The interacting effects of irrigation, sowing date and nitrogen on water status, protein and yield in pea (Pisum sativum L.).

Management for agronomic practices might improves growth and grain yield in pea. The main objective of this experiment was to assess the interacting effects of different irrigation regimes, sowing date and nitrogen fertilizer treatments on pea traits. We evaluated three irrigation regimes (50, 75, and 100% of the plant irrigation requirement), two sowing dates (February and March), and nitrogen [application of nitroregn (N1) and without nitrogen as control (N0)] in 2019 and 2020 under field conditions. Chlorphyll content, leaf area index, leaf water potential, grain yield and water productivity were higher in the late sowing (March) than in early sowing (February) treatment. Percentage of vegetation cover in late sowing (60%) was significantly higher than in early sowing (52.7%) treatment. Grain yield in 75% water requirement treatment was not significantly different from yield in full irrigation treatment. Application of nitrogen fertilizer significantly reduced grain yield, grain protein and seeds per pod whilst increased chlorophyll content only. The 100% irrigation requirement treatment showed higher evaporation form the soil in N0 than in 50% and 75% irrigation treatments in late sown pea. Leaf evapotranspiration (ET) was lower in 50% water requirement irrigation regime than in the other irrigation treatments. Water use efficiency (WUE) which was higher in the late than early sowing treatment did not differ between 50% and full irrigation treatments in N0. In conclusion, the results of the current study suggested that application of nitrogen fertilizer did not benefit pea growth and that management of irrigation regime in late sowing might improve grain yield in pea and save irrigation water in regions with limited water availability.

Groundwater sustainability: Developing a non-cooperative optimal management scenario in shared groundwater resources under water bankruptcy conditions.

Groundwater level drawdown changes the hydrological cycle and poses challenges such as land subsidence and reduction of the groundwater quality. In this study, a new approach using a simulation-optimization framework was developed for shared groundwater management under water bankruptcy conditions (where water demand is greater than the allowable discharge capacity of water resources). The novelty of this study lies in using bankruptcy rules and a game model to manage a bankrupted shared groundwater resource considering aquifer sustainability. Accordingly, groundwater flow in the aquifer was numerically simulated by a finite-differences model (MODFLOW). Then, the repeated performance code of the finite-differences model was run for different discharge scenarios, and the results were applied to develop an MLP-ANN meta-model. By coupling the meta-model with a non-dominated sorting genetic algorithm II (NSGA-II)-based multi-objective optimization model, an optimized cultivation pattern under water bankruptcy conditions was achieved. Then, six different bankruptcy methods were utilized to specify groundwater allocation between three stakeholders. To manage the water bankruptcy conditions, different scenarios considering various groundwater extraction rates and cultivation areas were defined, and the optimization model was recoded for each scenario to find the corresponding optimized cultivation pattern. To consider the competition between stakeholders for groundwater extraction, a non-cooperative 3-player game was applied to achieve a compromise for different combinations of management strategies, which maximizes the profit and yields the best cultivation scenario. Applicability of the proposed methodology was investigated in an aquifer system located in Golestan Province, Iran, including three regions (Minudasht, Azadshahr, and Gonbade-kavus). Results show that the proposed method is capable of managing the bankruptcy conditions by generating greater agricultural profit and reducing groundwater drawdowns.