Mapping crop water productivity of rice across diverse irrigation and fertilizer rates using field experiment and UAV-based multispectral data

Abstract

Crop water productivity (CWP) is an important indicator for optimizing water use and yield in agriculture. In this study, an Unmanned Aerial Vehicle (UAV) equipped with a multispectral camera was used for estimating the CWP of rice crop. To our knowledge, this is the first study that assessed CWP of rice at high spatial resolution in the tarai region of north India using UAV-based multispectral data. A field experiment was conducted in Roorkee, India, where rice was cultivated under two irrigation levels (continuous flooding (CF), and alternate wetting and drying (AWD)) and three nitrogen treatments (high nitrogen (HN): 150 kg/ha, medium nitrogen (MN): 120 kg/ha, and low nitrogen (LN): 60 kg/ha). There were a total of seven treatments (T0 = rainfed, T1 = CF-HN, T2 = CF-MN, T3 = CF-LN, T4 = AWD-HN, T5 = AWD-MN, and T6 = AWD-LN). UAV-derived Normalized Difference Vegetation Index (NDVI) was used for the estimation of crop evapotranspiration (ETa) and CWP. The highest and lowest ETa were found in treatments T4 (316.06 mm) and T0 (311.49 mm), respectively. The above-ground biomass (AGB) and grain yield were calculated using the radiation utilization efficiency (RUE). The model estimated AGB with R² 0.63 and RMSE 0.61 t ha⁻¹, and yield with R² 0.95 and RMSE 0.41 t ha⁻¹. The CWP was highest in treatment T5 (1.13 kg m⁻³) and lowest in treatment T0 (0.76 kg m⁻³). For treatments, T1, T2 T3, T4, and T6, the CWPs were 1.13, 1.13, 1.07, 1.05, and 1.12 kg m⁻³, respectively. Considering the global CWP categories for rice crop as low (≤0.70 kg m⁻³), medium (0.70–1.25 kg m⁻³), and high (>1.25 kg m⁻³), the CWP in the present study was within the medium category. Among the treatments, AWD with MN was found to be the most suitable strategy for achieving high CWP. Monitoring the CWP of rice fields using UAV and providing high-resolution CWP maps could be helpful for farmers and policymakers in better allocating the resources and enhancing resource use efficiency.