This tutorial is going to walk through adding a new component to represent Aquaculture. Aquaculture represents about 7% of total water demand (USGS 2010). The USGS splits out aquaculture in its 5-year reports, but since aquaculture water use is determined by a combination of production and evaporation, we can model future changes.
The hope is that this will provide a basis for understanding how to add new demands in general, and other kinds components as well.
In [18]:
run(`git checkout -b aquacomp`)
M configs/standard-1year.yml
M configs/standard.yml
A prepare/netcdf2csv.jl
M src/lib/datastore-netcdf.jl
M src/lib/datastore-nonetcdf.jl
M src/optimize-surface.jl
M src/optimize.jl
D src/tools/netcdf2csv.jl
Switched to a new branch 'aquacomp'
In [17]:
`git status`
Out[17]:
`git status`
Most components have a similar structure, as follows:
After that is done, we need to do some things outside of the individual component.
We will consider each of these in order.
Make sure to use both normal comments, which start with #, and docstrings. Here is the comment at the top of the file.
In [1]:
# The Freshwater Aquaculture component.
#
# It uses aquaculture production data as a baseline, which is then allowed to change with temperature and production.
In [2]:
using DataFrames
using Mimi
include("lib/datastore.jl")
LoadError: could not open file /Users/jrising/research/water/model/operational-problem/docs/lib/datastore.jl
while loading In[2], in expression starting on line 3
in include at /Applications/Julia-0.4.0.app/Contents/Resources/julia/lib/julia/sys.dylib
in include_from_node1 at /Applications/Julia-0.4.0.app/Contents/Resources/julia/lib/julia/sys.dylib
In [3]:
@defcomp Aquaculture begin
regions = Index()
# The basic pattern of aquaculture (could vary in time)
demand_baseline = Parameter(index=[regions, time], unit="1000 m^3")
# The effect of production on demand
production_baseline = Parameter(index=[time], unit="MT") # 299,396 in 2010
production = Parameter(index=[time], unit="MT")
# Demand combining the two effects
demand = Variable(index=[regions, time], unit="1000 m^3")
end
Out[3]:
Aquaculture
In [4]:
function run_timestep(c::Aquaculture, tt::Int)
v, p, d = getvpd(c)
# Scale with production
v.demand[:, tt] = (p.production[tt] / p.production_baseline[tt]) * p.demand_baseline[:, tt]
end
Out[4]:
run_timestep (generic function with 3 methods)
In [5]:
function initaquaculture(m::Model)
aquaculture = addcomponent(m, Aquaculture);
scaling = config["timestep"] / 12.
# Baseline from USGS
aquaculture[:demand_baseline] = repeat(convert(Vector{Float64}, readtable(datapath("aquaculture/usgsextract.csv"))[:AQ_WFrTo]) * scaling, outer=[1, m.indices_counts[:time]])
# Production data from Fisheries of the United States
production = readtable(datapath("aquaculture/production.csv"))
aquaculture[:production_baseline] = repeat(production[production[:year] .== 2010, :production] * scaling, outer=[numsteps])
aquaculture[:production] = repeat(production[production[:year] .>= 2010, :production] * scaling, inner=[round(Int64, 1. / scaling)])
aquaculture
end
Out[5]:
initaquaculture (generic function with 1 method)
Up to this point, these are all values that go into the component file itself. Now let's switch to the unit test file, as we try it out. We make a new file test/test_Aquaculture.jl.
Here's what the test_Aquaculture.jl file looks like:
In [7]:
# Load the component
#include("../src/SimpleAquaculture.jl")
include("../src/lib/datastore.jl")
include("../src/lib/readconfig.jl")
# Set up the model
counties = convert(Vector{Float64}, readtable(datapath("aquaculture/usgsextract.csv"))[:,:FIPS])
config = readconfig("../configs/single.yml")
numsteps = 1
numcounties = length(counties)
m = Model()
setindex(m, :time, [1]) # Single period
setindex(m, :regions, counties)
# Add the component
initaquaculture(m)
# Run the model
run(m)
# Check that it matches 2010
demand_baseline = repeat(convert(Vector{Float64}, readtable(datapath("aquaculture/usgsextract.csv"))[:AQ_WFrTo]), outer=[1, m.indices_counts[:time]])
println(m[:Aquaculture, :demand] - demand_baseline)
1.0
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Now we need to embed this into the rest of the model. If you look in model.jl, there are a sequence of include lines for each component, and then init lines. The order of the init lines matters, because this is that order that components will be computed, and each component needs its dependent components to already have been computed.
However, the only imput to this component is the level of production, which is set by the optimization or simulation information.
In [9]:
include("../src/model2.jl")
Loading from saved region network...
WARNING: imported binding for edges overwritten in module Main
Loading from saved water network...
Loading from saved region network...
Creating model...
Out[9]:
Mimi.VariableReference(Mimi.Model(Dict(:regions=>3109,:crops=>9,:time=>1,:edges=>18561,:canals=>21598,:aquifers=>3108,:gauges=>22559,:reservoirs=>2671),Dict(:regions=>Any["01001","01003","01005","01007","01009","01011","01013","01015","01017","01019" … "56027","56029","56031","56033","56035","56037","56039","56041","56043","56045"],:crops=>Any["alfalfa","otherhay","Barley","Barley.Winter","Maize","Sorghum","Soybeans","Wheat","Wheat.Winter"],:time=>Any[24106],:edges=>Any[1,2,3,4,5,6,7,8,9,10 … 18552,18553,18554,18555,18556,18557,18558,18559,18560,18561],:canals=>Any[1,2,3,4,5,6,7,8,9,10 … 21589,21590,21591,21592,21593,21594,21595,21596,21597,21598],:aquifers=>Any[1,2,3,4,5,6,7,8,9,10 … 3099,3100,3101,3102,3103,3104,3105,3106,3107,3108],:gauges=>Any["usgs.02456000","junction.13805-dn","junction.11142-up","usgs.03488000","usgs.12113347","junction.13981-up","junction.12762-up","usgs.0214627970","usgs.01396800","usgs.05532000" … "reservoir.1656","usgs.02374950","usgs.02110701","reservoir.2121","usgs.14313200","usgs.06312500","usgs.07329500","usgs.13118700","junction.9255-up","junction.18031-up"],:reservoirs=>Any[1,2,3,4,5,6,7,8,9,10 … 2662,2663,2664,2665,2666,2667,2668,2669,2670,2671]),DataStructures.OrderedDict{Symbol,Mimi.ComponentState}(:Thermoelectric=>ComponentState,:Livestock=>ComponentState,:Agriculture=>ComponentState,:WaterDemand=>ComponentState,:Allocation=>ComponentState,:ReturnFlows=>ComponentState,:Aquifer=>ComponentState,:Reservoir=>ComponentState,:WaterNetwork=>ComponentState,:Transportation=>ComponentState,:Market=>ComponentState,:IndustrialDemand=>ComponentState,:UrbanDemand=>ComponentState),Set(UTF8String["WaterDemandurbanuse","Allocationwithdrawals","Marketproduced","Allocationreturns","Agriculturedeficit_coeff","Reservoirinflows","Thermoelectricdemand","Reservoirstoragecapacitymin","Allocationcostfromsw","Aquiferwithdrawal" … "Marketregionexports","Marketdomestic_prices","Marketinternationalsales","Allocationcostfromsupersource","UrbanDemanddomesticdemand","UrbanDemandcommercialdemand","Transportationcost_edge","IndustrialDemandminingwaterdemand","Agriculturewater_demand","WaterDemandtotalirrigation"]),Dict{Symbol,Mimi.Parameter}(:miningwaterdemand=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
14.9833
24.2
21.8917
41.4833
13.825
6.91667
0.0
11.525
0.0
1.15
1.15
0.0
40.3333
⋮
106.008
155.558
0.0
69.1333
13.825
11.525
73.7417
3456.83
18.4333
21.8917
40.3333
2.30833),:recharge=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
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⋮
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0.0
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0.0),:totalirrigation=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
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0.0),:storagecapacitymin=>Mimi.CertainArrayParameter([2.89841e5,3.6248e5,270009.0,2.85321e5,2.50727e5,3.33652e5,267298.0,1.87476e5,2.40842e5,3.75036e5 … 3.97346e5,3.45333e5,3.19302e5,2.93403e5,3.70769e5,289336.0,3.06562e5,2.64949e5,2.75896e5,3.08412e5]),:costfromsupersource=>Mimi.CertainScalarParameter(Set(Tuple{Mimi.ComponentState,Symbol}[(ComponentState,:costfromsupersource)]),100000.0),:water_demand=>Mimi.CertainArrayParameter([1639.61100235402,1639.61100235402,1180.60761343329,1180.60761343329,1475.96435526564,1136.4914374721,1375.99595071683,684.8361981980679,684.8361981980679]),:captures=>Mimi.CertainArrayParameter(2671x1 Array{Float64,2}:
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[:, :, 1] =
-Inf 1.47016 -Inf … -Inf 3.54694 3.75659 3.75514
-Inf 1.02648 -Inf -Inf 3.42608 3.94333 3.96342
-Inf 1.75034 -Inf -Inf 3.48831 3.67414 3.6796
-Inf 1.35474 -Inf -Inf 3.68896 3.77739 3.65787
-Inf 1.39667 -Inf -Inf 3.79821 3.97719 3.91855
-Inf 1.19478 -Inf … -Inf 3.35167 3.47313 3.49492
-Inf 1.47722 -Inf -Inf 3.39444 3.7782 3.7951
-Inf 1.53143 -Inf -Inf 3.92056 3.86605 3.87627
-Inf 1.41439 -Inf -Inf 3.86157 3.69799 3.71521
-Inf 1.61479 -Inf -Inf 3.66669 4.00187 4.02072
-Inf 1.592 -Inf … -Inf 3.75209 3.59136 3.55933
-Inf 1.5386 -Inf -Inf 3.77276 2.85038 3.46366
-Inf 1.78499 -Inf -Inf 3.55267 3.52832 3.49007
⋮ ⋱ ⋮
0.56746 0.601507 4.60517 -Inf -Inf 3.76226 3.76145
1.78777 1.437 4.60517 -Inf -Inf 3.64008 3.55029
1.11985 0.965542 4.60517 -Inf -Inf 3.61226 3.59651
0.962604 0.925874 4.60517 … -Inf -Inf 4.60517 4.60517
0.589563 0.740624 4.60517 -Inf -Inf 3.24757 3.27579
1.08221 1.06437 4.60517 -Inf -Inf 3.74349 3.66942
0.424393 0.392971 4.44058 -Inf -Inf 4.60517 4.60517
1.15407 1.16426 4.54875 -Inf -Inf 3.897 3.91378
1.08786 1.12384 4.60517 … -Inf -Inf 4.03777 4.05705
1.30867 1.31792 4.60517 -Inf -Inf 4.60517 4.60517
0.804506 0.792592 4.60517 -Inf -Inf 4.60517 4.60517
1.15341 0.853673 4.56516 -Inf -Inf 3.70406 3.64238),:aquiferconnexion=>Mimi.CertainArrayParameter(3109x3109 Array{Float64,2}:
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⋮ ⋮ ⋱ ⋮
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⋮ ⋮
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4.71299e5
3.645e5
4.53611e5
3.70879e5
615606.0
3.83809e5
6.03757e5
4.19201e5
⋮
5.27611e5
5.53504e5
5.29533e5
4.77487e5
4.35853e5
5.15744e5
5.26343e5
5.69011e5
5.35517e5
4.69453e5
4.69227e5
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0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 100.32 0.0 0.0 … 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
168.075 0.0 0.0 44.3985 0.0 … 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 620.866 0.0 0.0 0.0 0.0 0.0 0.0
⋮ ⋱
0.0 0.0 0.0 0.0 0.0 1.20653 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.382317 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.61164
0.0 0.0 0.0 0.0 0.0 … 0.0 0.167123 0.0
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0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ),:returns=>Mimi.CertainArrayParameter(21598x1 Array{Float64,2}:
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0.0232489 0.0232489 1.30763 … 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 … 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 … 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
⋮ ⋱ ⋮
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 … 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 … 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373
0.0232489 0.0232489 1.30763 2.22123 4.75618 2.58375 2.33373),:rainfedareas=>Mimi.CertainArrayParameter(3109x9x1 Array{Float64,3}:
[:, :, 1] =
0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 2643.0 0.0 0.0 … 0.0 466.198 0.0 416.827
0.0 3457.23 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 945.751 0.0 269.116
57.0607 3188.52 0.0 0.0 0.0 0.0 0.0 82.1513
10.1172 0.0 0.0 0.0 0.0 0.0 0.0 2437.42
0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0
0.0 1381.6 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
⋮ ⋱ ⋮
5406.6 2505.01 1139.19 0.0 0.0 0.0 0.0 0.0
808.967 802.088 0.0 0.0 0.0 0.0 0.0 0.0
1256.95 1150.52 0.0 0.0 0.0 0.0 0.0 0.0
719.127 927.136 259.404 0.0 … 0.0 0.0 0.0 0.0
2242.77 629.691 0.0 0.0 0.0 0.0 0.0 0.0
3867.58 3337.04 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1813.8 751.097 0.404686 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
362.194 40.8733 0.0 0.0 0.0 0.0 0.0 0.0
4755.06 1879.77 0.0 0.0 0.0 0.0 242.812 54.6326),:piezohead0=>Mimi.CertainArrayParameter([70.8958,70.8958,70.8958,70.8958,70.8958,70.8958,70.8958,70.8958,70.8958,70.8958 … 32.9918,70.8958,34.439,70.8958,70.8958,70.8958,70.8958,70.8958,70.8958,70.8958]),:commercialdemand=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
⋮
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0),:storagecoef=>Mimi.CertainArrayParameter([0.1,0.1,0.1,0.1,0.1,0.1,0.1,0.1,0.1,0.1 … 0.0691382,0.1,0.0755149,0.1,0.1,0.1,0.1,0.1,0.1,0.1]),:elevation=>Mimi.CertainArrayParameter([88.45,47.275,67.1,68.32,265.35,138.775,135.725,172.325,227.225,179.645 … 1525.0,1521.95,1414.59,1209.02,2188.38,2056.01,2073.39,2067.9,1238.61,1300.83]),:costfromsw=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
369.029
397.678
339.772
304.793
321.66
314.176
365.389
329.508
320.018
442.321
323.793
347.46
402.148
⋮
382.491
380.3
358.034
362.527
332.95
385.696
352.881
375.002
380.702
317.539
333.935
327.78 ),:waterfromsupersource=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
⋮
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0),:added=>Mimi.CertainArrayParameter(22619x1 Array{Float64,2}:
967.02
1471.54
1344.33
521.162
2025.89
1004.45
1121.29
49.0551
27.9891
320.511
10.1662
53.7024
33.6556
⋮
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
996.933
699.246 ),:watertotaldemand=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
⋮
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0),:irrigatedareas=>Mimi.CertainArrayParameter(3109x9x1 Array{Float64,3}:
[:, :, 1] =
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 2.42812 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
⋮ ⋮
12397.6 9522.67 1719.11 0.0 0.0 0.0 0.0 0.0 0.0
7449.86 1470.63 0.0 0.0 0.0 0.0 0.0 0.0 0.0
4042.41 896.784 0.0 0.0 276.401 0.0 0.0 0.0 0.0
12138.6 2594.85 7043.96 0.0 1384.43 0.0 0.0 0.0 0.0
9184.75 5955.36 0.0 0.0 0.0 0.0 0.0 0.0 0.0
10785.3 4031.89 16.9968 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
5413.08 3397.74 91.459 0.0 0.0 0.0 0.0 0.0 0.0
777.402 1589.61 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
4744.94 607.029 4113.23 0.0 422.492 0.0 0.0 127.476 0.0
1403.86 185.346 0.0 0.0 0.0 0.0 0.0 0.0 0.0),:industrywaterdemand=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
4727.79
0.0
182.058
0.0
0.0
0.0
34.5667
111.767
0.0
0.0
40.3333
4696.68
2329.9
⋮
5.75833
27.6583
0.0
146.342
8.06667
8.06667
0.0
298.442
5.75833
18.4333
4.60833
23.0417 ),:returned=>Mimi.CertainArrayParameter(22559x1 Array{Float64,2}:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
⋮
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0),:precipitation=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
1655.23
2100.44
1568.05
1932.65
1503.72
1687.27
1815.19
1629.58
1786.33
1614.56
1822.31
1535.13
1656.98
⋮
438.065
366.45
445.993
557.524
491.249
462.057
406.124
234.964
848.404
374.395
296.851
398.779),:livestockuse=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
⋮
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0),:regionimports=>Mimi.CertainArrayParameter(3109x9x1 Array{Float64,3}:
[:, :, 1] =
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
⋮ ⋮
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0),:deltatime=>Mimi.CertainScalarParameter(Set(Tuple{Mimi.ComponentState,Symbol}[(ComponentState,:deltatime)]),12.0),:domesticuse=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
⋮
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0),:imported=>Mimi.CertainArrayParameter(18561x9x1 Array{Float64,3}:
[:, :, 1] =
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
⋮ ⋮
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0),:costfromgw=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
⋮
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0),:areaaquif=>Mimi.CertainArrayParameter([1.56537e8,5.25073e8,2.34271e8,1.62178e8,1.68513e8,1.61911e8,2.01471e8,1.58583e8,1.56205e8,1.55395e8 … 6.80642e8,1.80456e9,5.46713e8,6.54514e8,1.27835e9,2.71719e9,1.09203e9,5.40681e8,5.80859e8,6.21605e8]),:domesticdemand=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
586.508
2646.78
478.192
563.467
445.967
265.025
311.117
2684.8
496.633
402.142
563.467
156.708
362.967
⋮
447.083
1252.52
76.05
364.117
142.883
551.942
262.717
1139.6
600.333
498.933
177.45
191.275),:demand=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
17.2833
40.3333
43.7833
8.06667
112.925
16.1333
46.0917
36.875
20.7417
32.2667
20.7417
10.3667
9.21667
⋮
59.9167
80.6583
66.8333
82.9667
141.733
97.9417
72.5917
28.8083
10.3667
66.8333
55.3083
61.0667 ),:industrialuse=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
⋮
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0),:depthaquif=>Mimi.CertainArrayParameter([50.0,50.0,50.0,50.0,50.0,50.0,50.0,50.0,50.0,50.0 … 65.9836,50.0,68.8779,50.0,50.0,50.0,50.0,50.0,50.0,50.0]),:internationalsales=>Mimi.CertainArrayParameter(3109x9x1 Array{Float64,3}:
[:, :, 1] =
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
⋮ ⋮
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0),:regionexports=>Mimi.CertainArrayParameter(3109x9x1 Array{Float64,3}:
[:, :, 1] =
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
⋮ ⋮
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0),:removed=>Mimi.CertainArrayParameter(22559x1 Array{Float64,2}:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
⋮
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0),:waterfromreservoir=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
43113.5
0.0
83.0
0.0
72137.1
27.7
0.0
3456.8
5959.6
1327.4
2530.4
56360.1
29203.3
⋮
1244.4
5116.1
0.0
4770.4
69.2
6678.6
1839.0
14338.9
235.1
5531.0
69.1
138.3),:urbanuse=>Mimi.CertainArrayParameter(3109x1 Array{Float64,2}:
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
⋮
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0),:domestic_prices=>Mimi.CertainArrayParameter(3109x9 Array{Float64,2}:
0.0464978 0.0464978 2.61525 2.61525 … 4.44246 9.51236 5.1675 4.66746
0.0464978 0.0464978 2.61525 2.61525 4.44246 9.51236 5.1675 4.66746
0.0464978 0.0464978 2.61525 2.61525 4.44246 9.51236 5.1675 4.66746
0.0464978 0.0464978 2.61525 2.61525 4.44246 9.51236 5.1675 4.66746
0.0464978 0.0464978 2.61525 2.61525 4.44246 9.51236 5.1675 4.66746
0.0464978 0.0464978 2.61525 2.61525 … 4.44246 9.51236 5.1675 4.66746
0.0464978 0.0464978 2.61525 2.61525 4.44246 9.51236 5.1675 4.66746
0.0464978 0.0464978 2.61525 2.61525 4.44246 9.51236 5.1675 4.66746
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0.0464978 0.0464978 2.61525 2.61525 4.44246 9.51236 5.1675 4.66746
⋮ ⋱ ⋮
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In [ ]:
Now let's consider optimization. Like agriculture, aquaculture production can go into the producer-viewed objective function.
Content source: AmericasWater/awash
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