1 00:00:09,837 --> 00:00:10,835 - All right. 2 00:00:10,835 --> 00:00:12,058 Welcome, everybody. 3 00:00:12,058 --> 00:00:17,058 Our first talk today in this Forest Ecosystems track is 4 00:00:18,780 --> 00:00:23,780 from Rebecca Lilja, with the USDA Forest Service, 5 00:00:27,403 --> 00:00:30,597 presenting "Forest to Faucets 2.0." 6 00:00:33,301 --> 00:00:34,804 - [Rebecca] Hello, my name is Rebecca Lilja. 7 00:00:34,804 --> 00:00:37,104 I'm a GIS specialist in the US Forest Service, 8 00:00:38,159 --> 00:00:40,162 Eastern region, State Private Forestry. 9 00:00:40,162 --> 00:00:41,643 I'm located in Durham, New Hampshire, 10 00:00:41,643 --> 00:00:43,680 and I'm excited to be here today to talk 11 00:00:43,680 --> 00:00:46,353 to you about the National Forests to Faucets 2.0 assessment. 12 00:00:49,723 --> 00:00:50,919 I'm speaking to you today 13 00:00:50,919 --> 00:00:52,980 as part of a larger core team of folks 14 00:00:52,980 --> 00:00:54,181 from the forest service 15 00:00:54,181 --> 00:00:56,170 including Sally Claggett from the Eastern region, 16 00:00:56,170 --> 00:00:59,104 and then three folks from the Southern research station, 17 00:00:59,104 --> 00:01:01,905 Peter Caldwell, Ge Sun, who are research hydrologists 18 00:01:01,905 --> 00:01:03,755 and Erika Mack who is a data analyst. 19 00:01:05,069 --> 00:01:07,147 We also have 30 advisors on our team 20 00:01:07,147 --> 00:01:09,784 including National Forest System folks, 21 00:01:09,784 --> 00:01:12,946 state folks from state agencies, academia, industry 22 00:01:12,946 --> 00:01:14,296 and also some NGO partners. 23 00:01:16,566 --> 00:01:18,004 So why Forest to Faucets? 24 00:01:18,004 --> 00:01:20,264 We all know that the link between forest and clean water 25 00:01:20,264 --> 00:01:21,400 has long been established in literature, 26 00:01:21,400 --> 00:01:24,090 and clean and safe, abundant drinking water is a necessity 27 00:01:24,090 --> 00:01:26,506 to about 75% of the nation 28 00:01:26,506 --> 00:01:28,410 who is on surface drinking water systems. 29 00:01:28,410 --> 00:01:31,467 Drinking water quality and quantity 30 00:01:31,467 --> 00:01:33,922 are increasingly at risks from various factors 31 00:01:33,922 --> 00:01:37,133 including forest loss, forest degradation, and development. 32 00:01:38,503 --> 00:01:39,780 And future and reliable, safe drinking water supplies 33 00:01:39,780 --> 00:01:41,050 depend on forests 34 00:01:42,153 --> 00:01:44,103 and conservation restoration of those forests. 35 00:01:46,054 --> 00:01:49,270 So Forest to Faucet 2.0 builds on some previous works 36 00:01:49,270 --> 00:01:51,552 that have been in the works for about 15 years, 37 00:01:51,552 --> 00:01:55,081 including Forests, Water and People from 2009, 38 00:01:55,081 --> 00:01:57,410 Forests to Faucets Version One, 39 00:01:57,410 --> 00:01:59,400 out of the Washington Office Ecosystem Services 40 00:01:59,400 --> 00:02:00,900 and within the Forest Service. 41 00:02:02,076 --> 00:02:05,420 The Forest on the Edge, Forest to Faucet collaboration 42 00:02:05,420 --> 00:02:08,483 that came out in 2014 and then the, 43 00:02:10,017 --> 00:02:11,300 out of the Southern research station, 44 00:02:11,300 --> 00:02:16,198 this "Quantifying the Roles of National Forest System Lands 45 00:02:16,198 --> 00:02:18,818 "and Providing Surface Drinking Water Supply." 46 00:02:18,818 --> 00:02:20,460 I also will talk to you about an updated 47 00:02:20,460 --> 00:02:22,457 to this last product 48 00:02:22,457 --> 00:02:26,260 that talks about the contribution of drinking water 49 00:02:26,260 --> 00:02:27,913 off forests for the nation. 50 00:02:30,557 --> 00:02:32,259 So Forests to Faucets 2.0, 51 00:02:32,259 --> 00:02:34,638 the assessment had four main objectives. 52 00:02:34,638 --> 00:02:36,143 The first was to evaluate the, 53 00:02:36,981 --> 00:02:39,860 a watershed's natural ability to produce clean water 54 00:02:39,860 --> 00:02:42,130 based on five biophysical characteristics. 55 00:02:42,130 --> 00:02:44,621 With that baseline, we wanted to look at 56 00:02:44,621 --> 00:02:45,640 how important that subwatershed is 57 00:02:45,640 --> 00:02:47,440 to surface drinking water, 58 00:02:47,440 --> 00:02:50,453 specifically downstream surface water intakes. 59 00:02:51,958 --> 00:02:52,791 And then we wanted to look at 60 00:02:52,791 --> 00:02:55,041 where these important forests were 61 00:02:55,041 --> 00:02:58,635 that were protecting this water and who owns those forests. 62 00:02:58,635 --> 00:03:01,322 And last, we looked at risks to the important watersheds. 63 00:03:01,322 --> 00:03:03,590 So we wanted to evaluate what, if any, 64 00:03:03,590 --> 00:03:08,590 risks from insect disease, wildfire, future development 65 00:03:09,000 --> 00:03:10,860 and any water reductions to it 66 00:03:10,860 --> 00:03:13,520 from development and climate change 67 00:03:14,578 --> 00:03:16,473 may put these watersheds at risk in the future. 68 00:03:19,280 --> 00:03:21,430 Here is our analysis design for Forests to Faucets 2.0. 69 00:03:21,430 --> 00:03:23,840 I just wanna highlight here some new data that was added 70 00:03:23,840 --> 00:03:27,150 to the assessment, including WASSI, 71 00:03:27,150 --> 00:03:29,302 which is a water balance model 72 00:03:29,302 --> 00:03:32,179 that gave us the mean animal water supply. 73 00:03:32,179 --> 00:03:34,370 We also added water use data from USGS, 74 00:03:34,370 --> 00:03:38,340 and then we also updated our development pressure. 75 00:03:38,340 --> 00:03:41,410 So in the past, we looked at housing density 76 00:03:41,410 --> 00:03:43,982 and changes in housing density over time. 77 00:03:43,982 --> 00:03:46,860 Here we used a different product from EPA, 78 00:03:46,860 --> 00:03:49,460 the integrated climate and land use scenario 79 00:03:49,460 --> 00:03:51,955 where development was modeled based 80 00:03:51,955 --> 00:03:54,734 on different socioeconomic and emission scenarios. 81 00:03:54,734 --> 00:03:57,430 And then finally, for the changes in water supply, 82 00:03:57,430 --> 00:04:00,330 we looked at where water yield was decreasing 83 00:04:00,330 --> 00:04:03,263 over time, again using that WASSI water balance model. 84 00:04:04,510 --> 00:04:06,269 So I'm gonna walk you through 85 00:04:06,269 --> 00:04:10,200 each of those four different indices that we created 86 00:04:10,200 --> 00:04:12,633 and show you some really pretty maps. 87 00:04:13,668 --> 00:04:16,780 So the ability to produce clean water was the first. 88 00:04:16,780 --> 00:04:19,610 This methodology came from Forest, Water and People 89 00:04:19,610 --> 00:04:20,990 back in 2009. 90 00:04:20,990 --> 00:04:22,880 And so we're assessing each subwatershed 91 00:04:22,880 --> 00:04:26,093 across the continental US, based on its natural ability 92 00:04:26,093 --> 00:04:27,269 to produce clean water 93 00:04:27,269 --> 00:04:29,828 based on five biophysical characteristics. 94 00:04:29,828 --> 00:04:30,911 So those five characteristics 95 00:04:30,911 --> 00:04:32,250 were the percent of natural cover. 96 00:04:32,250 --> 00:04:35,060 Typically we use percent forest cover in this index, 97 00:04:35,060 --> 00:04:38,450 but we increased it to look at shrub and grasslands 98 00:04:38,450 --> 00:04:40,230 because across the nation, 99 00:04:40,230 --> 00:04:41,830 shrub and grassland also produce 100 00:04:42,672 --> 00:04:46,712 some water quality benefits. 101 00:04:46,712 --> 00:04:48,674 And this was out of, 102 00:04:48,674 --> 00:04:51,923 derived from the National Land Cover data set of 2016. 103 00:04:53,951 --> 00:04:55,465 We looked at the percent of the watershed 104 00:04:55,465 --> 00:04:57,385 that was of agricultural land. 105 00:04:57,385 --> 00:04:59,535 Again from the National Land Cover Dataset. 106 00:05:00,881 --> 00:05:04,110 And here you'll see that the darker brown areas 107 00:05:05,380 --> 00:05:07,870 have less than 10% agricultural land. 108 00:05:07,870 --> 00:05:11,203 The yellow areas are more than 30% agricultural land. 109 00:05:13,382 --> 00:05:14,638 We looked at percent of the watershed 110 00:05:14,638 --> 00:05:16,343 that was impervious surface. 111 00:05:16,343 --> 00:05:18,570 So again, here, the red areas, 112 00:05:18,570 --> 00:05:21,783 more than 10% of the watershed is impervious surface. 113 00:05:24,650 --> 00:05:26,830 Next, we looked at the percent of the watershed that, 114 00:05:26,830 --> 00:05:30,050 where the riparian area was in natural cover. 115 00:05:30,050 --> 00:05:32,342 So again, natural cover was defined as 116 00:05:32,342 --> 00:05:33,840 forest, grasslands, and shrub, 117 00:05:33,840 --> 00:05:38,663 and we worked with USGS and our research fellow 118 00:05:38,663 --> 00:05:40,904 of the Forest Service, Sinan Abood, 119 00:05:40,904 --> 00:05:43,280 who had developed a variable with riparian area. 120 00:05:43,280 --> 00:05:45,720 Typically we have used 30 meters 121 00:05:45,720 --> 00:05:48,940 for our riparian buffer when we are evaluating 122 00:05:49,925 --> 00:05:53,024 how much of that is in natural cover or forest cover, 123 00:05:53,024 --> 00:05:54,464 but this, for this analysis, 124 00:05:54,464 --> 00:05:56,764 we wanted to look at the larger riparian area. 125 00:05:57,843 --> 00:05:59,224 So let me zoom in here. 126 00:05:59,224 --> 00:06:01,000 This is Lake Winnipesaukee. 127 00:06:01,000 --> 00:06:03,030 The variable with riparian areas, 128 00:06:03,030 --> 00:06:06,500 if you see here in this dark gray, look, 129 00:06:06,500 --> 00:06:10,041 use a combination of the 50 year flood plain, 130 00:06:10,041 --> 00:06:13,603 soils, wetlands and other characteristics to delineate this. 131 00:06:13,603 --> 00:06:15,130 And then we looked at how much of that area 132 00:06:15,130 --> 00:06:17,060 is in natural cover across the nation 133 00:06:18,178 --> 00:06:20,946 to get that percent riparian natural cover variable, 134 00:06:20,946 --> 00:06:25,085 and finally for ability to produce clean water, 135 00:06:25,085 --> 00:06:27,721 the final variable was the mean annual water yield, 136 00:06:27,721 --> 00:06:29,021 again out of the WASSI model. 137 00:06:29,021 --> 00:06:31,650 And this gives the annual water yield 138 00:06:31,650 --> 00:06:35,593 in millimeters per year at the outlet of each watershed. 139 00:06:36,670 --> 00:06:39,870 And that way we could evaluate how much water 140 00:06:39,870 --> 00:06:41,980 is actually available to create. 141 00:06:41,980 --> 00:06:44,224 When we first ran this, 142 00:06:44,224 --> 00:06:46,326 we didn't have that median annual water yield. 143 00:06:46,326 --> 00:06:48,961 And, you know, Arizona has a lot of natural cover, 144 00:06:48,961 --> 00:06:50,505 but it doesn't have a lot of water. 145 00:06:50,505 --> 00:06:52,415 So this is the final output 146 00:06:52,415 --> 00:06:54,766 of that ability to produce clean water index. 147 00:06:54,766 --> 00:06:56,345 So this gives you an idea 148 00:06:56,345 --> 00:07:00,966 of where a watershed has its natural ability 149 00:07:00,966 --> 00:07:02,005 to produce clean water. 150 00:07:02,005 --> 00:07:04,905 So this was our baseline assessment for each subwatershed. 151 00:07:06,670 --> 00:07:09,473 Now that we understand the baseline of each subwatershed 152 00:07:10,364 --> 00:07:11,590 across the nation, we wanted to evaluate 153 00:07:11,590 --> 00:07:14,706 how important that watershed is 154 00:07:14,706 --> 00:07:16,990 to downstream surface drinking water consumers. 155 00:07:16,990 --> 00:07:20,701 And we did that using the Relative Importance 156 00:07:20,701 --> 00:07:22,404 of Surface Drinking Water index. 157 00:07:22,404 --> 00:07:23,719 And I like to think of this index 158 00:07:23,719 --> 00:07:26,102 as a function of supply and demand, 159 00:07:26,102 --> 00:07:31,024 where supply is the mean annual water yield for a watershed. 160 00:07:31,024 --> 00:07:33,630 So how much water is coming off that watershed. 161 00:07:33,630 --> 00:07:37,060 And then demand is how many people are being served 162 00:07:37,060 --> 00:07:40,060 by that watershed and by downstream watersheds, 163 00:07:40,060 --> 00:07:43,110 and that demand function we call 164 00:07:43,110 --> 00:07:45,310 the surface drinking water protection model. 165 00:07:46,960 --> 00:07:49,002 I'm gonna get into the weeds a little bit, 166 00:07:49,002 --> 00:07:49,835 but I want to illustrate 167 00:07:49,835 --> 00:07:54,370 how we ran that drinking water protection model. 168 00:07:54,370 --> 00:07:57,190 So here's a simple diagram of three watersheds 169 00:07:57,190 --> 00:07:59,585 flowing into the ocean. 170 00:07:59,585 --> 00:08:02,390 So the bottom left here would be the ocean, 171 00:08:02,390 --> 00:08:04,610 and we have HUC one, HUC two and HUC three. 172 00:08:04,610 --> 00:08:07,830 HUC one here at the bottom has two intakes, 173 00:08:07,830 --> 00:08:09,660 and the combination of those two intakes 174 00:08:09,660 --> 00:08:11,240 serves a hundred thousand people. 175 00:08:11,240 --> 00:08:13,585 HUC two, there's no intakes, 176 00:08:13,585 --> 00:08:16,290 and HUC three there's one intake that serves 50,000 people. 177 00:08:16,290 --> 00:08:18,910 So in order to give them a value, 178 00:08:18,910 --> 00:08:22,210 we wanted to both look at the intakes in the watershed 179 00:08:22,210 --> 00:08:24,564 and the intakes downstream. 180 00:08:24,564 --> 00:08:26,044 So for HUC one, 181 00:08:26,044 --> 00:08:27,384 it's pretty simple because closing the ocean, 182 00:08:27,384 --> 00:08:28,621 there's these two intakes. 183 00:08:28,621 --> 00:08:30,040 It's a hundred thousand people. 184 00:08:30,040 --> 00:08:32,244 We, it's in the watershed. 185 00:08:32,244 --> 00:08:35,262 So it, we're gonna give them a 100% of that 100,000 people. 186 00:08:35,262 --> 00:08:37,458 So the value of HUC one is a 100,000. 187 00:08:37,458 --> 00:08:38,930 HUC two however has no intakes, 188 00:08:38,930 --> 00:08:42,220 but we wanted to give it a proportion of the downstream. 189 00:08:42,220 --> 00:08:46,503 And we use the decay curve to give it a weight factor 190 00:08:46,503 --> 00:08:48,161 for a proportional weight. 191 00:08:48,161 --> 00:08:51,725 So it's going to get 100% of the zero. 192 00:08:51,725 --> 00:08:52,670 So 100% of the intakes 193 00:08:52,670 --> 00:08:54,559 that are in the watershed. 194 00:08:54,559 --> 00:08:56,044 So 100%, times zero, 195 00:08:56,044 --> 00:08:59,020 and then also about 77.9% of these 100,000. 196 00:08:59,020 --> 00:09:00,870 So a little proportion of those 100,000 197 00:09:00,870 --> 00:09:03,020 would be given to HUC two. 198 00:09:03,020 --> 00:09:08,020 And so the total value of HUC two would be 77,900. 199 00:09:08,260 --> 00:09:12,143 Now HUC three has a intake that serves 50,000 people. 200 00:09:13,180 --> 00:09:16,760 So we're gonna give again 100% of those 50,000 people. 201 00:09:16,760 --> 00:09:19,060 We're gonna give 77% of zero, 202 00:09:19,060 --> 00:09:22,118 and then we're going to give 60% 203 00:09:22,118 --> 00:09:24,150 of the 100,000 to equal 110,700. 204 00:09:24,150 --> 00:09:27,598 And we did this across all 83,000 watersheds 205 00:09:27,598 --> 00:09:28,431 across the nation. 206 00:09:28,431 --> 00:09:31,260 Some of the reaches were as much as 300 watersheds. 207 00:09:31,260 --> 00:09:35,438 So even though a watershed may be 1,000 kilometers away, 208 00:09:35,438 --> 00:09:36,560 we're going to give a very small proportion 209 00:09:36,560 --> 00:09:39,100 of the downstream water consumers to that watersheds. 210 00:09:39,100 --> 00:09:41,250 Therefore every watershed across the nation 211 00:09:41,250 --> 00:09:43,675 was given a value of, 212 00:09:43,675 --> 00:09:46,283 a proportional value of the downstream watersheds. 213 00:09:48,410 --> 00:09:51,410 So again, we combined that supply, 214 00:09:51,410 --> 00:09:53,580 the Median Annual Water Yield, 215 00:09:53,580 --> 00:09:56,350 and the demand that Surface Water Protection Model 216 00:09:56,350 --> 00:09:58,180 combined to give 217 00:09:58,180 --> 00:10:00,243 this Relative Importance of Surface Drinking Water, 218 00:10:00,243 --> 00:10:01,502 or we call it the IMP. 219 00:10:01,502 --> 00:10:03,340 And this is the final product, 220 00:10:03,340 --> 00:10:05,580 and I'll show you later on when we get into the story map, 221 00:10:05,580 --> 00:10:07,770 when you click on each individual watershed, 222 00:10:07,770 --> 00:10:11,740 you get both the information about the current watershed. 223 00:10:11,740 --> 00:10:13,170 So the watershed has 224 00:10:13,170 --> 00:10:16,980 say five surface drinking water intakes. 225 00:10:16,980 --> 00:10:19,900 It serves 50,000 people, but they're also, you know, 226 00:10:19,900 --> 00:10:21,980 4 million people downstream of it. 227 00:10:21,980 --> 00:10:24,739 So you have all of that information at your hand, 228 00:10:24,739 --> 00:10:25,770 and then the relative importance of it 229 00:10:25,770 --> 00:10:28,320 compared to all other watersheds across the nation. 230 00:10:30,701 --> 00:10:33,810 So next we looked at forest areas 231 00:10:33,810 --> 00:10:35,750 that protect drinking water 232 00:10:35,750 --> 00:10:38,970 in these important subwatersheds. 233 00:10:38,970 --> 00:10:42,490 So we looked at forest ownership across the nation, 234 00:10:42,490 --> 00:10:44,320 using all lands. 235 00:10:44,320 --> 00:10:46,460 We looked at natural forest system lands. 236 00:10:46,460 --> 00:10:48,470 We looked at other protected forests 237 00:10:48,470 --> 00:10:53,020 from state and local agencies, as well as private forests. 238 00:10:53,020 --> 00:10:55,530 We also looked at some protected private forests 239 00:10:55,530 --> 00:10:58,073 from various conservation easements. 240 00:10:58,920 --> 00:11:00,230 We used the National Conservation Easement Database, 241 00:11:00,230 --> 00:11:03,341 and where there were permanent conservation easements, 242 00:11:03,341 --> 00:11:04,773 we did consider those protected forest. 243 00:11:06,600 --> 00:11:09,990 So forest ownership does not, is not a value that we add 244 00:11:09,990 --> 00:11:13,830 to the kind of equation in the model, but we are using this 245 00:11:13,830 --> 00:11:17,263 in our filtering in our watershed tool. 246 00:11:17,263 --> 00:11:18,500 So you can use forest ownership 247 00:11:18,500 --> 00:11:20,733 to filter what watersheds you're looking at. 248 00:11:21,598 --> 00:11:22,797 So say you want to look at watersheds 249 00:11:22,797 --> 00:11:24,183 that have high protection 250 00:11:24,183 --> 00:11:26,700 or watersheds that have a high percent of private forest, 251 00:11:26,700 --> 00:11:27,820 you can do that. 252 00:11:27,820 --> 00:11:30,100 And then each watershed will also have a pop-up 253 00:11:30,100 --> 00:11:33,130 that gives you the proportion of the forest ownership, 254 00:11:33,130 --> 00:11:34,980 and there's various charts available. 255 00:11:36,843 --> 00:11:39,502 Finally, we looked at risks to these important watersheds. 256 00:11:39,502 --> 00:11:41,300 So we wanna identify subwatersheds 257 00:11:41,300 --> 00:11:45,600 that were at risks from fire, insect disease, 258 00:11:45,600 --> 00:11:48,223 development pressure and changes in water yield. 259 00:11:50,020 --> 00:11:53,167 So for wildfire risk, we looked at areas 260 00:11:53,167 --> 00:11:55,067 with high and high wildfire potential. 261 00:11:56,424 --> 00:11:57,600 We use the Wildfire Hazard Potential 262 00:11:57,600 --> 00:11:59,650 from the Fort Collins Fire Lab. 263 00:11:59,650 --> 00:12:02,827 And we looked at just the high and very high areas, 264 00:12:02,827 --> 00:12:04,266 which are in the bottom left here 265 00:12:04,266 --> 00:12:06,443 are the red, orange and yellow areas. 266 00:12:06,443 --> 00:12:09,247 We, and then looked at just the areas 267 00:12:09,247 --> 00:12:11,807 that were both, had high fire risk 268 00:12:11,807 --> 00:12:13,780 and were important to surface drinking water consumers 269 00:12:13,780 --> 00:12:15,847 to get our final index. 270 00:12:15,847 --> 00:12:18,520 So here the red areas are the most at risk 271 00:12:19,361 --> 00:12:21,443 and are most important to surface drinking water consumers. 272 00:12:23,585 --> 00:12:25,230 Next we have the insect disease risk, 273 00:12:25,230 --> 00:12:30,230 and these are areas that have at least 25% 274 00:12:30,383 --> 00:12:33,326 of the standing live basal area greater than one inch 275 00:12:33,326 --> 00:12:34,922 that will, are expected to die 276 00:12:34,922 --> 00:12:36,840 in that 15 year timeframe due to insects and disease. 277 00:12:36,840 --> 00:12:38,620 So we combine that risk 278 00:12:38,620 --> 00:12:40,640 with the surface drinking water importance index 279 00:12:40,640 --> 00:12:43,564 to get this final map where you're showing areas 280 00:12:43,564 --> 00:12:45,420 that are both important to surface drinking water consumers 281 00:12:45,420 --> 00:12:47,193 and are at risk for insect disease. 282 00:12:49,765 --> 00:12:51,161 Next, we looked at development risk, 283 00:12:51,161 --> 00:12:54,000 and we used both two times steps 284 00:12:54,000 --> 00:12:55,466 and two emissions scenarios. 285 00:12:55,466 --> 00:12:58,903 So we had a 2010 to 2040 time step, and a 2010 to 2090. 286 00:12:59,798 --> 00:13:03,140 And we both had low and high growth in emission scenarios 287 00:13:03,140 --> 00:13:05,520 for a total of four total scenarios. 288 00:13:05,520 --> 00:13:07,448 This one you're looking at here 289 00:13:07,448 --> 00:13:09,261 is kind of the worst case scenario. 290 00:13:09,261 --> 00:13:12,313 So 2010 to 2090 under high emission, high growth model. 291 00:13:13,443 --> 00:13:15,644 So here the, at the bottom left, 292 00:13:15,644 --> 00:13:17,160 you have areas in the darker grays and blacks 293 00:13:17,160 --> 00:13:20,680 that show more percent, 294 00:13:20,680 --> 00:13:22,130 more percent of the watershed 295 00:13:22,982 --> 00:13:24,353 that's gonna expect land use change, 296 00:13:25,250 --> 00:13:26,350 and then combined with 297 00:13:27,239 --> 00:13:28,903 the surface drinking water importance, 298 00:13:28,903 --> 00:13:31,140 you have on the right here the areas in red 299 00:13:31,140 --> 00:13:33,750 that are both important to surface drinking water 300 00:13:33,750 --> 00:13:36,440 and will experience land use change 301 00:13:37,407 --> 00:13:40,323 over that 80 year time step in the high emission scenario. 302 00:13:42,864 --> 00:13:45,105 And final risk is water yield. 303 00:13:45,105 --> 00:13:47,166 So we looked at areas that were going to decrease 304 00:13:47,166 --> 00:13:49,505 in water yield over those same time steps 305 00:13:49,505 --> 00:13:51,583 and same emission scenarios. 306 00:13:51,583 --> 00:13:55,070 So here again is the high emission, high growth 307 00:13:55,070 --> 00:13:57,113 over 2010 to 2090 time step. 308 00:13:58,224 --> 00:14:00,500 And we used again that WASSI water balance model 309 00:14:00,500 --> 00:14:03,770 to predict these water yield changes. 310 00:14:03,770 --> 00:14:06,026 and the bottom right is showing just areas 311 00:14:06,026 --> 00:14:08,690 that are are expected to decrease in water yield. 312 00:14:08,690 --> 00:14:11,230 And again, we have on the right, 313 00:14:11,230 --> 00:14:16,202 we combine those decreases in water yield 314 00:14:16,202 --> 00:14:17,820 where there's important surface drinking watersheds, 315 00:14:17,820 --> 00:14:22,320 and you have your final index here. 316 00:14:22,320 --> 00:14:25,270 And I should mention all of our indices have been normalized 317 00:14:25,270 --> 00:14:27,726 to a zero to a hundred scale. 318 00:14:27,726 --> 00:14:31,910 So they're easily mapped and easily displayed 319 00:14:31,910 --> 00:14:33,200 in a normalized way. 320 00:14:33,200 --> 00:14:36,280 So everything's relative to each other. 321 00:14:36,280 --> 00:14:38,502 There is the raw data in there 322 00:14:38,502 --> 00:14:40,800 that if you wanted the actual score, you could look at that. 323 00:14:40,800 --> 00:14:42,710 But for comparison purposes, 324 00:14:42,710 --> 00:14:45,843 it was easiest to normalize that 325 00:14:45,843 --> 00:14:49,203 and depict it here in a quantile fashion. 326 00:14:51,200 --> 00:14:52,920 So who is using these datasets? 327 00:14:52,920 --> 00:14:56,843 So we have worked a lot with state forest planners 328 00:14:56,843 --> 00:15:00,460 to identify important surface drinking water watersheds 329 00:15:00,460 --> 00:15:02,150 in their state forest action plans 330 00:15:02,150 --> 00:15:06,381 where they can apply different conservation 331 00:15:06,381 --> 00:15:08,410 and management strategies to protect 332 00:15:08,410 --> 00:15:11,426 these important surface drinking water watersheds, 333 00:15:11,426 --> 00:15:14,260 as well as the upstream land area 334 00:15:14,260 --> 00:15:17,223 above important water resources. 335 00:15:17,223 --> 00:15:21,805 National Forest System, national forest planners 336 00:15:21,805 --> 00:15:22,638 can identify important 337 00:15:22,638 --> 00:15:24,920 surface drinking water watersheds within their forests 338 00:15:24,920 --> 00:15:27,123 and what the risks are to those forests. 339 00:15:28,250 --> 00:15:31,210 Water managers and water utilities can use these data 340 00:15:31,210 --> 00:15:34,510 to identify areas upstream from their systems 341 00:15:34,510 --> 00:15:36,520 that may have the highest risk for development 342 00:15:36,520 --> 00:15:38,200 and decrease water yield 343 00:15:38,200 --> 00:15:43,190 and have increased partnerships to mitigate those risks. 344 00:15:43,190 --> 00:15:44,990 And I'm gonna talk about in a minute 345 00:15:45,967 --> 00:15:48,272 some work we're doing with the National Agroforestry Center 346 00:15:48,272 --> 00:15:52,140 on identifying areas of where riparian restoration can occur 347 00:15:52,140 --> 00:15:54,923 and our agroforestry opportunities. 348 00:15:57,931 --> 00:16:00,410 So we have developed a suite of products 349 00:16:00,410 --> 00:16:02,750 around this assessment. 350 00:16:02,750 --> 00:16:06,331 The data is done, and I'll show you a story map in a minute. 351 00:16:06,331 --> 00:16:07,788 We're working on a watershed tool 352 00:16:07,788 --> 00:16:10,070 that will allow you to interact more with the data, 353 00:16:10,070 --> 00:16:14,191 select specific watersheds and get reports, download data. 354 00:16:14,191 --> 00:16:17,200 We're working on a general technical report, 355 00:16:17,200 --> 00:16:20,855 a publication that will be out early 2021. 356 00:16:20,855 --> 00:16:21,780 And we're doing a lot of these type of webinars. 357 00:16:21,780 --> 00:16:24,290 And when the watershed tools are out, 358 00:16:24,290 --> 00:16:27,640 we will do a lot of training on those, how to use them. 359 00:16:27,640 --> 00:16:29,210 And hopefully people are using these data 360 00:16:29,210 --> 00:16:33,343 to supplement their work and hopefully change the world. 361 00:16:35,010 --> 00:16:40,010 So this is our phase one story map that shows the same apps 362 00:16:40,510 --> 00:16:42,660 that I've showed you throughout the slide presentation 363 00:16:42,660 --> 00:16:44,394 in a web format. 364 00:16:44,394 --> 00:16:46,360 So when you open the story map, 365 00:16:46,360 --> 00:16:48,310 and I'll give you the link in the chat, 366 00:16:49,750 --> 00:16:51,960 first, it gives you a brief explanation 367 00:16:51,960 --> 00:16:53,450 of what Forest to Faucet is. 368 00:16:53,450 --> 00:16:56,816 It goes through which of these different tabs, 369 00:16:56,816 --> 00:16:58,093 what they mean. 370 00:16:58,093 --> 00:16:59,420 If you go to the important watershed tab, 371 00:16:59,420 --> 00:17:02,350 you'll get that surface drinking water importance index. 372 00:17:02,350 --> 00:17:07,350 If you click on any watershed, you'll get the index score. 373 00:17:07,470 --> 00:17:09,680 How many surface drinking water intakes 374 00:17:10,615 --> 00:17:12,570 are in this watershed, how many people are served, 375 00:17:12,570 --> 00:17:14,390 and then how many people are, 376 00:17:14,390 --> 00:17:17,035 surface drinking water consumers are downstream. 377 00:17:17,035 --> 00:17:18,480 You'll also get all of the watershed characteristics 378 00:17:18,480 --> 00:17:20,270 and the risks. 379 00:17:20,270 --> 00:17:23,734 And you can search for your area and your town 380 00:17:23,734 --> 00:17:26,034 and get the characteristics of your watershed. 381 00:17:27,873 --> 00:17:29,590 The next tab is the risks to surface drinking water 382 00:17:29,590 --> 00:17:32,211 and all four risks are here. 383 00:17:32,211 --> 00:17:35,550 You can look at them and compare the risks 384 00:17:35,550 --> 00:17:37,810 to the Surface Drinking Water Importance Index. 385 00:17:37,810 --> 00:17:41,470 You can also, for those climate change risks, you have, 386 00:17:41,470 --> 00:17:44,550 we have all four scenarios in one screen 387 00:17:44,550 --> 00:17:48,623 that you can compare all four scenarios in one place. 388 00:17:50,600 --> 00:17:52,040 And then in the explore data tab, 389 00:17:52,040 --> 00:17:55,080 you can explore all the model inputs and outputs 390 00:17:55,980 --> 00:17:57,760 individually or together. 391 00:17:57,760 --> 00:17:59,190 You can overlay them. 392 00:17:59,190 --> 00:18:01,233 It's a typical web map where you, 393 00:18:02,117 --> 00:18:03,163 so this is the Forest Ownership layer. 394 00:18:04,391 --> 00:18:06,894 Here's the Ability to Produce Clean Water Index. 395 00:18:06,894 --> 00:18:07,997 So again, you can click on it 396 00:18:07,997 --> 00:18:10,435 and get the basic characteristics of the watershed. 397 00:18:10,435 --> 00:18:14,870 And for each risk, you're able to click on the watershed, 398 00:18:14,870 --> 00:18:19,870 and you get the predicted the raw value of the risk. 399 00:18:20,896 --> 00:18:23,490 So for this example, here's the changes in water quantity. 400 00:18:23,490 --> 00:18:27,995 This watershed's expected to have a 28% decrease 401 00:18:27,995 --> 00:18:32,160 in water yield, which makes it very high risk 402 00:18:32,160 --> 00:18:33,860 for future water quantity risks, 403 00:18:33,860 --> 00:18:36,623 water quantity risk, and it's an important watershed. 404 00:18:39,450 --> 00:18:42,240 Coming soon, we're adding some additional tools 405 00:18:42,240 --> 00:18:43,780 to our story map 406 00:18:43,780 --> 00:18:48,780 including interactive querying with reports. 407 00:18:49,090 --> 00:18:50,760 So here's an example of one of, 408 00:18:50,760 --> 00:18:53,010 what one of the reports would look like for a watershed. 409 00:18:53,010 --> 00:18:54,730 You could select an individual watershed 410 00:18:54,730 --> 00:18:58,740 or a group of watersheds and get basic characteristics 411 00:18:58,740 --> 00:19:02,990 of the watershed, all of the indices for that watershed, 412 00:19:02,990 --> 00:19:07,452 how many public water supplies, what cities they serve, 413 00:19:07,452 --> 00:19:11,757 all of the characteristics about the land cover 414 00:19:11,757 --> 00:19:13,633 and riparian cover, and the ownership, 415 00:19:14,536 --> 00:19:16,981 really nice format. 416 00:19:16,981 --> 00:19:19,581 And you'll be able to do some pretty robust queries. 417 00:19:20,570 --> 00:19:23,130 Here's an example of one of the dashboards 418 00:19:23,130 --> 00:19:24,730 as part of that query tool. 419 00:19:24,730 --> 00:19:27,030 You'll be able to select 420 00:19:27,030 --> 00:19:29,210 based on how important the watershed is, 421 00:19:29,210 --> 00:19:32,170 different ownership percentages, 422 00:19:32,170 --> 00:19:34,530 and it will give you a snapshot of that information. 423 00:19:34,530 --> 00:19:36,830 Then you'll also be able to extract the report 424 00:19:37,714 --> 00:19:38,547 and extract the data. 425 00:19:39,803 --> 00:19:42,820 And why, what I'm most excited about is this tool 426 00:19:42,820 --> 00:19:44,303 they're developing as part of that, 427 00:19:45,399 --> 00:19:47,710 of this reporting function is 428 00:19:47,710 --> 00:19:49,410 for any watershed you click on 429 00:19:49,410 --> 00:19:51,180 you'll be able to select the upstream 430 00:19:51,180 --> 00:19:54,200 or downstream watersheds as part of that selection set. 431 00:19:54,200 --> 00:19:57,660 So say you're in Vermont, 432 00:19:57,660 --> 00:19:59,920 and there's a watershed that you're working in. 433 00:19:59,920 --> 00:20:02,263 You can click on that watershed and say 434 00:20:02,263 --> 00:20:03,460 I want to know what's everything downstream of me. 435 00:20:03,460 --> 00:20:05,240 So you'll hit the downstream button 436 00:20:05,240 --> 00:20:07,640 you'll select everything downstream review. 437 00:20:07,640 --> 00:20:09,000 It can give you a summary of all those watersheds, 438 00:20:09,000 --> 00:20:10,999 what cities they're serving. 439 00:20:10,999 --> 00:20:15,730 You'll get information about the risk factors to those. 440 00:20:15,730 --> 00:20:17,440 So you will, say you're doing land management 441 00:20:17,440 --> 00:20:19,139 in those watersheds, 442 00:20:19,139 --> 00:20:21,070 you can see the impact of those. 443 00:20:21,070 --> 00:20:22,000 And the vice versa, 444 00:20:22,000 --> 00:20:26,270 if you're a water surface drinking water utility, 445 00:20:26,270 --> 00:20:27,530 you could click on your watershed. 446 00:20:27,530 --> 00:20:28,850 See what everything is upstream. 447 00:20:28,850 --> 00:20:31,623 Get summaries of risks, development pressures, 448 00:20:33,403 --> 00:20:34,520 and that sort of thing 449 00:20:34,520 --> 00:20:36,850 and be able to do some, hopefully again, 450 00:20:36,850 --> 00:20:40,963 some mitigation and partnering to mitigate those risks. 451 00:20:42,390 --> 00:20:44,330 So, as I've mentioned several times, 452 00:20:44,330 --> 00:20:46,500 we're working with Source Water Protection, 453 00:20:46,500 --> 00:20:51,500 both state and federal EPA Source Water Protection folks, 454 00:20:53,082 --> 00:20:55,764 to use these data to help mitigate risks 455 00:20:55,764 --> 00:20:58,190 to surface drinking water utilities. 456 00:20:58,190 --> 00:21:01,570 The state of Georgia is actually looking at these data 457 00:21:01,570 --> 00:21:06,120 to tell kind of a baseline for their payment 458 00:21:06,120 --> 00:21:07,670 for ecosystem services work that they're doing. 459 00:21:07,670 --> 00:21:08,610 So kind of a baseline 460 00:21:08,610 --> 00:21:11,730 where watersheds would be most important 461 00:21:11,730 --> 00:21:14,860 and may have the highest value for payment 462 00:21:15,820 --> 00:21:18,070 for those ecosystem services for clean water. 463 00:21:19,112 --> 00:21:21,130 And then the National Agroforestry Center 464 00:21:21,130 --> 00:21:24,780 is partnering with us to develop two more indices 465 00:21:24,780 --> 00:21:26,705 for opportunities. 466 00:21:26,705 --> 00:21:28,104 So instead of looking at the risks, 467 00:21:28,104 --> 00:21:30,124 look at where the opportunities lie. 468 00:21:30,124 --> 00:21:32,574 So both in riparian restoration and agroforestry. 469 00:21:33,520 --> 00:21:35,910 So for the riparian restoration opportunities, 470 00:21:35,910 --> 00:21:36,870 we're gonna identify 471 00:21:36,870 --> 00:21:40,480 where we have important surface drinking water watersheds, 472 00:21:40,480 --> 00:21:43,380 but they have the high potential for riparian restoration. 473 00:21:45,230 --> 00:21:47,380 So for this riparian restoration opportunity, 474 00:21:47,380 --> 00:21:50,441 we looked at watersheds that had a high percent 475 00:21:50,441 --> 00:21:52,040 of the riparian area that was agriculture, 476 00:21:52,040 --> 00:21:55,338 but it was also important to surface drinking water. 477 00:21:55,338 --> 00:21:57,082 So let me zoom in here. 478 00:21:57,082 --> 00:21:59,904 So again, this is that variable with riparian area. 479 00:21:59,904 --> 00:22:02,297 And instead of looking at areas that were natural cover, 480 00:22:02,297 --> 00:22:03,842 you know, forest, grassland, and shrub, 481 00:22:03,842 --> 00:22:06,498 we looked at the percent of the riparian area 482 00:22:06,498 --> 00:22:07,517 that was agriculture. 483 00:22:07,517 --> 00:22:10,761 So if a watershed had a high percent of a watershed 484 00:22:10,761 --> 00:22:14,500 that was agriculture, we wanted to flag those 485 00:22:14,500 --> 00:22:18,033 as potential riparian restoration areas. 486 00:22:19,025 --> 00:22:20,401 And then the National Agroforestry Center 487 00:22:20,401 --> 00:22:21,234 can work with their partners 488 00:22:23,042 --> 00:22:25,260 in different stewardship programs and urban programs 489 00:22:25,260 --> 00:22:28,270 to implement riparian restoration 490 00:22:28,270 --> 00:22:30,900 in these important drinking water watershed. 491 00:22:30,900 --> 00:22:33,224 They also wanted to look at where there were 492 00:22:33,224 --> 00:22:34,280 some agroforestry potential. 493 00:22:34,280 --> 00:22:36,010 So identify watersheds 494 00:22:36,010 --> 00:22:38,000 that were important to surface drinking water consumers, 495 00:22:38,000 --> 00:22:41,142 but also had a high potential for agroforestry. 496 00:22:41,142 --> 00:22:44,370 And we defined high potential as agricultural lands 497 00:22:44,370 --> 00:22:46,633 that were considered marginal. 498 00:22:48,260 --> 00:22:49,920 And when we say marginal, we mean 499 00:22:49,920 --> 00:22:52,240 that it is an agricultural land use, 500 00:22:52,240 --> 00:22:56,790 but the soil type is not a prime farmland soil type. 501 00:22:56,790 --> 00:23:00,100 So the orange areas here are agricultural lands, 502 00:23:00,100 --> 00:23:03,710 but they are not on a prime soil type. 503 00:23:03,710 --> 00:23:05,440 So we calculated the percent 504 00:23:05,440 --> 00:23:08,402 of these marginal agricultural lands 505 00:23:08,402 --> 00:23:09,330 for each watershed, 506 00:23:09,330 --> 00:23:12,623 multiplied it by the surface drinking water importance 507 00:23:12,623 --> 00:23:14,560 to get this index of agroforestry opportunities. 508 00:23:14,560 --> 00:23:19,042 So the Brown areas are where there's a large percent 509 00:23:19,042 --> 00:23:21,860 of those agroforestry opportunities 510 00:23:21,860 --> 00:23:24,210 in important surface drinking water watersheds. 511 00:23:25,360 --> 00:23:26,360 Let me zoom in here. 512 00:23:26,360 --> 00:23:27,193 You can see the orange areas again 513 00:23:27,193 --> 00:23:30,980 are those agricultural land use types, 514 00:23:30,980 --> 00:23:33,820 but they are not on prime soils. 515 00:23:33,820 --> 00:23:37,580 So these are opportunities for maybe alley cropping 516 00:23:37,580 --> 00:23:42,023 and other agroforestry management activities. 517 00:23:43,670 --> 00:23:46,630 And then lastly, I wanna share some new work 518 00:23:46,630 --> 00:23:48,741 out of the Southern Research Station 519 00:23:48,741 --> 00:23:51,005 that supplements Forest to Faucet, 520 00:23:51,005 --> 00:23:52,359 and that we plan on adding 521 00:23:52,359 --> 00:23:54,860 to the Forest to Faucet watershed tools when it's released, 522 00:23:54,860 --> 00:23:57,500 but Ning Liu and Peter Caldwell 523 00:23:58,523 --> 00:23:59,998 and other research scientists 524 00:23:59,998 --> 00:24:02,410 have taken that Southern Research Station work 525 00:24:02,410 --> 00:24:05,460 where they quantify the benefits of forest land 526 00:24:05,460 --> 00:24:09,420 in the Southern region for the entire nation. 527 00:24:09,420 --> 00:24:10,720 And this is exciting work. 528 00:24:12,163 --> 00:24:15,140 So not only did they look at, you know, 529 00:24:15,140 --> 00:24:16,780 where the water is coming from, 530 00:24:16,780 --> 00:24:19,462 but they actually looked at how much of the water 531 00:24:19,462 --> 00:24:23,343 in that water balance model is coming from forests. 532 00:24:23,343 --> 00:24:24,530 So if you look at this map here, 533 00:24:24,530 --> 00:24:27,163 the purple, or they quantified that, 534 00:24:28,150 --> 00:24:32,266 75 to 100% of the water coming from that watershed 535 00:24:32,266 --> 00:24:35,683 is from forest, from a forest cover. 536 00:24:38,510 --> 00:24:42,190 Now they broke that down in to some ownership as well. 537 00:24:42,190 --> 00:24:46,782 So we are actually in water resource region one here 538 00:24:46,782 --> 00:24:47,845 in New England. 539 00:24:47,845 --> 00:24:52,845 So that was in the previous slide at 75% to 100% 540 00:24:54,266 --> 00:24:55,530 comes off forests, but we can also, 541 00:24:55,530 --> 00:24:59,110 they stratified that by land ownership type. 542 00:24:59,110 --> 00:25:02,130 So we can see here that for New England, 543 00:25:02,130 --> 00:25:07,130 about 25 or 26% of that forest is family forests or private. 544 00:25:09,710 --> 00:25:13,180 And about another 25% is corporate. 545 00:25:13,180 --> 00:25:16,366 We have a small percent here, about 10% federal. 546 00:25:16,366 --> 00:25:19,222 So this gives us both, 547 00:25:19,222 --> 00:25:21,760 we had used in Forest to Faucet 548 00:25:21,760 --> 00:25:26,660 just the total watershed forest ownership, 549 00:25:26,660 --> 00:25:30,380 but this actually quantifies how much water 550 00:25:30,380 --> 00:25:33,903 is coming from forest land uses and forest ownership types. 551 00:25:35,870 --> 00:25:39,389 So finally the data is available for download. 552 00:25:39,389 --> 00:25:41,710 You can use the story map to view the data 553 00:25:41,710 --> 00:25:44,509 or you can download the data directly 554 00:25:44,509 --> 00:25:45,473 using this bit.ly link. 555 00:25:46,423 --> 00:25:49,410 You'll get a geo database with watersheds 556 00:25:49,410 --> 00:25:53,100 with a huge table of data that, 557 00:25:53,100 --> 00:25:55,486 and there's a data dictionary in there, 558 00:25:55,486 --> 00:25:57,453 it'll define what all the fields mean. 559 00:25:58,626 --> 00:26:02,070 And you can go forth and use this in your work 560 00:26:02,070 --> 00:26:04,513 either as baseline or look at risks. 561 00:26:06,310 --> 00:26:08,490 And here's my contact information. 562 00:26:08,490 --> 00:26:10,900 You, feel free to contact me 563 00:26:10,900 --> 00:26:14,160 if you have any questions or comments about the dataset. 564 00:26:14,160 --> 00:26:15,530 Also, there's a link here. 565 00:26:15,530 --> 00:26:17,570 I'll put it in the chat in a minute 566 00:26:17,570 --> 00:26:21,470 for the Forest to Faucet website that gives you links 567 00:26:21,470 --> 00:26:23,510 to both the data, the story map, 568 00:26:23,510 --> 00:26:26,890 and when the reports and tools are done, 569 00:26:26,890 --> 00:26:27,870 they'll also be there. 570 00:26:27,870 --> 00:26:30,750 So if you ever Google Forest to Faucet, 571 00:26:30,750 --> 00:26:33,466 you should be able to get that website as well. 572 00:26:33,466 --> 00:26:34,643 And I thank you very much. 573 00:26:37,040 --> 00:26:42,040 - I'm curious about the kind of ongoing updates to this. 574 00:26:42,140 --> 00:26:44,130 So I know some of these sets are gonna be 575 00:26:44,130 --> 00:26:47,080 kind of regularly changing, some won't be. 576 00:26:47,080 --> 00:26:49,668 And as you kind of looked at the landscape 577 00:26:49,668 --> 00:26:52,840 of spatial products that are available and going into this, 578 00:26:52,840 --> 00:26:55,960 what would be a reasonable interval for updating this 579 00:26:55,960 --> 00:26:58,680 into 2.1, 2.2, or do you envision this more 580 00:26:59,703 --> 00:27:01,940 as like a five, 10 year update into a 3.0, 4.0? 581 00:27:03,423 --> 00:27:05,806 Like I'm curious what you think about keeping it up to date. 582 00:27:05,806 --> 00:27:08,663 How often we can do it and what might change as you go? 583 00:27:09,680 --> 00:27:13,930 - Yeah, currently the plan is every five years 584 00:27:13,930 --> 00:27:15,750 as land cover data sets are available 585 00:27:15,750 --> 00:27:17,880 'cause the main piece of it 586 00:27:17,880 --> 00:27:19,430 is the biophysical characteristics. 587 00:27:19,430 --> 00:27:20,930 We are running into some changes 588 00:27:20,930 --> 00:27:23,430 in the drinking water, 589 00:27:23,430 --> 00:27:25,170 surface drinking water information system, 590 00:27:25,170 --> 00:27:27,186 the EPA's database we use 591 00:27:27,186 --> 00:27:29,566 for surface drinking water consumers. 592 00:27:29,566 --> 00:27:30,980 We're running into some changes in there already 593 00:27:30,980 --> 00:27:33,202 that people have flagged for us. 594 00:27:33,202 --> 00:27:34,784 That just happened to be like 595 00:27:34,784 --> 00:27:37,640 in the year we published the data, there was a major change. 596 00:27:37,640 --> 00:27:40,200 So we are gonna look at how we can maybe 597 00:27:40,200 --> 00:27:43,970 update those more frequently with some scripting. 598 00:27:43,970 --> 00:27:46,750 So that's, it doesn't change the entire assessment per se, 599 00:27:46,750 --> 00:27:48,670 but because the assessment, 600 00:27:48,670 --> 00:27:50,644 and the way we're publishing it 601 00:27:50,644 --> 00:27:53,830 is more of a strategy and kind of a methodology 602 00:27:53,830 --> 00:27:55,763 as opposed to, you know, the results. 603 00:27:56,663 --> 00:27:58,750 And then folks can take the results as they are to, 604 00:27:58,750 --> 00:28:00,805 you know, do further work. 605 00:28:00,805 --> 00:28:03,251 So we're hoping that these tools will be dynamic. 606 00:28:03,251 --> 00:28:07,650 I can't promise that it's gonna be annual, 607 00:28:07,650 --> 00:28:11,280 but I would like to see that hopefully in the future 608 00:28:11,280 --> 00:28:13,630 we can get some funding to keep it 609 00:28:13,630 --> 00:28:15,660 at least some of these more dynamic data sets 610 00:28:15,660 --> 00:28:19,060 that are updated annually updated in the watershed tools. 611 00:28:19,060 --> 00:28:21,590 And that's why we are building this 612 00:28:21,590 --> 00:28:26,310 more robust watershed tools website. 613 00:28:26,310 --> 00:28:27,950 So people can actually download the data, 614 00:28:27,950 --> 00:28:29,050 and it can be dynamic. 615 00:28:32,045 --> 00:28:32,960 - I have lots of questions. 616 00:28:32,960 --> 00:28:37,960 I'm curious what, as you started to work with stakeholders, 617 00:28:38,830 --> 00:28:40,630 if there are any opportunities 618 00:28:40,630 --> 00:28:44,760 for regionally-specific versions of this framework 619 00:28:44,760 --> 00:28:47,988 and data kind of modeling exercise? 620 00:28:47,988 --> 00:28:51,980 Could this be taken down to a more specific scale 621 00:28:51,980 --> 00:28:53,670 here in the Northeast or for certain 622 00:28:53,670 --> 00:28:56,840 like larger watersheds or groups of watersheds 623 00:28:56,840 --> 00:29:00,112 that are of interest where you may have wanted some data 624 00:29:00,112 --> 00:29:02,155 at the large national scale, you couldn't get, 625 00:29:02,155 --> 00:29:03,813 but you could get down at a regional scale? 626 00:29:03,813 --> 00:29:06,532 Is that a worthwhile area to pursue, or is it, 627 00:29:06,532 --> 00:29:10,629 would you really need to get down to pretty small sites 628 00:29:10,629 --> 00:29:13,510 to see this change in scale and resolution 629 00:29:13,510 --> 00:29:14,816 that would make it different 630 00:29:14,816 --> 00:29:15,983 than what you're showing at the national level? 631 00:29:17,870 --> 00:29:19,030 - Yeah, that's a really good question. 632 00:29:19,030 --> 00:29:21,190 I think, I mean, 633 00:29:21,190 --> 00:29:24,070 the way we kind of frame the entire assessment 634 00:29:24,070 --> 00:29:26,410 to national data sets. 635 00:29:26,410 --> 00:29:28,430 So, I mean, unless you have a more, 636 00:29:28,430 --> 00:29:30,710 especially more refined land cover, 637 00:29:30,710 --> 00:29:33,567 the Chesapeake Bay, for example, 638 00:29:33,567 --> 00:29:37,410 has a really refined land cover dataset 639 00:29:37,410 --> 00:29:39,615 that could really change, 640 00:29:39,615 --> 00:29:41,630 especially if you're looking at riparian areas, 641 00:29:41,630 --> 00:29:42,952 land cover within riparian areas 642 00:29:42,952 --> 00:29:45,100 and that sort of thing really change the results, 643 00:29:45,100 --> 00:29:47,030 having that more. 644 00:29:47,030 --> 00:29:49,340 So there is opportunities where 645 00:29:49,340 --> 00:29:54,340 if there is that kind of greater resolution data set 646 00:29:54,870 --> 00:29:55,703 that you could do some, 647 00:29:55,703 --> 00:30:00,270 but there is no plans to kind of take it and scale it down 648 00:30:00,270 --> 00:30:02,363 using regional data sets at this time. 649 00:30:03,709 --> 00:30:06,706 But I can see, you could definitely take the methodology, 650 00:30:06,706 --> 00:30:10,890 and, you know, where there is higher resolution data, 651 00:30:10,890 --> 00:30:12,990 you could definitely grab it and apply it. 652 00:30:14,809 --> 00:30:15,650 With the other, with the drinking water. 653 00:30:15,650 --> 00:30:17,310 And the other thing was, 654 00:30:17,310 --> 00:30:19,610 if you have a different scale watershed. 655 00:30:19,610 --> 00:30:21,310 We've asked, people have asked us, 656 00:30:22,367 --> 00:30:24,071 can we rescale it to the 10-digit watershed? 657 00:30:24,071 --> 00:30:25,020 Could we rescale it to the 14-digit watershed? 658 00:30:25,020 --> 00:30:27,430 And yes, we can, 659 00:30:27,430 --> 00:30:31,583 but I don't know if you're going to get a lot of, 660 00:30:32,840 --> 00:30:36,907 as this, the purpose of this is to kind of like, you know, 661 00:30:36,907 --> 00:30:38,257 look at a nation or region, 662 00:30:39,107 --> 00:30:42,109 kind of figure out where the highest priorities are, 663 00:30:42,109 --> 00:30:43,830 and then kind of do some on the ground work. 664 00:30:43,830 --> 00:30:45,730 So I don't think you're gonna get, 665 00:30:45,730 --> 00:30:47,760 for this particular, using this methodology, 666 00:30:47,760 --> 00:30:51,053 you're gonna get much of a change in your result. 667 00:30:54,270 --> 00:30:56,620 - Okay, we have a couple questions in the chat. 668 00:30:57,969 --> 00:30:59,943 The first one from Ned Swanberg. 669 00:31:01,066 --> 00:31:02,780 Is there a way to also connect forest management 670 00:31:02,780 --> 00:31:05,830 to groundwater source drinking water? 671 00:31:05,830 --> 00:31:08,910 - Yeah, so we have, we have started talking, 672 00:31:08,910 --> 00:31:11,470 well, we've been, through this entire developing 673 00:31:11,470 --> 00:31:13,530 of this methodology, we have been talking with folks 674 00:31:13,530 --> 00:31:17,530 on how to develop a groundwater model, similar, 675 00:31:17,530 --> 00:31:20,760 where we are prioritizing land area to 676 00:31:20,760 --> 00:31:23,230 groundwater drinking water systems. 677 00:31:23,230 --> 00:31:25,520 It's very, very hard. 678 00:31:25,520 --> 00:31:27,040 That is definitely something you could do 679 00:31:27,040 --> 00:31:28,803 on a regional local scale. 680 00:31:29,922 --> 00:31:30,830 It's just, there's so much variability 681 00:31:30,830 --> 00:31:34,090 in how groundwater is recharged across the nation. 682 00:31:34,090 --> 00:31:37,800 We just, haven't got a good grasp on a nationwide model. 683 00:31:37,800 --> 00:31:40,240 And again, if someone does have some leads 684 00:31:40,240 --> 00:31:41,970 on some modeling that's been done 685 00:31:43,742 --> 00:31:45,730 on valuing land area to groundwater systems, 686 00:31:45,730 --> 00:31:47,405 please let me know. 687 00:31:47,405 --> 00:31:49,803 'Cause we would love to work with you 688 00:31:49,803 --> 00:31:52,333 on getting that model refined and developed. 689 00:31:55,886 --> 00:31:57,986 - Okay, and this one from Catherine White, 690 00:31:59,085 --> 00:32:01,420 a question specific to forest service use. 691 00:32:01,420 --> 00:32:05,610 Is there a connection to the priority watersheds 692 00:32:05,610 --> 00:32:08,286 that the Forest Service will sometimes use 693 00:32:08,286 --> 00:32:10,050 to prioritize management? 694 00:32:10,050 --> 00:32:11,440 - Yeah, so the, I think she's talking 695 00:32:11,440 --> 00:32:14,140 about the watershed condition framework 696 00:32:14,140 --> 00:32:15,730 that the Forest Service uses. 697 00:32:15,730 --> 00:32:18,543 Yes, so there, I have talked a lot. 698 00:32:18,543 --> 00:32:20,610 I know Katie, she's, 699 00:32:20,610 --> 00:32:24,226 Ted Geier from the Eastern region and I have talked a lot 700 00:32:24,226 --> 00:32:25,676 about the differences between 701 00:32:26,543 --> 00:32:28,203 what the National Forest System did 702 00:32:28,203 --> 00:32:29,560 and Forest to Faucet. 703 00:32:29,560 --> 00:32:31,990 Forest to Faucet is again all lands, 704 00:32:31,990 --> 00:32:36,610 and we don't have a lot of the really specific 705 00:32:36,610 --> 00:32:39,070 water quality information across the nation 706 00:32:39,070 --> 00:32:41,160 that the Forest Service used 707 00:32:41,160 --> 00:32:42,506 for their watershed condition framework. 708 00:32:42,506 --> 00:32:44,780 So it is definitely a bigger, broader brush 709 00:32:45,660 --> 00:32:46,630 across the nation 710 00:32:46,630 --> 00:32:48,830 as opposed to what the Forest Service uses. 711 00:32:48,830 --> 00:32:49,980 They are complimentary. 712 00:32:50,883 --> 00:32:54,460 And before Ted retired, we had been talking about 713 00:32:54,460 --> 00:32:59,410 using some of the surface water consumer modeling we did 714 00:32:59,410 --> 00:33:02,603 to help refine the watershed condition framework 715 00:33:02,603 --> 00:33:03,853 in the future.