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.

Geometric increase in population coupled with rapid urbanization, industrialization and agricultural development are causing increased pressure on global water resources. Agriculture is the largest consumer of fresh water resources, thus the scope of enhancing water productivity in agriculture is taken to be the priority area of research. The right amount and frequency of irrigation is essential for optimum use of limited water resources for crop production as well as management. A field experiment with split plot design was carried out during November to February 2015-16 at PFDC (Precision Farming Development Centre), Water Technology Centre, IARI, New Delhi to study the effect of different irrigation levels and frequencies on Broccoli (Brassica oleracea var. italica) under drip irrigation. The experiment included three levels of irrigation frequencies: N1 (once every day), N2 (once every 2 days) and N3 (once every 3 days) with different irrigation levels of 100, 80 and 60 % of crop evapotranspiration (ETc). Results revealed that drip irrigation frequency significantly (p<0.05) affected the broccoli yield. The maximum yield (24.46±0.18 t/ha) was obtained with 80% of ETc with once in 2 days irrigation followed by 100% of ETc with once in 2 days. Lowest yield (16.53±0.1 t/ha) was obtained at 60% of ETc at once in 3 days irrigation. Overall, it was observed that irrigation on 80% of ETc with once in two days is an appropriate cycle for optimum yield of broccoli.

In order to address current global water shortages, geovisualization tools such as remote sensing and geographic information systems aid planners and decision makers in generating more effective and correct judgments for the execution of water harvesting activities for the maximum utilization of rainwater. Keeping in view, a weighted sum approach technique was used to infer hydrological behavior and priorities at watershed level in the Harohar sub-basin of middle Gangetic plains. It was observed that monsoon rainfall (1.7 mm year⁻¹) and post-monsoon rainfall (0.6 mm year⁻¹) has been declined whereas pre-monsoon rainfall (1.5 mm year⁻¹) has significantly increased over the period 1985–2019. Furthermore, morphometric, slope, hydrological, geomorphological, and lithological variations results revealed that 56.30% of areas are prioritized as very high, followed by high (30.5%), and only 2–7% of areas fall under very low to low priority for construction of rain water harvesting structures. Water harvesting facilities such as farm ponds, check dams, tanks, aharpynes, and conservation ditches might be offered in prioritized locations for optimum utilization of surface runoff and ground water recharge. Based on the above scientific findings, this study may be helpful in water resource planning at the basin/watershed level across the globe

An integrated sensing device for irrigation scheduling was developed to assess the soil–plant–atmosphere continuum for irrigation scheduling. A field experiment was carried out to evaluate ISDI performance and CWSI estimation across various irrigation regimes in wheat crop at WTC farm, ICAR-IARI, New Delhi, India. The experiment considered were full irrigation (FI) and various deficit irrigation levels (DI-15, DI-30, DI-45, and DI-60), receiving 15, 30, 45, and 60% less water in comparison to FI, respectively. The calibration and performance of the ISDI sensor probes was done with gravimetric methods along with time domain reflectometry (TDR) and a handheld infrared thermometer. The field calibration of the ISDI's soil moisture probe and TDR gave promising results, with R2 values ranging from 0.76 to 0.81 and 0.81 to 0.86, respectively, for soil depths up to 45 cm. ISDI's infrared sensor probe also demonstrated strong alignment with a handheld infrared thermometer (R2: 0.95), indicating reliable methods. Furthermore, a regression equation of lower baseline and upper threshold for CWSI computation was derived as (Tc–Ta)ll = 1.97 × VPD – 1.43 (R2:0.86) and 1.93 °C, respectively. It was recommended to initiate irrigation when CWSI ≥ 0.35 for wheat to achieve optimal crop yields.

Field and laboratory experiments were carried out during November to February 2015–16 at Precision Farming Development Centre, Water Technology Centre, IARI, New Delhi to study the field evaluation and calibration of soil moisture sensors (tensiometers and gypsum blocks) in drip irrigated broccoli (Brassica oleracea var. italica). The experiment included three levels of irrigation frequencies: N1 (once every day), N2 (once every 2 days) and N3 (once every 3 days) with three irrigation levels of 100, 80 and 60% of crop evapotranspiration (ETc). For evaluating the performance of different soil moisture sensors, the sensors’ readings were taken from plot on daily basis and these readings were compared with those obtained from the gravimetric method. It was observed that the calibration of two sensors (Tensiometers and Gypsum blocks) give the similar calibration equation, having a quite low RMSE and ensuring good performances after field calibration. The value of coefficient of determination (R²) for Gypsum block was estimated as 0.76, 0.83, 0.84 and 0.85 for 0–15, 15–30, 30–45 and 45–60 cm soil depths whereas, the value of coefficient of determination (R²) for tensiometers was estimated as 0.84, 0.83, 0.75 and 0.73 for 015, 15–30, 30–45 and 45–60 cm soil depths respectively. The tensiometers were found less responsive to dry conditions than gypsum block sensors whereas gypsum blocks were found less responsive to wet conditions. It was concluded that field calibration of soil moisture sensors are essential for improving to measure the soil moisture content and diurnal soil moisture variations lead to water vapour flux into the soil. It is recommended that field based calibrations developed may be preferred over laboratory based calibrations, since field data are more representative of the situations in the field where sensors were installed.