Evaluation of Methods for Predicting Seepage Loss Rates for the Hard Lined Irrigation Canals of the Lower Rio Grande Valley of Texas
MetadataShow full item record
This project investigated the measured loss rates and observed canal lining conditions by the Texas AgriLife Extension Service to evaluate the Davis-Wilson empirical formula and to further develop a canal condition rating system for predicting loss rates. This research is to help irrigation districts of the Lower Rio Grande Valley of Texas to identify and prioritize the high loss deteriorated lined canals for rehabilitation and management. The ponding test method was used to estimate the loss rates on 32 canal sections. The condition rating scores were evaluated for 26 of these canals. Test calculation revisions and testing errors were first evaluated to understand the potential impacts to the seepage loss rates and condition rating system. The condition rating system had good results for canals with a ranking of 1, predicting losses less than 0.38 (ft^(3)/ft^(2)/day). Canals with rankings of 2 and 3 had a larger range in loss rates. This could be attributed to either the subsoil types having more influence as the lining conditions become more deteriorated or errors in the rating system. The Davis-Wilson empirical formula had poor results at predicting loss rates for the local lining conditions. The seepage loss rates were used to calibrate the formula and derive new coefficients (Cvalues). The C-values were correlated with the scores of the condition rating system (i.e. Ranking 1 = C-values 1-11). Relationships were also found between the canal dimensions, water loss rates, and conditions ratings. In general, larger, deeper canals were in better condition and had lower loss rates. Smaller canals had more variability in both loss rates and condition ratings.
Davis-Wilson empirical formula
condition rating system
Leigh, Eric (2014). Evaluation of Methods for Predicting Seepage Loss Rates for the Hard Lined Irrigation Canals of the Lower Rio Grande Valley of Texas. Master's thesis, Texas A & M University. Available electronically from