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franklin1895franklin1895
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Merge remote-tracking branch 'origin/benton-cascade' into benton-cascade
2 parents 8086e7f + e21f196 commit 1074aae

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‎scripts/marsh_ms/Alter_Elevations.py‎

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‎scripts/marsh_ms/Plot_Test_Marsh_Accretion.py‎

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import copy
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import matplotlib.pyplot as plt
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import numpy as np
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import os
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import copy
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import pandas as pd
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os.chdir("E:\\Chapter 2\\")
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#save_path = 'C:\\Users\\frank\\OneDrive - University of North Carolina at Chapel Hill\\Chapter 2\\Cascade_CSV_Outputs\\Hindcasts\\'
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Base_Name_List = ['Geom_1',
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'Geom_3',
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'Geom_4',
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'Geom_5']
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Base_Name = Base_Name_List[0]
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if Base_Name == 'Geom_1':
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Cascade_Offset = 90
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if Base_Name == 'Geom_3':
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Cascade_Offset = 490
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if Base_Name == 'Geom_4':
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Cascade_Offset = 170
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if Base_Name == 'Geom_5':
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Cascade_Offset = 160
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run_name = 'Geom_1_IH_10_S1.npz' #'Geom_4_IL_10_S49_New_Sink.npz'
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#for geos in range(len(Base_Name_List)):
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# temp_run_name = copy.deepcopy(Base_Name_List[geos]+'_Calibrated_Hindcast_2.npz')
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# run_name.append(copy.deepcopy(temp_run_name))
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output = np.load(run_name, allow_pickle=True)
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cascade = output["cascade"]
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cascade = cascade[0]
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bmft = cascade._bmft_coupler
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bmftc = bmft._bmftc[0]
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O_flux = bmftc.fluxes
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Forest_e = bmftc.Forest_edge
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Marsh_e = bmftc.Marsh_edge
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initial_C = bmftc._marshOM_initial # kg's C accross entire platfrom
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initial_marsh_C_g = initial_C*1000
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# Create initial C layer
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Initial_Marsh_Width = Forest_e[49] - Marsh_e[49]
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Per_m_Marsh_C_g = initial_marsh_C_g/Initial_Marsh_Width
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Initial_Transect_C_Value = np.zeros(len(bmftc.elevation[0]))
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# Add initial C to marsh cells
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Initial_Transect_C_Value[int(Marsh_e[49]):int(Forest_e[49])] = Per_m_Marsh_C_g
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Total_C_Deposited_TS = [Initial_Transect_C_Value]
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#Bmftc._BayOM[yr]
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Shoreline_location_TS = cascade.brie.x_s_save
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All_Reletive_Shoreline = ((-Shoreline_location_TS+1624+90)+Forest_e[49])[0]
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# Start Year = [50]
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Start_Year = 49
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End_Year = Start_Year+125
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C_autoch = bmftc._organic_dep_autoch# Subtract eroded mass from depositional record
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C_alloch = bmftc._organic_dep_alloch
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Total_Annual_C_Change = np.sum((C_alloch,C_autoch),axis=0)
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for years in range(Start_Year,End_Year):
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temp_sum = np.sum(Total_Annual_C_Change[Start_Year:years],axis=0)
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marsh_accumulation = temp_sum[int(Marsh_e[years]):]
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temp_total_marsh_C_Change = np.zeros(len(temp_sum))
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temp_total_marsh_C_Change[int(Marsh_e[years]):] = marsh_accumulation
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new_C_deposition_plus_C0 = np.sum((temp_total_marsh_C_Change,Initial_Transect_C_Value),axis=0)
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new_C_deposition_plus_C0[new_C_deposition_plus_C0 < 0] = 0
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Total_C_Deposited_TS.append(copy.deepcopy(new_C_deposition_plus_C0))
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plt.plot(Total_C_Deposited_TS[0][0:])
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#plt.plot(Total_C_Deposited_TS[10][0:])
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plt.plot(Total_C_Deposited_TS[24][0:],alpha=0.8)
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#plt.plot(Total_C_Deposited_TS[30][0:])
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plt.plot(Total_C_Deposited_TS[49][0:], alpha=0.8)
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plt.plot(Total_C_Deposited_TS[74][0:], alpha=0.8)
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plt.plot(Total_C_Deposited_TS[99][0:], alpha=0.8)
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plt.plot(Total_C_Deposited_TS[124][0:],alpha=0.8)
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# plt.axvline(x=All_Reletive_Shoreline[0])
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# plt.axvline(x=Marsh_e[49])
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# #plt.axvline(x=All_Reletive_Shoreline[24])
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# plt.axvline(x=Marsh_e[74])
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# #plt.axvline(x=All_Reletive_Shoreline[49])
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# plt.axvline(x=Marsh_e[99])
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# plt.axvline(x=All_Reletive_Shoreline[74])
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# #plt.axvline(x=Marsh_e[124])
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# plt.axvline(x=All_Reletive_Shoreline[99])
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# #plt.axvline(x=Marsh_e[144],color = 'grey')
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# plt.axvline(x=All_Reletive_Shoreline[124])
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# #plt.axvline(x=Marsh_e[172],color='black')
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plt.xlim(4500,7500)
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#plt.ylim(0,3000)
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plt.show()
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plt.plot(Total_Annual_C_Change[25][0:])
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plt.plot(Total_Annual_C_Change[50][0:])
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plt.plot(Total_Annual_C_Change[75][0:])
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plt.plot(Total_Annual_C_Change[100][0:])
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plt.plot(Total_Annual_C_Change[124][0:])
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plt.xlim(4000,7000)
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plt.ylim(0,3000)
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plt.show()
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plt.plot(bmftc.elevation[50])
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plt.plot(bmftc.elevation[55])
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plt.plot(bmftc.elevation[60])
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plt.plot(bmftc.elevation[70])
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plt.plot(bmftc.elevation[80])
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plt.show()
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elev = bmftc.elevation
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plt.plot(elev[50][4500:])
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plt.axvline(x=Forest_e[50]-4500,linestyle ='dashed',color='blue')
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plt.axvline(x=Marsh_e[50]-4500,linestyle ='dashed', color='blue')
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#plt.show()
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plt.plot(elev[70][4500:],color = 'orange')
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plt.axvline(x=Forest_e[70]-4500,linestyle ='dashed',color='orange')
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plt.axvline(x=Marsh_e[70]-4500,linestyle ='dashed', color='orange')
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#plt.show()
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plt.plot(elev[90][4500:],color = 'red')
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plt.axvline(x=Forest_e[90]-4500,linestyle ='dashed',color='red')
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plt.axvline(x=Marsh_e[90]-4500,linestyle ='dashed', color='red')
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#plt.show()
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plt.plot(elev[110][4500:],color = 'green')
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plt.axvline(x=Forest_e[110]-4500,linestyle ='dashed',color='green')
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plt.axvline(x=Marsh_e[110]-4500,linestyle ='dashed', color='green')
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plt.plot(elev[130][4500:],color = 'black')
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plt.axvline(x=Forest_e[130]-4500,linestyle ='dashed',color='black')
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plt.axvline(x=Marsh_e[130]-4500,linestyle ='dashed', color='black')
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#plt.show()
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plt.plot(elev[150][4500:],color = 'grey')
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plt.axvline(x=Forest_e[150]-4500,linestyle ='dashed',color='grey')
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plt.axvline(x=Marsh_e[150]-4500,linestyle ='dashed', color='grey')
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plt.show()
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plt.plot(elev[51][4500:])
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plt.plot(elev[101][4500:])
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plt.plot(elev[151][4500:])
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plt.show()
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b3d = cascade._barrier3d[0]
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z = 20

‎scripts/marsh_ms/Process_Batches.py‎

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import copy
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import matplotlib.pyplot as plt
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import numpy as np
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import os
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import copy
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import pandas as pd
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os.chdir("E:\\Chapter 2\\")
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Base_Save_Path = 'C:\\Users\\frank\\OneDrive - University of North Carolina at Chapel Hill\\Chapter 2\\Updated_Marsh_Accretion_C_Release\\'
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#save_path = 'C:\\Users\\frank\\OneDrive - University of North Carolina at Chapel Hill\\Chapter 2\\Cascade_CSV_Outputs\\Hindcasts\\'
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#run_name = 'Geom_1_IL_Baseline_S20.npz' #'Geom_4_IL_10_S49_New_Sink.npz'
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#for geos in range(len(Base_Name_List)):
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# temp_run_name = copy.deepcopy(Base_Name_List[geos]+'_Calibrated_Hindcast_2.npz')
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# run_name.append(copy.deepcopy(temp_run_name))
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Storm_List = ['Baseline',
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'5',
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'10']
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RSLR = ['IL',
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'I',#,
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'IH']
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Base_Name_List = ['Geom_1',
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'Geom_3',
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'Geom_4',
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'Geom_5']
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#Base_Name_List = ['Geom_1']
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for Geometries in range(len(Base_Name_List)):
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Base_Name = Base_Name_List[Geometries]
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if Base_Name == 'Geom_1':
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Cascade_Offset = 110
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if Base_Name == 'Geom_3':
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Cascade_Offset = 490
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if Base_Name == 'Geom_4':
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Cascade_Offset = 170
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if Base_Name == 'Geom_5':
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Cascade_Offset = 160
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for RSLR_Rates in range(len(RSLR)):
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for Storm_Mean_Intensities in range(len(Storm_List)):
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Save_Name = Base_Name+'_'+RSLR[RSLR_Rates]+'_'+Storm_List[Storm_Mean_Intensities]
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All_Runs_Shoreline_Location = []
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All_C_Values = []
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for S_Nums in range(0,50):
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# Load a specific Model Run
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if Base_Name == 'Geom_4':
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Load_Name = Base_Name+'_'+RSLR[RSLR_Rates]+'_'+Storm_List[Storm_Mean_Intensities]+'_S'+str(S_Nums)+'_New_Sink.npz'
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else:
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Load_Name = Base_Name+'_'+RSLR[RSLR_Rates]+'_'+Storm_List[Storm_Mean_Intensities]+'_S'+str(S_Nums)+'.npz'
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output = np.load(Load_Name, allow_pickle=True)
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cascade = output["cascade"]
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cascade = cascade[0]
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bmft = cascade._bmft_coupler
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bmftc = bmft._bmftc[0]
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O_flux = bmftc.fluxes
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Forest_e = bmftc.Forest_edge
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Marsh_e = bmftc.Marsh_edge
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initial_C = bmftc._marshOM_initial # kg's C accross entire platfrom
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initial_marsh_C_g = initial_C*1000
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# Create initial C layer
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Initial_Marsh_Width = Forest_e[49] - Marsh_e[49]
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Per_m_Marsh_C_g = initial_marsh_C_g/Initial_Marsh_Width
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Initial_Transect_C_Value = np.zeros(len(bmftc.elevation[0]))
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# Add initial C to marsh cells
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Initial_Transect_C_Value[int(Marsh_e[49]):int(Forest_e[49])] = Per_m_Marsh_C_g
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Total_C_Deposited_TS = [Initial_Transect_C_Value]
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#Bmftc._BayOM[yr]
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Shoreline_location_TS = cascade.brie.x_s_save
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All_Reletive_Shoreline = ((-Shoreline_location_TS+1624+Cascade_Offset)+Forest_e[49])[0]
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# Start Year = [50]
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Start_Year = 50
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End_Year = Start_Year+125
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C_autoch = bmftc._organic_dep_autoch# Subtract eroded mass from depositional record
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C_alloch = bmftc._organic_dep_alloch
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Total_Annual_C_Change = np.sum((C_alloch,C_autoch),axis=0)
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for years in range(Start_Year,End_Year):
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# temp_sum = np.sum(Total_Annual_C_Change[Start_Year:years],axis=0)
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# marsh_accumulation = temp_sum[int(Marsh_e[years]):int(Forest_e[years])]
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# new_C_deposition_plus_C0 = np.sum((temp_sum,Initial_Transect_C_Value),axis=0)
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# new_C_deposition_plus_C0[new_C_deposition_plus_C0 < 0] = 0
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# Total_C_Deposited_TS.append(copy.deepcopy(new_C_deposition_plus_C0))
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temp_sum = np.sum(Total_Annual_C_Change[Start_Year:years], axis=0)
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marsh_accumulation = temp_sum[int(Marsh_e[years]):]
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temp_total_marsh_C_Change = np.zeros(len(temp_sum))
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temp_total_marsh_C_Change[int(Marsh_e[years]):] = marsh_accumulation
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new_C_deposition_plus_C0 = np.sum((temp_total_marsh_C_Change, Initial_Transect_C_Value), axis=0)
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new_C_deposition_plus_C0[new_C_deposition_plus_C0 < 0] = 0
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Total_C_Deposited_TS.append(copy.deepcopy(new_C_deposition_plus_C0))
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All_Runs_Shoreline_Location.append(copy.deepcopy(All_Reletive_Shoreline))
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All_C_Values.append(copy.deepcopy(Total_C_Deposited_TS))
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print(Save_Name+'_S'+str(S_Nums)+' loaded')
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Mean_Shoreline_Location = np.nanmean(All_Runs_Shoreline_Location, axis=0)
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Mean_C_Values = np.nanmean(All_C_Values, axis=0)
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Full_Save_Path = Base_Save_Path+Save_Name
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# Save each of the arrays including mean and full values
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np.save(Full_Save_Path+'_Mean_C_Added_Marsh.npy',Mean_C_Values)
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np.save(Full_Save_Path+'_Mean_Shoreline_Location_Marsh.npy',Mean_Shoreline_Location)
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np.save(Full_Save_Path+'_All_Shoreline_Location_Marsh.npy',All_Runs_Shoreline_Location)
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np.save(Full_Save_Path+'_All_C_Added_Marsh.npy',All_C_Values)
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x = 20

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