Getter Reference: Climate, Rainfall, and Hydrology
Rendered from 11_all_get_functions.ipynb.
Climate and rainfall
climate
Kind: Model-level category
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.climate.areal_depletion_impervious(format=None) | user | float | sequence/list | Model-level scalar, sequence, mapping, or table depending on the declared type |
m.get.climate.areal_depletion_pervious(format=None) | user | float | sequence/list | Model-level scalar, sequence, mapping, or table depending on the declared type |
m.get.climate.evaporation_constant(format=None) | user | float | single | Model-level scalar, sequence, mapping, or table depending on the declared type |
m.get.climate.evaporation_dry_only(format=None) | user | bool | single | Model-level scalar, sequence, mapping, or table depending on the declared type |
m.get.climate.evaporation_monthly(format=None) | user | float | sequence/list | Model-level scalar, sequence, mapping, or table depending on the declared type |
m.get.climate.evaporation_recovery_pattern(format=None) | ref | str | single | Model-level scalar, sequence, mapping, or table depending on the declared type |
m.get.climate.evaporation_time_series(format=None) | ref | str | single | Model-level scalar, sequence, mapping, or table depending on the declared type |
m.get.climate.evaporation_type(format=None) | user | enum | single | Model-level scalar, sequence, mapping, or table depending on the declared type |
m.get.climate.snowmelt_parameters(format=None) | user | mixed | table | Model-level scalar, sequence, mapping, or table depending on the declared type |
m.get.climate.temperature_time_series(format=None) | ref | str/table | series/table | Model-level scalar, sequence, mapping, or table depending on the declared type |
m.get.climate.wind_speed_monthly(format=None) | user | float | sequence/list | Model-level scalar, sequence, mapping, or table depending on the declared type |
m.get.climate.wind_speed_type(format=None) | user | enum | single | Model-level scalar, sequence, mapping, or table depending on the declared type |
Copy-ready call list:
m.get.climate.areal_depletion_impervious(format=None)
m.get.climate.areal_depletion_pervious(format=None)
m.get.climate.evaporation_constant(format=None)
m.get.climate.evaporation_dry_only(format=None)
m.get.climate.evaporation_monthly(format=None)
m.get.climate.evaporation_recovery_pattern(format=None)
m.get.climate.evaporation_time_series(format=None)
m.get.climate.evaporation_type(format=None)
m.get.climate.snowmelt_parameters(format=None)
m.get.climate.temperature_time_series(format=None)
m.get.climate.wind_speed_monthly(format=None)
m.get.climate.wind_speed_type(format=None)climate_adjustment
Kind: Model-level category
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.climate_adjustment.conductivity(format=None) | user | float | sequence/list | Model-level scalar, sequence, mapping, or table depending on the declared type |
m.get.climate_adjustment.evaporation(format=None) | user | float | sequence/list | Model-level scalar, sequence, mapping, or table depending on the declared type |
m.get.climate_adjustment.rainfall(format=None) | user | float | sequence/list | Model-level scalar, sequence, mapping, or table depending on the declared type |
m.get.climate_adjustment.temperature(format=None) | user | float | sequence/list | Model-level scalar, sequence, mapping, or table depending on the declared type |
Copy-ready call list:
m.get.climate_adjustment.conductivity(format=None)
m.get.climate_adjustment.evaporation(format=None)
m.get.climate_adjustment.rainfall(format=None)
m.get.climate_adjustment.temperature(format=None)rain_gage
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.rain_gage.count(ids=None, format=None) | derived | integer | single | int scalar count |
m.get.rain_gage.filename(ids=None, format=None) | ref | path | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.rain_gage.format(ids=None, format=None) | user | enum | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.rain_gage.id(ids=None, format=None) | user | str | single | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.rain_gage.interval(ids=None, format=None) | user | time | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.rain_gage.rainfall(ids=None, format=None) | result | float | time series | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.rain_gage.snow_catch_factor(ids=None, format=None) | user | float | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.rain_gage.source_type(ids=None, format=None) | user | enum | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.rain_gage.station(ids=None, format=None) | user | str | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.rain_gage.time_series(ids=None, format=None) | ref | str | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.rain_gage.units(ids=None, format=None) | user | enum | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.rain_gage.count(ids=None, format=None)
m.get.rain_gage.filename(ids=None, format=None)
m.get.rain_gage.format(ids=None, format=None)
m.get.rain_gage.id(ids=None, format=None)
m.get.rain_gage.interval(ids=None, format=None)
m.get.rain_gage.rainfall(ids=None, format=None)
m.get.rain_gage.snow_catch_factor(ids=None, format=None)
m.get.rain_gage.source_type(ids=None, format=None)
m.get.rain_gage.station(ids=None, format=None)
m.get.rain_gage.time_series(ids=None, format=None)
m.get.rain_gage.units(ids=None, format=None)Hydrology and catchments
subcatchment
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.subcatchment.area(ids=None, format=None) | user | float | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.centroid(ids=None, format=None) | user/derived | coordinates | single/list | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.count(ids=None, format=None) | derived | integer | single | int scalar count |
m.get.subcatchment.curb_length(ids=None, format=None) | user | float | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.depression_storage_impervious(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.depression_storage_pervious(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.evaporation(ids=None, format=None) | result | float | time series | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.subcatchment.groundwater_elevation(ids=None, format=None) | result | float | time series | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.subcatchment.groundwater_flow(ids=None, format=None) | result | float | time series | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.subcatchment.id(ids=None, format=None) | user | str | single | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.impervious_percent(ids=None, format=None) | user | float | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.infiltration(ids=None, format=None) | result | float | time series | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.subcatchment.n_impervious(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.n_pervious(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.outlet(ids=None, format=None) | ref | str | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.percent_routed(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.pollutant_concentration(ids=None, format=None) | result | float | time series × pollutant | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.subcatchment.polygon(ids=None, format=None) | user | coordinates | sequence/list | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.rain_gage(ids=None, format=None) | ref | str | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.rainfall(ids=None, format=None) | result | float | time series | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.subcatchment.runoff(ids=None, format=None) | result | float | time series | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.subcatchment.slope(ids=None, format=None) | user | float | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.snow_depth(ids=None, format=None) | result | float | time series | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.subcatchment.snow_pack(ids=None, format=None) | ref | str | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.soil_moisture(ids=None, format=None) | result | float | time series | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.subcatchment.subarea_routing(ids=None, format=None) | user | enum | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.tag(ids=None, format=None) | user | str | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.width(ids=None, format=None) | user | float | single/series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.subcatchment.zero_depression_storage_impervious_percent(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.subcatchment.area(ids=None, format=None)
m.get.subcatchment.centroid(ids=None, format=None)
m.get.subcatchment.count(ids=None, format=None)
m.get.subcatchment.curb_length(ids=None, format=None)
m.get.subcatchment.depression_storage_impervious(ids=None, format=None)
m.get.subcatchment.depression_storage_pervious(ids=None, format=None)
m.get.subcatchment.evaporation(ids=None, format=None)
m.get.subcatchment.groundwater_elevation(ids=None, format=None)
m.get.subcatchment.groundwater_flow(ids=None, format=None)
m.get.subcatchment.id(ids=None, format=None)
m.get.subcatchment.impervious_percent(ids=None, format=None)
m.get.subcatchment.infiltration(ids=None, format=None)
m.get.subcatchment.n_impervious(ids=None, format=None)
m.get.subcatchment.n_pervious(ids=None, format=None)
m.get.subcatchment.outlet(ids=None, format=None)
m.get.subcatchment.percent_routed(ids=None, format=None)
m.get.subcatchment.pollutant_concentration(ids=None, format=None)
m.get.subcatchment.polygon(ids=None, format=None)
m.get.subcatchment.rain_gage(ids=None, format=None)
m.get.subcatchment.rainfall(ids=None, format=None)
m.get.subcatchment.runoff(ids=None, format=None)
m.get.subcatchment.slope(ids=None, format=None)
m.get.subcatchment.snow_depth(ids=None, format=None)
m.get.subcatchment.snow_pack(ids=None, format=None)
m.get.subcatchment.soil_moisture(ids=None, format=None)
m.get.subcatchment.subarea_routing(ids=None, format=None)
m.get.subcatchment.tag(ids=None, format=None)
m.get.subcatchment.width(ids=None, format=None)
m.get.subcatchment.zero_depression_storage_impervious_percent(ids=None, format=None)infiltration_horton
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.infiltration_horton.decay(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.infiltration_horton.dry_time(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.infiltration_horton.maximum_rate(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.infiltration_horton.maximum_volume(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.infiltration_horton.minimum_rate(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.infiltration_horton.decay(ids=None, format=None)
m.get.infiltration_horton.dry_time(ids=None, format=None)
m.get.infiltration_horton.maximum_rate(ids=None, format=None)
m.get.infiltration_horton.maximum_volume(ids=None, format=None)
m.get.infiltration_horton.minimum_rate(ids=None, format=None)infiltration_green_ampt
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.infiltration_green_ampt.hydraulic_conductivity(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.infiltration_green_ampt.initial_moisture_deficit(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.infiltration_green_ampt.suction_head(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.infiltration_green_ampt.hydraulic_conductivity(ids=None, format=None)
m.get.infiltration_green_ampt.initial_moisture_deficit(ids=None, format=None)
m.get.infiltration_green_ampt.suction_head(ids=None, format=None)infiltration_curve_number
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.infiltration_curve_number.conductivity(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.infiltration_curve_number.curve_number(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.infiltration_curve_number.dry_time(ids=None, format=None) | user | float | series by subcatchment | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.infiltration_curve_number.conductivity(ids=None, format=None)
m.get.infiltration_curve_number.curve_number(ids=None, format=None)
m.get.infiltration_curve_number.dry_time(ids=None, format=None)aquifer
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.aquifer.bottom_elevation(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.aquifer.conductivity(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.aquifer.conductivity_slope(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.aquifer.count(ids=None, format=None) | derived | integer | single | int scalar count |
m.get.aquifer.field_capacity(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.aquifer.id(ids=None, format=None) | user | str | single | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.aquifer.lower_evaporation_depth(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.aquifer.lower_groundwater_loss_rate(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.aquifer.porosity(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.aquifer.tension_slope(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.aquifer.unsaturated_moisture(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.aquifer.upper_evaporation_fraction(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.aquifer.upper_evaporation_pattern(ids=None, format=None) | ref | str | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.aquifer.water_table_elevation(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.aquifer.wilting_point(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.aquifer.bottom_elevation(ids=None, format=None)
m.get.aquifer.conductivity(ids=None, format=None)
m.get.aquifer.conductivity_slope(ids=None, format=None)
m.get.aquifer.count(ids=None, format=None)
m.get.aquifer.field_capacity(ids=None, format=None)
m.get.aquifer.id(ids=None, format=None)
m.get.aquifer.lower_evaporation_depth(ids=None, format=None)
m.get.aquifer.lower_groundwater_loss_rate(ids=None, format=None)
m.get.aquifer.porosity(ids=None, format=None)
m.get.aquifer.tension_slope(ids=None, format=None)
m.get.aquifer.unsaturated_moisture(ids=None, format=None)
m.get.aquifer.upper_evaporation_fraction(ids=None, format=None)
m.get.aquifer.upper_evaporation_pattern(ids=None, format=None)
m.get.aquifer.water_table_elevation(ids=None, format=None)
m.get.aquifer.wilting_point(ids=None, format=None)groundwater
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.groundwater.a1(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.groundwater.a2(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.groundwater.a3(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.groundwater.aquifer(ids=None, format=None) | ref | str | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.groundwater.b1(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.groundwater.b2(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.groundwater.deep_flow_equation(ids=None, format=None) | user | expression | single/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.groundwater.fixed_depth(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.groundwater.lateral_flow_equation(ids=None, format=None) | user | expression | single/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.groundwater.node(ids=None, format=None) | ref | str | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.groundwater.subcatchment(ids=None, format=None) | ref | str | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.groundwater.surface_elevation(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.groundwater.threshold_elevation(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.groundwater.a1(ids=None, format=None)
m.get.groundwater.a2(ids=None, format=None)
m.get.groundwater.a3(ids=None, format=None)
m.get.groundwater.aquifer(ids=None, format=None)
m.get.groundwater.b1(ids=None, format=None)
m.get.groundwater.b2(ids=None, format=None)
m.get.groundwater.deep_flow_equation(ids=None, format=None)
m.get.groundwater.fixed_depth(ids=None, format=None)
m.get.groundwater.lateral_flow_equation(ids=None, format=None)
m.get.groundwater.node(ids=None, format=None)
m.get.groundwater.subcatchment(ids=None, format=None)
m.get.groundwater.surface_elevation(ids=None, format=None)
m.get.groundwater.threshold_elevation(ids=None, format=None)snow_pack
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.snow_pack.base_temperature(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.count(ids=None, format=None) | derived | integer | single | int scalar count |
m.get.snow_pack.depth_at_100_percent_cover(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.destination_subcatchment(ids=None, format=None) | ref | str | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.fraction_to_immediate_melt(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.fraction_to_impervious(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.fraction_to_outflow(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.fraction_to_pervious(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.fraction_to_subcatchment(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.free_water_capacity_fraction(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.id(ids=None, format=None) | user | str | single | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.impervious_fraction(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.initial_free_water(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.initial_snow_depth(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.maximum_melt_coefficient(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.minimum_melt_coefficient(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.pervious_fraction(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.plowable_fraction(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.snow_pack.removal_depth(ids=None, format=None) | user | float | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.snow_pack.base_temperature(ids=None, format=None)
m.get.snow_pack.count(ids=None, format=None)
m.get.snow_pack.depth_at_100_percent_cover(ids=None, format=None)
m.get.snow_pack.destination_subcatchment(ids=None, format=None)
m.get.snow_pack.fraction_to_immediate_melt(ids=None, format=None)
m.get.snow_pack.fraction_to_impervious(ids=None, format=None)
m.get.snow_pack.fraction_to_outflow(ids=None, format=None)
m.get.snow_pack.fraction_to_pervious(ids=None, format=None)
m.get.snow_pack.fraction_to_subcatchment(ids=None, format=None)
m.get.snow_pack.free_water_capacity_fraction(ids=None, format=None)
m.get.snow_pack.id(ids=None, format=None)
m.get.snow_pack.impervious_fraction(ids=None, format=None)
m.get.snow_pack.initial_free_water(ids=None, format=None)
m.get.snow_pack.initial_snow_depth(ids=None, format=None)
m.get.snow_pack.maximum_melt_coefficient(ids=None, format=None)
m.get.snow_pack.minimum_melt_coefficient(ids=None, format=None)
m.get.snow_pack.pervious_fraction(ids=None, format=None)
m.get.snow_pack.plowable_fraction(ids=None, format=None)
m.get.snow_pack.removal_depth(ids=None, format=None)unit_hydrograph
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.unit_hydrograph.count(ids=None, format=None) | derived | integer | single | int scalar count |
m.get.unit_hydrograph.id(ids=None, format=None) | user | str | single | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.unit_hydrograph.long_term_k(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.unit_hydrograph.long_term_r(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.unit_hydrograph.long_term_t(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.unit_hydrograph.medium_term_k(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.unit_hydrograph.medium_term_r(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.unit_hydrograph.medium_term_t(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.unit_hydrograph.month(ids=None, format=None) | user | enum/integer | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.unit_hydrograph.rain_gage(ids=None, format=None) | ref | str | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.unit_hydrograph.short_term_k(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.unit_hydrograph.short_term_r(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.unit_hydrograph.short_term_t(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.unit_hydrograph.count(ids=None, format=None)
m.get.unit_hydrograph.id(ids=None, format=None)
m.get.unit_hydrograph.long_term_k(ids=None, format=None)
m.get.unit_hydrograph.long_term_r(ids=None, format=None)
m.get.unit_hydrograph.long_term_t(ids=None, format=None)
m.get.unit_hydrograph.medium_term_k(ids=None, format=None)
m.get.unit_hydrograph.medium_term_r(ids=None, format=None)
m.get.unit_hydrograph.medium_term_t(ids=None, format=None)
m.get.unit_hydrograph.month(ids=None, format=None)
m.get.unit_hydrograph.rain_gage(ids=None, format=None)
m.get.unit_hydrograph.short_term_k(ids=None, format=None)
m.get.unit_hydrograph.short_term_r(ids=None, format=None)
m.get.unit_hydrograph.short_term_t(ids=None, format=None)lid_control
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.lid_control.count(ids=None, format=None) | derived | integer | single | int scalar count |
m.get.lid_control.id(ids=None, format=None) | user | str | single | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_control.type(ids=None, format=None) | user | enum | series by ID | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.lid_control.count(ids=None, format=None)
m.get.lid_control.id(ids=None, format=None)
m.get.lid_control.type(ids=None, format=None)lid_surface
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.lid_surface.roughness(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_surface.side_slope(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_surface.slope(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_surface.storage_depth(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_surface.vegetation_fraction(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.lid_surface.roughness(ids=None, format=None)
m.get.lid_surface.side_slope(ids=None, format=None)
m.get.lid_surface.slope(ids=None, format=None)
m.get.lid_surface.storage_depth(ids=None, format=None)
m.get.lid_surface.vegetation_fraction(ids=None, format=None)lid_pavement
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.lid_pavement.clogging_factor(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_pavement.impervious_surface_fraction(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_pavement.permeability(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_pavement.thickness(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_pavement.void_ratio(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.lid_pavement.clogging_factor(ids=None, format=None)
m.get.lid_pavement.impervious_surface_fraction(ids=None, format=None)
m.get.lid_pavement.permeability(ids=None, format=None)
m.get.lid_pavement.thickness(ids=None, format=None)
m.get.lid_pavement.void_ratio(ids=None, format=None)lid_soil
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.lid_soil.conductivity(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_soil.conductivity_slope(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_soil.field_capacity(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_soil.porosity(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_soil.suction_head(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_soil.thickness(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_soil.wilting_point(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.lid_soil.conductivity(ids=None, format=None)
m.get.lid_soil.conductivity_slope(ids=None, format=None)
m.get.lid_soil.field_capacity(ids=None, format=None)
m.get.lid_soil.porosity(ids=None, format=None)
m.get.lid_soil.suction_head(ids=None, format=None)
m.get.lid_soil.thickness(ids=None, format=None)
m.get.lid_soil.wilting_point(ids=None, format=None)lid_storage
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.lid_storage.clogging_factor(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_storage.height(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_storage.seepage_rate(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_storage.void_ratio(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.lid_storage.clogging_factor(ids=None, format=None)
m.get.lid_storage.height(ids=None, format=None)
m.get.lid_storage.seepage_rate(ids=None, format=None)
m.get.lid_storage.void_ratio(ids=None, format=None)lid_drain
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.lid_drain.closed_level(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_drain.coefficient(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_drain.control_curve(ids=None, format=None) | ref | str | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_drain.delay(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_drain.exponent(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_drain.offset_height(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_drain.open_level(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.lid_drain.closed_level(ids=None, format=None)
m.get.lid_drain.coefficient(ids=None, format=None)
m.get.lid_drain.control_curve(ids=None, format=None)
m.get.lid_drain.delay(ids=None, format=None)
m.get.lid_drain.exponent(ids=None, format=None)
m.get.lid_drain.offset_height(ids=None, format=None)
m.get.lid_drain.open_level(ids=None, format=None)lid_usage
Kind: Object collection
| Getter | Source | Declared type | Declared size | Output note |
|---|---|---|---|---|
m.get.lid_usage.area(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_usage.drain_outflow(ids=None, format=None) | result | float | time series | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.lid_usage.drain_to(ids=None, format=None) | ref | str | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_usage.evaporation(ids=None, format=None) | result | float | time series | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.lid_usage.from_impervious_percent(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_usage.from_pervious_percent(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_usage.infiltration(ids=None, format=None) | result | float | time series | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.lid_usage.inflow(ids=None, format=None) | result | float | time series | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.lid_usage.initial_saturation(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_usage.lid_control(ids=None, format=None) | ref | str | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_usage.number(ids=None, format=None) | user | integer | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_usage.outlet(ids=None, format=None) | ref | str | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_usage.storage(ids=None, format=None) | result | float | time series | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.lid_usage.subcatchment(ids=None, format=None) | ref | str | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
m.get.lid_usage.surface_outflow(ids=None, format=None) | result | float | time series | Time series; NumPy by default, or timestamp-indexed DataFrame with format='df' |
m.get.lid_usage.width(ids=None, format=None) | user | float | series/table | One ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame |
Copy-ready call list:
m.get.lid_usage.area(ids=None, format=None)
m.get.lid_usage.drain_outflow(ids=None, format=None)
m.get.lid_usage.drain_to(ids=None, format=None)
m.get.lid_usage.evaporation(ids=None, format=None)
m.get.lid_usage.from_impervious_percent(ids=None, format=None)
m.get.lid_usage.from_pervious_percent(ids=None, format=None)
m.get.lid_usage.infiltration(ids=None, format=None)
m.get.lid_usage.inflow(ids=None, format=None)
m.get.lid_usage.initial_saturation(ids=None, format=None)
m.get.lid_usage.lid_control(ids=None, format=None)
m.get.lid_usage.number(ids=None, format=None)
m.get.lid_usage.outlet(ids=None, format=None)
m.get.lid_usage.storage(ids=None, format=None)
m.get.lid_usage.subcatchment(ids=None, format=None)
m.get.lid_usage.surface_outflow(ids=None, format=None)
m.get.lid_usage.width(ids=None, format=None)