 



S1: what about the third? oh i'm sorry (xx) okay that's great. that's good. so uh yeah both, both of these... wait which came first? 
S2: <READING> both field-based, empirical models and numerical, model approaches </READING>
S1: <READING> were considered </READING> but, which, which came first? <READING> the paper, reviewed the strengths and weaknesses </READING>
S2: <READING> and weaknesses of, available models and made recommen- </READING> [S1: okay ] and [S1: and these are the two ] the_ those are the two yeah both field-based empirical and numerical modelling approaches were the two.
<P :05> 
S1: it feels to me like this, sentence should come first... you know, first they considered [S2: so the (xx) ] that_ first they considered these models and then [S2: okay that's fine, ] they committed_ then the paper so
S2: put that yeah put that (in parentheses i'll move that up too no problem) 
S1: mkay okay and then that follows this be- better too [S2: okay ] okay? that just fits in there better. um they
S2: the task committee? 
S1: mhm
S2: would you say the task committee? 
S1: i would. 
S2: the committee (xx) 
S1: s- something like that, organized. <P :04> <READING> extremal hypothesis or geofluvial, </READING> geofluvial feels like it's an adjective geofluvial what?
S2: geofluvial, model. that's a type of model it's a geof- the two models are extremal hypothesis or geofluvial. so i can put the word model, after each of 'em, extremal model [S1: yeah yeah ] extremal hypothesis model or geofluvial model, or i could say_ cuz i had, geo-
S1: okay i got_ that's that's okay yeah mkay... <READING> an extremal hypothesis model is one, that, </READING> or, which whatever you like <READING> this type of model numerical... this type of model numerical, predicts? </READING> [S2: oh ] model, numerical model predicts [S2: yeah ] predicts the potential for (xx) 
S2: yeah, when you're r- like someti- that's one of those things when i read it i don't even read it, out of order i just write
S1: <READING> potential, that does not predict the rate therefore only, an overall estimate of change is given, not how the individual links change (xx) with time this type of model is also </READING> 
S2: i actually wanna change that. 
S1: okay 
S2: so we don't [S1: okay ] we don't_ i don't need to talk about it
S1: and it's not as attractive because, 
S2: with the advancement of computer capabilities allow us, (xx) cuz i mean, we don't_ the extremal hypothesis model doesn't, predict anything with time. so the computer models allow us, to predict things with time (so we should) 
S1: do you say that? that the extremal hypothesis model doesn't allow [S2: yeah right here ] <READING> therefore only an overall estimate of change is given </READING>
S2: <READING> not how the individual links change with time. </READING>
S1: mm, um, i'm not_ i_ and it kinda seems like you could be a little more, clear on_ highlight, the pro- uh highlight more, the problem of time [S2: okay ] so um, when you're talking in class this week you'll be talking about nested problem statements [S2: mhm yeah (xx) i know what those are ] so one solution is the um, extremal hypothesis model [S2: mhm ] it does, X Y and Z, however, you know it solved the problem by using this m- the uh extremal hypothesis model. however it doesn't work on the uh, it, it's not very good about time. so, [S2: yeah mhm ] now the problem becomes time, and now we have a solution to the time problem, and so that's why this isn't as uh um, as attractive [S2: mhm ] as it once was because now, [S2: it's also spatial too so ] oh it's spatial? okay. 
S1: okay, so, again, i think_ like i said, the lectures this week are really critical for you. um, okay now we m- move on to the geofluvial model. <READING> this is (xx) unlike extremal models utilize the advancement in computer tech- </READING> they becoming more sophisticated every year but [S2: (xx) ] what does that do for me? by_ in what way, are they becoming more_ exactly what problem do they solve by becoming more 
S2: well i mean computers are getting faster i mean what do_ [S1: okay ] how much do you wanna go <S1 LAUGH> in detail do you want to get into i mean Bill Gates puts out something that's faster every two weeks (xx) (xx) 
S1: yeah, they utilize, the advancement in computer technology 
S2: technology just, stop there or?
S1: um what [S2: (xx) ] advancement, do they utilize and how does it benefit the model?
S2: speed. (xx) i mean just
S1: speed allows the model to do what? 
S2: to to actually move fa- i mean you know the model is moving faster instead of having_ it's the same problem that_ this is like a whole nother topic it's like, you know the old computers would take, four days to solve a problem new ones it's just like a calculator i mean everything's, quicker faster, i mean it's uh, a lot of it's speed a lot of it is uh, the other part of it would be, um... storage, you know modern computers have a lot larger hard disk than they used to and this is [S1: okay ] this'll be extremely 
S1: okay but you're using that as a tool to get, what you want. [S2: mhm ] and what you want is, the speed, um, the capacity [S2: mhm ] allows you to get where you want to go. where is it that you wanna go?
S2: to a better model, i mean to a
S1: to a better_ and why d- why is this a better model it gives you, something, what does it give you? what is_ is speed 
S2: more accur- i mean, these k- these uh, equations aren't even solvable on the slower computers. [S1: okay ] i mean it would just you know it's it's not practical to turn on a m- a computer and let it it run for a month just to get a prediction of a, of a one hundred, you know foot channel. you see_ i mean [S1: okay ] so... i mean i_ it was just kind of uh, i i was thinking that most of the people_ i guess what i was thinking is that most people realize w- that_ how computers are advancing, and modelling i mean, pretty much all the professors and stuff realize that modelling is getting more sophisticated and better because of the increasing speeds and capacities of computers. [S1: mhm ] so, i mean i didn't want to go into too much detail about that would it be better_ [S1: i think mo- ] i mean do i need to go into detail or [S1: i th- well ] should i just throw it out completely? 
S1: when i when i see a phrase like um, <READING> they utilized the advancement by becoming more sophisticated </READING> i feel like, more detail is needed right there this is just a little [S2: okay ] too vague i mean it it sounds like um, spin you know it sounds like, sorta like 
S2: well what i mean what about i mean the next sentence <READING> increased computer speed allows the inclusion of more processors (xx) increased time steps </READING> [S1: okay ] (and then) i'm going into the details.
S1: right 
S2: so
S1: but still_ yeah that's the details of what?
S2: of how they're more sophisticated.
S1: yeah but what's the end product? [S2: (i) mean ] the end product is a model that... 
S2: predicts, river bank erosion.
S1: okay 
S2: i mean, pretty much the the end product is a a model that will allow you to predict, river bank erosion, essentially. by including all these different processes. (now) let's see let me read [S1: (xx) ] how 'bout [S1: yeah ] something like this unlike extremal models geofluvial models utilize the advancement in cur- computer technology [S1: yeah this is ] the increased computer speed allows the inclusion of more processors finer grade spacing and increased time steps all of which increase the accuracy of this type of model, [S1: okay ] all of which increase the accuracy of this type of model [S1: accuracy, okay ] thus making geofluvial the more attractive option for the future.
S1: is is that the main, thing is that it's more accurate?
S2: not just accurate it's also more uh, it's also, faster. i mean, the solution is faster 
S1: the solution comes faster but the [S1: mhm ] ultimate goal is that you have an accurate model?
S2: right i mean that's the ultimate goal
S1: okay so so this is
S2: i mean a- a- accuracy is the ultimate goal i mean it_ they're willing to sacrifice time, for accuracy, but there reaches a point where, time does become an issue because you know no one wants to wait a month before seeing, the results. [S1: mhm ] so, that's why they're becoming, more in use because now you can turn it on run it for eight hours and get a nice prediction of what happened over the course of a month. [S1: mhm ] whereas you know maybe five ten years ago, you know what takes place in our time as a second might take place in ten seconds in computer time [S1: mhm ] whereas now it's opposite you know we can do ten seconds real time in one second computer time. [S1: mhm ] that type of thing. so, well anyway, does that sound better if i just [S1: yeah ] get rid of the end here? now isn't this sentence too long though now? [S1: no ] (xx) we just_ no it's okay? 
S1: in fact i could say_ i was gonna say you could even hook this one up there, almost. uh, but but i think a period is good. um, this this and this <READING> all of which increase the accurac- </READING> no i think that's fine (sentence) it's not too 
S2: but then i have a_ i mean it continues
S1: that's okay 
S2: that's alright? 
S1: yeah 
S2: okay, it seems pretty long. alright.
S1: i think it's just, fine. 
S2: okay
<P :05> 
S1: uh you could connect these two sentences with a semicolon.
S2: okay 
S1: because they're_ if you wanted to but a period's fine too. um, okay i wanted to [S2: okay ] keep in mind that the most important thing, about, this geofluvial model, is, the accuracy. mkay? and here we have it, right in the very last sentence at the end of the paragraph. so... a- as you're as you're in lectures this week, think about wh- uh think um, (i'll) still be talking about criteria, for a [S2: mhm ] solution, you know what what makes [S2: what i- ] the best solution and i may have talked to you about (this in previous) 
S2: oh you took 'em from the essay what did you say about this paragraph the last time right here? i mean
S1: mm it's in here um, [S2: mhm ] accuracy
S2: na- nothing? 
S1: no 
S2: you just changed that? okay 
S1: yeah <P :06> yeah... yeah anyway, r- keep keep in mind that um, that's wo- that's gonna be one of your criteria, for success [S2: mhm ] and so she'll be talking about that [S2: well ] mkay? [S2: mkay ] um now we're talking about (xx) transport. we're still geofluvial model thi- so this method, this bacterial bedload transport method, [S2: mhm ] is what's a significant departure and included two innovative features this [S2: mhm ] mkay i think you need to, just period here. okay, okay. like i said we're we're gonna_ the introduction is crucial, you know it's really, the, most important part of the_ well, for your readers. it's nice to have 'em not_ a, good introduction so, i think we'll continue to rework that. so, the research objective is, to, improve on the Kovacs-Parker model? 
S2: yup
S1: and this task force talks about
S2: i'm done completely with the task force [S1: yeah ] i won't mention it again.
S1: but they're...
S2: there's actually a good chance 
S1: this is still part of it? 
S2: yeah b- yeah it's a g- it's part [S1: so only the Kovacs ] of my proposal there's a good chance when i actually, there's a good chance actually when i show this to my professor he's gonna tell me to throw it all out anyway so, [S1: oh great ] it's only partially [S1: yeah yeah, yeah, yeah ] relevant i mean it's more of a 
S1: okay, but, uh the task committee did review this [S2: mhm ] this and this, and the Kovacs-Parker model was one of them that they reviewed. 
S2: yes. i i_ [S1: mkay ] yeah the way i had the introduction written up so far is i was trying to include, almost a time line [S1: mhm ] um [S1: yeah, that'll be helpful ] (in terms of you know) there is extremal p- there's_ these are the two types of models, the geofluvial model's better, um one of the geofluvial models is, Kovacs-Parker, task force likes Kovacs-Parker, that's why_ that's, one of the big reasons i am, doing this. and that's [S1: okay ] what i was trying to set_ i'm trying to kinda set up, set up the fastball you know for the [S1: yeah ] yeah so, but i don't even know 
S1: so, you know that the Kovacs-Parker, is, a, good solution.
S2: yes 
S1: right? but, you wanna make it better?
S2: oh yeah, i- i- it's deficient in quite a few ways
S1: so, your research objective is to improve, on, the Kovacs, Parker model
S2: yup 
S1: and do you say that anywhere, exactly? 
S2: mhm, well <READING> this, this research is not intended to address all the above deficiencies in Kovacs-Parker model but would address some of the more significant ones. </READING>
S1: so, [S2: so ] the the the [S2: <READING> this research (xx) </READING> oh, okay, the objective of this ] objective is, to address, [S2: got it ] some of the more significant, [S2: deficiencies ] deficiency in the Kovacs. that's what your research objective is and i feel like it's again, it's b- a little bit buried, in the last paragraph 
S2: but don't you need to set up_ okay so alright [S1: well, yeah ] i- if i put it in a small paragraph here, [S1: yeah ] stating this [S1: mhm ] but then i won't have addressed any of the deficiencies, and i need to talk about where it's good before i talk about its deficiencies. i i [S1: okay ] could put in a small, paragraph here, setting this up, [S1: okay ] but i was just wondering [S1: um ] basically what i did is i do a quick description of the Parker-Kovacs model here [S1: right ] based on these two paragraphs, and then say okay, this is [S1: right ] what's, where it's lacking this is what i'm gonna do [S1: right ] um, i see your p- i see your point exactly obviously but um i could put a small paragraph in here saying, um, the goal of this research is to, um, make some of the, well i was wondering about s- 
S1: i think this is perfect the way it said it right here, is to address some of the [S2: but then put put it up to here, or leave it there? ] mm, some of the more significant deficience_ u- mm, is to improve on the Kovacs-Parker model and, um
S2: but i- should i_ you're s- you're, commenting on it being buried in the third paragraph [S1: right ] so... 
S1: hm 
S2: i mean i could move that, sentence, up here but i can't leave the rest of this paragraph 
S1: actually this is a good sentence too.
<P :09> 
S2: okay so how 'bout, we do something like
S1: you know what? [S2: this is ] i don't i don't think you should decide yet. i think this week is a- is perfect timing, the lectures this week are perfect timing for you and i think you should, listen on, Tuesday and Thursday [S2: okay ] because i think uh i i think it'll just, really fall into place for you but, uh some of the things that i've out- um highlighted today, um... you're ready [S2: okay ] you're ready. uh i wanted to talk to you about um... did you, work on your node diagram?
S2: oh, a little bit, not too much
S1: that would be really helpful, uh whe- when is it due?
S2: what? the proposal? 
S1: the diagram.
S2: mm there is no diagram due.
S1: oh that's not? really...? hm... um okay, so <S2 LAUGH> so there wasn't an actual assignment you just [S2: no ] discussed it [S2: yup ] well then, i'm gonna give you some homework <LAUGH> i think it would be really, helpful and um, if you have trouble with it i think, it would be great for you to make an appointment with Professor Olsen
S2: oh i don't think i'll have a problem with it it just_ i don't know there's other things i'm just working on right now.
S1: yeah? [S2: but ] i think it would go_ it would, blend nicely, and really help you along this way so with the node diagram and with the two lectures this week, i think it'll really help you shake out, a nice introduction, um, okay so
S2: well the, the one thing i was thinking of if i go into the node diagram, [S1: mhm ] i basically figured that i would have to throw out, numerous 
S1: no i don't mean it goes in your paper.
S2: oh cuz i_ cuz if i use the node diagram as an introduction then i really [S1: no no no no no no ] have to give up all that cuz it won't flow at all.
S1: no all_ it's it's uh as, just, almost like an an alternative to an outline. where you, um, you see, the flow, from the problem statement, to, s- n- suggested
S2: well the, the problem_ [S1: uh, solutions ] the node diagram she talked about was a historical one. in terms of going back [S1: well you can do it that way too but, it's an idea ] i mean that's that's the only one she talked about, it's different than uh, cuz i_ what i assume you're talking about is something more like, here's the problem [S1: mhm ] and then here are solutions to the problem. [S1: right ] that's yeah it's a little diff- it's_ she kinda addressed that but she actually had it going back (forever) um [S1: well sh- i think ] but there's more than one_ i mean, now, in terms of addressing that way the problem, isn't it really like five problems though for this, cuz i'm talking about the five deficiencies [S1: well then, then um ] and then, i mean so i mean, basically it's like, it's, it's almost like here's the model 
S1: but they all, but they all, [S2: stem from just, from that ] come stem from what's the what's the, okay, [S2: from the Kovacs-Parker model ] and the and the Kovacs-Parker. but the Kovacs-Parker is, one solution_ it's just one of many solutions to, what's the big, picture? what's the [S2: river bank river bank erosion ] okay 
S2: i mean yeah you could have river bank erosion, and then there are f- the fi- i mean i could you know [S1: okay ] they all would_ there's like, twelve models alone, reviewed in that paper.
S1: mhm mhm over_ another_ i just wanna talk in general, um, overall, i i feel like you're, um, u- um, using different terms, for the same, thing and i feel like they're not fully defined [S2: mhm ] um
S2: well there's_ yeah that's one of the problems though, unlike a lot of other, unlike a lot of other, disciplines [S1: mhm ] where, steel is steel is steel, [S1: mhm ] unfortunately in a lot of civil engineering especially what i'm getting into the_ there's so many, different terms i mean people in, the Midwest say things different than the Southeast say things_ you know there's a lot of terms for the same thing [S1: yeah ] and now [S1: and that's one reason ] and there and there's slight, there is slight, frequent(sic) there are slight defi- i mean there are slight differences between them [S1: mhm ] um, but i guess i was trying to encompass, mm, i don't know exactly what i wanna say but i guess i was, trying to encompass, you know address, some different terms for similar things, and 
S1: that's good, [S2: channel morphology ] that's good but you kinda need to do it right [S2: okay ] up front so 
S2: well it's kinda like channel morphology is anything that changes in the channel, anything. [S1: okay ] so river, bank erosion is a subset of channel morphology. 
S1: okay great great great 
S2: okay? so i mean, i don't know what, ah but see that's not, no this can't be from the same tree anymore y- you're talking [S1: okay ] about okay i mean well, it could be like way way up here [S1: okay ] it can't be up there [S1: okay ] so now i don't know 
S1: what what are some other types of channel morphology?
S2: (i don't know) <LAUGH> you know there [S1: i yeah, i can't ] you know the bottom_ <S1 LAUGH> well i mean if you stand in a river what do you see i mean there's banks, and braided channels i mean there's yeah there's tons of 'em. i mean if you look at a river, and even a change (xx) river is a chain- is a type but i mean that's way, like you said that's way up
S1: okay, [S2: up the chain ] and and you're not concerned with these things? you are concerned with, river bank erosion 
S2: oh i'm mo- yeah, with river bank erosion um, i'm slightly concerned with channel morphology as well and i talk about that because we do have the uh, we do have_ i wanna in- one of the things i wanna include in the Ko- Kovacs-Parker model is changes in the longitudinal direction. [S1: okay ] which is actually the riverbed changes.
S1: so another one that you (interested in) is longitudinal direction change.
S2: right. 
S1: okay, and you're gonna be talking about_ and that's different than river bank erosion? 
S2: right, but i- but it's gonna be yeah 
S1: okay, so 
S2: mkay 
S1: i i would, i really would like to see you, [S2: sure ] take it back, you know and maybe, channel morphology is just one of, you know [S2: okay ] a bunch of 
S2: now if mkay, i i can_ i need to get going like real badly <LAUGH>
S1: yeah, oh sorry sorry
S2: um, but uh, yeah but i could take it back that far i guess i um you know maybe after i do that i'll see how i might work it in can i have that, the front page, too? 
S1: here?
S2: yup
S1: yeah
S2: (xx) 
S1: yeah, [S2: uh ] cuz i'd like to hear what you have to say about the uh lectures, this week
S2: yeah i i might go, i mean if i can take it back there it's, uh, i don't we_ yeah i'll think about how i wanna try and do that. i have i've already thought [S1: i hope you'll be inspired ] well i- i i've already thought that i've, probably put too much in on that uh, task force there [S1: i don't_ ] extremal models technically is not, relevant wh- or the the extremal hypothesis models that i mention in there, [S1: yeah ] (frankly) that's not relevant whatsoever [S1: right ] it's just, there's two ways of solving it, and so i mention the two ways and then i [S1: yeah ] kinda discard it it's really not relevant whatsoever, so that's the kinda thing where i think [S1: well i think we'll really take off ] in the end my professor might say get rid of it, you know 
S1: i'm hoping we'll really take off next week and i hope that, i- lectures today are inspirational just, if you think what does it have to do with me? [S2: mhm ] just bear with it because i want you to_ you wanna keep that? 
S2: no i don't need it actually
S1: okay, um... yeah.
S2: okay, thanks a lot i appreciate it.
S1: okay, see you next week. hey thanks for doing the recording thing.
S2: oh it's not_ no problem at all.
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