<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20170815</CreaDate>
<CreaTime>13255800</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
</Esri>
<dataIdInfo>
<idAbs>The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee.</idAbs>
<searchKeys>
<keyword>FWHydrography</keyword>
<keyword>Hydrography</keyword>
<keyword>Stream / River</keyword>
<keyword>Lake / Pond</keyword>
<keyword>Canal / Ditch</keyword>
<keyword>Reservoir</keyword>
<keyword>Spring / Seep</keyword>
<keyword>Swamp / Marsh</keyword>
<keyword>Artificial Path</keyword>
<keyword>Reach Code</keyword>
</searchKeys>
<idPurp>NHD Waterbody</idPurp>
<idCredit>USGS, NHD, WyGISC</idCredit>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
<idCitation>
<resTitle>NHD - Waterbody</resTitle>
</idCitation>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAgAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCACFAMgDASIAAhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQAAAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWmp6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEAAwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSExBhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElKU1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD2rTNMsDpVmTY2xJgT/lkv90e1Wv7L0/8A58bb/vyv+FGl/wDIJsv+uCf+girdAFT+y9P/AOfG2/78r/hR/Zen/wDPjbf9+V/wq3RQBU/svT/+fG2/78r/AIUf2Xp//Pjbf9+V/wAKt0UAVP7L0/8A58bb/vyv+FH9l6f/AM+Nt/35X/CmX91LA6IpESMNxnI3BcckEe470+2uWmkKcNt5Z1+7z0H19qfKyeZXsH9l6f8A8+Nt/wB+V/wo/svT/wDnxtv+/K/4VbopFFT+y9P/AOfG2/78r/hR/Zen/wDPjbf9+V/wq3RQBU/svT/+fG2/78r/AIUf2Xp//Pjbf9+V/wAKt0UAVP7L0/8A58bb/vyv+FH9l6f/AM+Nt/35X/CrdFAFT+y9P/58bb/vyv8AhTZLDTIYmkks7REUZZjEoAH5VdJAGScAVhXqzanOGtmMttGQNoxsZt2DnPDY6+2OM99KcOZ6uyInLlWm5pDTdOYArZWpB6ERL/hR/Zen/wDPjbf9+V/wrB0+O8XUIrWOaVPKbe6scYTPII5Bzk9z7YrqadWn7N2TuKnPnV7WKn9l6f8A8+Nt/wB+V/wo/svT/wDnxtv+/K/4VborI0Kn9l6f/wA+Nt/35X/Cj+y9P/58bb/vyv8AhVuigCp/Zen/APPjbf8Aflf8KKt0UAVNL/5BNl/1wT/0EVbqppf/ACCbL/rgn/oIq3QAUhIUZNLVDVfIW1Mkqu8iK7RLGCWJCnoB3/8ArUbCbsh8tnFOZJFQrKzDMnKng9PXHX659KljmyyqxXkcHcOf889KzI49SjS1/fl3WNPtDSd24DcDjvnp26jNTmSQzRvAzHz9qkuPljABJIzjJPTj61V21qZp67E4kaY7pFjSMqwjZX3E++APTPf/AOtJbWxgiRPNLqFC4wAMc9AOPT8qzJ3S0jS63b4QQERF+YswA2qc8dD+Y9OdoYAAzwBSatrcqLu9RaTcN23PPXFVnlBnUtI8Yj3HC8hwMA544wT/AJ5w+BEQsQTvZizDcSAe4/SixVyeoLidoGi+UFGJDdc9CeOOenfFR3V+ltJHCsck08nKxxjkgEAnPQAZ/wAkik1GFJIgx2+Yudpb+WO4OBkemaqMdVzbMmUtHboW1YOoZTlSMg0tQ203nQLIeD3GCOaGuo1Yod28A8bT6Z69KXK72KurXJqKinkaNBsALE/xHAx35qqLvEgbzVYMCvB+QMATkHv7/SmoNq4nJJ2Lc8CXMDwyDKOMEVWSCLS7AiCIuyqFGSAzntk/U/qajj1VIYf+Jg0dvMGwAWAD5Pylc+vT65rI1q8lvJHtormSCAqqs6MB97kcg5B/TAPPatqdGcpcr2/AynUilzLcg8PJcy6/Jct+9iMT+ZLg43lyQAeM8E446emeevrF0XSzbbLkSbWKskgTkSncfnP5npW1Ri5qdTQMPFxhqFFFFcxuFFFFABRRRQBU0v8A5BNl/wBcE/8AQRVuqml/8gmy/wCuCf8AoIq3QAVWv53trRpYwhcEYD9Dk4x9as0HgHAz7UpK6sgOUu/EEkU8UqIPsvyh/wB5twRzj24ZeuAcc46VHJrYj043TFFXzYliV2LrtJAPUYzhjnknj8lkubO81CW3haOPP+utJ4hkqygF+f7oxgfX1FS61BHBPY27RQR2G8DMsYKhtp2jgdyOenbuaxqtwipJu/8Anov8zmTk7u+g6OG+sUluJLSJIpARIiOWIGc4AyPVuh7j0rN8VeHNSuf9K03ULjDJ5ckMbMVKbiRkDOQMjI5zz9Ky31iDUdVt9EtHmkAYu5AICMjHgIF7Y7A/jg59BiiWa2CJJEybNjhVyC3HX9ePftWqo1sPK2sdE0+/9eaJTp14uO5neGjef2LBFeIkc6ZXaBg7QQDnHf8AAe9SX14LK6Ek0sgJQr8hBAJ29e3049fWn3dz9h3KFuHO35PlVUHoM4456Z4JNSRzC+gZoIxs8zIcAMGGSMjPfj+WMituSpy8z69ehorJcieqIreVX12RioyYEKSEEAjLBlHo24DP4VNqLQeWJWmWFkwCzMqkA+5Iwe9ILhYbX965MikOQXxtyc7Sc+/c1S8R2rzaBLNEiLcQqsiNJtAXB+Yc8Yxng8dKmvOUIucN0hr4WvmVp9clj2wyxzMxAzIqZG7eAACCOeCfcA9alsJI4LQvnYQiRKgYZGAeN568Y57c4JrA0O6l1VI7ea6i8y1Uzb4gPlQRhRuOMFvn9M8HniraXFzdW9u0HmShVcoQ3VxwVYEDJ+8Rg+g5Arsw0416SaVr73+/0OVzad737HRfbJDp4kljEsw+ZUjYA5yQRnpkd/6CspLpZ7cs4LC6zyFGxWHTkdQTxnnPI9asQ25ltTJ9qkhmKhJI92BCxJJOMZx168HA65zVZ7OKQpHJsxECAkQIOCcPncOg4/X1q4Rgmy5OTsZ8s8nn3vkBpoRujSANny1G0by3uecAHOB3zmtNayR2ov7b95HDHIVd5AGjO4DJB4OMHpjODwDmtyxFrqGFEUb8lv8AVhRIvIHI6ng57ZJrZ+y27gxhUkVwvybgF2gjsOuMentW0sSqTSt6maoc6vc5TRdefS4VtpEaZZG3DCngE8nPc5PPAHfqcV0mkeIbLV4naKQBkIBBOAc9ME9eKy7rwzEbtbhbTawz9yQvkHdkAHHPJ9uc+tZdsYz5lsBJEApTKuFxhiRkMAASykg5PIx3zU1IUq7cor1fb5BCdWlaMtjvgc9KKwtJU2cX7jzJIZSXAIGNzHP3upx+P9BujkCvOqQ5HZM7oS5lcKKKKzLCiiigCppf/IJsv+uCf+girdVNL/5BNl/1wT/0EVboAKKKydf0+41O1gt4TiLzlaba+1ioPIHHpnuOlHoKTsrlW4e0mvpLmMbp7WQFpY8lSo5KcHlsA8c44JxXLSeKZr2Od73TFuoDLthR+Nqk+mCSRx0/Su5fbplg0Flb7mjiLRxgALxxyeB/WuT8V3Uur6fp1tYM8El6geVVycIxGQQCM8nnj+pGEqUqtaKjPlfXS6Oas3CDZzF3aQxaustkrmdJiI1iU8gj5eW5bJyCCPUV6Dps8aWMMrzGWWcFfKl++CRuI+UEjgDj2/A1vDmn3C2RV7tbhxk+ZgN84bHU88Y44HXv0ENpdeReXMaxTT3cjZKCXceHORuyQoDMBx69c9NKOHlTbk6jkrbdurIiuWzta5s3iK7+aJrgeUhbeMsrqQf4ehOSPy9qlWGN2LJb+VcZ3xPJFnBKjJ77e49evrzdjfzw6yQsm0gfOBg8A8evXH4UzaJN6ujMFTbh14J6/wCHT09q6faXVjo5NbkU8USWk3lx+UioSHiUFuADwMcn86it5Au6NnaRN2zcRggYAweec7eOO4/FrSx3cxgMcrqyHOGHy5II+9+J47dR0qaVHZptgdgoG0kZxxyAevP55J/AS11Fe+qORbQ20rxDbyxE26zXIKbMbMZOVO7HZR0/vVsPqflwyySSFZGiIQsCAu7HJbJ4+U+nTpW9sMrHeGHYjAxx/wDr6+1ckkaXNwFgiuYoFbLjLfNIGLHBJJOcAnGOnfpVYOjGLld6afLyMai5Ph6m/fxBbJC8YkRCrquOcgcA56DgcnPp71zcVtLeTRgR4eVipdBnylwR3OM9B1PbHbG7LJ9s09ZoD5skYwZJAQGUEZPy8Akc8fl6ZE14LrUlt4zlYcFVgkG4MDt2sex+YDJPXPPJA68PzJNIitytpjdT00wRWl9a2v2qREDQM5LFSF54xyWA6Z64rU0jUrk2pmvhAZXcljCW+X5enI+p5xgfTm44hkeRnleMpMXBIX5SMZ6jI4x+B64rKMV7byR21rIImKjfJIg3sueXX5sKRk8Ec844pcyqU+SXQfL7OXNE6RYBuV2J3KxYbSVHPqAcH8ajk06zlkWR7eMyJ91gMEde4+p/Op4pFljDoSQe5GKfXn80k9zs5YtDI4kiLlQAXbc2ABk9P6U+iipKCiiigAooooAqaX/yCbL/AK4J/wCgirdVNL/5BNl/1wT/ANBFW6ACiiigCKXeMuNxVeSgAO4Y7e9Y0kdpqdta6lG7pDhWdVjIZtucKfQhuMduR3rccgIxY4UA5NZq20Ajk8iIQmZ2lCKy/OxA5APHufcVV48rvuZzTb8jPubW608pLDKZbn5z5u0d+oCgc5IUnJ7HGOK5hvFWt6VKr37iS2NwqbkiwNvPKtk7hkNgew5rsbnc9hJbSxzynaTK0SD0z8oAPOcHB/wFcB4u0GW202M2/mtGo4zJu6n7hA9Np59ufbswtNVZxhLtb/J3/r8zhxTnCLlC+h6Nbal9u02O6j3BWAKyKVwTjvyQOeOp7c0231W1RbaJrxJricZVSyqzf8Bzx3x+AzXnPg7xQtusOm3sKmGR1wZeQGJIBB7dQSSexx1Fdxc2ksusq08Yk8phLEoznIOcqScevGOMnnkCubEU50G4P/h/TU2o11VipRLUeoS3HiFbGTT5VSGATpcORySSpGOnr0NWreVN58vc0LNuB8ojHrz/ABZPPH8qqxW01mC7v5t0zGRjkuFXk7QDjA42jGO5x1qa/kbEiJlZx88ShgGfGM4xzjjHI7j6VXx2sraGqbSbZPLdQQFFCBkkfZlOfmBwQcd+D+XtWObm7kuLhbUorw7ngLHGVbgbhwMZxgZBwtNNlcSWM6O0Nssz/vQoEhQH3OBgnDcgEDjHTFeCSGJds0v2iGe3L5Ck7wDn7pzxjp688HHHTCEIp63ZlOcm1fRF42Vq1xvuw4ilTasRxtQgjOe5yQuBzyPpWZc29okstwLIx2rPvQRlCJXDFt2AM53e+CF4I/i1jFbahb27l0WLZ5qpjy1J6qGzyBgrxz0/OlEzq87zvJcIGAlWVxmP5iMegXIJ4OeegGKuEn3/AK/zInFP+v60IFkuleEC3kkjYA7Yl2Fvu8AZAGCCOf5HItPJCu77V5wupZgwgjuGOcPkjHTvyvPX8abostudOji2KA6naIyzbQx7DHXnqO4P4F9Y3DebMDboyFQsHmEAsxH3uoHAzgAnPeqdufkelhK/LzLU0LTVUijkM0iJDHzuYnIALcc98Afn+Jv2OoQ38bNEHQq7IUkXa3ynGcHtXH3bam2qNcSx+aPLVY8IRiQ9BkYwRz7jHrW3ougz6fcrczXB3FCGjHIJbaefoQR78VjXo04x5m9WaUqs3KyWhv0UUVwHYFFFFABRRRQBU0v/AJBNl/1wT/0EVbqppf8AyCbL/rgn/oIq3QAUUUUAI33G4zx09ax53uIYhLBG4lab50J5ZdxC8nOPYe+OK2awbK/u5JLpLi2jjmUK7/NhSpOR1wc43DP+zTWvu3tczm9i4yhXik2JuRw24jk5BHDdyff8e1Qw2ytaxxCHy4zgou8BkTr83qOcY569anS5WLT3ukjkZIl2+TEAzAKSCAAOvbHt61bOZ4g8MoCunyMFz1HBrW7TuSkmcJrHgQXV8t9aupWeTeyRqFC55zndyDx/niunsree30sQ6hKJmibJuFJffjjPOTuBHT1wOahsJbw3Ulvd3MTbJm+UrtO3jGMHB5bAyOfqM1fkhdGlnEJk3fMpVl3JhcAru4zyev6ilGChpFmcIRu5JWFRZnvACqfZ/LO05I544wfYt+lILmJo3vJYSYEVmMzfN8vI+UDJ+vH50Q3cMSJAZnJI+/L99if1zwe3am3d6EsGuYkNzArAOiDczKTtOB36k470+Vt2/r+maXVrlbWtVFlFCwEgSRwiXG3KKW4GQCCc5ABGcU/TrV1zLLGzbiAqMqjHyk8heAPm/QVn6hqKXGlXN9qESppsDROkcbbpGKsGJYY+XpjHp+FaSyQ3cNu4nQCXDRfvPvHqRx1ORnr2/A7yhy00rddX+P8Aw5kpc027kxuYB5ZCBd8bEoRjGPwznGeKoQ6e0U8NyJGXcC5QR7QAegCjrj0Pbv6tgnt7WNoHuB5ax7sIGlLPuclt7cEk7SO/B5Iq7YrNFp8TKxldkIMrcHqSMgn3x7VLXs07ehS99q5maJN89158LCGKUNDIrl1kHJO3uAMjPatiKLy5xiRmDtuf5gfm9wenXt6VQikluZURbS7ZoJzL+9fZsJ46n7wALdj/AFq59qxKouTAoB2yMHJAJHQenNKrPnlePX5hTXKrMu7I0laRo4w54BwAT36/56VI0ipjJPJwMAnnOKg3211bRhpUljmwVIPD9+Pb2qyAAMCua93qdC8gopMjOMjI7UtIYUUUUAFFFFAFTS/+QTZf9cE/9BFW6qaX/wAgmy/64J/6CKt0AFFFFACMwRCx6AZrm7W2Fw1xPLHJm7Uy5UjAQjAGM56HPvk1p6szRrG+V8tclgfYdenP0HrWRo0mbY2++fy45fLLg5AXaMqOAFwc578ccEEdFKE0udbf8E56kk5KLNbTA/2ZBJFHA7ZICsM9fTA9DmrZuE8/yRGWOQVO5eck5IBOeO/14qoZzK0aW+ZImKo8oJbAx06nt1PuPrUupXsdjp097sVvs6FgWBAIxng47jjPrSlFylZLcpNKO+xLc28E+PPiRlXJGRkge3H+cVGkCyyXEcgeSFwCC7FhyOQPb29/SnWLy3dmk86lDKS6pnBVT90Eg8nHXnqan+VcFVyegwDxyB+H/wBaoba90tWepn6nEphijZYnGRnzI8jAIyTjgDGfbn3qOCCzF28wLpJEfMd0GxGL5z/vfXnp65zfnjju7d4HRyrjkbiO/qDn04zWctvbsWhyk+4qSrSFuOwI6j5WHbHJrWDTjYzkrSuRvbi6sZba64sio3YcqRgAkMccgkMD1PPvw+8ja5VLeLcsUrMhZAF8rYSCc5B5/wAfWponYTofKMbDdhPLI2px7c4IPQ45B96pa5bXM+gKdPuhJIjL85/jAbDZIPTGc8Z60SnNNcv9P8ibKzZzt9bRWs9vdf2tN+4kdWlIYSNtyAuTw3Pbrxx1zXQ+G55H0mF5royyzLuBkTy3b1J6bgBjkeh9cVkatNBd6XBLdzQxXEkvzGElw+1RlQUBO09eCDz74rW0O9szbWJilhBfzQAiDMuGxwc5A5BwfUZPFdtZt4dc297fn5HNSSVZ22/4Y1DF510+4xqijduXIOc8cg+gIPr9OKxtX0O4N6txbTtGhYIVUZ35PcYAx8xGCeQO+a13l23lsimWNQQWQ4bO4HHPPfI4/lVqdQyh9iOYzkZOMcjv/npXFGpKEkzrlCM00zHazC5twPJlCZcyqTC/GPxHtkY6/WMzS2pMUtrcBdojSSEs2OyjIOSBk8ke/bjb86ItuckHbkL6j1x1x160vlQygqGw4IZ9h2nOQeR/nrWbd/iXmHJ/Kzhdb8KanbSfbNHupC8pCsYWYORknJ5+ncfrXQeFX1kWxh1bJZEBDN1JJJx68DjnuK0/P2NFEYvmf5y0Q+Vmz7/n/WprYTrLKJVULnIZT97jqfes/ZqKstEKFNKfMizRRRSOgKKKKAKml/8AIJsv+uCf+girdVNL/wCQTZf9cE/9BFW6ACiiigDK1C3WWVo5ZCsUg3hlHKMuOenOR/LvmuNjmNhmxIKSbShmuFOx+oHy9FJ3IDkHr0716DLbLLIHZm4xtx255x9elVo9F06OVpfsqPIxJLSEuef97NdEcRKEOSPXc5qlBzldHJaN4lvIldZEe8WJQpMMLEqxJJJxxjP4+3FbF3qjanpOo2enQzm8CeWFkUj74Izyeg55OBxxXRqqoMKoUegGKWsoVJJ3kldW/plKi+Xl5jNscixtbeZPJukiCiNjuxtxgkKenGev41djlSUFo8McYDY4NNltIJpBI0SeaBgPt5//AFf4VIY9ybXO4cdv896cpKTuaRTWg1T5cIyNqqB0HT/61Zr26iaS4ttpdn3svl539B168e35dK1DGHA38kEHgkDg5FPojPl2CUebcxLWWRli8q2kSIsY2+Xlc/KCVzwBgjp746kWRDcXNw5aJIY1fawIBEwIG4kfoP8AIrSoolUu7pWEqdlZs5t9Ff7NcW820mS4eVFiAzIvULluhOPX6nFSfYrS4tAqY320hyRyqt3D54IwAD7nOAa0dStZ5jDLbytHJGxB25yVPoM4znHJ6DNTQQOIJVdIopZGJZof4jj731/wqo1GopN3I9mrtWM90g1CZLq1uim392uIzgnJyM+5xnHp16g2HmtBcpGJR5rH7r54GOeMccCuT0y01vQrto7iJWhurktIYxvZ85JxxwP88V09hazzxq17GymJ8wsZDvK8EZ/HqPat6sYxbXNdLYzpTcvs2fU0QrPsIyiBc4IGc06VWddq7QCOSwz+n50+iuO51WKv2CHfuBdRjACnGPxHPr+Zq0BgYooocm9wSS2CiiikMKKKKAKml/8AIJsv+uCf+girdFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAH//Z</Data>
</Thumbnail>
</Binary>
</metadata>
