Cufí et al. (2025) A Farm-Scale Water Balance Assessment of Various Rice Irrigation Strategies Using a Bucket-Model Approach in Spain

Identification

• Journal: Agriculture
• Year: 2025
• Date: 2025-10-07
• Authors: Sílvia Cufí, Gerard Arbat, Jaume Pinsach, Blanca Cuadrado-Alarcón, Arianna Facchi, Josep María Villar Mir, Farida Dechmi, F. Ramírez de Cartagena
• DOI: 10.3390/agriculture15192089

Research Groups

• Department of Chemical and Agricultural Engineering and Technology, University of Girona, Spain
• Institute for Sustainable Agriculture (IAS), Spanish National Research Council (CSIC), Cordoba, Spain
• Department of Agricultural and Environmental Sciences–Production, Landscape, Agroenergy, University of Milan, Italy
• Department of Chemistry, Physics and Environmental and Soil Sciences, University of Lleida, Spain
• Agrifood Research and Technology Centre of Aragon, Department of Agricultural and Forest Systems and the Environment (Soil and Irrigation EEAD-CSIC Associated Unit), Zaragoza, Spain

Short Summary

This study developed and validated a farm-scale bucket-type water mass balance model to assess the water use efficiency of various rice irrigation strategies in a 121-hectare farm in Spain. The model demonstrated that 10-day fixed-turn irrigation achieved the highest water savings (30%), followed by early cut-off (17%) and dry seeding with delayed flooding (15%), primarily by reducing the flooded period.

Objective

• To develop, calibrate, and validate a bucket mass balance model to evaluate the effect of different water-saving rice irrigation methods at the farm scale.
• To assess the water use efficiency and the impact of various irrigation practices on water savings in a Mediterranean rice agroecosystem.

Study Configuration

• Spatial Scale: A 121-hectare rice farm located in the lower Ter River valley (Baix Ter rice irrigation district), Girona, north-east Spain. The farm was conceptualized into 15 Hydrological Response Units (HRUs) based on soil variability and irrigation network.
• Temporal Scale: Five cropping seasons (2020–2024) for data collection, model calibration (2020–2022), and validation (2023–2024). Scenario simulations covered the same 2020–2024 period.

Methodology and Data

• Models used:
  • Bucket-type water mass balance model (custom-developed).
  • Hydrus-1D (for simulating vertical percolation and deriving linear regression parameters).
  • Modified Newton–Raphson numerical method (for iterative water balance closure).
• Data sources:
  • Experimental data collected at farm and field scales (2020–2024).
  • Soil maps (1:25000), specific soil study (1:5000), and textural analyses for soil properties.
  • Drill and Drop probes for soil water content.
  • NivuFlow 750 volumetric water meters (accuracy ±1%) for farm-scale irrigation discharge.
  • Ultrasonic flow meter CZ Octave US DN150 and tangential turbine meter CZ TJ125 (accuracy ±1%) for field-scale irrigation discharge.
  • Radar transmitter Sitrans LR100 (accuracy ±0.005 m) for ponding water level.
  • Canopeo App for weekly crop canopy cover measurements.
  • Agro-climatic meteorological station data (Catalan Meteorological Service) for daily precipitation, reference evapotranspiration, and mean air temperature.
  • Farmer's operational records for sowing dates and daily drainage valve opening fractions.

Main Results

• The bucket model showed satisfactory performance during calibration (2020–2022) and validation (2023–2024) periods, with Nash–Sutcliffe efficiency (NSE) values greater than 0.50, percent bias (PBIAS) lower than ±20%, and RMSE-observation standard deviation ratio (RSR) lower than 0.70 for 5-day moving averages.
• For seasonal data, the model achieved an NSE of 0.98, PBIAS of 0.9%, R² of 0.99, RMSE of 92.8 mm season⁻¹, and RSR of 0.15.
• Seasonal irrigation water use ranged from approximately 1200 mm to 3100 mm, depending on the irrigation strategy and soil category. Soil I consistently required less irrigation due to lower percolation fluxes.
• Water-saving potential of alternative strategies compared to traditional continuous flooding:
  • 10-day fixed-turn irrigation: 30% reduction in irrigation water use.
  • Early irrigation cut-off (one month before harvest): 17% reduction.
  • Dry seeding with delayed flooding (DFL): 15% reduction.
  • No-runoff practice (compared to punctual runoff): 6% reduction.
• Percolation was the highest water output in all scenarios, with Deep Percolation Fraction (DPF) ranging from 0.55 (fixed-turn) to 0.70 (no-runoff, early cut-off, continuous irrigation).
• Fixed-turn irrigation and DFL strategies, while saving water, may lead to crop water stress (soil matric potential below -20 kPa) and potentially impact rice yield.

Contributions

• Developed, calibrated, and validated a robust and computationally efficient bucket-type water mass balance model for farm-scale rice irrigation assessment, expanding on previous district-scale applications.
• Quantified the water-saving potential of various irrigation strategies (fixed-turn, early cut-off, DFL, no-runoff) specifically for a 121-hectare rice farm in a Mediterranean climate, considering spatial soil variability.
• Highlighted that managing the ponding water level and shortening the flooded period are critical drivers for diminishing water use and improving overall irrigation efficiency in paddy areas.
• Provided a practical tool that can facilitate adaptive water governance and informed decision-making for farmers and water authorities in water-scarce regions.

Funding

• MEDWATERICE project (PRIMA program, European Union, Spanish Agencia Estatal de Investigación grant PCI2019-103738).
• PROMEDRICE project (PRIMA program, European Union, Spanish Agencia Estatal de Investigación grant PCI2023-143435).
• Ministerio de Ciencia, Innovación y Universidades of Spain (FPU predoctoral grant FPU20/01123).

Citation

@article{Cufí2025FarmScale,
  author = {Cufí, Sílvia and Arbat, Gerard and Pinsach, Jaume and Cuadrado-Alarcón, Blanca and Facchi, Arianna and Mir, Josep María Villar and Dechmi, Farida and Cartagena, F. Ramírez de},
  title = {A Farm-Scale Water Balance Assessment of Various Rice Irrigation Strategies Using a Bucket-Model Approach in Spain},
  journal = {Agriculture},
  year = {2025},
  doi = {10.3390/agriculture15192089},
  url = {https://doi.org/10.3390/agriculture15192089}
}