducShC7D8ZxJvQJ-I0cWmqTLVcvIxhOHURkVxYfBaQx~z21faQNJ9LkIIHjJJQ82eBPhTfB5TK9ZBGWHDa6OPa9FA7IgxDobQYa~XroV4o2HRTbSLQqJbjUvoPq6iAkDV65~b7K6P9acs2WZhyAK7XkeenawErOKoFQHXVoSSPIPDqQWWY4jULx6fLYXuI0kvPm6L5kJQDSdsGvEQ1TwirA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA","download_file_url":"https://www.academia.edu/attachments/71004475/download_file?st=MTczMjczNjg4Niw4LjIyMi4yMDguMTQ2&","full_thumbnail_url":"https://0.academia-photos.com/attachment_thumbnails/71004475/mini_magick20211002-1618-izamrd.png?1633181720"}],"downloadable_attachments_with_full_thumbnails":[{"id":71004475,"asset_id":54833625,"asset_type":"Work","always_allow_download":false,"scribd_thumbnail_url":"https://attachments.academia-assets.com/71004475/thumbnails/1.jpg","download_url":"https://d1wqtxts1xzle7.cloudfront.net/71004475/52449bb4e5d3ceaac0ad2735d1571e458c95-libre.pdf?1633205991=\u0026response-content-disposition=attachment%3B+filename%3DCounty_level_incidence_rates_of_chronic.pdf\u0026Expires=1732740486\u0026Signature=WFThRRtRSZGoRQg5evJfaEs1UaS3rWFdAxE1vLaKjxMWN1PrzkHA9uMXZVRg43UBAGu37SsNeTs~VHZMdcZmfufB7Y3TT2bv0msD32km0kebRKbydlsr9cf1BHT3zQUducShC7D8ZxJvQJ-I0cWmqTLVcvIxhOHURkVxYfBaQx~z21faQNJ9LkIIHjJJQ82eBPhTfB5TK9ZBGWHDa6OPa9FA7IgxDobQYa~XroV4o2HRTbSLQqJbjUvoPq6iAkDV65~b7K6P9acs2WZhyAK7XkeenawErOKoFQHXVoSSPIPDqQWWY4jULx6fLYXuI0kvPm6L5kJQDSdsGvEQ1TwirA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA","download_file_url":"https://www.academia.edu/attachments/71004475/download_file?st=MTczMjczNjg4Niw4LjIyMi4yMDguMTQ2&","full_thumbnail_url":"https://0.academia-photos.com/attachment_thumbnails/71004475/mini_magick20211002-1618-izamrd.png?1633181720"}],"has_pdf":true,"has_fulltext":true,"page_count":9,"ordered_authors":[{"id":138386,"first_name":"Bradley","last_name":"Rundquist","domain_name":"und","page_name":"BradleyRundquist","display_name":"Bradley Rundquist","profile_url":"https://und.academia.edu/BradleyRundquist","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":98134,"name":"United States","url":"https://www.academia.edu/Documents/in/United_States","nofollow":false},{"id":174502,"name":"Incidence","url":"https://www.academia.edu/Documents/in/Incidence","nofollow":false},{"id":225942,"name":"Radon","url":"https://www.academia.edu/Documents/in/Radon","nofollow":false},{"id":1312021,"name":"Environmental Exposure","url":"https://www.academia.edu/Documents/in/Environmental_Exposure","nofollow":false},{"id":4032301,"name":"Population surveillance","url":"https://www.academia.edu/Documents/in/Population_surveillance"}],"publication_year":null,"publication_year_with_fallback":2017,"paper_rank":null,"all_time_views":4,"active_discussion":{}}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_54833632" data-work_id="54833632" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/54833632/Detection_of_Shelterbelt_Density_Change_Using_Historic_APFO_and_NAIP_Aerial_Imagery">Detection of Shelterbelt Density Change Using Historic APFO and NAIP Aerial Imagery</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Grand Forks County, North Dakota, boasts the highest concentration of shelterbelts in the World. As trees age and reach their lifespan limits, renovations should have taken place with new trees being planted. However, in recent years, the... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_54833632" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Grand Forks County, North Dakota, boasts the highest concentration of shelterbelts in the World. As trees age and reach their lifespan limits, renovations should have taken place with new trees being planted. However, in recent years, the rate of tree removal is thought to exceed the rate of replanting, which can result in a net loss of shelterbelts. Through manual digitization and geographic object-based image analysis (GEOBIA), we mapped shelterbelt densities in the Grand Forks County using historical and contemporary aerial photography, and estimated actual changes in density over 54 years. Our results showed a doubling in shelterbelt densities from 1962 to 2014, with an increase of 6402 m2/km2 over the 52 years (or 123 m2/km2/year). From 2014 to 2016, we measured 1,040,178 m2 of shelterbelt areas removed from the county, creating a density loss of −157 m2/km2/year. The total change over two years was relatively small compared with that seen over the previous 52 years. However, t...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/54833632" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="23ed2d6bb172b5dd2b2f4d2d73335390" rel="nofollow" data-download="{"attachment_id":71004380,"asset_id":54833632,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/71004380/download_file?st=MTczMjczNjg4Niw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="138386" href="https://und.academia.edu/BradleyRundquist">Bradley Rundquist</a><script data-card-contents-for-user="138386" type="text/json">{"id":138386,"first_name":"Bradley","last_name":"Rundquist","domain_name":"und","page_name":"BradleyRundquist","display_name":"Bradley Rundquist","profile_url":"https://und.academia.edu/BradleyRundquist","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_54833632 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="54833632"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 54833632, container: ".js-paper-rank-work_54833632", }); });</script></li><li class="js-percentile-work_54833632 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 54833632; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_54833632"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_54833632 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="54833632"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 54833632; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=54833632]").text(description); $(".js-view-count-work_54833632").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_54833632").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="54833632"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i></div><span class="InlineList-item-text u-textTruncate u-pl6x"><a class="InlineList-item-text" data-has-card-for-ri="1252" href="https://www.academia.edu/Documents/in/Remote_Sensing">Remote Sensing</a><script data-card-contents-for-ri="1252" type="text/json">{"id":1252,"name":"Remote Sensing","url":"https://www.academia.edu/Documents/in/Remote_Sensing","nofollow":false}</script></span></li><script>(function(){ if (false) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=54833632]'), work: {"id":54833632,"title":"Detection of Shelterbelt Density Change Using Historic APFO and NAIP Aerial Imagery","created_at":"2021-10-02T06:33:14.300-07:00","owner_id":138386,"url":"https://www.academia.edu/54833632/Detection_of_Shelterbelt_Density_Change_Using_Historic_APFO_and_NAIP_Aerial_Imagery","slug":"Detection_of_Shelterbelt_Density_Change_Using_Historic_APFO_and_NAIP_Aerial_Imagery","dom_id":"work_54833632","summary":"Grand Forks County, North Dakota, boasts the highest concentration of shelterbelts in the World. As trees age and reach their lifespan limits, renovations should have taken place with new trees being planted. However, in recent years, the rate of tree removal is thought to exceed the rate of replanting, which can result in a net loss of shelterbelts. Through manual digitization and geographic object-based image analysis (GEOBIA), we mapped shelterbelt densities in the Grand Forks County using historical and contemporary aerial photography, and estimated actual changes in density over 54 years. Our results showed a doubling in shelterbelt densities from 1962 to 2014, with an increase of 6402 m2/km2 over the 52 years (or 123 m2/km2/year). From 2014 to 2016, we measured 1,040,178 m2 of shelterbelt areas removed from the county, creating a density loss of −157 m2/km2/year. The total change over two years was relatively small compared with that seen over the previous 52 years. However, t...","publication":"Remote Sensing","publication_with_fallback":"Remote 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href="https://www.academia.edu/54833635/Monitoring_Landscape_Dynamics_in_Central_U_S_Grasslands_with_Harmonized_Landsat_8_and_Sentinel_2_Time_Series_Data">Monitoring Landscape Dynamics in Central U.S. Grasslands with Harmonized Landsat-8 and Sentinel-2 Time Series Data</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Remotely monitoring changes in central U.S. grasslands is challenging because these landscapes tend to respond quickly to disturbances and changes in weather. Such dynamic responses influence nutrient cycling, greenhouse gas... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_54833635" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Remotely monitoring changes in central U.S. grasslands is challenging because these landscapes tend to respond quickly to disturbances and changes in weather. Such dynamic responses influence nutrient cycling, greenhouse gas contributions, habitat availability for wildlife, and other ecosystem processes and services. Traditionally, coarse-resolution satellite data acquired at daily intervals have been used for monitoring. Recently, the harmonized Landsat-8 and Sentinel-2 (HLS) data increased the temporal frequency of the data. Here we investigated if the increased data frequency provided adequate observations to characterize highly dynamic grassland processes. We evaluated HLS data available for 2016 to (1) determine if data from Sentinel-2 contributed to an improvement in characterizing landscape processes over Landsat-8 data alone, and (2) quantify how observation frequency impacted results. 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class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Snow cover is an important variable in both climatological and hydrological studies because of its relationship to environmental energy and mass flux. However, variability in snow cover can confound satellite-based efforts to monitor... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_54833641" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Snow cover is an important variable in both climatological and hydrological studies because of its relationship to environmental energy and mass flux. However, variability in snow cover can confound satellite-based efforts to monitor vegetation phenology. This research explores the utility of the PhenoCam Network cameras to estimate Fractional Snow Cover (FSC) in grassland. The goal is to operationalize FSC estimates from PhenoCams to inform and improve the satellite-based determination of phenological metrics. The study site is the Oakville Prairie Biological Field Station, located near Grand Forks, North Dakota. We developed a semi-automated process to estimate FSC from PhenoCam images through Python coding. Compared with previous research employing RGB images only, our use of the monochrome RGB + NIR (near-infrared) reduced pixel misclassification and increased accuracy. The results had an average RMSE of less than 8% FSC compared to visual estimates. Our pixel-based accuracy ass...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/54833641" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="b4bb182748bf9e3a3117763cc1b10a84" rel="nofollow" data-download="{"attachment_id":71004381,"asset_id":54833641,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/71004381/download_file?st=MTczMjczNjg4Nyw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="138386" href="https://und.academia.edu/BradleyRundquist">Bradley Rundquist</a><script data-card-contents-for-user="138386" type="text/json">{"id":138386,"first_name":"Bradley","last_name":"Rundquist","domain_name":"und","page_name":"BradleyRundquist","display_name":"Bradley Rundquist","profile_url":"https://und.academia.edu/BradleyRundquist","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_54833641 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="54833641"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 54833641, container: ".js-paper-rank-work_54833641", }); });</script></li><li class="js-percentile-work_54833641 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 54833641; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_54833641"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_54833641 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="54833641"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 54833641; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=54833641]").text(description); $(".js-view-count-work_54833641").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_54833641").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="54833641"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i></div><span class="InlineList-item-text u-textTruncate u-pl6x"><a class="InlineList-item-text" data-has-card-for-ri="1252" href="https://www.academia.edu/Documents/in/Remote_Sensing">Remote Sensing</a><script data-card-contents-for-ri="1252" type="text/json">{"id":1252,"name":"Remote Sensing","url":"https://www.academia.edu/Documents/in/Remote_Sensing","nofollow":false}</script></span></li><script>(function(){ if (false) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=54833641]'), work: {"id":54833641,"title":"Semi-Automatic Fractional Snow Cover Monitoring from Near-Surface Remote Sensing in Grassland","created_at":"2021-10-02T06:33:15.487-07:00","owner_id":138386,"url":"https://www.academia.edu/54833641/Semi_Automatic_Fractional_Snow_Cover_Monitoring_from_Near_Surface_Remote_Sensing_in_Grassland","slug":"Semi_Automatic_Fractional_Snow_Cover_Monitoring_from_Near_Surface_Remote_Sensing_in_Grassland","dom_id":"work_54833641","summary":"Snow cover is an important variable in both climatological and hydrological studies because of its relationship to environmental energy and mass flux. 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Rundquist","profile_url":"https://und.academia.edu/BradleyRundquist","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":162010,"name":"Geomatic Engineering","url":"https://www.academia.edu/Documents/in/Geomatic_Engineering","nofollow":false}],"publication_year":null,"publication_year_with_fallback":2021,"paper_rank":null,"all_time_views":14,"active_discussion":{}}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_69252510" data-work_id="69252510" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/69252510/TEMPORARY_FLOODWATER_STORAGE_VOLUME_ESTIMATIONS_USING_1_m_LiDAR_AND_30_m_NED_DEMS_OF_THE_RED_RIVER_OF_THE_NORTH_BASIN">TEMPORARY FLOODWATER STORAGE VOLUME ESTIMATIONS USING 1-m LiDAR AND 30-m NED DEMS OF THE RED RIVER OF THE NORTH BASIN</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Compared here are storage volumes determined for 120 transect locations from 1-m Light Detection and Ranging (LiDAR) and 30-m National Elevation Dataset (NED) Digital Elevation Models (DEMs). The transects represent flat-, moderate-, and... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_69252510" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Compared here are storage volumes determined for 120 transect locations from 1-m Light Detection and Ranging (LiDAR) and 30-m National Elevation Dataset (NED) Digital Elevation Models (DEMs). The transects represent flat-, moderate-, and high-relief terrain in the Forest River Watershed of the Red River of the North Basin. Results indicate that either DEM yields acceptable storage estimates for terrain with flat to moderate-relief and LiDAR provides the more accurate estimate in areas of high-relief. In general, storage depths derived from LiDAR DEMs are greater than those extracted from NED DEMs, although storage estimates are not significantly different between the two datasets for flat-and moderate-relief areas. Each dataset can be used for storage estimation as a function of the local relief conditions, and certain section characteristics, which provided a basis to explain the patterns of observed discrepancies.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/69252510" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="43bd301076b6b6c73b98c0fc8cb9a474" rel="nofollow" data-download="{"attachment_id":79418876,"asset_id":69252510,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/79418876/download_file?st=MTczMjczNjg4OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="138386" href="https://und.academia.edu/BradleyRundquist">Bradley Rundquist</a><script data-card-contents-for-user="138386" type="text/json">{"id":138386,"first_name":"Bradley","last_name":"Rundquist","domain_name":"und","page_name":"BradleyRundquist","display_name":"Bradley Rundquist","profile_url":"https://und.academia.edu/BradleyRundquist","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_69252510 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="69252510"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 69252510, container: ".js-paper-rank-work_69252510", }); });</script></li><li class="js-percentile-work_69252510 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 69252510; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_69252510"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_69252510 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="69252510"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 69252510; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=69252510]").text(description); $(".js-view-count-work_69252510").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_69252510").removeClass('hidden') })</script></div></li></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_69252511" data-work_id="69252511" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/69252511/Flood_damage_assessment_and_survey_of_mitigation_efforts_at_Stump_Lake_North_Dakota_a_study_of_a_closed_basin_lake_flood">Flood damage assessment and survey of mitigation efforts at Stump Lake, North Dakota : a study of a closed-basin lake flood</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Since 1993, Devils Lake, a terminal lake in northeastern North Dakota, has risen 7.3 m in response to an unprecedented ten-year regional wet cycle. Lake area has nearly tripled, resulting in more than $400 million dollars in direct flood... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_69252511" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Since 1993, Devils Lake, a terminal lake in northeastern North Dakota, has risen 7.3 m in response to an unprecedented ten-year regional wet cycle. Lake area has nearly tripled, resulting in more than $400 million dollars in direct flood damages. Beginning in 1999 Devils Lake began to overflow into Stump Lake, a smaller closed lake sub-basin located in Nelson County. Outflow from Devils Lake has combined with local runoff to produce a 1.5-m rise in Stump Lake over the past three years. Extensive rural flooding marked by an increase in the number, size, and permanence of wetlands has also occurred within both lake basins over the same period. The authors document the flood history of Stump Lake and rural Nelson County, assess the flood damages resulting from the rise of Stump Lake and the growth of rural wetlands in Nelson County, and survey the flood mitigation efforts associated with this closed-basin flood hazard. Remote sensing image interpretation, field work, personal interview...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/69252511" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="b3aad8a0e5c686166e7b68ee7c8a74e4" rel="nofollow" data-download="{"attachment_id":79418879,"asset_id":69252511,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/79418879/download_file?st=MTczMjczNjg4OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="138386" href="https://und.academia.edu/BradleyRundquist">Bradley Rundquist</a><script data-card-contents-for-user="138386" type="text/json">{"id":138386,"first_name":"Bradley","last_name":"Rundquist","domain_name":"und","page_name":"BradleyRundquist","display_name":"Bradley Rundquist","profile_url":"https://und.academia.edu/BradleyRundquist","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_69252511 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="69252511"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 69252511, container: ".js-paper-rank-work_69252511", }); });</script></li><li class="js-percentile-work_69252511 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 69252511; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_69252511"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_69252511 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="69252511"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 69252511; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=69252511]").text(description); $(".js-view-count-work_69252511").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_69252511").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="69252511"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i></div><span class="InlineList-item-text u-textTruncate u-pl6x"><a class="InlineList-item-text" data-has-card-for-ri="402" href="https://www.academia.edu/Documents/in/Environmental_Science">Environmental Science</a><script data-card-contents-for-ri="402" type="text/json">{"id":402,"name":"Environmental Science","url":"https://www.academia.edu/Documents/in/Environmental_Science","nofollow":false}</script></span></li><script>(function(){ if (false) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=69252511]'), work: {"id":69252511,"title":"Flood damage assessment and survey of mitigation efforts at Stump Lake, North Dakota : a study of a closed-basin lake flood","created_at":"2022-01-23T07:05:57.884-08:00","owner_id":138386,"url":"https://www.academia.edu/69252511/Flood_damage_assessment_and_survey_of_mitigation_efforts_at_Stump_Lake_North_Dakota_a_study_of_a_closed_basin_lake_flood","slug":"Flood_damage_assessment_and_survey_of_mitigation_efforts_at_Stump_Lake_North_Dakota_a_study_of_a_closed_basin_lake_flood","dom_id":"work_69252511","summary":"Since 1993, Devils Lake, a terminal lake in northeastern North Dakota, has risen 7.3 m in response to an unprecedented ten-year regional wet cycle. Lake area has nearly tripled, resulting in more than $400 million dollars in direct flood damages. Beginning in 1999 Devils Lake began to overflow into Stump Lake, a smaller closed lake sub-basin located in Nelson County. Outflow from Devils Lake has combined with local runoff to produce a 1.5-m rise in Stump Lake over the past three years. Extensive rural flooding marked by an increase in the number, size, and permanence of wetlands has also occurred within both lake basins over the same period. The authors document the flood history of Stump Lake and rural Nelson County, assess the flood damages resulting from the rise of Stump Lake and the growth of rural wetlands in Nelson County, and survey the flood mitigation efforts associated with this closed-basin flood hazard. Remote sensing image interpretation, field work, personal 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Rundquist","profile_url":"https://und.academia.edu/BradleyRundquist","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":402,"name":"Environmental Science","url":"https://www.academia.edu/Documents/in/Environmental_Science","nofollow":false}],"publication_year":2003,"publication_year_with_fallback":2003,"paper_rank":null,"all_time_views":4,"active_discussion":{}}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_85592025" data-work_id="85592025" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/85592025/Sustainable_Development_Goals_in_the_Earth_and_Environmental_Sciences">Sustainable Development Goals in the Earth & Environmental Sciences</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList 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