Kumwenda et al. (2025) FIEA: An android tool for sustainable furrow irrigation

Identification

• Journal: Smart Agricultural Technology
• Year: 2025
• Date: 2025-12-08
• Authors: Lenard Kumwenda, Grivin Chipula, Patsani Gregory Kumambala, Thomas Nyanda Reuben, Lameck Fiwa, Stanley Phiri
• DOI: 10.1016/j.atech.2025.101704

Research Groups

• Agricultural Engineering Department, Bunda College of Agriculture, Lilongwe University of Agriculture and Natural Resources, Malawi
• L Gravam Consulting Engineers, Lilongwe, Malawi

Short Summary

This study introduces the Furrow Irrigation Evaluation App (FIEA), an Android-based tool that computes application efficiency and water losses using simplified SCS hydraulic relationships. FIEA was validated against established desktop models, demonstrating high accuracy for application efficiency and runoff, thus providing a field-ready solution for sustainable irrigation management in data-scarce environments.

Objective

• To develop an Android application for furrow irrigation evaluation.
• To validate FIEA's performance outputs (application efficiency, runoff, deep percolation) against SURDEV and WinSRFR under cut-back and non–cut-back conditions.
• To conduct a sensitivity analysis of inflow rate, furrow length, and soil intake characteristics on irrigation performance.

Study Configuration

• Spatial Scale: Field-level, individual furrows (e.g., furrow lengths from 100 m to 600 m).
• Temporal Scale: Single irrigation event, real-time evaluation.

Methodology and Data

• Models used:
  • Furrow Irrigation Evaluation App (FIEA): Android-based tool using simplified Soil Conservation Service (SCS) hydraulic relationships.
  • WinSRFR: Desktop hydraulic model (benchmark).
  • SURDEV: Desktop hydraulic model (benchmark).
• Data sources:
  • Published field examples from Cuenca [44] and Jurri¨ens et al. [24].
  • Synthetic datasets generated using Monte Carlo simulation in Microsoft Excel.

Main Results

• FIEA was successfully developed using Android Studio (version 2024.1.1) and provides dynamic visualization of application efficiency (AE), runoff depth (RO), and deep percolation depth (DP).
• Cut-back irrigation operations significantly improved application efficiency (e.g., 58 % vs. 37 % for non–cut-back at 275 m furrow length).
• FIEA showed high agreement with benchmark models (WinSRFR and SURDEV) for AE (R² = 0.92–0.99; NRMSE = 1.8–9.6 %) and RO (R² = 0.91–0.99).
• Deep percolation (DP) estimation showed lower correspondence (R² = 0.02–0.31) with benchmark models, attributed to FIEA's simplified geometric representations and SCS-based formulations.
• Sensitivity analysis identified furrow inflow rate (Pearson correlation coefficient |r| ≤ 0.58) and furrow length (|r| ≤ 0.62) as the dominant drivers influencing AE, RO, and DP.

Contributions

• Development of the first Android-based furrow irrigation decision-support tool (FIEA) that computes application efficiency, runoff, and deep percolation using simplified SCS hydraulic relationships.
• First mobile application for furrow irrigation cross-validated against established desktop models (WinSRFR and SURDEV).
• Provides an offline, field-ready, low-cost, and accessible alternative to complex desktop models, enabling rapid diagnosis of water losses in data-scarce and resource-limited environments.
• Supports sustainable, climate-resilient irrigation management by empowering agronomists, extension workers, and farmers with real-time performance evaluation.

Funding

• Higher Education Partnerships in sub-Saharan Africa (HEP SSA) project at Lilongwe University of Agriculture and Natural Resources.

Citation

@article{Kumwenda2025FIEA,
  author = {Kumwenda, Lenard and Chipula, Grivin and Kumambala, Patsani Gregory and Reuben, Thomas Nyanda and Fiwa, Lameck and Phiri, Stanley},
  title = {FIEA: An android tool for sustainable furrow irrigation},
  journal = {Smart Agricultural Technology},
  year = {2025},
  doi = {10.1016/j.atech.2025.101704},
  url = {https://doi.org/10.1016/j.atech.2025.101704}
}