Modification of configuration options via custom configuration files and on-the-fly
This notebook demonstrates how to:
Read a custom configuration file from a user’s file-system to update model parameters
Update selected config variables after loading the configuration file
Run step-by-step manual calculations with different model parameterizations
Run calculations for batches of reservoirs with custom configurations
< Saving Results To LaTeX | Contents | Parametric Uncertainty >
[8]:
from dataclasses import dataclass
from os.path import exists
import pathlib
import gdown
from typing import List, Dict, Tuple, Any, NamedTuple
from rich import print as rprint
try:
import reemission
except ImportError:
print("Unable to import reemission. Please ensure it is installed.")
%pip install git+https://github.com/tomjanus/reemission.git --quiet
DEV_MODE = False
if DEV_MODE:
import importlib
importlib.reload(reemission)
# Import from the temperature module
from reemission.temperature import MonthlyTemperature
# Import from the emissions module
from reemission.emissions import CarbonDioxideEmission, MethaneEmission
# Import from the constants module
from reemission.constants import Climate, SoilType, Biome, TreatmentFactor, LanduseIntensity
# Import from the catchment module
from reemission.catchment import Catchment
# Import from the reservoir module
from reemission.reservoir import Reservoir
# Import from the biogenic module
from reemission.biogenic import BiogenicFactors
# Import function for resetting configuration to default settings
from reemission.config_registration import reset_all as reset_all_configs
from reemission.registry import config
# Import from the model module
from reemission.model import EmissionModel
# Import from the input module
from reemission.input import Inputs
# Helper class to encapsulate inputs for running emissions calculation with different input values
@dataclass
class ReemissionInputs:
mt: MonthlyTemperature
coordinates: List[float]
catchment_inputs: Dict[str, Any]
reservoir_inputs: Dict[str, Any]
year_profile: Tuple[int | float, ...]
# Helper class to encapsulate the results of emissions calculations
class EmissionResults(NamedTuple):
net_co2: float
net_ch4: float
net_total: float
def __str__(self):
return (
f"Net areal CO2 emissions: {self.net_co2:.2f} g CO2e m-2 yr-1\n"
f"Net areal CH4 emissions: {self.net_ch4:.2f} g CO2e m-2 yr-1\n"
f"Net areal total emissions: {self.net_total:.2f} g CO2e m-2 yr-1"
)
__repr__ = __str__
1. Define inputs for the step-by-step emissions calculations
see 01-Step-By-Step-Manual-Calculations.ipynb for more details
[ ]:
# Define inputs (see 01-Step-By-Step-Manual-Calculations.ipynb for more details)
mt = MonthlyTemperature([10.56,11.99,15.46,18.29,20.79,22.09,22.46,22.66,21.93,19.33,15.03,11.66])
coordinates = [22.6, 94.7]
biogenic_factors = BiogenicFactors(
biome = Biome.TROPICALMOISTBROADLEAF,
climate = Climate.TROPICAL,
soil_type=SoilType.MINERAL,
treatment_factor = TreatmentFactor.NONE,
landuse_intensity = LanduseIntensity.LOW)
catchment_area_fractions = [
0.0, 0.0, 0.0, 0.0, 0.0, 0.01092, 0.11996, 0.867257, 0.0]
reservoir_area_fractions = [
0.0, 0.0, 0.0, 0.0, 0.0, 0.45, 0.15, 0.4, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
catchment_inputs = {
'runoff': 1685.5619, 'area': 78203.0, 'population': 8463, 'riv_length': 9.2,
'area_fractions': catchment_area_fractions, 'slope': 8.0, 'precip': 2000.0,
'etransp': 400.0, 'soil_wetness': 140.0, 'mean_olsen': 5.85,
'biogenic_factors': biogenic_factors}
reservoir_inputs = {
'volume': 7663812, 'area': 100.56470, 'max_depth': 32.0, 'mean_depth': 13.6,
'area_fractions': reservoir_area_fractions, 'soil_carbon': 10.228,
'mean_radiance': 4.5, 'mean_radiance_may_sept': 4.5, 'mean_radiance_nov_mar': 3.2,
'mean_monthly_windspeed': 3.8, 'water_intake_depth': 20.0}
year_profile = (1, 5, 10, 20, 30, 40, 50, 65, 80, 100)
inputs = ReemissionInputs(
mt=mt,
coordinates=coordinates,
catchment_inputs=catchment_inputs,
reservoir_inputs=reservoir_inputs,
year_profile=year_profile
)
2. Define a function that goes through all steps of emission calculations and returns net areal CO2, CH4 emissions and total net aerial emissions
[ ]:
def calculate_emissions_step_by_step(
inputs: ReemissionInputs,
p_calc_method: str = 'g-res') -> EmissionResults:
""" """
# Initialize the catchment and reservoir objects with input data
catchment_1 = Catchment(**inputs.catchment_inputs)
rprint(catchment_1.biogenic_factors)
reservoir_1 = Reservoir(
**inputs.reservoir_inputs,
temperature = inputs.mt,
coordinates=inputs.coordinates,
inflow_rate=catchment_1.discharge)
# Calculate net areal CO2 an CH4 emissions
em_co2 = CarbonDioxideEmission(
catchment=catchment_1,
reservoir=reservoir_1,
eff_temp=inputs.mt.eff_temp(gas='co2'),
p_calc_method=p_calc_method)
em_ch4 = MethaneEmission(
catchment=catchment_1,
reservoir=reservoir_1,
monthly_temp=inputs.mt)
net_areal_co2 = em_co2.factor(
number_of_years = inputs.year_profile[-1])
net_areal_ch4 = em_ch4.factor()
net_areal_total = net_areal_co2 + net_areal_ch4
return EmissionResults(
net_co2=net_areal_co2,
net_ch4=net_areal_ch4,
net_total=net_areal_total
)
3. Source inputs and instantiate the EmissionModel object for batch emission calculations
[ ]:
if not exists(pathlib.Path('./inputs.json')):
# Download the required input file from an external link
!gdown 1T9Pal8h9Ce6phw1qdPM5AkuZM_hnvBGT
input_data = Inputs.fromfile('inputs.json')
model_batch = EmissionModel(inputs=input_data, p_model='g-res')
4. Modify individual configuration parameters in global config on-the-fly using config.update
[ ]:
# Calculate emissions with manually defined inputs and inputs sourced from inputs .json file
rprint("Calculating emissions with the default `k1_diff` value")
reset_all_configs() # Resets config to defaults
model_outputs_step_by_step = calculate_emissions_step_by_step(inputs, p_calc_method='g-res')
rprint(model_outputs_step_by_step)
model_batch.calculate()
outputs_batch = model_batch.outputs
rprint("")
rprint("Reservoir 1 CO2 net emissions: ", outputs_batch['Reservoir 1']['co2_net'])
rprint("Reservoir 1 CH4 net emissions: ", outputs_batch['Reservoir 1']['ch4_net'])
rprint("Reservoir 1 total net emissions: ", outputs_batch['Reservoir 1']['co2_net'] + outputs_batch['Reservoir 1']['ch4_net'])
# Recalculate emissions after modifying the value of k1_diff parameter for CO2 emission calculations
rprint("\nCalculating emissions with the modified `k1_diff` value")
config.update("model_config", {("CARBON_DIOXIDE",): {"k1_diff": 0.5}})
model_outputs_step_by_step = calculate_emissions_step_by_step(inputs, p_calc_method='g-res')
rprint(model_outputs_step_by_step)
model_batch.calculate()
outputs_batch = model_batch.outputs
rprint("")
rprint("Reservoir 1 CO2 net emissions: ", outputs_batch['Reservoir 1']['co2_net'])
rprint("Reservoir 1 CH4 net emissions: ", outputs_batch['Reservoir 1']['ch4_net'])
rprint("Reservoir 1 total net emissions: ", outputs_batch['Reservoir 1']['co2_net'] + outputs_batch['Reservoir 1']['ch4_net'])
5. Run the model with the updated k1_diff value by overriding config with custom_config.ini and config.override method
[ ]:
# Calculate emissions with manually defined inputs and inputs sourced from inputs .json file
rprint("Calculating emissions with the default 'model_config'")
reset_all_configs() # Resets config to defaults
model_outputs_step_by_step = calculate_emissions_step_by_step(inputs, p_calc_method='g-res')
rprint(model_outputs_step_by_step)
model_batch.calculate()
outputs_batch = model_batch.outputs
rprint("")
rprint("Reservoir 1 CO2 net emissions: ", outputs_batch['Reservoir 1']['co2_net'])
rprint("Reservoir 1 CH4 net emissions: ", outputs_batch['Reservoir 1']['ch4_net'])
rprint("Reservoir 1 total net emissions: ",
outputs_batch['Reservoir 1']['co2_net'] + outputs_batch['Reservoir 1']['ch4_net'])
# Recalculate emissions after modifying the value of k1_diff parameter for CO2 emission calculations
rprint("\nCalculating emissions with custom 'model_config' containing modified `k1_diff` value")
config.override("model_config", 'custom_config.ini')
model_outputs_step_by_step = calculate_emissions_step_by_step(inputs, p_calc_method='g-res')
rprint(model_outputs_step_by_step)
model_batch.calculate()
outputs_batch = model_batch.outputs
rprint("")
rprint("Reservoir 1 CO2 net emissions: ", outputs_batch['Reservoir 1']['co2_net'])
rprint("Reservoir 1 CH4 net emissions: ", outputs_batch['Reservoir 1']['ch4_net'])
rprint("Reservoir 1 total net emissions: ",
outputs_batch['Reservoir 1']['co2_net'] + outputs_batch['Reservoir 1']['ch4_net'])