Component Of Hydrological Cycle Research Articles

Analysing the Effects of Atmospheric Teleconnections on Streamflow Regime in the Eastern Black Sea Basin in Türkiye

Analysing the variations in hydrological cycle components is essential for water resources planning and management. In this study, the relationship between the streamflow data belonging to five discharge gauging stations in the Eastern Black Sea Basin in Türkiye and the Arctic Oscillation (AO), East Atlantic-Western Russia (EAWR), North Atlantic Oscillation (NAO) and North Sea Caspian Pattern (NCP) was investigated. For this purpose, Spearman’s correlation test, ensemble empirical mode decomposition (EEMD) and relative importance analysis were used. Accordingly, Spearman’s correlation coefficients were calculated between raw streamflow data, decomposed streamflow data via EEMD and atmospheric teleconnections. Then, the relative importance analysis was applied to determine the atmospheric teleconnections’ influences on streamflow data. The findings showed that the relationship between raw streamflow data and atmospheric teleconnections is generally more significant and negative in the winter and spring. Furthermore, it was observed that the linkage between the decomposed streamflow data and atmospheric teleconnections could differentiate. Although no significant correlation between atmospheric teleconnections and raw streamflow data was detected in some months, significant correlations were detected between atmospheric teleconnections and decomposed streamflow data. This reveals the importance of examining the relationship between atmospheric teleconnections and streamflow data for different periods. The relative importance analysis revealed that the influence of atmospheric teleconnections on streamflow data could change from station to station and from component to component. This study showed that investigating the effects of atmospheric teleconnections on streamflow data for different components and periods is important.

The contributions of Indigenous People's earth observations to water quality monitoring

Indigenous Knowledge, observations and understandings of Earth processes are not sufficiently included in global Earth Observations. Drawing on the results obtained during a 3-day hackathon event, we present evidence, best practices and recommendations to water quality organizations seeking to engage and share information with Indigenous communities. The hackathon event revealed three key findings: First, Indigenous Peoples report precise and accurate observations of changes in various Earth systems, particularly the hydrological cycle. Second, this information can significantly enhance global Outreach and Engagement efforts, aiding in the understanding of hydrological cycle components, water quality, mapping water courses, and monitoring and mitigating the effects of climate change (i.e., floods, droughts, etc.). Third, enabling Indigenous Peoples to contribute their scientific knowledge and utilize Earth Observations is crucial for the protection of other vital components of the water cycle. We addressed two crucial questions: What opportunities exist to include Indigenous Knowledge into Earth Observations, and what are the main challenges in doing so?

GROUNDWATER AND ECOSYSTEMS: UNDERSTANDING THE CRITICAL INTERPLAY FOR SUSTAINABILITY AND CONSERVATION

Groundwater, a vital component of the Earth's hydrological cycle, plays a central role in supporting ecosystems worldwide. This research paper explores the multifaceted relationship between groundwater and ecosystems, emphasizing its critical importance for the health and resilience of both aquatic and terrestrial habitats. The paper delves into the ecosystem services provided by groundwater, including habitat provision, water purification, and nutrient cycling. The intricate connection between groundwater availability and biodiversity is examined, highlighting the significance of groundwater in sustaining diverse habitats such as wetlands, springs, and riparian zones. Additionally, the research investigates the role of groundwater in hydrological processes, particularly its contribution to base flow in rivers and the sustenance of stream ecosystems during dry periods. Anthropogenic factors leading to groundwater depletion, such as over-extraction for agriculture and urbanization, are analyzed, emphasizing the far-reaching consequences for ecosystems. The paper proposes strategies for sustainable groundwater management, including monitoring, water-efficient agricultural practices, and nature-based solutions. It underscores the importance of policy development, community engagement, and international collaboration in preserving groundwater-dependent ecosystems. Looking towards the future, the research identifies challenges and opportunities, including uncertainties related to climate change, population growth, and global water trade. It suggests areas for further research, such as integrated hydrological models and studies on social-ecological systems, and emphasizes the need for innovative policies that prioritize ecosystem health. In conclusion, the research emphasizes the critical need for sustainable groundwater management practices, recognizing groundwater as a finite resource essential for maintaining biodiversity, ecosystem functionality, and human well-being. KEYWORDS: Biodiversity, Ecosystems, Groundwater, Sustainability, Water Management.

Dynamic Changes in Terrestrial Water Balance Using Remote Sensing on the Loess Plateau

In recent decades, the water cycle process in the Loess Plateau has undergone drastic changes under the influence of anthropogenic disturbance and climate variability. The Loess Plateau has been greatly affected by human activities and climate change, and the dynamics of water balance and its key influencing factors remain unknown in this region. To deepen our understanding of water resource status in the Loess Plateau, we analyzed the dynamic changes in the hydrological cycle components and terrestrial water balance via remote sensing during the 2001–2020 period. Moreover, we also discussed the dominant factors affecting the terrestrial water balance. The results indicate that precipitation and ET exhibited increasing trends, with upward rates of 2.56 mm/yr and 5.27 mm/yr, respectively. Spatially, the annual average precipitation and ET showed increasing trends from the north to south. Precipitation in 62.05% of the entire region presented a significant upward trend, with a change rate of 0~2 mm/yr, and the annual change rate of ET in a range of 0~30 mm/year accounted for 89.12%. The runoff exhibited a fluctuating and significantly upward trend during the 2000–2022 period, with a change rate of 3.92 × 108 m3/yr, and was relatively large in the middle reach of the Yellow River. The annual average water consumption in the upper reach of the YRB presented a significant decreasing trend, with a downward rate of −0.06 × 108 m3/yr from 2001 to 2020, and yet it displayed a significant increasing trend in the middle and lower reaches of the YRB with the upward rate of 0.07~0.11 × 108 m3/yr. Based on the principle of water balance, the recharge amount was calculated at less than the discharge amount during the 2001–2020 period, and the difference between recharge and discharge is gradually expanding, with a change rate of −3.72 × 108 m3/yr. The spatial distributions of TWSC revealed that the eastern region was in an imbalanced state, while the western region was in a relatively balanced state. Terrestrial water balance changes were mainly affected by climate factors and human disturbance, and land use/cover change was the dominant factor. The results will be of great significance for optimizing water resource management and formulating various water-saving strategies in the Loess Plateau.

Widespread increase in plant transpiration driven by global greening

Global plant transpiration (PT) is a crucial component of the Earth's hydrological cycle and plays a significant role in regulating the exchange of water and energy between the land surface and the atmosphere. However, the long-term trend and the underlying driver of global PT remain unclear due to the significant uncertainties in estimating PT on a global scale. This study uses two sub-Mixture Density Networks (MDNc and MDNa) to predict vegetation canopy resistance (rc) and aerodynamic resistance (ra), then the predicted rc and ra are imported into the Penman-Monteith-Leuning (PML) model to simulate PT. The observed PT at 112 SAPFLUXNET sites are used to validate the performance of hybrid MDN-PML model. The verified MDN-PML model is further applied to map the spatial distribution of global PT and reconstruct a long-term (1990–2020) global PT dataset. The results indicate that the long-term average global PT is 397.2 ± 63.1 mm. During the period 1990–2020, the global PT exhibit a significant upward trend (0.79 ± 0.28 mm/year (P < 0.05)), which equates to a 6.0% increase compared with the long-term average global PT. A widespread trend of elevated PT is observed in approximately 70% of the global land surface. The trend attribution analysis results show that the change in leaf area index (LAI) can explain 66.2% of the global PT trend, indicating that elevated LAI due to global greening is the dominant factor contributing to the upward trend in global PT. The elevated LAI can be largely attributed to the CO2 fertilization effect induced by elevated atmospheric CO2 concentration. Additional analysis reveals that the increased global PT is more sensitive to CO2 fertilization effect in high LAI areas than in low LAI areas. Projected climate scenarios indicate that global land surface PT will continue to rise from 2023 to 2100, and the rate of increase in the future will be higher than in historical periods. The rising rates of global PT under the three Representative Concentration Pathway scenarios (RCP) 2.6, RCP4.5, and RCP8.5 climate change scenarios are 0.86 mm/year, 1.16 mm/year, and 1.45 mm/year, respectively, during the period 2023–2100. Our results highlight the impact of global change and vegetation greening on the global PT and hydrological cycle. This study is of great significance for the scientific response to the challenges of climate change for regional water resource management.

Does ERA5-land capture the changes in the terrestrial hydrological cycle across the globe?

Changes in the terrestrial hydrological cycle determine the future water availability across the globe with profound impacts in different facets of society. Precise estimation of such changes is vital for the effective implementation of water management policies. Among the numerous data products that describe the hydrological cycle components, ERA5-Land is one of the most increasingly used dataset. Still, there has been no assessment of its ability capacity to represent the water cycle shifts variability over land. This study endeavors to bridge this gap by comparing the magnitude and direction of change in precipitation minus evaporation (P—E) and runoff, as estimated globally by the ERA5-Land data product. Our findings reveal significant inconsistencies in the changes identified, with the climatological mean of P—E decreasing more substantially than runoff for numerous regions. Consequently, ERA5 presents a declining water availability for most of the regions, but the magnitude of change is incompatible to the change between P—E and runoff. To further validate, the estimates provided by the ERA5-Land product, two different hydrologic models (TerraClimate and Global Land Data Assimilation System, GLDAS-Noah) are also utilized. TerraClimate demonstrates a more reasonable alignment between changes in P—E and runoff, followed by GLDAS-Noah, particularly for the arid regions lying in the parts of Northern Africa and Southern Asia, the European continent, and the northern parts of Asia. Inconsistencies remain high for the tropical regions for both data products. Still, the estimates of change in water availability are better represented by the hydrologic model-based data sources for most parts of the globe, especially for the regions with low precipitation, such as the regions with arid and continental climates. Our results imply that ERA5-Land should be used with extreme caution when assessing the long-term changes in the terrestrial water cycle. Additionally, pinpointing the regions of the highest bias can help to improve the hydrological coupling of ERA5-Land in future versions of the reanalysis.

Distribution and transformation characteristics of water vapor field in the fissured rock mass and its ecological significance

Opencast mining has produced a large number of high and steep rock slopes, leading to serious safety and environmental challenges. Extreme water scarcity conditions severely impede the survival and development of natural and artificial vegetation when carrying out ecological restoration work. The water vapor field within rocks is a significant but often neglected component of the terrestrial hydrologic cycle and can provide a hidden but critical source of water for plants. However, there is a lack of understanding of the distribution characteristics of the water vapor field within rocks and the pattern of liquid water formation as well as whether it is quantitatively significant and ecologically relevant. This study conducted monitoring experiments on the water vapor field of fissured rock mass and studied the distribution and transformation characteristics of water vapor field in the fissured rock mass and its ecological significance. The results showed temperature and absolute humidity gradually decreased with horizontal depth in spring and summer, and the opposite in autumn and winter. Relative humidity increased rapidly and stabilized with horizontal depth in the spring and summer, and increased rapidly in the autumn and winter, before decreasing slightly. The driving force of water vapor migration is the water vapor partial pressure gradient. In spring and summer, water vapor migrated from air along the fissures to the deep part of the rock mass, while the opposite was true in autumn and winter. While the water vapor migrated through the fissured rock mass, water vapor saturation zones would be produced locally, where potential condensate is generated. The fissure network functioned as a sustained system of water supply pipelines, and the plant roots that grew into the fissures could absorb the condensate, continuously supplying the growth and development of the rock slope plants. This study provides a comprehensive understanding of the rock water vapor field and its effects on ecosystems in arid and semi-arid areas, which can guide the restoration of ecosystems on rock slopes.

Analysis of the correlation between land use and surface runoff in a Brazilian savanna basin

– Since the 1980s, the Brazilian savanna (Cerrado) has been suppressed to make space for agricultural production, mainly soybean, corn, and cotton. This savanna strategically contains important South American river sources – Paraná, Paraguai, São Francisco, Araguaia, Tocantins, and tributaries of the Amazon River. Land use and cover are conditioning factors in generating the hydrological cycle components, notably surface runoff. Thus, this study aimed to evaluate spatial and temporal land use changes and their correlations with surface runoff in the Grande River basin. The study area is a relevant São Francisco River sub-basin, covering part of the Urucuia Aquifer System, encompassing the dry forest and savanna biomes. The inputs included landscape ecology metrics, land use time series from 1990 to 2020, and water flow values near the basin outlet. The landscape metrics were modeled with the R software landscapemetrics package. Aside from the time series trend, the correlation between land use, land cover, and flow variations was also evaluated through statistical tests – Mann-Kendall, Sen's slope, Pittitt, and rho Spearman. Changes were observed in areas covered by forest, savanna, and grassland formations. The areas presented reduction from 22,121 km2, 27,889 km2, and 15,366 km2 to 9916 km2, 27,870 km2, and 5666 km2, respectively. On the other hand, there was an increase, especially in rainfed agriculture (from 5241 km2 to 20,856 km2) and, more recently (2005), in irrigated agriculture (from 94 km2 to 1362 km2). Results show a reduction in the fragments of native vegetation (from 2,235 km2 to 1794 km2) and an increase in the fragments of agricultural activities (from 678 km2 to 1081 km2). For most classes, the change point was identified as the year 2005. A strong direct correlation was observed between the average and minimum flows (Q90) with forest and grassland formations. In comparison, an inverse correlation was noticed between pasture, urban infrastructure, rainfed agriculture, and irrigated agriculture classes.

Drought cascade lag time estimation across Africa based on remote sensing of hydrological cycle components

Droughts in Africa have a disproportionate detrimental influence on food security, water supply, social equilibrium and the economy compared to other regions in the World. Crop growth is principally rain-fed with highly seasonal rainfall regimes over most of the Continent. Hydraulic infrastructure and harvest storage are scarce. Drought is primarily initiated by a lack of precipitation, and it spreads slowly to soil moisture, vegetation, streamflow, and groundwater, affecting the entirety hydrological processes across the landscape. This is called drought propagation and it is often characterized within a cascade framework linking the different types of droughts in sequence. In this study we perform continental-scale analysis of the drought cascade over the African Continent using remote sensing data from multiple sources. We examine the spatio-temporal variation of drought types. The drought cascade elements include precipitation, normalized difference vegetation index, total water storage, and surface soil moisture. Drought characteristics and the propagation time lag between different drought types are assessed over Africa. Time series analyses are conducted on the drought indices in order to estimate the behavior of each type of drought across twenty-three basins. Consistent propagation behavior is observed at continental and basin scales. The drought cascade begins with persistent precipitation deficit and translates instantaneously to soil moisture deficit, after one month to vegetation and after two months to total water storage of the hydrological system.

Improving the accuracy of reconstructed terrestrial water storage during the GRACE/GRACE-FO gap based on a new variable filter reconstruction model

ABSTRACT Terrestrial water storage (TWS) is a fundamental component of the global hydrological cycle. Understanding changes in TWS is essential for assessing the characteristics of drought and flood events in a region. However, the discontinuity between Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) severely affects and limits their applicability in long-term hydrological studies. In this study, a new variable filter reconstruction model (NVFRM) is proposed to reconstruct the TWS anomaly (TWSA) by combining the Gamma test (GT) and Long short-term memory (LSTM) neural network. The research findings reveal that the TWSA reconstructed by the NVFRM is consistent with the GRACE-FO during the testing period (June 2018–December 2020). It shows that the Pearson correlation coefficient (PR), Nash-Sutcliffe efficiency coefficient (NSE), and root mean square error (RMSE) are 0.91, 0.81, and 4.90 cm, respectively, which demonstrates the reliability of the NVFRM. More importantly, four drought events are identified by the drought severity index (DSI) derived from the reconstructed TWSA, including August 2003–April 20 April 200420 April 200411–September 20 June 2011,20 June 201118–September 2018, and September 2019–December 2019, respectively. Flood events are monitored based on the flood potential index (FPI), which is calculated by using the reconstructed TWSA and precipitation. Flood events in the Poyang Lake Basin are characterized by a high FPI index of 0.58, 0.52 and 0.32 in summer (June–August), indicating a greater probability of flooding. The NVFRM model proposed in this study provides an effective measure for filling the missing TWSA in regional hydrological research, which is of great significance for monitoring extreme hydrological events and facilitating disaster prevention and mitigation.

Physics-informed machine learning for understanding rock moisture dynamics in a sandstone cave

Abstract. Rock moisture, which is a hidden component of the terrestrial hydrological cycle, has received little attention. In this study, frequency domain reflectometry is used to monitor fluctuating rock water content (RWC) in a sandstone cave of the Yungang Grottoes, China. We identified two major cycles of rock moisture addition and depletion, one in summer affected by air vapour concentration and the other in winter caused by freezing–thawing. For the summer-time RWC, by using the long short-term memory (LSTM) network and the SHapley Additive exPlanations (SHAP) method, we find relative humidity, air temperature and wall temperature have contributions to rock moisture, and there is a good match between predicted and measured RWC using the three variables as model inputs. Moreover, by using summer-time vapour concentration and the difference between dew point temperature and wall temperature as input variables of the LSTM network, which belongs to physics-informed machine learning, the predicted RWC has a better agreement with the measured RWC, with increased Nash–Sutcliffe efficiency (NSE) and decreased mean absolute error (MAE) and root mean square error (RMSE). After identifying the causal factors of RWC fluctuations, we also identified the mechanism controlling the inter-day fluctuations of vapour condensation. The increased vapour concentration accompanying a precipitation event leads to transport of water vapour into rock pores, which is subsequently adsorbed onto the surface of rock pores and then condensed into liquid water. With the aid of the physics-informed deep learning model, this study increases understanding of sources of water in caves, which would contribute to future strategies of alleviating weathering in caves.

Impacts of climate change and anthropogenic stressors on runoff variations in major river basins in China since 1950

Runoff is one of the main components of hydrological cycle and an important index for water resources evaluation, understanding the runoff change and their causes is vital to water resource management. In the study, we analyzed the runoff change and the impacts of climate change and land use alteration on runoff variation based on natural runoff and previous studies in China. The results showed that there was a significant increasing trend in the annual runoff during 1961–2018 (p < 0.05), with change rate of 0.4 mm/a and abrupt point at 1999 across China, climate change dominated the runoff variation with a contribution of 54 %. In previous studies, the runoff of the major basins in China had a downward trend on the whole (−0.99 mm/a) except Continental River Basin (CRB) showed an increasing trend (0.25 mm/a), the abrupt points were mainly concentrated in 1991–2000, and human activity was the leading factor of runoff change with the contribution of 54 % across China. Human activity was the dominant factor of runoff change in Songhua and Liao River Basin (SLRB), Yellow River Basin (YRB), Hai River Basin (HRB) and Pearl River Basin (PRB), the contribution was >56 %, while climate change was the dominant factor of runoff change in Huai River Basin (HuRB), CRB, and Yangtze River Basin (YZRB). Overall, there was a significant correlation between runoff and precipitation, unused land, urban and grassland in China. We concluded that runoff change and the contribution of climate change and human activities varies greatly among different basins. The findings in this work can shed light on the quantitative understanding of runoff changes in national scale and offer a scientific basis for sustainable water management.

A hybrid optimized model for predicting evapotranspiration in early and late rice based on a categorical regression tree combination of key influencing factors

Crop evapotranspiration (ETC) is an important component of the agricultural hydrological cycle, and its accurate estimation is important for assessing the hydrological environment of farmlands and guiding crop irrigation. To improve the prediction accuracy of ETC for early and late rice, this study analyzed the importance of the influencing factors based on a categorical regression tree (CART) machine learning algorithm. Based on the importance results of the influencing factors obtained from CART analysis, different combinations of input factors were constructed, and daily ETC prediction models were developed for early and late rice using the least squares support vector machine (LSSVM). A three-element heuristic optimization algorithm, Sine Cosine Algorithm (SCA), Slime Mold Algorithm (SMA), and Sparrow Search Algorithm (SSA), were used to optimize the ETC model to improve the performance of the early and late rice ETC prediction models. The results of this study revealed that the strongest correlation between early and late rice ETC was net solar radiation (Rn), with importance of 0.830 and 0.802, respectively. The next strongest correlations were temperature (T), wind speed (u), soil moisture (SM) and u, leaf area index (LAI), SM (0.092, 0.02, 0.014 and 0.058, 0.049, 0.034), respectively. The accuracy of the model tended to increase as the number of influencing factors in the input combinations constructed based on the importance results increased. The accuracy of the model increased more rapidly when the input factors were one to four and the accuracy of the model increased slightly when the input factors were more than four. The SSA-LSSVM model with four-factor combinations of inputs was the least-factor combination with guaranteed model accuracy of RMSE = 0.514 mm/d, R2 = 0.924, KGE = 0.565, WI = 0.978,and MAE = 0.414 mm/d; RMSE = 0.468 mm/d, R2 = 0.910, KGE = 0.670, WI = 0.985, and MAE = 0.368 mm/d. This study may provide a reference for the prediction of evapotranspiration as a key factor in the study of the agricultural hydrological environment of early and late rice.

WetSpass to model the components of hydrologic cycle in the big watershed of Khafr affected by land use

WetSpass to model the components of hydrologic cycle in the big watershed of Khafr affected by land use

Spatial distribution and drivers of throughfall beneath shrub canopies in a semi‐arid desert steppe

AbstractThe spatial distribution of water is mainly controlled by the vegetation canopy, which determines the partitioning of rainfall into interception, throughfall (TF) and stemflow. TF is known to be a critical component of hydrological and biogeochemical cycles. Spatiotemporal patterns of TF have been studied in different ecosystems, although the majority of studies focused on forests. Few reports on small‐scale TF variability and drivers in semi‐arid desert steppes have been published. Herein, we investigated the variability of TF of two morphologically distinct artificial revegetation shrubs (Caragana liouana and Salix psammophila) within a semi‐arid desert steppe, synthesized the data and analysed the characteristics of TF distribution and drivers at the rainfall event scales. We found that (1) morphological differences were sufficient to generate significant (p &lt; 0.05) differences in TF between the two shrub species under the same rainfall and meteorological conditions, with a TF percentage of 70.22% for C. liouana and 79.87% for S. psammophila; (2) a linear outward radical increase in TF was identified with increasing distance from the base of the isolated shrubs. Wind speed had a greater effect on the distribution of TF beneath the shrub structure for C. liouana, whereas the distribution of TF beneath the shrub structure for S. psammophila was more affected by wind direction; and (3) canopy architecture, in particular the stem angle and canopy base area, which affected the openness of the canopy and played an important role in the distribution of TF in the two shrubs. The results reveal the key factors driving water use under rainfall during revegetation and the TF utilization mechanism in semi‐arid areas and highlight the complementary effect of different species on ecosystem hydrological functions.

Changes of Rainfall Partitioning and Canopy Interception Modeling after Progressive Thinning in Two Shrub Plantations on the Chinese Loess Plateau

Understanding the interaction between the hydrological cycle and vegetation management strategies, such as thinning, is essential to improve watershed management and support ecological services. However, it remains unclear how thinning affects the key components of hydrological cycle of dense shrublands in the semiarid regions. Thus, the purpose of this study was to analyze and evaluate the effect of thinning on rainfall partitioning and interception simulations in dense shrublands. In a 5-year field experiment, we compared rainfall partitioning in two re-vegetated shrublands (Caragana korshinskii and Salix psammophila) in the Chinese Loess Plateau under two thinning intensities (moderate thinning [MT] and heavy thinning [HT] refer to the removal of 25% and 50% of the branches, respectively) or no thinning (NT) (control). We modeled canopy interception losses (I) in the two thinning treatments and control treatment using the revised Gash model. The results showed that under MT and HT, the throughfall (TF) rate increased by about 12% and 20%, respectively, compared to NT. The stemflow (SF) and observed I rates decreased by about 26% and 33%, respectively, under MT, and the corresponding values for HT were about 50% and 52%, respectively. The observed I rate decreased proportional to the percentage of biomass removed from the C. korshinskii and S. psammophila plots. The results also revealed a significant linear correlation between the plant area index (PAI) value and the canopy water balance of the two shrub plantations (R2 > 0.83, P < 0.05). The performance of the revised Gash model (i.e., relative error [RE] < 20%) was satisfactory according to the Nash − Sutcliffe model efficiency (NSE) coefficient (0.34–0.71). Based on the RE values, the performance of the revised Gash model was better when applied to the plots subjected to MT and HT (RE ≤ 3%) than NT (RE = 9.3%) for S. psammophila. Changes in the canopy storage capacity and canopy evaporation rate strongly affected changes in simulated interception loss. The model can facilitate water management in semiarid shrub plantations by accurately simulating the effect of thinning on interception loss.

Estimating Vegetation Greening Influences on Runoff Signatures Using a Log‐Based Weighted Ensemble Method

AbstractVegetation greening profoundly impacts the water cycle, and recent concerns about greening impacts have focused on various hydrological cycle components. However, the impacts of greening on catchment runoff signatures reflecting magnitude, low/high flow frequency, low/high flow duration and flow dynamics remain poorly understood. To properly simulate these runoff signatures, we use five modified hydrological models incorporating vegetation dynamics and further derive three ensemble approaches to obtain eight runoff time series outputs in a major tributary of the Yellow River Basin. Multiple validations suggest that the log‐based weighted ensemble (LWE) approach is robust for depicting the impact of greening on selected runoff signatures. This is especially true for the low flow part of the runoff time series and the overall performance of the selected signatures since LWE explicitly reduces the low flow bias. With this approach, five experiments were designed to isolate the impact of vegetation greening on runoff signatures, and the comparisons among the experiments indicate that greening noticeably decreases runoff magnitude, increases low flow frequency/duration and decreases high flow frequency/duration signatures. However, greening has little influence on runoff dynamic signatures. Each percent increase in leaf area index results in (a) changes of −0.2 ± 0.1% for magnitude signatures; (b) changes of −0.34 ± 0.30% and 0.56 ± 0.28% with wide ranges for annual high flow days and annual low flow days, respectively; and (c) marginal change on flow dynamic signatures. This study provides new insights by disentangling greening impacts on various runoff signatures using a trade‐off ensemble method.

Vegetation variation regulates soil moisture sensitivity to climate change on the Loess Plateau

Soil moisture is a key component of global hydrological cycles and is closely linked to climate and vegetation. However, exactly how vegetation affects the response of soil moisture to climate remains unclear. In this study, soil moisture sensitivity was investigated as an indicator of soil moisture response to climate change (including temperature and precipitation). Twenty years of data from the GLEAM (Global Land Evaporation Amsterdam Model), meteorological station, and remote sensing of the Loess Plateau of China were used to estimate the impact of the vegetation regulatory action on soil moisture sensitivity. The results show that soil moisture sensitivity to both temperature and precipitation exhibits distinct spatiotemporal patterns. With increasing Enhanced Vegetation Index (EVI), soil moisture sensitivity to temperature decreased at first and increased subsequently, while that to precipitation decreased continuously, reaching a stable value. The overall level of soil moisture sensitivity to both temperature and precipitation in the Loess Plateau was declining. Specifically, vegetation variation contributed 23.78% and −78.57% of the soil moisture sensitivity to precipitation in the surface and root zone, respectively, which is higher than it contributed to the soil moisture sensitivity to temperature (11.4% and 17.23%). The results of this study provide a scientific basis for the effective implementation of the ‘Grain for Green’ Program and the sustainable management of water resources on the Loess Plateau.

Experimental partitioning of rainfall into throughfall, stemflow and interception loss by Haloxylon ammodendron, a dominant sand-stabilizing shrub in northwestern China

Rainfall partitioning by the vegetation canopy represents a significant component of the local hydrological cycle by reshaping the amount and spatial distribution of rainfall. Measuring the components of rainfall partitioning, however, has been a challenging task due to laborious- and time-consuming field experiments. In this study, to probe the influences of long-term afforestation on dynamic patterns of rainfall partitioning, the dominant sand-stabilizing shrub Haloxylon ammodendron at three different ages was selected for field measurements during the 2020–2021 growing season. The throughfall percentage for young H. ammodendron (YH, 75.9 %) was significantly higher than that for middle-aged H. ammodendron (MAH, 63.4 %) and mature H. ammodendron (MH, 62.4 %) (p < 0.05 for all cases). However, the interception loss percentage of YH (22.3 %) was significantly lower than that for MAH (35.0 %) and MH (36.5 %) (p < 0.05 for all cases). No significant difference was found for stemflow percentage among YH (1.8 %), MAH (1.5 %) and MH (1.1 %). Smaller rainfall events contributed to a higher interception loss percentage and a lower net rainfall percentage for all ages. Both throughfall and stemflow percentage first showed increasing trends and then tended to be stable with increasing rainfall amount and duration, whereas interception loss percentage showed the opposite patterns. Rainfall partitioning was significantly correlated with the plant area index, stem basal area and canopy height (p < 0.05 for all cases), which may account for significant differences in rainfall partitioning patterns, as all shrubs experienced the same weather conditions. The average funneling ratio was 56.6, 26.7 and 17.9 for YH, MAH and MH, respectively. These results suggested that H. ammodendron afforestation can have a significant impact on rainfall partitioning by reducing net rainfall reaching the soil and may have some implications for local water budget and ecosystem management in oasis–desert ecotones.

The Diurnal Variation Characteristics of Latent Heat Flux under Different Underlying Surfaces and Analysis of Its Drivers in The Middle Reaches of the Heihe River

The Latent Heat Flux (LE) is an important component of surface water heat transfer and hydrological cycle, and monitoring it is of great value for water resource management and crop water demand estimation. The Heihe River Basin has complex topography, which ensures better variable control in LE analysis. In this paper, the time series analysis and statistics of LE under different underlying surface conditions in summer were carried out by using the eddy correlation observation data in the Heihe River Basin, and the regression factors were analyzed. The results show that when the underlying surface types are greatly different, there are obvious differences in the daily distribution of LE, the daily variation trend of LE and the influencing factors. The range of diurnal distribution of LE in dune, Gobi and desert from −50 W/m2 to 100 W/m2. The diurnal LE distribution of vegetable fields, cornfields and wetlands were about 55% concentrated between −50 W/m2 and 100 W/m2. Temperature and carbon dioxide concentration (CO2) are the dominant factors affecting latent heat flux. Further analysis of temperature and CO2 is carried out by stepwise regression analysis, and multiple regression models are established. In terms of correlation and confidence, the results are better than the single factor fitting, which can better reflect the synergistic effect of temperature and CO2 on LE.