Hydrological Processes最新文献

Flooded rice ecosystems are typically maintained with a 5–10 cm water layer, which strongly influences surface energy and water balance processes. As evapotranspiration (ET) is a crucial part of surface water and energy cycles, understanding its response to ponding depth is essential for water resource management. A two-year experiment was conducted using lysimeters to investigate the seasonal dynamics of ET under different ponding depths: shallow flooding (SF, 0–2 cm), medium flooding (MF, 5–7 cm), and deep flooding (DF, 8–10 cm). Results showed that evaporation (E) gradually decreased with increasing water depth, whereas transpiration (Tr) first increased and then declined. Seasonal ET followed the order MF (511.65 mm) > DF (498.55 mm) > SF (484.25 mm), consistent with the pattern observed for grain yield, while no significant differences in water use efficiency were detected among treatments. Daytime ET rates varied across the growth stages, with the order SF > MF > DF in the early stages and MF > SF in the middle and late stages. This shift was related to the partitioning of E and Tr and their distinct responses to water depth. Structural equation modelling analysis indicated that radiation was the dominant meteorological driver of ET through direct effects. LAI exerted an important indirect influence. Water depth affected microclimate and crop physiological parameters, resulting in different responses of E and Tr. E was exponentially correlated with water temperature and declined with increasing ponding depth, whereas Tr exhibited a logarithmic relationship with canopy conductance, as determined by LAI and leaf stomatal conductance, in the order of MF > SF. This study provides insights into the effects of irrigation management on rice water use and the environmental and biophysical controls that influence rice ET.

Both freeze–thaw cycles and vegetation cover changes significantly influence slope runoff and sediment yield in permafrost regions. Nevertheless, their synergistic mechanisms remain inadequately quantified and poorly understood. Through simulated rainfall experiments conducted on slopes in the source region of the Yangtze River, this study investigated the impacts of vegetation cover variation combined with soil freeze–thaw processes on runoff and sediment yield from typical alpine meadows and alpine steppes. The results indicate that: (1) The three factors of vegetation type and coverage, as well as rainfall intensity, jointly shape the relationship between precipitation runoff and sediment. Alpine meadows showed stronger erosion resistance than alpine steppes. (2) The freeze–thaw process of soil dominated the runoff and sediment generation: Runoff volume across varying vegetation coverage followed the order: autumn freezing period > spring thawing period > summer thawed period. However, sediment yield was highest during the spring thawing period, followed by the autumn freezing period and summer thawed period. (3) For higher vegetation coverage, freeze–thaw effects had a greater impact on runoff than on sediment yield; on the contrary, under low-coverage vegetation, the freeze–thaw process influenced sediment yield more than runoff; These findings provide theoretical guidance for achieving integrated soil erosion regulation goals in alpine grassland ecosystems within the Qinghai–Tibet Plateau under climate change.

Understanding rainfall partitioning and streamflow generation processes has become indispensable due to the increasing frequency of hydrological extremes globally. River catchments in the tropics are particularly vulnerable to changing characteristics of rainfall. Thus, decoding rainfall partitioning into pre-event and event water becomes more critical in tropical catchments where runoff generation processes are often poorly understood. In this context, the present study aims to understand the runoff generation processes in the Vamanapuram River—a humid tropical forested experimental catchment in the southwestern Ghats, India—utilising high-resolution (30-min) hydrological measurements. Data from 78 and 76 storm events (during 2022 and 2023) were used for storm hydrograph separation using the conductivity mass balance method at Kallar River Gauging Station (KRGS) and Chettachal River Gauging Station (CRGS), respectively. Both KRGS and CRGS are found to be sub-surface dominated catchments irrespective of season, with pre-event water domination in 96% (KRGS) and 88% (CRGS) of the storm events. The averaged (volume-weighted) pre-event water fraction (PEWF(avg)) over the storm duration, and at the peak of the storm hydrograph (PEWF(peak)), are PEWF metrics used for understanding the dominant runoff generation processes. The seasonality in the mean Pre-Event Water Fraction metrics showed higher values during the dry period and lower values in the wet period. The mean PEWF(avg) decreased from 0.78 (in the upstream KRGS) to 0.75 (in the downstream CRGS); similarly, the mean PEWF(peak) decreased from 0.76 to 0.73. Pearson rank correlation and dominance analysis showed that (i) the storm size and mean precipitation intensity are the key storm properties and (ii) 5-day antecedent rainfall and initial groundwater levels are the key antecedent wetness conditions that control the variability in the PEWF.

Spatiotemporal variability of available soil moisture (ASM) complicates soil water resource management and vegetation restoration in the Chinese Loess Plateau (CLP). Our objectives were to investigate the spatial variability and temporal stability of ASM at different slope positions and estimate deep and mean profile ASM using ASM from representative soil layers. The mean relative difference (MRD), associated standard deviation of relative difference (SDRD), index of temporal stability (ITS), mean absolute value of bias error (MABE) and root mean squared error (RMSE) were used to identify representative soil layers. The estimation accuracy was verified by absolute error (AE), relative error (RE), RMSE and Nash-Sutcliffe efficiency coefficient (NSE). The results suggested that (1) the dynamics of ASM exhibited complexity. The ASM for the top, middle and bottom slopes varied within the range of 5.76%–14.24%, 5.85%–10.74% and 3.38%–6.69%, respectively. (2) The correlations of ASM amongst different soil layers varied across slope positions. The highly significant positive correlation was observed below 200 cm soil layer at the bottom slope (r = 0.96, p < 0.001). (3) The ASM estimation at the middle slope was more reliable than other slope positions. The representative soil layer (600–700 cm) explained 78.50% and 94.00% variability of deep and mean profile ASM, respectively. (4) The estimation for mean profile ASM was more accurate than deep ASM. The RMSEs were 1.95% and 1.84%, 1.92% and 0.94%, 2.70% and 1.84% for deep and mean profile ASM at the top, middle and bottom slopes, respectively. This work proposes an indirect method for determining mean profile ASM in the fragmented terrain area on the CLP; it also can reliably estimate deep soil moisture that cannot be measured due to the presence of Calcaric Regosol.

Variations in water coverage are of great importance to ecological systems. After the water stored in Three Gorges Reservoir was filled in 2003, the water area in the mid-lower Yangtze River was affected. To reveal the variation of water coverage in 2003–2022 in the middle and lower Yangtze River and its affecting factors, this study rebuilt continuous datasets based on Landsat and MODIS images, then extracted a long time-series water coverage using the Adaptive Step Length–Quantum-Behaved Particle Swarm Optimisation–Random Forest (ASL-QPSO-RF) approach with an accuracy of more than 90%. Based on the extracted water coverage, from 2003 to 2022, the water coverage decreased by 10%, 24%, and 7% for effective, seasonal, and permanent water bodies, respectively. For the lower river, during 2003–2022, the coverage declines of permanent water bodies in the lower river dominated that in the mid-lower Yangtze River with a contribution of 70% and were significantly affected by the deepening of the channel in the lower river (increased by 27%) with a coverage reduction of 145 km² for a 1-m deeper channel. During 2003–2012, that deepening was both related to the decline of sediment transport and the increase in sand mining, with contributions of 57% and 43%, respectively. In addition, the reduction of sand mining in the lower river weakened the coverage decline of the water body and the deepening of the channel during 2017–2022. For the middle river, the decline in the coverage of seasonal water bodies in the middle river dominated that in the mid-lower Yangtze River, with a contribution of 108%. Considering that the guaranteed channel depth increased by 37% in the middle river, the coverage decline of the effective water body in the middle river was mainly related to the significant deepening of the channel in the middle river (1 m deeper, a reduction of 184 km²) during 2003–2022. The deepening of the channel in the middle river was dominated by a significant decline in sediment transport during 2003–2012. These results provide a reference for better management of the mid-lower Yangtze River.

Quantifying weathering-driven carbon sinks in human-impacted subtropical basins remains a critical gap. In the carbonate-dominated, densely populated Xiangjiang River Basin, this study tracked hydrochemistry through two hydrological years to partition solute sources and constrain CO₂ consumption at high resolution. Findings revealed precipitation total dissolved solids (TDSs) spanning 1.7–201.4 mg/L, where Ca²⁺, K⁺, SO₄²⁻ and NO₃⁻ constituted the principal ionic constituents and the values for Xiangjiang River water were 25.8–183.1 mg/L, with Ca²⁺ and HCO₃⁻ as the dominant ions. The chemical weathering contributions from carbonate rock (62.2%) and silicate rock (14.5%) were estimated using a forward model, indicating that carbonate rock weathering is the primary source of the Xiangjiang River solutes. The average annual weathering fluxes of carbonate and silicate rocks in the Xiangjiang River were 21.6 and 3.4 t/km²/year, respectively, with corresponding CO₂ consumption rates of 293.1 × 10³ and 81.0 × 10³ mol/km²/year. This study provides the first high-resolution quantification confirming that the subtropical monsoon climate of the Xiangjiang River Basin generates intermediate weathering-driven CO₂ consumption rates, positioning its carbon sink capacity between that of arid/plateau regions and tropical zones. The findings establish hydrochemical baselines for the Xiangjiang and offer quantitative benchmarks for regional water-resource management and carbon-cycle modelling under intensifying anthropogenic pressures.