• Soil physicochemical and biological properties were used for SQI development. • Major parameters studied were FDA, DHA, MBC, SOC, Av. NPK, AWC, MAS and SPR. • Highest SQI value of 0.90 was found in ZTDSR-ZTW at 0-10 cm soil depth.

Lysimetric and eddy covariance techniques are commonly used to directly estimate actual crop evapotranspiration ($E{T}_a$). However, these technologies are costly, laborious, and require skills which make in situ ET estimation difficult, particularly in developing countries. With this in mind, an attempt was made to determine $E{T}_a$ and stagewise crop coefficient (K_c) values of transplanted puddled rice using a modified non-weighing paddy lysimeter. The results were compared to indirect methods, viz., FAO Penman–Monteith and pan evaporation. Daily $E{T}_a$ ranged from 1.9 to 8.2 mmday⁻¹, with a mean of 4.02 ± 1.35 mmday⁻¹, and their comparison showed that the FAO Penman–Monteith equation performed well for the coefficient of determination (R² of 0.63), root mean squared error (RMSE = 0.80), and mean absolute percentage error (MAPE = 13.6 %), and was highly correlated with $E{T}_a$ throughout the crop season. However, the pan evaporation approach was underestimated (R² of 0.24; RMSE = 0.98; MAPE = 22.13%) due to a consistent pan coefficient value (0.71), vegetation role and measurement errors. In addition, actual K_c values were obtained as 1.13 ± 0.13, 1.27 ± 0.2, 1.23 ± 0.16, and 0.93 ± 0.18 for the initial, crop development, mid-season, and end-season stages, respectively. These estimated crop coefficient values were higher than FAO K_c values. Statistical analysis results revealed that the overall stagewise-derived average K_c values were in line with FAO values, but different from the derived pan K_c values, although found insignificant at a 5% significance level. In addition, water productivity and agro-meteorological indices were derived to evaluate the cultivar performance in this experiment. Therefore, such a methodology may be used in the absence of weighing lysimeter-derived K_c values. The derived regional K_c values can be applied to improve irrigation scheduling under similar agro-climatic conditions.