sDRIPS Configuration File

The sDRIPS configuration file (sdrips_config.yaml) serves as the primary control interface for running the model. It provides a structured mechanism for tailoring simulations to user needs and computational resources.

Configuration parameters are divided into two major categories:

  1. High-level module controls

    • Define the overall functional mode of sDRIPS (e.g., generating advisories for farmers or canal operators).
    • Specify whether to integrate in-situ sensor data, local weather station inputs, or rely exclusively on satellite and numerical weather model estimates without bias correction.

  2. Low-level module controls

    • Configure common parameters such as the running period, boundary polygon location, project directory paths, data-cleaning options, etc.

Together, these controls determine the scope, inputs, and computational logic of a given sDRIPS run.

High-level module controls

High-level controls govern the core objectives of a model run. A high-level control in sDRIPS is defined as a configuration switch that activates a distinct analytical capability or output dimension beyond the core water requirement estimation workflow.
Unlike low-level controls (which specify run parameters, inputs, file structures and output format), high-level controls represent conceptual modules that extend the scientific scope of sDRIPS.

Examples:
- New considerations → Incorporating additional physical processes (e.g., deep groundwater–surface water interaction).
- New outputs → Generating novel advisory products (e.g., crop yield forecasts, fertilizer optimization metrics).

In essence, a high-level control introduces a new modeling domain, process pathway, or decision-support output that meaningfully expands the functionality of sDRIPS.

Users can activate or deactivate modules to suit specific applications such as:

  • Command area advisories → estimating water requirements at the irrigation command level.
  • Canal water allocation → distributing water resources across canal networks.
  • Data integration modes → enabling or disabling in-situ sensor and weather station data to improve accuracy.

Below is a representative snippet from the configuration file: 

# -------------------------------
# HIGH-LEVEL MODULE CONTROLS
# -------------------------------
Command_Area_Net_Water_Requirement: true   # Advisory: water requirement per command area
Canal_water_allotment: false               # Advisory: water allotment per canal (primary → tertiary)
Insitu_Sensor_integration: false           # Integrate in-situ sensor data for bias correction
Weather_station_integration: false         # Integrate local weather station data for improved accuracy

Command Area Water Allotment

This control is designed to generate irrigation advisories at the command area level (i.e., farmer-focused outputs).
When enabled, sDRIPS estimates the net crop water requirement within each defined command area and translates it into actionable recommendations for farmers.

  • If the user wishes to incorporate in-situ sensor data or local weather station observations, those features should be activated in parallel while keeping this control enabled.
  • This functionality is most useful for field-scale water management and scheduling decisions.

Canal Water Allotment

This control generates advisories for canal operators and irrigation managers.
When enabled, sDRIPS:

  1. Estimates the net water requirement for all fields served by a canal command area.
  2. Aggregates demand across the irrigation hierarchy:
    • Tertiary canals (child nodes) → Secondary canals → Primary canals (root canal).

This hierarchical aggregation ensures that water requirements are properly scaled from field-level needs to the canal network level, supporting equitable and efficient distribution.

  • In-situ or weather station integration can be activated alongside this featurefor improved accuracy.
  • This module is particularly relevant for system-level water allocation and canal scheduling.

In-Situ Sensor Configuration

Activating this control enables the incorporation of locally deployed sensors (e.g., air temperature, wind speed, soil moisture) into the analysis.

  • Sensor data are used to bias-correct satellite and model inputs, thereby improving the fidelity of water requirement estimates.
  • This feature is intended for applications where ground validation data are available.

Weather Station Configuration

This control incorporates local meteorological station data (e.g., precipitation, air temperature, wind speed, atmospheric pressure) into sDRIPS.

  • Similar to in-situ sensors, weather station inputs enhance local accuracy by replacing or correcting global model estimates.
  • This module is particularly valuable in regions with dense weather station coverage.

Adding a New High-Level Control

To extend the capabilities of sDRIPS, new high-level controls can be defined using the Developer version.

A high-level control refers to a feature that introduces a new analytical capability or output dimension to the system (e.g., crop yield prediction, fertilizer application effects, groundwater–surface water interactions).

Adding a new control involves:
1. Declaring the control in sdrips_config.yaml with a Boolean toggle (true / false).
2. Implementing the corresponding logic in the source code so that the new control activates relevant computations or outputs.
3. Updating documentation to reflect the new functionality.

Low-level module controls

Low-level controls govern the operational details of an sDRIPS run. These parameters are common across high-level modules and provide essential contextual inputs:

  • Boundary definition → Path to the region of interest boundary file (Shapefile or GeoJSON), field name of interest, and unique identifier.
  • Running period → Start and end dates for the run.
  • Project structure → Directory paths, links to supplementary configuration files, and output storage locations.
  • Precipitation configuration → Specification of how precipitation should be incorporated into the analysis (a parameter shared across all high-level modules).
  • Data handling options → Directory-cleaning settings, overwrite rules, and log management.
  • Output options → Outputs can include PNGs (for practitioners), CSVs (for researchers and practitioners), and rasters (for advanced analysis).