Wheat production under rainfed conditions is restrained by water scarcity, elevated temperatures, and lower nutrient uptake due to possible drought. The complex genotype, management, and environment (G × M × E) interactions can obstruct the selection of suitable high yielding wheat cultivars and nitrogen (N) management practices prerequisite to ensure food security and environmental sustainability in arid regions. The agronomic traits, water use efficiency (WUE), and N use efficiencies were evaluated under favorable and unfavorable weather conditions to explore the impacts of G × M × E on wheat growth and productivity. The multi-N rate (0, 70, 140, 210, and 280 kg N ha⁻¹) field experiment was conducted under two weather conditions (favorable and unfavorable) using three wheat cultivars (AUR-809, CHK-50, and FSD-2008) in the Pothowar region of Pakistan. The experiments were laid out in randomized complete block design (RCBD), with split plot arrangements having cultivars in the main plot and N levels in the subplot. The results revealed a significant decrease in aboveground biomass, grain yield, crop N-uptake, WUE, and N use efficiency (NUE) by 15%, 22%, 21%, 18%, and 8%, respectively in the unfavorable growing season (2014–2015) as compared to favorable growing season (2013–2014) as a consequence of less rainfall and heat stress during the vegetative and reproductive growth phases, respectively. FSD-2008 showed a significantly higher aboveground biomass, grain yield, crop N-uptake, WUE, and NUE as compared to other wheat cultivars in both years. Besides, N₁₄₀ appeared as the most suitable dose for wheat cultivars during the favorable growing season. However, any further increase in N application rates beyond N₁₄₀ showed a non-significant effect on yield and yield components. Conversely, the wheat yield increased significantly up to 74% from N₀ to N₇₀ during the unfavorable growing season, and there was no substantial difference between N₇₀–N₂₈₀. The findings provide opportunities for maximizing yield while avoiding excessive N loss by selecting suitable cultivars and N application rates for rainfed areas of Pothowar Plateau by using meteorological forecasting, amount of summer rainfall, and initial soil moisture content.

Extreme temperature events as a consequence of global climate change result in a significant decline in rice production. A two-year phytotron experiment was conducted using three temperature levels and two heating durations to compare the effects of heat stress at booting, flowering, and combined (booting + flowering) stages on the production of photosynthates and yield formation. The results showed that high temperature had a significant negative effect on mean net assimilation rate (MNAR), harvest index (HI), and grain yield per plant (YPP), and a significant positive effect under treatment T₃ on mean leaf area index (MLAI) and duration of photosynthesis (DOP), and no significant effect on biomass per plant at maturity (BPP_M), except at the flowering stage. Negative linear relationships between heat degree days (HDD) and MNAR, HI, and YPP were observed. Conversely, HDD showed positive linear relationships with MLAI and DOP. In addition, BPP_M also showed a positive relationship with HDD, except at flowering, for both cultivars and Wuyunjing-24 at combined stages. The variation of YPP in both cultivars was mainly attributed to HI compared to BPP_M. However, for biomass, from the first day of high-temperature treatment to maturity (BPP_T-M), the main change was caused by MNAR followed by DOP and then MLAI. The projected alleviation effects of multiple heat stress at combined stages compared to single-stage heat stress would help to understand and evaluate rice yield formation and screening of heat-tolerant rice cultivars under current scenarios of high temperature during the rice-growing season.

The intensification of extreme rainfall events under changing climate regimes has heightened concerns over nutrient losses from paddy agriculture, particularly nitrogen (N), a primary contributor to non-point source pollution. Despite advances in drainage management, limited studies have integrated probabilistic rainfall modeling with N transport simulation to evaluate mitigation strategies in rice-based systems. This study addresses this critical gap by coupling the Log-Pearson Type III (LP-III) distribution with the DRAINMOD-N II model to simulate N dynamics under varying rainfall exceedance probabilities and drainage design configurations in the Kunshan region of eastern China. The DRAINMOD-N II showed good performance, with R² values of 0.70 and 0.69, AAD of 0.05 and 0.39 mg L⁻¹, and RMSE of 0.14 and 0.91 mg L⁻¹ for NO₃⁻-N and NH₄⁺-N during calibration, and R² values of 0.88 and 0.72, AAD of 0.06 and 0.21 mg L⁻¹, and RMSE of 0.10 and 0.34 mg L⁻¹ during validation. Using around 50 years of historical precipitation data, we developed intensity–duration–frequency (IDF) curves via LP-III to derive return-period rainfall scenarios (2%, 5%, 10%, and 20%). These scenarios were then input into a validated DRAINMOD-N II model to assess nitrate-nitrogen (NO₃⁻-N) and ammonium-nitrogen (NH₄⁺-N) losses across multiple drain spacing (1000–2000 cm) and depth (80–120 cm) treatments. Results demonstrated that NO₃⁻-N and NH₄⁺-N losses increase with rainfall intensity, with up to 57.9% and 45.1% greater leaching, respectively, under 2% exceedance events compared to 20%. However, wider drain spacing substantially mitigated N losses, reducing NO₃⁻-N and NH₄⁺-N loads by up to 18% and 12%, respectively, across extreme rainfall scenarios. The integrated framework developed in this study highlights the efficacy of drainage design optimization in reducing nutrient losses while maintaining hydrological resilience under extreme weather conditions.