Assessing irrigation canal seepage reduction using polymer sealants

Abstract

Irrigation canals around the world experience varying degrees of seepage losses, with several potential adverse consequences and influenced by numerous factors. A synthesis and interpretation of field seepage data from peer-reviewed literature (impact factor >1.5) on seepage measurement and control reveals several key insights: (i) seepage rates differ significantly due to diverse field conditions; (ii) the inflow-outflow method is the most reliable for measuring canal seepage in the field; and (iii) polymer sealants (PSs) offer a cost-effective alternative for reducing seepage in irrigation canals. Compared to conventional liners (CLs) such as concrete, geomembranes, or masonry, PSs are not only more affordable but also can be applied selectively, allowing for seepage when the surface water supply is sufficient and groundwater recharge is desirable. Studies show PSs can reduce seepage by 64% to 88%, while CLs achieve reductions of 53% to 95%, highlighting the potential of PSs for further research and application. However, best field application techniques for PSs, the uncertainty in evaluating effectiveness, and ambiguity in potential environmental impacts require more comprehensive investigation. The most widely researched PS for reducing canal seepage is linear anionic polyacrylamide (LAPAM), a synthetic polymer sealant (SPS). When applied to canal water, LAPAM forms flocs through cation bridging with divalent cations (Mg2+ and Ca2+) commonly found in canal water, which settle along the canal perimeter and reduce hydraulic conductivity. Observed seepage reduction from field trials of LAPAM that had been conducted prior to this study on three mid-sized canals (two in Colorado, USA and one in Sindh, Pakistan) using the recommended inflow-outflow method for seepage testing were analyzed. The average pre-LAPAM seepage rate was approximately 0.32 m/day, while the post-LAPAM rate dropped to 0.04 m/day, with results demonstrating seepage reductions between 69% and 100%. An uncertainty analysis of the pre- and post-LAPAM tests indicated an 85% probability that the seepage reductions were due to the LAPAM treatment. While LAPAM has proven effective, the long-term environmental impact of LAPAM treatment remains uncertain, underscoring the need to explore natural alternatives to synthetic polymer sealants. Biopolymer sealants (BPSs) were identified and evaluated through both laboratory and field experiments, designed to mirror the approach used with LAPAM. These experiments were conducted in triplicate (lab) and duplicate (field) to enhance confidence. In the lab, constant head saturated hydraulic conductivity (KSAT) tests simulated irrigation canal perimeter conditions. Five BPSs—pectin citrus (PC), cellulose hydroxyethyl ether (CHE), pullulan desalinated (PD), sodium alginate low viscosity (SALV), and xanthan gum (XG)—were initially tested and compared against LAPAM. The pre-and post-polymer KSAT values revealed that PC, PD, and XG achieved average reductions exceeding 40%, which was used as the threshold for further exploration. Subsequent testing under conditions more representative of irrigation canals identified XG as the most effective BPS. Alternative application rates were assessed, with 20 mg/L identified as the preferred concentration, as higher concentrations did not significantly enhance KSAT reduction. Long-term performance tests in the lab showed that XG, at 40 mg/L, can reduce hydraulic conductivity by over 90% for 9–10 months and by 60–70% over 1.5 months at 20 mg/L. These findings were validated using seepage tests in the field, where XG applied to a 3-km earthen canal reach at 20 mg/L reduced seepage by up to 63% over a month (at which time the canal was taken out of service). While the use of SPSs may still be justified for controlling canal seepage, this research shows that BPSs such as XG, have the potential to replace SPSs for canal sealing. However, further work is needed to optimize application methods and dosage rates, to better understand working mechanisms, to demonstrate long-term effectiveness, and to assess scalability across diverse field conditions.