Bidabadi et al. (2026) Historical diversion-shortfall characterization and verified operational modeling for off-farm operational risk zoning in Jarghuyeh Irrigation District, Iran

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2026
• Date: 2026-04-14
• Authors: Misagh Bidabadi, S. Mehdy Hashemy, Mahmoud Mashal
• DOI: 10.1016/j.ejrh.2026.103443

Research Groups

• Water Engineering Department, Faculty of Agricultural Technology, University College of Agriculture & Natural Resources, University of Tehran, Tehran, Iran

Short Summary

This study develops a spatially explicit framework to assess off-farm operational risk in the Jarghuyeh Irrigation District under diversion-flow shortfalls and manual canal operation. It reveals pronounced spatial clustering of vulnerability and risk, escalating from low (0-2%) under normal conditions to extreme (up to 35%) under severe stress, highlighting the limited adaptive capacity of the manual system.

Objective

• To develop a spatially explicit and methodologically transparent framework for assessing off-farm operational risk in irrigation districts exposed to diversion-flow shortfalls under manual canal operation.

Study Configuration

• Spatial Scale: Jarghuyeh Irrigation District, central Iran, covering a maximum cultivated area of approximately 11,000 hectares. The study focuses on 659 individual irrigation units within a primary and secondary open canal network totaling approximately 121 kilometers.
• Temporal Scale: Approximately two decades of daily diverted flow data were analyzed. Hydraulic-operational simulations were conducted with a time step of 15 minutes. Risk maps represent scenario-specific (steady-state) conditions derived from the multi-year daily inflow record.

Methodology and Data

• Models used:
  • Risk assessment framework (Risk = Hazard Probability × Vulnerability × Consequence).
  • Integrator–Delay (ID) model for hydraulic–operational simulation of canal flow dynamics.
  • Manual-based Standard Operating Procedure (SOP) model for gate adjustments.
  • Principal Component Analysis (PCA) to synthesize performance indicators into an integrated consequence index.
  • Non-parametric bootstrap resampling for uncertainty analysis of hazard thresholds.
  • Nelder–Mead simplex method for ID model parameter calibration.
  • Morris screening sensitivity analysis for ID model parameters.
• Data sources:
  • Approximately two decades of daily diverted flows from the Jarghuyeh Irrigation District’s monitoring and archival database.
  • Daily total water demand computed from individual stakeholder water-rights and estimated canal conveyance losses.
  • Field-operational records of delivered discharge (Qd, in liters per second) and travel time (Td, in minutes) for model calibration and verification.

Main Results

• The ID model accurately reproduced observed delivered discharge (Qd) and travel time (Td) across various operational capacity regimes, with high performance metrics (R² 0.905–0.990, NSE 0.912–0.984, KGE 0.903–0.995, PBIAS -0.458% to 1.822%, MAPE 0.516% to 1.834%).
• Historical inflow data revealed a strongly skewed distribution dominated by severe deficits (6–11 m³/s), with "Unprecedented" and "Exceptional" shortage conditions accounting for approximately 72% of the total probability. Standard parametric distributions were unsuitable, leading to a non-parametric, quantile-based hazard classification.
• Spatial vulnerability showed pronounced clustering: under normal conditions, vulnerability was low (<10%), but under "Unprecedented" scenarios, over 80% of the district faced high to extreme vulnerability (>70%), with more than 380 irrigation units experiencing severe deficits. Proximity to the diversion dam significantly influenced vulnerability.
• The integrated consequence index, derived via PCA, indicated substantial operational consequences even under normal conditions (mean ~53%, median 56.5%), with downstream units consistently more disadvantaged. As shortfalls intensified, the consequence distribution skewed towards higher values. The PCA-based consequence index demonstrated high stability to weight perturbations (mean Spearman ρ = 0.996–1.000, hotspot persistence 0.95–1.00).
• Integrated risk maps showed a systematic escalation of operational risk: from low values (0–2%) under minor shortages to extreme values (approaching 35%) under the most severe stress conditions. Approximately 65–70% of the irrigated area experienced normalized operational risk-index values above 1.5% in high-shortfall scenarios, highlighting the limited adaptive capacity of the existing manual operating system.

Contributions

• Introduces a novel hazard definition by isolating diverted-inflow shortfall as an inherent, data-observable hazard, distinct from generic drought indices or structural failures.
• Employs a data-driven approach to derive hazard probabilities directly from the empirical shortfall distribution, avoiding subjective expert-assigned weightings.
• Develops an objective evaluation of vulnerability and consequence using a PCA-based composite index, supported by sensitivity diagnostics confirming its stability and reproducibility.
• Incorporates a demand-to-supply performance metric specifically designed to capture the response of manual Standard Operating Procedures (SOPs) under inflow stress, providing operationally relevant insights.
• Achieves exceptionally high spatial resolution in risk mapping, computing indicators for 659 individual irrigation units, which enables the identification of localized hotspots of operational failure.
• Utilizes high temporal resolution (daily to sub-daily) in underlying hydraulic-operational simulations, accurately capturing intra-seasonal delivery performance and operational timing.

Funding

• Iran National Science Foundation (INSF) under project No.4034905.

Citation

@article{Bidabadi2026Historical,
  author = {Bidabadi, Misagh and Hashemy, S. Mehdy and Mashal, Mahmoud},
  title = {Historical diversion-shortfall characterization and verified operational modeling for off-farm operational risk zoning in Jarghuyeh Irrigation District, Iran},
  journal = {Journal of Hydrology Regional Studies},
  year = {2026},
  doi = {10.1016/j.ejrh.2026.103443},
  url = {https://doi.org/10.1016/j.ejrh.2026.103443}
}