Search Results (55)

Anthropogenic activities (represented by dams and land use change) and climate change have disrupted the delicate balance between natural and anthropogenic factors affecting riverine material transport, yet their effects across different river basins remain underexplored. This study investigated multi-decade (1980–2023) variations in sediment and particulate carbon (C), nitrogen (N), and phosphorus (P) exports from the Jinsha (JSR) and Jialing River (JLR) basins, two cascading developmental river systems in Southwestern China, and evaluated the cumulative impacts of land use change and dam construction. The results revealed significant decreases in particulate fluxes from both basins, despite stable water discharge. Particulate material fluxes declined by 90.9–99.6% in the JSR (last decade vs. 1980–1989, with an abrupt change occurring during 2002–2003) and by 54.0–79.3% in the JLR (with an abrupt change occurring in 1994). Over time, the influence of precipitation and water discharge on material transport has diminished, whereas land use change and dams have become increasingly dominant. Key drivers include forest expansion, increased impervious surfaces, reservoir construction, and reductions in grassland and farmland; however, there are spatial differences in the relative importance of these drivers. This study provides crucial insights for decision making on regional ecological conservation and cascading development. Full article

The Jinsha River Basin in Yunnan serves as a crucial ecological barrier in southwestern China. Objective ecological assessment and identification of key driving factors are essential for the region’s sustainable development. The Remote Sensing Ecological Index (RSEI) has been widely applied in ecological assessments. In recent years, interpretable machine learning (IML) has introduced novel approaches for understanding complex ecological driving mechanisms. This study employed Google Earth Engine (GEE) to calculate three vegetation indices—NDVI, SAVI, and kNDVI—for the study area from 2000 to 2022, along with their corresponding RSEI models (NDVI-RSEI, SAVI-RSEI, and kNDVI-RSEI). Additionally, it analyzed the spatiotemporal variations of these RSEI models and their relationship with vegetation indices. Furthermore, an IML model (XGBoost-SHAP) was employed to interpret the driving factors of RSEI. The results indicate that (1) the RSEI levels in the study area from 2000 to 2022 were primarily moderate; (2) compared to NDVI-RSEI, SAVI-RSEI is more susceptible to soil factors, while kNDVI-RSEI exhibits a lower saturation tendency; and (3) potential evapotranspiration, land cover, and elevation are key drivers of RSEI variations, primarily affecting the ecological environment in the western, southeastern, and northeastern parts of the study area. The XGBoost-SHAP approach provides valuable insights for promoting regional sustainable development. Full article

Yunnan Province, as a critical ecological security barrier in China, has long been highly susceptible to drought events. Characterizing the spatiotemporal distributions of drought and identifying its driving factors is crucial. Due to the complexity of drought occurrence, linear correlation analysis alone is insufficient to quantify drought drivers and their interactions. This study used the Standardized Precipitation Evapotranspiration Index (SPEI) as a drought indicator to analyze the spatiotemporal trends of drought across Yunnan and its six major river basins. The geographic detector model (GDM) and random forest (RF) were utilized to quantify the impacts of meteorological, topographical, soil, and human activities on drought, as well as the interactions among these factors. The results showed that 63.61% of the study area exhibits a significant drying trend (p-value < 0.05), with the Jinsha River Basin (JSRB) experiencing the highest frequency of extreme drought events. Precipitation (PRE), temperature, potential evapotranspiration (PET), vapor pressure deficit (VPD), and relative humidity (RH) were identified as the primary controlling factors of drought, with factor interactions displaying nonlinear enhancement effects. PRE plays a dominant role in driving drought across Yunnan, whereas elevation primarily influenced drought severity in the JSRB, Lancang River Basin (LCRB), and Nujiang River Basin (NJRB). The RF-based SPEI prediction model demonstrated superior performance in simulating short-term drought (SPEI_1, R² > 0.931, RMSE < 0.279), particularly in the JSRB (R² = 0.947 RMSE = 0.228). These findings provide a scientific basis for regional water resource management applications and drought early warning systems, offering a robust framework for understanding and mitigating drought impacts in ecologically sensitive regions. Full article

Vegetation dynamics significantly influence watershed ecohydrological processes. Physically based hydrological models often have general plant development descriptions but lack vegetation dynamics data for ecohydrological simulations. Solar-induced chlorophyll fluorescence (SIF) and the Normalized Difference Vegetation Index (NDVI) are widely used in monitoring vegetation dynamics and ecohydrological research. Accurately predicting long-term SIF and NDVI dynamics can support the monitoring of vegetation anomalies and trends. This study proposed a SWAT-ML framework, combining the Soil and Water Assessment Tool (SWAT) and machine learning (ML), in the Jinsha River Basin (JRB). The lag effects that vegetation responds to using hydrometeorological elements were considered while using SWAT-ML. Based on SWAT-ML, SIF and NDVI series from 1982 to 2014 were reconstructed. Finally, the spatial and temporal characteristics of vegetation dynamics in the JRB were analyzed. The results showed the following: (1) the SWAT-ML framework can simulate ecohydrological processes in the JRB with satisfactory results (NS > 0.68, R² > 0.79 for the SWAT; NS > 0.77, MSE < 0.004 for the ML); (2) the vegetation index’s mean value increases (the Z value, the significance indicator in the Mann–Kendall method, is 1.29 for the SIF and 0.11 for the NDVI), whereas the maximum value decreases (Z value = −0.20 for SIF and −0.42 for the NDVI); and (3) the greenness of the vegetation decreases (Z value = −2.93 for the maximum value and −0.97 for the mean value) in the middle reaches. However, the intensity of the vegetation’s physiological activity increases (Z value= 3.24 for the maximum value and 2.68 for the mean value). Moreover, the greenness and physiological activity of the vegetation increase in the lower reaches (Z value = 3.24, 2.68, 2.68, and 1.84 for SIF_max, SIF_ave, NDVI_max, and NDVI_ave, respectively). In the middle and lower reaches, the connection between the SIF and hydrometeorological factors is stronger than that of the NDVI. This research developed a new framework and can provide a reference for complex ecohydrological simulation. Full article

In high-mountain canyon regions, many settlements are located on large, deep-seated ancient landslides. The deformation characteristics, triggering mechanisms, and long-term developmental trends of these landslides significantly impact the safety and stability of these communities. However, the deformation mechanism under the influence of human engineering activities remains unclear. SBAS-InSAR (Small Baseline Subset-Interferometric Synthetic Aperture Radar) technology, UAV LiDAR, and field surveys were utilized in this study to identify a large ancient landslide in the upper Jinsha River Basin: the Zhongxinrong landslide. It extends approximately 1220 m in length, with a vertical displacement of around 552 m. The average thickness of the landslide mass ranges from 15.0 to 35.0 m, and the total volume is estimated to be between 1.48 × 10⁷ m³ and 3.46 × 10⁷ m³. The deformation of the Zhongxinrong landslide is primarily driven by a combination of natural and anthropogenic factors, leading to the formation of two distinct accumulation bodies, each exhibiting unique deformation characteristics. Accumulation Body II-1 is predominantly influenced by rainfall and road operation, resulting in significant deformation in the upper part of the landslide. In contrast, II-2 is mainly affected by rainfall and river erosion at the front edge, causing creeping tensile deformation at the toe. Detailed analysis reveals a marked acceleration in deformation following rainfall events when the cumulative rainfall over a 15-day period exceeds 120 mm. The lag time between peak rainfall and landslide displacement ranges from 2 to 28 days. Furthermore, deformation in the high-elevation accumulation area consistently exhibits a slower lag response compared to the tensile deformation area at lower zones. These findings highlight the importance of both natural and anthropogenic factors in landslide risk assessment and provide valuable insights for landslide prevention strategies, particularly in regions with similar geological and socio-environmental conditions. Full article

Extensive and profound landscape alterations significantly contribute to ecological vulnerability in environmentally delicate regions. Existing research primarily emphasizes ecological risks caused by landscape alterations, while overlooking vulnerable characteristics of landscape functions; particularly lacking are studies on the driving mechanism of landscape ecological risk through the reciprocal relationship between landscape pattern risk and function risk. Based on these issues, this paper constructed a landscape pattern risk index (LPRI), a landscape function risk index (LFRI), and a landscape ecological risk index (LERI) in the counties of the dry–hot valley of the Jinsha River in southwest China. By employing a coupling degree and a coordination model, we analyzed temporal and spatial variations in the interaction between two types of ecological risk, thereby revealing the driving mechanisms of landscape ecological risk. The results indicated that the average LPRI values of the study area were 0.373, 0.327, and 0.427, respectively, while the average LFRI values were 0.451, 0.356, and 0.442 in 2000, 2010, and 2020, respectively. More than 90% of the study area exhibited a medium coupling relationship between the two types of ecological risks. The area proportion of the coupling coordination regions has increased from 25.58% to 31.07% from 2010 to 2020. The two types of risk exhibited a low level of constraint inhibition. Extremely evident expansion of high pattern–function risk areas and the area increase of coupling coordination region resulted in the acceleration of regional landscape ecological risk level. Increasing competition between market-driven land-use activities and ecological regulations from the government has rendered the diversification of landscape ecological risk sources and its underlying mechanisms intricate. This study serves as a model reference for assessing landscape ecological risk and a theoretical basis for sustainable landscape management and ecological regulation in the Yangtze River basin. Full article

Mountain regions play a crucial role in maintaining global biodiversity, with altitude exerting a significant influence on soil microbial diversity by altering plant diversity, soil nutrients, and microclimate. However, differences in microbial community composition between topsoil (0–10 cm deep) and subsoil (10–20 cm deep) remain poorly understood. Here, we aimed to assess soil microbial diversity, microbial network complexity, and microbial community assembly in the topsoil and subsoil layers of the dry–hot Jinsha River valley in southwestern China. Using high-throughput sequencing in soil samples collected along an altitudinal gradient, we found that bacterial diversity in topsoil decreased with increasing altitude, while bacterial diversity in subsoil showed no altitude-dependent changes. Fungal diversity in topsoil also varied with altitude, while subsoil fungal diversity showed no change. These findings suggest that microbial diversity in topsoil was more sensitive to changes in altitude than subsoil. Bacterial community assembly tended to be governed by stochastic processes, while fungal assembly was deterministic. Soil bacterial and fungal network complexity was enhanced with increasing altitude but reduced as diversity increased. Interestingly, the presence of woody plant species negatively affected bacterial and fungal community composition in both soil layers. Soil pH and water content also negatively affected microbial community composition, while organic carbon and total nitrogen positively influenced the microbial community composition. Simultaneously, herb and woody plant diversity mainly affected soil bacterial diversity in the topsoil and subsoil, respectively, while woody plant diversity mainly affected soil fungal diversity in subsoil and soil nutrients had more effect on soil fungal diversity. These findings suggest that altitude directly and indirectly affects microbial diversity in topsoil, subsequently influencing microbial diversity in subsoil through nutrient availability. Full article

Constructing and operating cascade reservoirs significantly contribute to comprehensive basin water resource management, while altering natural hydrological regimes of rivers, which imposes negative impacts on riverine ecology. The main aim of this study is to synergistically optimize the objectives of increasing hydropower generation and alleviating hydrological regime alteration for cascade reservoirs. This study first proposed a dynamic time warping scenario backward reduction (DTW-SBR) framework to extract streamflow scenarios from the historical streamflow series regarded as benchmarks for calculating deviation degrees of hydrological regimes. Then a multi-objective long-term operation model considering the hydrological regime and hydroelectricity was formed for minimizing the deviation degrees of hydrological regimes at the downstream section (O1) and maximizing the hydropower generation of cascade reservoirs (O2). The non-dominated sorting genetic algorithm-II (NSGA-II) combined with the long-term conventional operation (CO) rules of cascade reservoirs was adopted to produce the Pareto-front solutions to derive the recommended policies for guiding the long-term operation of cascade reservoirs. The six large reservoirs in the middle reaches of the Jinsha River, China with a 10-day runoff dataset spanning from 1953 to 2015 constitute a case study. The results showed that nine streamflow scenarios were extracted for calculating the O1 by the DTW-SBR framework, which could reflect the intra- and inter- annual variability of hydrological regimes at the Panzhihua hydrological station. The Pareto-front solutions obtained by the NSGA-II revealed competitive relationships between the O1 and O2. As compared to the long-term CO rules of cascade reservoirs, the O1 value could be reduced by up to 42,312 (corresponding rate of 10.51%) and the O2 value could be improved by up to 1752 × 10⁸ kW·h (corresponding rate of 5.14%). Based on the inclination to be dominated by different objectives, three typical operation schemes, A, B and C, were chosen from the Pareto-front solutions; Scheme A could be considered as the recommended solution, which simultaneously reduced the O1 value by 23,965 with the rate of 5.95% and increased the O2 value by 1752 × 10⁸ kW·h with the rate of 5.14%, as compared to the long-term CO rules. This study can provide references on boosting the synergies of hydropower production and hydrological regime restoration for the long-term ecological operation of cascade reservoirs. Full article

As a feature of global warming, climate change has been a severe issue in the 21st century. A more comprehensive reconstruction is necessary in the climate assessment process, considering the heterogeneity of climate change scenarios across various meteorological elements and seasons. To better comprehend the change in minimum temperature in winter in the Jinsha River Basin (China), we built a standard tree-ring chronology from Picea likiangensis var. balfouri and reconstructed the regional mean minimum temperature of the winter half-years from 1606 to 2016. This reconstruction provides a comprehensive overview of the changes in winter temperature over multiple centuries. During the last 411 years, the regional climate has undergone seven warm periods and six cold periods. The reconstructed temperature sensitively captures the climate warming that emerged at the end of the 20th century. Surprisingly, during 1650–1750, the lowest winter temperature within the research area was about 0.44 °C higher than that in the 20th century, which differs significantly from the concept of the “cooler” Little Ice Age during this period. This result is validated by the temperature results reconstructed from other tree-ring data from nearby areas, confirming the credibility of the reconstruction. The Ensemble Empirical Mode Decomposition method (EEMD) was adopted to decompose the reconstructed sequence into oscillations of different frequency domains. The decomposition results indicate that the temperature variations in this region exhibit significant periodic changes with quasi-3a, quasi-7a, 15.5-16.8a, 29.4-32.9a, and quasi-82a cycles. Factors like El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and solar activity, along with Atlantic Multidecadal Oscillation (AMO), may be important driving forces. To reconstruct this climate, this study integrates the results of three machine learning algorithms and traditional linear regression methods. This novel reconstruction method can provide valuable insights for related research endeavors. Furthermore, other global climate change scenarios can be explored through additional proxy reconstructions. Full article

The upper Jinsha River, located in a high-mountain gorge with complex geological features, is highly prone to large-scale landslides, which could result in the formation of dammed lakes. Analyzing the movement characteristics of the typical Xiaomojiu landslide in this area contributes to a better understanding of the dynamics of landslides in the region, which is of great significance for landslide risk prediction and analysis. True displacement data on the surface of landslides are crucial for understanding the morphological changes in landslides, providing fundamental parameters for dynamic analysis and risk assessment. This study proposes a method for calculating the actual deformation of landslide bodies based on multi-track Interferometric Synthetic Aperture Radar (InSAR) deformation data. It iteratively solves for the optimal true deformation vector of the landslide on a per-pixel basis under a least-squares constraint based on the assumption of consistent displacement direction among adjacent points on the landslide surface. Using multi-track Sentinel data from 2017 to 2023, the line of sight (LOS) accumulative de-formation of the Xiaomojiu landslide was obtained, with a maximum LOS deformation of −126 mm/year. The true surface displacement of the Xiaomojiu landslide after activation was calculated using LOS deformation. The development of two rotational sub-slipping zones on the landslide body is inferred based on the distribution of actual displacements along the central profile line. Analysis of temporal changes in water body area data revealed that the Xiaomojiu landslide was activated after a barrier lake event and continuously moved due to the influence of higher water levels’ in the river channel. In conclusion, the proposed method can be applied to calculate the true surface displacement of landslides with complex mechanisms for analyzing the movement status of landslide bodies. Furthermore, the spatiotemporal analysis of the Xiaomojiu landslide characteristics can support analyzing the mechanisms of similar landslides in the Jinsha River Basin. Full article

The stability of riverbank slopes is crucial in watershed ecology. The morphology and tensile strength properties of plant roots play a significant role in slope stability, which is of great importance for the ecological stability of riverbanks. The Jinsha and Yalong River basins are the largest hydropower bases in China and are in the ecologically fragile areas of the dry and hot river valleys, yet fewer studies are available on these basins. Further studies on the growth morphology and root mechanical properties of plant roots in the riparian zone at different elevations have not been reported. Therefore, we selected the dominant species of Cynodon dactylon root as the research subject, analyzed the root morphology, and conducted indoor single-root tensile tests to study its root structure and mechanical properties at various elevations. The results showed that the root morphology of Cynodon dactylon was positively correlated with elevation. Compared to low elevations (L and M), the root length increased by 57.3% and 21.47%, the root diameter increased by 24.85% and 13.92%, the root surface area increased by 93.5% and 67.37%, and the total root volume increased by 119.91% and 107.36%. As the elevation gradient increased, the flooding time decreased, leading to more developed plant roots for Cynodon dactylon. The Young’s modulus ranged from 148.43 to 454.18 MPa for Ertan Cynodon dactylon roots and 131.31 to 355.53 MPa for Guanyingyan Cynodon dactylon roots. The maximum tensile strength, ultimate tensile strength, ultimate elongation, and Young’s modulus of the plant root of the Cynodon dactylon showed a power function relationship with the diameter. The maximum tensile strength increased as the diameter increased, while the remaining properties decreased following a power function relationship. The maximum tensile strength, ultimate tensile strength, and Young’s modulus of Cynodon dactylon were positively correlated with elevation, while the ultimate elongation was negatively correlated with elevation. The results elucidate the influence of elevation on the root morphology and mechanical properties of dominant riparian species. This provides a theoretical basis for managing and protecting riparian slopes in ecologically fragile areas. Full article

Soil erosion is a significant global environmental issue and a crucial aspect of global change. Exploring the interactive effect of ecological land agglomeration and habitat quality on soil erosion can effectively guide the positive intervention of ecological restoration activities. The study calculated the comprehensive ecological land agglomeration with Fragstats 4.2 and the habitat quality with InVEST 3.7.0 for the years 2000, 2010, and 2020 within the Jinsha River Basin in Yunnan, China. In addition, the RUSLE model was utilized to calculate soil erosion in the study area. The Geographic and Temporally Weighted Regression (GTWR) model was employed to obtain the regression coefficients and their spatial and temporal variations. The findings of this study revealed the following: (1) During the study period, there was an overall 29.06% reduction in the soil erosion modulus with an annual rate of 1.70% reduction on average, accompanied by an increase in both the comprehensive ecological land agglomeration and habitat quality. Soil erosion was more severe in the eastern regions than in the western ones and the other two indicators were higher in the northeast and southwest. (2) The GTWR results demonstrate that comprehensive ecological land agglomeration and habitat quality were negatively correlated with soil erosion, with results of −0.1383 and 0.0021, respectively. However, in northwest regions, there was a significant positive correlation between habitat quality and soil erosion. (3) The interaction term between comprehensive ecological land agglomeration and habitat quality was significantly negatively correlated with soil erosion with a result of −0.0299, and the interaction coefficients have regional variations. This study offers valuable guidance for land-use development and soil and water conservation in the Jinsha River Basin. Full article

The impact of reservoirs on downstream river hydrological characteristics is always a focal point in relevant studies exploring the relationship between rivers and dams. Anticipating river runoff patterns following the construction of new dams is crucial for the design of riverine engineering projects, particularly during dry periods. This paper presents a semi-theoretical estimation method based on the correlation between hydrological alterations and reservoir operation. The method incorporates differences in runoff increment distribution and the discrepancy between theoretical and practical results. It was validated and applied in the sub-basins of the upper reaches of the Yangtze River, namely the Jinsha River and Min River. The runoff increment during the driest month for the Jinsha River and the Min River is 817 m³/s and 434 m³/s, respectively. The estimated prediction biases were within 30% of the practical runoff increments observed in the Jinsha River and Min River, which is an acceptable range considering the inherent variability in such studies. Since the construction of the Wudongde and Baihetan dams in 2021, the average runoff during the driest month and the navigation assurance runoff at a 95% probability were predicted to be 2866 m³/s and 2174 m³/s, respectively. Therefore, the method developed in this paper provides a reasonable and straightforward tool for researchers, which can help prevent future engineering invalidation and minimize resource costs. Moreover, in the application process, this method requires careful consideration of the characteristics of the studied river section and the operation of the reservoir group. It relies on measured data to determine the differences between theoretical and actual runoff rather than simply generalizing to all watersheds. Full article

The Upper Jinsha River (UJSR) has great water resource potential, but large-scale active landslides hinder water resource development and utilization. It is necessary to understand the spatial distribution and deformation trend of active landslides in the UJSR. In areas of high elevations, steep terrain or otherwise inaccessible to humans, extensive landslide studies remain challenging using traditional geological surveys and monitoring equipment. Stacking interferometry synthetic aperture radar (stacking-InSAR) technology, optical satellite images and unmanned aerial vehicle (UAV) photography are applied to landslide identification. Small baseline subset interferometry synthetic aperture radar (SBAS-InSAR) was used to obtain time-series deformation curves of samples to reveal the deformation types of active landslides. A total of 246 active landslides were identified within the study area, of which 207 were concentrated in three zones (zones I, II and III). Among the 31 landslides chosen as research samples, six were linear-type landslides, three were upward concave-type landslides, 10 were downward concave-type landslides, and 12 were step-type landslides based on the curve morphology. The results can aid in monitoring and early-warning systems for active landslides within the UJSR and provide insights for future studies on active landslides within the basin. Full article

The Jinsha River basin (JRB), known as China’s largest hydropower base, has been facing a surge in hydrological drought occurrences in the past several years. This study used the drought index model and soil and water assessment tool (SWAT) hydrological model to uncover the linkages between meteorological and hydrological drought using long-term datasets in the JRB. The results revealed that: (1) Over the past six decades, the JRB has experienced recurrent meteorological droughts, with the upper reaches being the most affected, accounting for a frequency of 17.5%. However, the frequency of drought in the middle and lower reaches has shown a marked increase in the last 15 years. (2) The frequency of hydrological drought in the JRB has been on the rise over the past six decades, with a particularly notable increase observed in the last two decades. Furthermore, a noticeable upward trend has been observed in the duration of these hydrological droughts. (3) The propagation durations from meteorological drought to hydrological drought exhibited noticeable seasonal differences in the JRB. The transmission duration during the flood season was shorter, whereas in the dry season, it was more protracted. Additionally, the connection between meteorological drought and hydrological drought demonstrates a weakening trend. The findings of this study hold significant implications for crafting an efficient reservoir dispatching strategy to safeguard the water security of the JRB. Full article