RAT-Forecasting

The forecasting plugin adds functionality to generate short-term forecasts of the reservoir state for up to 15 days. It uses forecasted weather data to forecast the inflow to reservoirs. Other Reservoir operations related fluxes, specifically, the storage change in the forecast window and the resulting outflow from the reservoir are estimated as different scenarios, which are described in detail below.

How to Use

To run the forecast plugin, set the value of the forecast option in the PLUGINS section of the configuration file to True.

PLUGINS: 
    forecast: True 
    forecast_lead_time: 15
    forecast_gen_start_date: end_date     # can either be “end_date” or a date in YYYY-MM-DD format
    forecast_gen_end_date:              # a date in YYYY-MM-DD format (Optional)
    forecast_rule_curve_dir: /path/to/rule_curve   (Optional)
    forecast_reservoir_shpfile_column_dict: {column_id: GRAND_ID, column_capacity: CAP_MCM}
    forecast_vic_init_state:            # path of VIC state file or date in YYYY-MM-DD format (Optional)
    forecast_rout_init_state:           # path of Routing state file or date in YYYY-MM-DD format (Optional)
    forecast_storage_scenario: [ST, GO, GC, RC]
    forecast_storage_change_percent_of_smax: [20, 10, 5]

The forecast_gen_start_date option controls when the generation of forecast will begin. If the value is set to end_date, the forecast will begin on the end date of RAT’s normal mode of running, i.e., in nowcast mode, which are controlled by start_date and end_date options in the BASIN section. Alternatively, a date in the YYYY-MM-DD format can also be provided to start the generation of forecast from that date. The forecast_gen_end_date option defines the end date for which forecasts will be generated. The forecast window for each date when the forecast is being generated or the number of days ahead for which the forecast is generated is controlled by the forecast_lead_time option, with a maximum of 15 days ahead.

The forecast_rule_curve_dir option should point to the directory containing the rule curve files for the reservoir. The forecast_reservoir_shpfile_column_dict option specifies the names of the columns that correspond to the ID and capacity of the reservoir, named column_id and column_capacity. These columns should be present in the reservoir_vector_file in the GEE section in the configuration file for running the forecasting plugin. The forecast_vic_init_state option can be used to define the date in 'YYYY-MM-DD' format of vic init file to be used. It can also be the path of the vic init state file that the user want to use. In case the path of vic init state file is provided instead of date, it is assumed that the state file is for the forecast_gen_start_date. Also, in this case, forecast_rout_init_state becomes a required parameter and has to be the actual path of the rout init state file.

forecast_storage_scenario is a list of scenarios that a user can provide to RAT to assume storage change during the forecasting period. It can include options like 'GO' (Gates Open), 'GC' (Gates Closed) or 'RC' (Rule Curve based). Or the user can include an option 'ST' to specify the values of storage change during the forecasting period expressed as a percentage of the maximum reservoir capacity using the forecast_storage_change_percent_of_smax.

Forecasted inflow and evaporation

• The inflow to the reservoir is simulated using forecasted precipitation from Climate Hazards Center InfraRed Precipitation with Stations-Global Ensemble Forecasting System (CHIRPS-GEFS) and forecasted temperature and wind data from Global Forecasting System (GFS). CHIRPS-GEFS uses satellite and observations of precipitation (CHIRPS) for bias correction and downscaling of the Global Ensemble Forecasting System (GEFS) precipitation forecasts. The Global Forecasting System (GFS) is a Numerical Weather Prediction system for operational weather prediction which forecasts meteorological variables, including temperature and wind.
• The forecasted meteorology is used to run the hydrological model component of RAT (MetSim + VIC + VIC Routing) to obtain forecasted streamflow and evaporation for each reservoir.

Reservoir Storage Change and Outflow Scenarios

The reservoir state – storage change, outflow, water surface elevation, and the water surface area – is estimated based on different scenarios of possible reservoir operations in the forecasting window. The scenarios used to estimate reservoir storage change are as follows -

• Target reservoir water level – Maintains a target water level by storing and releasing the necessary amount of water.

• Fraction of maximum reservoir storage – Storage change is estimated as a fraction of the maximum reservoir storage.

• Historical operations-based outflow scenarios – Storage change is estimated based on historical operations of the reservoir. Historical observations of the reservoir are obtained from Biswas et al. (2021), which infers the reservoir operations using long-term observations of the reservoir surface area.

• Gates Closed/Open - Simulation of the reservoir state by considering the dam gates to be either fully closed or fully open.

• User defined storage change – Users can directly input the expected volume of storage change in the forecasting window to simulate the reservoir states.

Publication

We used this forecasting plugin to perform a forensic study of devastating floods due to extreme precipitation that caused havoc in the entire state of Kerala, India in 2018. The forecasted data generated for the study can be accessed here - RAT-Forecasting-Kerala-2018. It contains inflow forecast, inflow nowcast and release scenarios.