Climate warming increases the frequencies of drought and excessive precipitation, and the influencing mechanisms and magnitudes of these extreme events on the water and carbon cycles of different crops still remain unclear. In this study, single‐point simulations for six irrigated and rain‐fed crops and global simulation were combined to comprehensively investigate the impacts of drought and excessive precipitation on evapotranspiration (ET), irrigation, net ecosystem exchange (NEE), and yields of crops. Results illustrated that the AgroIBIS‐based CLM5 simulated ET and NEE dynamics well for rice, corn, winter wheat, soybeans, sugar beets, and potatoes after parameter optimization. The impacts of abnormal precipitation on ET, NEE, and crop yield were larger at rain‐fed sites than at irrigated sites. The influencing magnitudes of precipitation shortage on ET depended on the occurring time of drought events relative to the growth stages of crops. Precipitation shortage (excessive precipitation) reduced (increased) ET and net carbon uptake by 4%–19% (4%–7%) and 3%–15% (1%–6%) compared to normal precipitation years at irrigated sites, while corresponding decrease (increase) was 7%–35% (24%–27%) and 19%–48% (12%–34%) at rain‐fed sites. The proportional influencing magnitudes of precipitation shortage on ET, NEE, and yield increased sequentially for rain‐fed crops. At the global scale, the simulated theoretical irrigation in extremely dry years was 25%–75% larger than that in normal precipitation years, and the actual irrigation was 3.5–4.0 times as large as the simulated theoretical value at irrigated sites, implying that drought intensified water resource shortage through excessive irrigation besides precipitation shortage.

Climate extremes, such as heatwaves and droughts, significantly impact terrestrial ecosystems. This study investigates the influence of compound hot–dry (CHD) events on vegetation productivity in northern East Asia. Four of the most widespread CHD events occurring during the summer from 2003 to 2019 were selected as the focus of this research. We first verified the performance of the Community Land Model version 5 (CLM5) in the region and then conducted factor-controlled experiments using CLM5 to assess the effects of different climate factors on gross primary productivity (GPP) changes during CHD events. Our results show that vegetation productivity exhibits greater sensitivity to CHD events within the transitional climatic zone (TCZ) than in other affected areas. In grassland areas within the TCZ, precipitation deficit is the primary factor leading to the decrease in GPP (explaining 56%–90% of GPP anomalies), while high temperatures serve as a secondary detrimental factor (explaining 13%–32% of GPP anomalies). In high-latitude forests outside the TCZ, high temperature has a more significant impact on suppressing GPP, while the decrease in soil moisture has a synchronously negligible impact on GPP. There are differences in the effects of high solar radiation on grasslands and woodlands during CHD events. It was observed that high radiation benefits trees by increasing the maximum carboxylation rate (V_cmax) and maximum electron transport rate (J_max), as well as enhancing photosynthesis, but has a negligible impact on grasses. Furthermore, this study highlights the potential for compound events to impact vegetation productivity more than expected from individual events due to confounding nonlinear effects between meteorological factors. More than 10% of the negative anomalies in GPP during two CHD events in 2017 and 2010 were attributed to these nonlinear effects. These research findings are significant for understanding ecosystem responses to climate extremes and their influence on carbon cycling in terrestrial ecosystems. They can also contribute to more precisely evaluating and predicting carbon dynamics in these regions.

Lakes are important surface water bodies, and ongoing climate change is a growing threat to the hydrological cycle and water resource availability of lakes in arid regions. Accurately estimating different drivers’ contributions to lake water volume can enhance our understanding of lake variations in arid regions. In this study, we combined the land surface model and hydrological model, as well as statistical methods, to analyze the spatiotemporal heterogeneity of lake area changes and the factors affecting these changes during the past decades in Bosten Lake, Ulungur Lake, Ebinur Lake, and Sayram Lake, which are located in a typical dry region in China. The study revealed that the average amounts of river inflow, TWVF, lake ice sublimation, lake surface precipitation, and river outflow in the four lakes were 17.41 × 10⁸ m³ yr⁻¹, 6.60 × 10⁸ m³ yr⁻¹, 0.41 × 10⁸ m³ yr⁻¹, 0.98 × 10⁸ m³ yr⁻¹, and 9.12 × 10⁸ m³ yr⁻¹, respectively. We found that river inflow is the dominant factor affecting changes in open lake areas, while lake surface precipitation is the main factor affecting changes in closed lake areas. Our findings suggest that the main factors dominating the variability of lake water volume differ in different phases and lake types.