{"id":5061,"date":"2011-04-18T10:02:14","date_gmt":"2011-04-18T14:02:14","guid":{"rendered":"https:\/\/esa.org\/esablog\/?p=5061"},"modified":"2011-04-18T10:02:14","modified_gmt":"2011-04-18T14:02:14","slug":"how-federal-investment-in-flood-management-can-save-money","status":"publish","type":"post","link":"https:\/\/esa.org\/esablog\/2011\/04\/18\/how-federal-investment-in-flood-management-can-save-money\/","title":{"rendered":"How federal investment in flood management can save money"},"content":{"rendered":"

This post contributed by Terence Houston, ESA Science Policy Analyst<\/em><\/p>\n

\"\"<\/a><\/p>\n

Is your neighborhood capable of weathering a flood? Would you still be able to drink tap water after such an event? Are the levees, dams, bridges and storm drains in your town capable of coping with a potential flood? The United States Geological Survey (USGS)\u2013at least for the time being\u2013 has the federal resources, investment and capability to answer these questions for our nation\u2019s communities.<\/span><\/p>\n

On April 15, USGS sponsored a briefing entitled \u201c2011 \u2013 The Year of the Flood?\u201d\u00a0 This briefing highlighted the many flood management <\/span>benefits<\/a> of the USGS streamgaging program. The speakers\u2014including Brian McCallum, Assistant Director of the USGS Georgia Water Science Center, Tom Graziano, Chief \u00a0Hydrologic Services Division of the NOAA National Weather Service, and Brian Hurt, a former City Engineer in Findlay, Ohio\u2014discussed the many benefits of maintaining up-to-date information on surface water data.<\/span><\/p>\n

The USGS operates and maintains a nationwide streamgaging network of about 7,000 gages. The network is supported by funding through the USGS\u2019s Cooperative Water Program, the USGS National Streamflow Information Program, other federal environmental agencies and roughly 800 state and local funding partners. Its users include a multitude of local, state and federal agencies, industry, educational institutions, non-governmental organizations and even individual citizens.<\/span><\/p>\n

The economic benefits and cost savings of adequate federal investment in streamgaging technologies is substantial.\u00a0 A study from the National Hydrologic Warning Council <\/em>estimated the value of hydrologic forecasts at $1.6 billion annually, and that report<\/a> attributed $1.02 billion in savings to successful forecasting for reservoir operation. If three to five percent of this total is attributed to the gage network that provides that necessary data for forecasting, the benefit is $30-$50 million annually. <\/span><\/p>\n

The Army Corps of Engineers presents an annual report to Congress, with detailed information on flood damages prevented by Corps projects. The average annual flood damage prevented by Corps projects between 1983-2002 is $23.2 billion.<\/span><\/p>\n

Nearly 20,000 communities across the nation participate in the <\/span>National Flood Insurance Program<\/a>, which is designed to provide an alternative to disaster assistance to reduce the costs of repairing infrastructural damage caused by floods. During Friday\u2019s briefing, Brian Hurt pointed out that methods that allow earlier flood warnings to residents allows them to preemptively secure valuables and consequently allow savings of \u201chundreds of thousands of dollars\u201d in the National Flood Insurance Program.<\/span><\/p>\n

Concurrently, the National Weather Service (NWS) uses USGS streamgaging data in its flood warning program. The data reported from the NWS flood warning program provides critical lead-time ahead of impending natural disasters for emergency response agencies, and consequently citizens, to take pre-emptive measures for minimizing the economic impacts of disasters and saving lives. Timely and accurate flood warnings help emergency response agencies to initiate community evacuations and road closures and to set up temporary shelters and mass care facilities.<\/span><\/p>\n

In addition to potential cost savings, USGS streamgaging data has multiple uses for communities. Streamflow data is used to manage multipurpose reservoir systems and other water management facilities to reduce impacts of flooding and drought on potable water resources. Consulting design engineers use historical peak streamflow data in the design of bridges and culverts which channel water. \u00a0Its data also record how continuing changes in the climate are impacting water availability and quality for communities. USGS monitoring includes tracking increases in sediment, pathogens, metals and pesticides, all of which detrimentally impact water resources used for drinking, recreation and other human activities.<\/span><\/p>\n

As policymakers work to address the federal deficit and prioritize federal investments, there needs to be ample consideration that investment in USGS streamgaging data is critical in a multitude of areas. That is, give communities \u201cmore bang for their buck,\u201d as well as peace of mind.<\/span><\/p>\n

Photo Credit: Don Becker, USGS<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

This post contributed by Terence Houston, ESA Science Policy Analyst Is your neighborhood capable of weathering a flood? Would you still be able to drink tap water after such an event? Are the levees, dams, bridges and storm drains in your town capable of coping with a potential flood? The United States Geological Survey (USGS)\u2013at least for the time being\u2013…<\/p>\n","protected":false},"author":43,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10],"tags":[308,864,991,865,1202,113,138,22,636,1095],"class_list":["post-5061","post","type-post","status-publish","format-standard","hentry","category-ecology-in-policy","tag-army-corps-of-engineers","tag-briefing","tag-climate-2","tag-disaster","tag-flood","tag-noaa","tag-usgs","tag-water","tag-water-resources","tag-weather"],"_links":{"self":[{"href":"https:\/\/esa.org\/esablog\/wp-json\/wp\/v2\/posts\/5061","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/esa.org\/esablog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/esa.org\/esablog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/esa.org\/esablog\/wp-json\/wp\/v2\/users\/43"}],"replies":[{"embeddable":true,"href":"https:\/\/esa.org\/esablog\/wp-json\/wp\/v2\/comments?post=5061"}],"version-history":[{"count":0,"href":"https:\/\/esa.org\/esablog\/wp-json\/wp\/v2\/posts\/5061\/revisions"}],"wp:attachment":[{"href":"https:\/\/esa.org\/esablog\/wp-json\/wp\/v2\/media?parent=5061"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/esa.org\/esablog\/wp-json\/wp\/v2\/categories?post=5061"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/esa.org\/esablog\/wp-json\/wp\/v2\/tags?post=5061"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}