Groundwater pollution by nitrate leaching from sugarcane fields in Okinawa is recognized as a critical issue. Controlled release fertilizer (CRF) has the potential to reduce N leaching from cropping systems. The study focused on confirming the effectiveness of CRF at balancing sugarcane yield and reducing nitrate leaching from sugarcane fields via a water footprint (WF) approach. A lysimeter study was conducted using four treatments: (i) bare land, (ii) P and K fertilization without N, (iii) urea fertilization, and (iv) CRF application. According to the results, for both plant cane and ratoon, the total sugarcane dry weight obtained for CRF was higher compared to urea application. The cumulative nitrate-N leaching of the plant cane season for all treatments was higher than of the ratoon season. For the total crop cycle (plant cane plus ratoon), heavier nitrate-N leaching was observed in the urea-applied condition than in the CRF-applied condition. For both crop seasons, the total sugarcane WF of the CRF application (plant cane: 192.33 m³/t, ratoon: 190.47 m³/t) was lower than that of the urea application (plant cane: 233.47 m³/t, ratoon: 237.59 m³/t). WF values indicated that the CRF application had a lower impact on the groundwater of the area.

Difficulties in direct monitoring of nitrate balance in agricultural fields reveal the importance of modeling and quantifying the affecting parameters on nitrate balance. We constructed meta-models for APSIMX-Sugarcane using the treed gaussian process and conducted a global sensitivity analysis for nitrate uptake and leaching under three conditions: (1) bare land (BL) to examine the influence of soil hydraulic characteristics, (2) N-free treatment under radiation use efficiency (RUE) ranges (i) 1.2–1.8 [N-free(a)] and (ii) 1.8–2.5 [N-free(b)], and (3) urea conditions to examine the influence of plant growth. Generated meta-models showed good accuracy (for all conditions: R² > 0.70; NRMSE < 16%; AI > 0.90). The most influential parameters (sensitivity indices ≥ 0.02) were as follows: for leached NO₃−N in BL: the parameter rerated to saturated flow-proportion of water between saturation and field capacity (SWCON) of all soil layers; for NO₃⁻ uptake and leached NO₃−N in N-free(a) and urea: RUE of the phenological stage (PS) 3 (RUE3) and 4, tt_emerg_to_begcane, green_leaf_no, and y_n_conc_crit_leaf of PS 4 (NCL4); in N-free(b): RUE3, NCL4, and SWCON of soil layers 0–15 cm; 15–30 cm, which confirmed that influential parameters were depended on N-stress. The outcomes of this study are useful for enhancing the accuracy and efficiency of crop modeling.

Process-based crop models are advantageous for the identification of management strategies to cope with both temporal and spatial variability of sugarcane yield. However, global optimization of such models is often computationally expensive. Therefore, we performed global sensitivity analysis based on Gaussian process emulation to evaluate the sensitivity of cane dry weight to trait parameters implemented in the Agricultural Productions System Simulator (APSIM)-Sugar model under selected environmental and management conditions in Khon Kaen (KK), Thailand. Emulators modeled 30 years, three soil types and irrigated or rainfed conditions, and emulator performance was investigated. rue, green_leaf_no, transp_eff_cf, tt_emerg_to_begcane and cane_fraction were identified as the most influential parameters and together they explained more than 90% of total variance on the simulator output. Moreover, results indicate that the sensitivity of sugarcane yield to the most influential parameters is affected by water stress conditions and nitrogen stress. Our findings can be used to improve the efficiency and accuracy of modeling and to identify appropriate management strategies to address temporal and spatial variability of sugarcane yield in KK.

The global optimization of parameters in process-based crop models is often considered computationally expensive. Gaussian process (GP) emulation is a widely used method for reducing the computational burden of the optimization process. Total above-ground biomass and cane dry weight of three Thai sugarcane cultivars (KK3, LK92-11 and 02-2-058) collected under rainfed and irrigated conditions were used to optimize cultivar-specific parameters in the Agricultural Production Systems sIMulator (APSIM)-Sugarcane crop model through a GP emulation. GP emulators were trained and validated to approximate APSIM-Sugarcane model and then used for optimizing the cultivar-specific parameters through the differential evolution algorithm. Resulting optimized parameters allowed to obtain simulations that quite well approximated the observed biomass and CDW (validation results between simulated and observed yields: R² 0.93–0.98; normalized root mean squared error: 5–22%; Willmott’s agreement index: 0.87–0.99). The best parametrization was obtained under the lowest water stressed conditions. Based on these results, we suggest that GP emulation can be efficiently implemented for the parameterization of computationally expensive simulators.

Excess nutrients released through leaching and/or runoff from agricultural lands into natural water bodies has caused water pollution all over the world. Water pollution by means of discharging chemical substances from paddy fields to water bodies has become a critical problem in Sri Lanka. The grey water footprint is considered as a rough estimate of water pollution associated with a particular activity. The grey water footprint associated with the paddy cultivation in the right bank of "Nilwala” downstream was calculated based on two levels of fertilizer applications; level 1: fertilization according to the recommendations of the Department of Agriculture, Sri Lanka and level 2: fertilization based on farmer's preferences. Sampling was performed once a day for a week after each fertilization. Nitrate concentration of water samples was analyzed through Ultraviolet Spectrometric Screening method while pH and electrical conductivity were measured using pH meter and conductivity meter, respectively. Daily rainfall over the study area was recorded throughout the study period. The grey water footprint calculated based on the nitrate discharge for fertilization level 1 and level 2 were 0.93 m3/ha and 2.26 m3/ha respectively. As it is analyzed by the one-sample t-tests, the nitrate concentrations, pH and electrical conductivity of paddy water are significantly lower than that of proposed ambient water quality standards for Sri Lanka. As revealed by two-sample t-tests, nitrate concentrations, pH and electrical conductivity of water samples were significantly different from each other with respect to the both levels of fertilization. However, the nitrate concentrations and electrical conductivity values of water samples related to both levels of fertilization and pH values related to fertilization level 1, were significantly higher than that of raw water in "Nilwala" river which is used for irrigation, while pH values related to fertilization level 2 were significantly lower than the same. Keywords: Grey water footprint, Paddy cultivation, Nitrate, pH, Electrical conductivity