FIEA: An android tool for sustainable furrow irrigation

Furrow irrigation performance is often constrained by limited field measurements and the reliance on desktop hydraulic models unsuitable for data-scarce environments. This study presents the Furrow Irrigation Evaluation App (FIEA), an Android-based tool that computes application efficiency (AE), runoff depth (RO), and deep percolation (DP) using simplified SCS hydraulic relationships. FIEA was validated against WinSRFR and SURDEV using published datasets and Monte-Carlo–generated scenarios. Results show high agreement for AE (R² = 0.92–0.99; NRMSE = 1.8–9.6 %) and RO (R² = 0.91–0.99), while DP showed lower correspondence (R² = 0.02–0.31) due to geometric simplifications. Sensitivity analysis identified inflow rate and furrow length as dominant drivers (|r| ≤ 0.62). By providing an offline, field-ready alternative to desktop models, FIEA enables rapid diagnosis of water losses and supports sustainable, climate-resilient irrigation management. Future improvements will refine DP estimation through enhanced geometric representation and sensor-integrated modelling.

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Publication Details

Journal
Smart Agricultural Technology
Published
2025-12-08
DOI
https://doi.org/10.1016/j.atech.2025.101704
Primary Topic
Irrigation Practices and Water Management
Type
article
Field-Weighted Citation Impact
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article

FIEA: An android tool for sustainable furrow irrigation

Thomas Nyanda Reuben, Lameck Fiwa, Grivin Chipula, Patsani Gregory Kumambala et al.
Smart Agricultural Technology
Irrigation Practices and Water Management
article

FIEA: An android tool for sustainable furrow irrigation

Thomas Nyanda Reuben, Lameck Fiwa, Grivin Chipula, Patsani Gregory Kumambala, Stanley Phiri, Lenard Kumwenda
article en

Abstract

Furrow irrigation performance is often constrained by limited field measurements and the reliance on desktop hydraulic models unsuitable for data-scarce environments. This study presents the Furrow Irrigation Evaluation App (FIEA), an Android-based tool that computes application efficiency (AE), runoff depth (RO), and deep percolation (DP) using simplified SCS hydraulic relationships. FIEA was validated against WinSRFR and SURDEV using published datasets and Monte-Carlo–generated scenarios. Results show high agreement for AE (R² = 0.92–0.99; NRMSE = 1.8–9.6 %) and RO (R² = 0.91–0.99), while DP showed lower correspondence (R² = 0.02–0.31) due to geometric simplifications. Sensitivity analysis identified inflow rate and furrow length as dominant drivers (|r| ≤ 0.62). By providing an offline, field-ready alternative to desktop models, FIEA enables rapid diagnosis of water losses and supports sustainable, climate-resilient irrigation management. Future improvements will refine DP estimation through enhanced geometric representation and sensor-integrated modelling.

Smart Agricultural TechnologyVol. 13
Lilongwe University of Agriculture and Natural Resources (MW), Christian Health Association of Malawi (MW)
Openalex Percentile: Top 53%
Irrigation Practices and Water Management
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