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chi_profiler.m
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chi_profiler.m
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function chi_profiler(DEM, S, fileTag, varargin)
% chi_profiler.m allows for interative river profile analysis via
% the integral or chi method (e.g. Perron and Royden, 2013). Users can
% regress through channel segments to get ksn and select knickpoints along
% river profiles
%
% Inputs:
% 1) DEM: TopoToolBox DEM GRIDobj (required)
% 2) S: TopoToolBox STREAMobj (required)
% 3) fileTag: 'project' name as a string used for output files and
% folder names. (required)
% 4) crita: Critical drainage area for channel head initiation in map
% units. (optional) {default --> 1e6}
% 5) mn: reference m/n (theta) value (optional) {default --> 0.45}
% 6) Ao: reference drainage area for chi integration (optional)
% {default --> 1}. Note: it is recommended to always use an 'Ao'
% of 1 as this results in chi versus elevation plots with a slope
% that is equal to the normalized steepness index.
% 7) smoWin: size of window used to smooth elevation data (set this
% to the cell size of the DEM if you don't want the data to be
% smoothed) (optional) {default --> 250}
% 8) flowOption: string of 'fill' or 'carve' for flow routing.
% (optional) {default --> empty assumes that DEM is already
% filled or carved}
%
% Outputs:
% No variable outputs to Matlab, but chi_profiler.m will produce a
% series of files that can be imported into Matlab and ArcGIS.
%
% - Data tables of each of the stream channels analyzed
% - Shapefiles of chi, ksn, regressed ksn segments and knickpoints
% - Tables of regressed ksn and knickpoint statistics
% Optional:
% - river profiler figures
% - chi and ksn map of entire river network in DEM as a shapefile
%
% See 'User_Guide.docx' for more information on the how to run
% chi_profiler.m and the output file organization
%
% Example:
% chi_profiler(DEM,S,'my_proj','crita',1e6,'mn',0.45,'Ao',1,'smoWin',250);
%
%
% Author: Sean F. Gallen
% Date Modified: 02/20/2017
% email: sean.gallen[at]erdw.ethz.ch
% Parse Inputs
p = inputParser;
p.FunctionName = 'chi_profiler';
% required inputs
addRequired(p,'DEM', @(x) isa(x,'GRIDobj'));
addRequired(p,'S',@(x) isa(x,'STREAMobj'));
addRequired(p,'fileTag', @(x) ischar(x))
% optional inputs
addOptional(p,'crita', 1e6, @(x) isscalar(x));
addOptional(p,'mn', 0.45, @(x) isscalar(x));
addOptional(p,'Ao', 1, @(x) isscalar(x));
addOptional(p,'smoWin', 250, @(x) isscalar(x));
addOptional(p,'flowOption', []);
parse(p,DEM, S, fileTag, varargin{:});
DEM = p.Results.DEM;
S = p.Results.S;
fileTag = p.Results.fileTag;
crita = p.Results.crita;
mn = p.Results.mn;
Ao = p.Results.Ao;
smoWin = p.Results.smoWin;
% make folder to get all the data
folder = [fileTag, '_stream_data/'];
if ~exist(folder, 'dir')
mkdir(cd,[fileTag, '_stream_data']);
end
%% create varables with topotoolbox functions
% set nan values if it hasn't already been done
DEM.Z(DEM.Z <= -9999) = NaN;
% declare cellsize
cs = DEM.cellsize;
% flow routing options
if isempty(p.Results.flowOption)
FD = FLOWobj(DEM);
elseif strcmp(p.Results.flowOption, 'fill');
DEM = fillsinks(DEM);
FD = FLOWobj(DEM);
elseif strcmp(p.Results.flowOption, 'carve');
FD = FLOWobj(DEM,'preprocess','carve');
DEM = imposemin(FD,DEM);
else
error('fillOption is not "fill" or "carve"');
end
% Calculate flow accumulation (A)
A = flowacc(FD).*(cs^2);
% Calculate distance from the channel head
DFD = flowdistance(FD,'downstream'); % this is actually distance from channel head
% Save STEAMobj
chanDir = [cd,'/',fileTag, '_stream_data'];
%mkdir(cd,[fileTag, '_stream_data']);
fileName = [fileTag, '_pickedstreams.mat'];
save([chanDir,'/',fileName],'S');
% Declare STREAMobj variables for faster processing through forloop
ordList = S.orderednanlist;
strmBreaks = find(isnan(ordList));
ksnReg = DEM;
ksnReg.Z = nan(size(DEM.Z));
strmNumGrid = DEM;
strmNumGrid.Z = nan(size(DEM.Z));
GridID = S.IXgrid;
disp(' ');
disp(['you will be analyzing ' num2str(length(strmBreaks)) ' stream channels'])
%% calcuate chi
% declare variables for chi integration
Schi = zeros(size(S.distance));
Six = S.ix; % donors
Sixc = S.ixc; % recievers
Sd = S.distance; % distance from mouth
Sa = (Ao./(A.Z(GridID))).^mn; % chi transformation variable
h = waitbar(0,'calculating \chi for user picked streams...');
% calculating chi for the entire river network
for lp = numel(Six):-1:1;
Schi(Six(lp)) = Schi(Sixc(lp)) + (Sa(Sixc(lp))+(Sa(Six(lp))-Sa(Sixc(lp)))/2) *(abs(Sd(Sixc(lp))-Sd(Six(lp))));
f = (numel(Six)+1 - lp)/numel(Six);
waitbar(f,h);
end
close(h);
%% declare all other stream network variables
Sz = double(DEM.Z(GridID)); % elevation
SmoZ = Sz; % dumby vector to get smoothed data
Sx = S.x; % x_coordinate
Sy = S.y; % y_coordinate
Sdfd = double(DFD.Z(GridID)); % distance from 'divide' (acually channel head)
Sda = double(A.Z(GridID)); % drainage area
%% plot stream network data on a map and as profiles
% plot a map with DEM and streams
map_fig = figure(2);
imageschs(DEM); hold on
plot(S,'-','LineWidth', 2,'Color', [0 0 0]);
set(map_fig,'units','centimeters', 'Position', [25 9 15 11])
% get axes limits for profile data
mindfm = nanmin(Sd)./1000; maxdfm = nanmax(Sd)./1000;
minel = nanmin(Sz); maxel = nanmax(Sz);
minchi = nanmin(Schi); maxchi = nanmax(Schi);
% plot all of the river river profile data as thin gray lines
h = waitbar(0,'Smoothing data and plotting all streams...');
profile_fig = figure(1);
id1 = 0;
for i = 1:length(strmBreaks);
strmInds = ordList(id1+1:strmBreaks(i)-1);
SmoZ(strmInds) = smoothChannelZ(SmoZ(strmInds),smoWin,cs);
subplot(3,1,1);
plot(Sd(strmInds)./1000,SmoZ(strmInds),'k-','lineWidth',0.5,'color',[0.5, 0.5, 0.5]); hold on
xlabel('distance (km)'); ylabel('elevation (m)');
subplot(3,1,2);
plot(Schi(strmInds),SmoZ(strmInds),'k-','lineWidth',0.5,'color',[0.5, 0.5, 0.5]); hold on
xlabel('\chi (m)'); ylabel('elevation (m)');
id1 = strmBreaks(i);
f = i/length(strmBreaks);
waitbar(f,h);
end
close(h)
subplot(3,1,1);
axis([mindfm maxdfm+(maxdfm-mindfm)*.1 minel maxel+(maxel-minel)*0.1])
subplot(3,1,2);
axis([minchi maxchi+(maxchi-minchi)*.1 minel maxel+(maxel-minel)*0.1])
set(profile_fig,'units','centimeters', 'Position', [1 2 15 18])
%% run through all the river profiles individually and have the user
%% decide if they want to get ksn for river channel segments and pick kps
% define step size for ksn bins, this is based on true distance
step = round(smoWin./cs);
% create empty matrices to catch chi regression and kp data
chiFits = [];
kp_data = [];
id1 = 0;
strmNum = 1;
for i = 1:length(strmBreaks);
strmInds = ordList(id1+1:strmBreaks(i)-1);
dataMat = nan(length(strmInds),11);
% save stream channel data in a matrix
dataMat(:,1) = Sdfd(strmInds);
dataMat(:,2) = Sz(strmInds);
dataMat(:,3) = Sda(strmInds);
dataMat(:,4) = Sd(strmInds);
dataMat(:,5) = smoothChannelZ(dataMat(:,2),smoWin,cs);
[mrows, mcols] = ind2sub(DEM.size,GridID(strmInds)); % row and column of data in matrix
dataMat(:,6) = mrows;
dataMat(:,7) = mcols;
dataMat(:,8) = GridID(strmInds);
dataMat(:,9) = Sx(strmInds);
dataMat(:,10) = Sy(strmInds);
dataMat(:,11) = Schi(strmInds);
% save data for this stream
dataFileName = [num2str(strmNum),'_', fileTag, '_chandata.mat'];
save([chanDir,'/',dataFileName],'dataMat');
% highlight river profile or interest
figure(profile_fig)
subplot(3,1,1);
s1 = plot((dataMat(:,4))./1000,dataMat(:,5),'-','lineWidth',2,'color',[0/255 205/255 205/255]);
xlabel('distance (km)'); ylabel('elevation (m)');
title(['stream ', num2str(strmNum), ' of ', num2str(length(strmBreaks))]);
subplot(3,1,2);
s2 = plot(dataMat(:,11),dataMat(:,5),'-','lineWidth',2,'color',[0/255 205/255 205/255]);
xlabel('\chi (m)'); ylabel('elevation (m)');
figure(map_fig)
s3 = plot(dataMat(:,9),dataMat(:,10),'-','lineWidth',2,'color',[250/255 250/255 250/255]);
title(['stream ', num2str(strmNum), ' of ', num2str(length(strmBreaks))]);
figure(profile_fig)
% run the chi profiler function
[newCF, newKP, regV] = profile_chi(dataMat, strmNum, profile_fig, map_fig, Ao, mn, step, chanDir, minchi, maxchi);
chiFits = [chiFits; newCF];
kp_data = [kp_data; newKP];
delete([s1,s2,s3]);
ksnReg.Z(GridID(strmInds)) = regV;
strmNumGrid.Z(GridID(strmInds)) = strmNum;
chiFileName = [fileTag, '_chiFits.mat'];
kpFileName = [fileTag, '_kpData.mat'];
save([chanDir,'/',chiFileName],'chiFits');
save([chanDir,'/',kpFileName],'kp_data');
strmNum = strmNum + 1;
id1 = strmBreaks(i);
end
if ~isempty(kp_data);
% make knickpoint shapefile
MP = struct('Geometry',{'Point'},...
'X',num2cell(kp_data(:,10)),...
'Y',num2cell(kp_data(:,11)),...
'strm_num',num2cell(kp_data(:,1)),...
'kp_num',num2cell(kp_data(:,2)),...
'kp_type',num2cell(kp_data(:,3)),...
'chi',num2cell(kp_data(:,4)),...
'elev',num2cell(kp_data(:,5)),...
'smo_el',num2cell(kp_data(:,9)),...
'd_area',num2cell(kp_data(:,6)),...
'dfm',num2cell(kp_data(:,7)),...
'dfd',num2cell(kp_data(:,8)),...
'GridX',num2cell(kp_data(:,12)),...
'Gridy',num2cell(kp_data(:,13)),...
'outletX',num2cell(kp_data(:,14)),...
'outletY',num2cell(kp_data(:,15)));
shapewrite(MP,[chanDir,'/',fileTag, '_kp_Data.shp']);
% make knickpoint data excel table.
X =kp_data(:,10);
Y = kp_data(:,11);
strm_num = kp_data(:,1);
kp_num = kp_data(:,2);
kp_type = kp_data(:,3);
chi = kp_data(:,4);
elev = kp_data(:,5);
smo_el = kp_data(:,9);
d_area = kp_data(:,6);
dfm = kp_data(:,7);
dfd = kp_data(:,8);
GridX = kp_data(:,12);
GridY = kp_data(:,13);
outletX = kp_data(:,14);
outletY = kp_data(:,15);
T = table(X, Y, strm_num, kp_num, kp_type, chi, elev, smo_el,...
d_area, dfm, dfd, GridX, GridY, outletX, outletY);
filename = [chanDir,'/',fileTag, '_kp_Data.xlsx'];
writetable(T,filename)
end
ksnRegS = ksnReg.Z(GridID);
if ~isempty(ksnRegS(~isnan(ksnRegS)));
% make shapefile of ksn regressions
MP = struct('Geometry',{'Point'},...
'X',num2cell(Sx(~isnan(ksnRegS))),...
'Y',num2cell(Sy(~isnan(ksnRegS))),...
'ksn_reg',num2cell(ksnRegS(~isnan(ksnRegS))));
shapewrite(MP,[chanDir,'/',fileTag, '_ksn_regressions.shp']);
chiFits = chiFits((chiFits(:,2) ~= -9999),:);
save([chanDir,'/',chiFileName],'chiFits');
% write excel table with regression data
stream_ID = chiFits(:,1);
segment_num = chiFits(:,2);
ksn = chiFits(:,3);
ksn_95uc = chiFits(:,4);
r_squared = chiFits(:,7);
min_chi = chiFits(:,8);
max_chi = chiFits(:,9);
min_elev = chiFits(:,10);
max_elev = chiFits(:,11);
outletX = chiFits(:,12);
outletY = chiFits(:,13);
T = table(stream_ID, segment_num, ksn, ksn_95uc, r_squared, min_chi,...
max_chi, min_elev, max_elev, outletX, outletY);
filename = [chanDir,'/',fileTag, '_ksn_regressions.xlsx'];
writetable(T,filename)
end
% if ~isempty(kp_data) && ~isempty(ksnRegS(~isnan(ksnRegS)));
% % save data with fileTag
% % make tab delimited table for knickpoint and chi data
% writeTXTtables(chanDir, fileTag, kp_data, chiFits);
% end
ChiGrid = DEM;
ChiGrid.Z = nan(size(DEM.Z));
ChiGrid.Z(GridID) = Schi;
% making ksn map for streams analyzed
ksnStreams = binnedKsn(S,Schi,SmoZ,smoWin,cs,Ao,mn);
ksnG = DEM;
ksnG.Z = nan(size(DEM.Z));
ksnG.Z(GridID) = ksnStreams;
% Make a shapefile with the analyzed stream segments numbered (0 mean
% it was not analyzed
MS = STREAMobj2mapstruct(S,'seglength',smoWin,'attributes',...
{'stream_num' strmNumGrid @min...
'chi' ChiGrid @mean...
'ksn' ksnG @mean...
'DrArea' A @mean});
shapewrite(MS,[chanDir,'/',fileTag, '_strmData.shp']);
% make an ascii of the channel segment chi-ksn values. (I can figure
% out how to make a shape file from this using topotoolbox. Any
% suggestions would be great.)
GRIDobj2ascii(ksnReg,[chanDir,'/',fileTag, '_chiksn_segs.txt']);
delete([profile_fig,map_fig]);
%% finally ask the user if they would like to make a chi map and ksn map
%% written as a shapefile for the entire drainage network
txt = sprintf('\nWould you like to make a chi map and a ksn map for your full drainage network?');
disp(txt);
txt = sprintf('Note: this may take a little time.\n');
disp(txt);
cont_opt = input('\ntype "y" for yes or "n" for no: ','s');
while ~strcmp(cont_opt,'y') && ~strcmp(cont_opt,'n'),
%case where you didn't enter a, b, c, or d:
disp(' ');
disp('Yes(y) or No(n) only!!!')
cont_opt = input('type "y" for yes or "n" for no: ','s');
end
if cont_opt == 'y'
S1 = STREAMobj(FD,'minarea',crita/(DEM.cellsize^2));
% Declare STREAMobj variables for faster processing through forloop
ordList = S1.orderednanlist;
strmBreaks = find(isnan(ordList));
GridID = S1.IXgrid;
Sz = double(DEM.Z(GridID)); % elevation
SmoZ = Sz; % dumby vector to get smoothed data
% get variables ready for chi integration
chis = zeros(size(S1.distance));
Six = S1.ix;
Sixc = S1.ixc;
Sx = S1.distance;
Sa = (Ao./(A.Z(S1.IXgrid))).^mn;
h = waitbar(0,'calculating \chi for full stream network...');
% calculating chi for the entire river network
for lp = numel(Six):-1:1;
chis(Six(lp)) = chis(Sixc(lp)) + (Sa(Sixc(lp))+(Sa(Six(lp))-Sa(Sixc(lp)))/2) *(abs(Sx(Sixc(lp))-Sx(Six(lp))));
f = (numel(Six)+1 - lp)/numel(Six);
waitbar(f,h);
end
close(h);
ChiGrid = DEM;
ChiGrid.Z = nan(size(DEM.Z));
ChiGrid.Z(S1.IXgrid) = chis;
% plot all of the river river profile data as thin gray lines
h = waitbar(0,'Smoothing elevation data for full stream network...');
id1 = 0;
for i = 1:length(strmBreaks);
strmInds = ordList(id1+1:strmBreaks(i)-1);
SmoZ(strmInds) = smoothChannelZ(Sz(strmInds),smoWin,cs);
id1 = strmBreaks(i);
f = i/length(strmBreaks);
waitbar(f,h);
end
close(h)
% making ksn map for streams analyzed
ksnStreams = binnedKsn(S1,chis,SmoZ,smoWin,cs,Ao,mn);
ksnG = DEM;
ksnG.Z = nan(size(DEM.Z));
ksnG.Z(GridID) = ksnStreams;
MS = STREAMobj2mapstruct(S1,'seglength',smoWin,'attributes',...
{'chi' ChiGrid @mean...
'ksn' ksnG @mean});
fileName = [chanDir,'/',fileTag, '_chi_ksn_map.shp'];
shapewrite(MS,fileName);
elseif cont_opt == 'n'
end
end