Search Results (8)

While water conservancy projects continuously enhance flood control and resource allocation capabilities, the adverse impacts on basin systems, particularly the structural disruption of surface water–groundwater continuity, have become increasingly pronounced. Therefore, establishing quantitative assessment of water system connectivity as a critical foundation for optimizing spatial water distribution, maintaining ecohydrological equilibrium, and enhancing flood–drought regulation efficacy is important. Focusing on the regulated reaches of the Panjiakou, Daheiting, and Taolinkou reservoirs in the Luan River Basin, this study established and integrated a three-dimensional assessment framework that synthesizes hydrological processes, hydraulic structural effects, and human activities as three fundamental drivers, and employed the Analytic Hierarchy Process (AHP) to develop a quantitative connectivity evaluation system. Results indicate that water conservancy projects significantly altered basin connectivity: surface water connectivity decreased by 0.40, while groundwater connectivity experienced a minor reduction (0.25) primarily through reservoir seepage. Consequently, the integrated surface–groundwater system declined by 0.39. Critically, project scale governs surface connectivity attenuation intensity, which substantially exceeds impacts on groundwater systems. The comprehensive assessment system developed in this study provides theoretical and methodological support for diagnosing river connectivity, formulating ecological restoration strategies, and protecting basin ecosystems. Full article

The study employed the PML (Penman–Monteith–Leuning) model to simulate the evolution law of long-sequence evapotranspiration in the mountainous region of the Luan River basin. Additionally, this study conducted a quantitative analysis to determine the effect of restoration on evapotranspiration water consumption. From 1981 to 2020, the results indicated that there were significantly less fluctuations in precipitation in the mountainous region of the Luan River basin than there were fluctuations in discharge. The restoration of vegetation in the mountainous region of the Luan River basin caused a mean annual growth rate of 3.47 mm in evapotranspiration. A linear positive correlation was observed between the evapotranspiration and vegetation NDVIs (normalized difference vegetation indexes) in mountainous regions. Specifically, for each 0.01 increase in the NDVI, there was an approximate 8.3 mm increase in evapotranspiration. When comparing the time periods of 1995–2001 and 2002–2020, it was observed that evapotranspiration increased by 70 mm. Furthermore, the evapotranspiration rate in the southeastern region exhibits significant variation, peaking at over 50 mm per year. In contrast, the northwest experiences variations of less than 10 mm per year. A quantitative analysis of the relationship between the evolution of mountain evapotranspiration and the response law of vegetation restoration is presented in this study; this information can be used as a guide when developing practical vegetation restoration strategies. Full article

Root-zone soil moisture (RZSM) plays a key role in the hydrologic cycle and regulates water–heat exchange. Although site observations can provide soil profile moisture measurements, they have a restricted representation. Satellites can determine soil moisture on a large scale, yet the depth of detection is limited. RZSM can be estimated on a large scale using the soil moisture analytical relationship (SMAR) and surface soil moisture (SSM). However, the applicability of the SMAR to different deep-root zones and covariate sources is unclear. This paper investigates the applicability of the SMAR in the Shandian River Basin, upstream of the Luan River in China, by combining site and regional soil moisture, soil properties, and meteorological data. In particular, we first compared the estimation results of the SMAR at different depths (10–20 cm; 10–50 cm) and using covariates from different sources (dataset, SMAR-P1; literature, SMAR-P2) at the site in order to generate SMAR calibration parameters. The parameters were then regionalized based on multiple linear regression by combining the SMAR-P1, SMAR-P2, and SMAR calibration parameters in the 10–50 cm root zone. Finally, the Shandian River RZSM was estimated using regional surface soil moisture and the aforementioned regionalized parameters. At the site scale, diffusion coefficient b obtained in the 10–20 cm root zone at the same depth as the surface layer exceeded the upper limit of the SMAR by one. This is not fit an environment within the site context, and thus the SMAR is not applicable at this particular depth. The opposite is observed for the 10–50 cm root zone. In addition, SMAR-P1 (RMSE = 0.02) outperformed SMAR-P2 (RMSE = 0.04) in the estimation of the RZSM at 10–50 cm. Parameter regionalization analysis revealed the failure of SMAR-P2 to pass the significance test (p > 0.05) for building a multivariate linear model, while SMAR-P1 successfully passed the significance test (p < 0.05) and finished the parameter regionalization process. The median RMSE and median R²_adj of the regional RZSM results were determined as 0.12 and 0.3, respectively. The regional RZSM agrees with the spatial trend of the Shandian River. This study examines the suitability of the SMAR model in varying deep-root zones and with diverse covariate sources. The results provide a crucial basis for future utilization of the SMAR. Full article

Terrestrial water storage (TWS) is a pivotal component of the global water cycle, profoundly impacting water resource management, hazard monitoring, and agriculture production. The Gravity Recovery and Climate Experiment (GRACE) and its successor, the GRACE Follow-On (GFO), have furnished comprehensive monthly TWS data since April 2002. However, there are 35 months of missing data over the entire GRACE/GFO observational period. To address this gap, we developed an operational approach utilizing singular spectrum analysis and principal component analysis (SSA-PCA) to fill these missing data over mainland China. The algorithm was demonstrated with good performance in the Southwestern River Basin (SWB, correlation coefficient, CC: 0.71, RMSE: 6.27 cm), Yangtze River Basin (YTB, CC: 0.67, RMSE: 3.52 cm), and Songhua River Basin (SRB, CC: 0.66, RMSE: 7.63 cm). Leveraging two decades of continuous time-variable gravity data, we investigated the spatiotemporal variations in TWS across ten major Chinese basins. According to the results of GRACE/GFO, mainland China experienced an average annual TWS decline of 0.32 ± 0.06 cm, with the groundwater storage (GWS) decreasing by 0.54 ± 0.10 cm/yr. The most significant GWS depletion occurred in the Haihe River Basin (HRB) at −2.07 ± 0.10 cm/yr, significantly substantial (~1 cm/yr) depletions occurred in the Yellow River Basin (YRB), SRB, Huaihe River Basin (HHB), Liao-Luan River Basin (LRB), and Southwest River Basin (SWB), and moderate losses were recorded in the Northwest Basin (NWB, −0.34 ± 0.03 cm/yr) and Southeast River Basin (SEB, −0.24 ± 0.10 cm/yr). Furthermore, we identified that interannual TWS variations in ten basins of China were primarily driven by soil moisture water storage (SMS) anomalies, exhibiting consistently and relatively high correlations (CC > 0.60) and low root-mean-square errors (RMSE < 5 cm). Lastly, through the integration of GRACE/GFO and Global Land Data Assimilation System (GLDAS) data, we unraveled the contrasting water storage patterns between northern and southern China. Southern China experienced drought conditions, while northern China faced flooding during the 2020–2023 La Niña event, with the inverse pattern observed during the 2014–2016 El Niño event. This study fills in the missing data and quantifies water storage variations within mainland China, contributing to a deeper insight into climate change and its consequences on water resource management. Full article

The occurrence of water scarcity and extreme hydrological events is becoming increasingly frequent worldwide. The river runoff process, as an important link in the water cycle of a basin, is an essential content of the study of hydrological processes in the basin. Vegetation is an influencing factor closely related to hydrological processes in a watershed. This article quantitatively analyzes the impact of vegetation restoration and climate variation on runoff in the Luan River Basin from 1982 to 2018. Firstly, trend analysis was conducted on runoff depth, precipitation, the Normalized Vegetation Index (NDVI), and reference evaporation. Then, Mann–Kendall mutation analysis and Pettitt mutation analysis were used to identify the year of runoff mutation. Finally, a Budyko model was constructed to quantitatively analyze the impact of vegetation and climate change on the runoff of the Luan River. The results showed that: (1) The runoff reduction rate of the Luan River was 1.2437 mm/a. The precipitation was increasing at a rate of 0.6977 mm/a. The reference evaporation rate decreased at a rate of 0.0977 mm/a. The annual growth rate of the Budyko parameter (n) was 0.0283. The annual growth rate of NDVI was 0.0022. (2) The coefficient of determination in the functional equation (a = 14.74, b = −3.4105) for NDVI and Budyko parameter (n) was 0.3297 (p < 0.01). (3) The contributions of Pr, ET₀, NDVI, and (n) to reduced flow were −17.49%, 1.46%, 35.25%, and 80.78%, respectively. The increase in vegetation would lead to a decrease in runoff. This study can clarify the impact of vegetation restoration on water resource security in the Luan River Basin. Full article

We tracked 39 western flyway white-naped cranes (Antigone vipio) throughout multiple annual cycles from June 2017 to July 2020, using GSM-GPS loggers providing positions every 10-min to describe migration routes and key staging areas used between their Mongolian breeding and wintering areas in China’s Yangtze River Basin. The results demonstrated that white-naped cranes migrated an average of 2556 km (±187.9 SD) in autumn and 2673 km (±342.3) in spring. We identified 86 critical stopover sites that supported individuals for more than 14 days, within a 100–800 km wide migratory corridor. This study also confirmed that Luan River catchment is the most important staging region, where white-naped cranes spent 18% of the annual cycle (in both spring and autumn) each year. Throughout the annual cycle, 69% of the tracking locations were from outside of the currently protected areas, while none of the critical staging areas enjoyed any form of site protection. We see further future potential to combine avian tracking data and remote-sensing information throughout the annual range of the white-naped crane to restore it and other such species to a more favourable conservation status. Full article

During the past decades, runoff has been highly influenced by climate change and human activities in Haihe River basin, and it is important to analyze the runoff trends and the drivers of its change to guide water resources management. The Mann–Kendall method and Pettitt test were conducted to analyze the hydrological and climate trends. Data from six sub-basins were used, including runoff at six representative hydrological stations and precipitation and air temperature at 49 meteorological stations. We used multiple-regression analysis and policy review to explore the influence of climate change and human activities on the runoff change at six sub-basins. According to the results, annual runoff showed a significant downward trend at six hydrological stations (p < 0.05), and the most probable change points at all stations showed up during the period from the late 1970s to the early 1980s. Moreover, the middle and late 1990s could be another probable abrupt change point at Luan River and Chaobai River. The declining trend of the annual mean precipitation at the six sub-basins was insignificant (p > 0.05), and there were no significant abrupt change points except the Zhang River area (p < 0.05). Compared with the precipitation trend, the annual mean air temperature exhibited a significant increasing trend at all stations, and the period from the late 1980s to the early 1990s might be the most probable abrupt change points at all four sub-basins. The trend analysis and the abrupt change point analysis suggest that mean air temperature is the main climate factor that will lead to the decline in the runoff time-series, while the insignificant downward trend of the precipitation might accelerate the downward trend of the runoff data. Through elevant policy measures, including land-use reform and the construction of the Three-North (north, northeast, and northwest China) Shelter Forest, China started to implement a family-contract responsibility system and initiated the first stage of construction of the Three-North Shelter Forest Program in 1978. The land-use reform policies greatly stimulated the peasants’ initiative for land management and significantly changed the land use pattern and water use quantity in the Haihe River basin in a short time. Besides, the precipitation decreased and the air temperature rose, so an abrupt change in runoff occurred from the late 1970s to the early 1980s. The abrupt change in the runoff in the middle and late 1990s highly tallied with the construction time of the Three-North Shelter Forest Program. After near 20 years of construction of the Three-North Shelter Forest Program, the forest area increased, the forest quality had been improved, and the vegetation coverage on the underlying surface had been changed significantly, so the construction of the Three-North Shelter Forest Program was an important cause of runoff change in the middle and late 1990s. Also, change in precipitation and air temperature enlarged the effect of change in the runoff. Full article

Climatic, socio-economic, geophysical, and human activity factors, among others, influence land use patterns. However, these driving factors also have different relationships with each other. Combining machine learning methods and statistical models is a good way to simulate the dominant land use types. The Luan River basin is located in a farming-pastoral transitional zone and is an important ecological barrier between Beijing and Tianjin. In this study, we predicted future land use and land cover changes from 2010 to 2020 in the Luan River’s upper and middle reaches under three scenarios—the natural scenario, the ecological scenario, and the sustainable scenario. The results indicate that cultivated land will decrease while the forested areas will increase quantitatively in the future. Built-up areas would increase quickly in the natural scenario, and augmented expansion of forest would be the main features of land use changes in both the ecological scenario and the sustainable scenario. Regarding the spatial pattern, different land use patterns will be aggregated and patches will become larger. Our findings for the scenario analysis of land use changes can provide a reference case for sustainable land use planning and management in the upper and middle Luan River basin. Full article