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.

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.

Stream nitrogen concentrations significantly impact nitrogen loads and greenhouse gas emissions, but their spatiotemporal heterogeneity and human influences remain highly uncertain. This study thoroughly explored the spatiotemporal variations in stream nitrogen concentrations in a typical headwater watershed in South China. Spatially distributed measurements were conducted during 2020–2022, and mathematical modeling was implemented based on incorporating these data. More than 4,400 data points were collected for water temperature and concentrations of ammonium nitrogen (NH₄‐N), nitrate nitrogen (NO_x‐N), dissolved total nitrogen (DTN), total nitrogen (TN), and dissolved oxygen. Results showed that NO_x‐N was the largest component of TN, with average concentrations of 1.20 and 1.66 mg L⁻¹, respectively. The stream N₂O concentration could be predicted using NH₄‐N and NO_x‐N concentrations via the Michaelis‐Menten equation. Significant downstream decreases in NH₄‐N, NO_x‐N, DTN, and TN concentrations were identified in the largest river in the watershed, and clear spatial differences in these nitrogen concentrations existed among the three main rivers. Clear seasonal and annual variations in stream nitrogen concentrations were observed. NH₄‐N, NO_x‐N, DTN, and TN concentrations correlated with cumulative precipitation from the preceding 8–12 days, while stream N₂O concentrations correlated over 13–20 days. Stream N₂O concentrations and emissions averaged 12.77 nmol L⁻¹ and 1.12 nmol m⁻² s⁻¹, respectively, and were lower in summer than in other seasons. Upstream tea plantations, villages, and adjacent agricultural lands significantly affected nitrogen concentrations, while overflow dams did not. These findings highlight nitrogen cycle's complexity and the need for high‐resolution data to guide effective watershed management.

Throughfall makes up the major portion of understory rainfall, and thereby plays a vital role in regulating the hydrological and biogeochemical processes in forest ecosystems. The aim of this study was to explore the alterations in throughfall and the associated chemical composition (Ca²⁺, Na²⁺, K⁺, Mg²⁺, H⁺, SO₄²⁻, NO₃⁻, Cl⁻, and F⁻) under Quercus acutissima Carruth. and Broussonetia papyrifera (L.) L’Her. ex Vent. trees, in relation to trunk distance and rainfall characteristics. Event-based measurements were carried out from April to December 2018 in a subtropical forest of eastern China. The throughfall amount (T_F) and throughfall ratio (T_F%) of Q. acutissima (35.7 mm, 83.0%) were higher than those of B. papyrifera (32.1 mm, 74.7%). Although no significant species differences in the ion concentrations of throughfall were detected, almost all ions (Ca²⁺, Na²⁺, K⁺, Mg²⁺, H⁺, SO₄²⁻, NO₃⁻, and Cl⁻) were enriched after passing through the canopies of the two tree species. T_F and T_F% increased with increasing distance from the trunk, while the concentrations of most ions in throughfall increased, since the trunk was approximated. Regression analysis and redundancy analysis revealed that rainfall amount, duration and intensity exerted significant impacts on throughfall generation and ion concentrations, and the antecedent dry period had a notable influence only on ion concentrations. Our findings indicated that forest canopy and rainfall characteristics play an important role in the alterations in throughfall and the associated chemical compositions.

Climate change has caused clear shrinkage or dramatic water level fluctuation of lakes in arid and semi-arid regions, while the underlain mechanisms remain unclear. The joint lake and basin investigations (spatial) and long-term studies (temporal) are urgently needed. In this study, the SWAT+ model with a revised lake module has been used to jointly simulate the water cycle of the largest saline lake in China and its collecting basin (Qinghai Lake Basin, QLB) at the hundred-year scale. Results show that the modeling framework consisted of the revised SWAT+, reanalysis data, and reconstructed water level based on lake gravity core performed quite well (NSE > 0.6 for lake water level) in simulating the hydrological processes of QLB at the hundred-year scale (1910 – 2018). Temporally, decadal variations of hydrological components in QLB decreased in sequence of precipitation (46.33 mm), lateral flow (26.85 mm), evapotranspiration (16.03 mm), snowmelt (10.44 mm), groundwater flow (5.66 mm), and overland flow (1.18 mm). Spatially, the precipitation, water yield, lateral flow, and groundwater flow in upstream regions of QLB, where the precipitation amount was small, were most sensitive to climate change. And sensitive regions of snowmelt were basically opposite to those of precipitation; Evapotranspiration was sensitive to climate change in regions covered with a mixed land of bare land and swamp. The long-term water level decrease of Qinghai Lake during 1928 – 2003 was mainly driven by variations of river runoff and lake surface evaporation, although their influences on the water level decrease were opposite; the clear water level increase since 2004 was dominated by river runoff change. The study provided a modeling framework capable of reproducing the hundred-year hydrological cycles of lake basins in semi-arid regions, which is an effective way of elucidating the driving factors and mechanisms underlying the dramatic variations in lake water level.