SSN1.initialize(q=q, s_p=s_p, s_t=s_t, s_s=s_s)
dc_nodam = SSN1.Run_254(
[0, te],
forcing,
rtol=1e-6,
)
#Passive Scenario
print('Running passive case..')
SSN2 = Watershed(Model=256)
SSN2.init_custom(links=l_id,
connectivity=connectivity,
A_i=A_i,
L_i=L_i,
A_h=A_h)
SSN2.dam_ids = dams
dam_params256 = SSN2.init_dam_params256(H_spill, H_max, S_max, _alpha,
diam, c1, c2, L_spill, L_crest)
q, s_p, s_t, s_s = Set_InitialConditions(0.5, A_i[0], A_i)
S = [100000 for _ in range(n_dams)]
SSN2.set_dam_state(states=[1 for _ in range(n_dams)])
SSN2.initialize(q=q, S=S, s_t=s_t, s_p=s_p, s_s=s_s)
dc_passive, st_passive = SSN2.Run_256([0, te], forcing, dam_params256)
#Active Control with GA
print('Running active control case')
# watershed object initialization
SSN5 = Watershed(Model=256)
SSN5.init_custom(links=l_id,
connectivity=connectivity,
A_i=A_i,
rate10 = [
12, 30, 63, 75, 84, 87, 90, 93.5, 95, 96.01, 97.44, 97.44, 99.42,
99.42, 99.67, 100
]
print(f'Simulations started at {datetime.datetime.now().time()}')
## SCENARIO-4 #############################################################################
SSN5 = Watershed(Model=256)
SSN5.init_custom(links=l_id,
connectivity=connectivity,
A_i=A_i,
L_i=L_i,
A_h=A_h)
SSN5.dam_ids = dams4
H_spill, H_max, S_max, _alpha, diam, c1, c2, L_spill, L_crest = PrepareDamParams(
dams4)
diam = [1.25 for _ in range(len(dams2))] + diam[4:]
dam_params256 = SSN5.init_dam_params256(H_spill, H_max, S_max, _alpha,
diam, c1, c2, L_spill, L_crest)
dc_passive_Peak_S4 = pd.DataFrame(columns=SSN5.__columns__()[0])
out_passive_Peak_S4 = pd.DataFrame(columns=SSN5.__columns__()[1])
for dstorm in dstorms:
forcing, cum_forcing, forcing_hour = Generate_SyntheticStorm(
dstorm,
24,
rate=(0.01 * np.diff(rate10, prepend=0)).tolist(),
timescale=30)
rtol=1e-6,
)
dc_nodam.to_csv(
f'/Users/gurbuz/Supp_DamStudy/final_ActiveControl/dc_nodam_{save_ext}.csv'
)
print(f'Done nodam in {time.time()-start}')
###################################################################################################
start = time.time()
print('Running Passive..')
SSN5 = Watershed(Model=256)
SSN5.init_custom(links=l_id,
connectivity=connectivity,
A_i=A_i,
L_i=L_i,
A_h=A_h)
SSN5.dam_ids = dams5
H_spill, H_max, S_max, _alpha, diam, c1, c2, L_spill, L_crest = PrepareDamParams(
dams5)
dam_params256 = SSN5.init_dam_params256(H_spill, H_max, S_max, _alpha,
diam, c1, c2, L_spill, L_crest)
q = initial_condition['q']
s_p = initial_condition['s_p']
s_t = initial_condition['s_t']
s_s = initial_condition['s_s']
fill_percent = np.repeat([0.0001], n_dams5)
S = (S_max * fill_percent).tolist()
SSN5.set_dam_state(states=[1 for _ in range(n_dams5)])
SSN5.initialize(q=q, S=S, s_t=s_t, s_p=s_p, s_s=s_s)
dc_passive_S5, st_passive_S5 = SSN5.Run_256([0, te], forcing,
dam_params256)
out_passive_S5 = SSN5.CalculateOutflow(dam_params256, st_passive_S5)
# pass
# print(f'(NODAM)Storm:{dstorm} is simulated with given initial conditions!')
# dc_nodam_Peak.to_csv('/Users/gurbuz/Supp_DamStudy/Dam_Configuration/dc_nodam_Peak_rand08.csv')
# print('No dam scenario is done and results are saved!\n')
# print(f'Time: {datetime.datetime.now().time()}')
## SCENARIO-1 #############################################################################
SSN2 = Watershed(Model=256)
SSN2.init_custom(links=l_id,
connectivity=connectivity,
A_i=A_i,
L_i=L_i,
A_h=A_h)
SSN2.dam_ids = dams1
H_spill, H_max, S_max, _alpha, diam, c1, c2, L_spill, L_crest = PrepareDamParams(
dams1)
dam_params256 = SSN2.init_dam_params256(H_spill, H_max, S_max, _alpha,
diam, c1, c2, L_spill, L_crest)
dc_passive_Peak_S1 = pd.DataFrame(columns=SSN2.__columns__()[0])
out_passive_Peak_S1 = pd.DataFrame(columns=SSN2.__columns__()[1])
for dstorm in dstorms:
forcing, cum_forcing, forcing_hour = Generate_SyntheticStorm(
dstorm,
24,
rate=(0.01 * np.diff(rate10, prepend=0)).tolist(),
timescale=30)
te = len(forcing) - 1