Search Results (13)

A total of 24 hydropower stations are planned for construction in the upper Yellow River, from the Longyangxia to the Qingtongxia section, with completion anticipated by 2050. These stations represent the densest and highest-capacity reservoirs in China and play a crucial role in the ecological preservation and water resource management of the Yellow River Basin. To assess the ecological impacts of reservoirs on the surrounding environment, we analyzed vegetation dynamics in 10 reservoir areas between 2000 and 2020 using the normalized difference vegetation index (NDVI), examined the relationship between vegetation and climatic elements using biased correlation, and quantified the impacts of climatic factors and reservoir construction on the riparian vegetation using a generalized linear model (GLM) and path analysis. The findings indicated that the rate of vegetation growth declined after reservoir construction, and the overall trend indicated greening. Climate change impacts on riparian vegetation showed significant spatial heterogeneity, and the GLM analysis identified reservoir construction as the primary contributor to riparian vegetation dynamics, with a contribution rate of >50%. Temperature and soil moisture were the main climatic factors influencing vegetation growth in the reservoir area, with a 10–20% contribution rate. Path analysis further verified that reservoir construction directly enhanced riparian vegetation growth (with an impact coefficient of 0.514) and indirectly affected vegetation by altering the microclimate. This study emphasizes the importance of reservoir construction in assessing the relationship between riparian vegetation and climatic factors and provides insights for improved ecological conservation and water resource management strategies. Full article

Due to water scarcity in the Yellow River basin, the existing operations for the Longyangxia and Liujiashan cascade reservoirs are insufficient to meet the demands of multiple objectives. This study establishes a coupled coordination model considering hydropower generation, water supply, and storage capacity at different periods during the year. At the same time, the model quantifies the impact of scheduling strategies on multiple objectives and determines the optimal operation for reservoirs at different periods. The results indicate that the scheduling strategy of the Longyangxia reservoir dominates the changes in hydropower generation, water supply, and storage capacity. Specifically, during the ice flood control period, the scenario of continuous release from Longyangxia and continuous storage at Liujiaxia achieves 1.26 billion kWh of hydropower generation, with a water supply shortage rate of 8.67%; During the non-flood period, releasing water from Longyangxia in April and May and storing it in June while Liujiaxia continuously releases water results in 4.68 billion kWh of hydropower generation and a shortage rate of 1.61%. During the flood control period, continuous storage at Longyangxia and controlling the water level of Liujiashan within flood control limits, with storage in September and release in October, achieves 5.65 billion kWh of hydropower generation and a shortage rate of 0%. Full article

Reservoirs are an important source of methane (CH₄) emissions, but the relative contribution of CH₄ ebullition and diffusion fluxes to total fluxes has received little attention in the past. In this study, we systematically monitored the CH₄ fluxes of nine cascade reservoirs (Dahejia, Jishixia, Huangfeng, Suzhi, Kangyang, Zhiganglaka, Lijiaxia, Nina, and Longyangxia) in the upper reaches of the Yellow River in the dry (May 2023) and wet seasons (August 2023) using the static chamber gas chromatography and headspace equilibrium methods. We also simultaneously measured environmental physicochemical properties as well as the abundance of methanogens and methanotrophs in sediments. The results showed the following: (1) All reservoirs were sources of CH₄ emissions, with an average diffusion flux of 0.08 ± 0.05 mg m⁻² h⁻¹ and ebullition flux of 0.38 ± 0.41 mg m⁻² h⁻¹. Ebullition flux accounted for 78.01 ± 7.85% of total flux. (2) Spatially, both CH₄ diffusion and ebullition fluxes increased from upstream to downstream. Temporally, CH₄ diffusion flux in the wet season (0.09 ± 0.06 mg m⁻² h⁻¹) was slightly higher than that in the dry season (0.08 ± 0.04 mg m⁻² h⁻¹), but CH₄ ebullition flux in the dry season (0.38 ± 0.48 mg m⁻² h⁻¹) was higher than that in the wet season (0.32 ± 0.2 mg m⁻² h⁻¹). (3) qPCR showed that methanogens (mcrA gene) were more abundant in the wet season (5.43 ± 3.94 × 10⁵ copies g⁻¹) than that in the dry season (3.74 ± 1.34 × 10⁵ copies g⁻¹). Methanotrophs (pmoA gene) also showed a similar trend with more abundance found in the wet season (7 ± 2.61 × 10⁵ copies g⁻¹) than in the dry season (1.47 ± 0.92 × 10⁵ copies g⁻¹. (4) Structural equation modeling revealed that the ratio of mcrA/pmoA genes, water N/P, and reservoir age were key factors affecting CH₄ ebullition flux. Variation partitioning further indicated that the ratio of mcrA/pmoA genes was the main factor causing the spatial variation in CH₄ ebullition flux, explaining 35.69% of its variation. This study not only reveals the characteristics and influencing factors of CH₄ emissions from cascade reservoirs on the Qinghai Plateau but also provides a scientific basis for calculating fluxes and developing global CH₄ reduction strategies for reservoirs. Full article

The upper reaches of the Yellow River are critical ecological barriers within the Yellow River Basin (YRB) that are crucial for source conservation. However, environmental challenges in this area, from Longyangxia to Lijiaxia, have emerged in recent years. To assess the ecological environment quality (EEQ) evolution from 1991 to 2021, we utilized remote sensing ecological indices (RSEIs) on the Google Earth Engine (GEE) platform. Spatial autocorrelation and heterogeneity impacting EEQ changes were examined. The results of this study show that the mean value of the RSEIs fluctuated over time (1991: 0.70, 1996: 0.77, 2001: 0.67, 2006: 0.71, 2011: 0.68, 2016: 0.65, and 2021: 0.66) showing an upward, downward, and then upward trend. The mean values of the overall RSEI are all at 0.65 and above. Most regions showed no significant EEQ change during 1991–2021 (68.59%, 59.23%, and 55.78%, respectively). Global Moran’s I values (1991–2021) ranged from 0.627 to 0.412, indicating significant positive correlation between EEQ and spatial clustering, and the LISA clustering map (1991–2021) shows that the area near Longyangxia Reservoir shows a pattern of aggregation, dispersion, and then aggregation again. The factor detection results showed that heat was the most influential factor, and the interaction detection results showed that greenness and heat had a significant effect on regional ecosystem distribution. Our study integrates spatial autocorrelation and spatial heterogeneity and combines them with reality to provide an in-depth discussion and analysis of the Longyangxia to Lijiaxia Basin. These findings offer guidance for ecological governance, vegetation restoration, monitoring, and safeguarding the upper Yellow River’s ecological integrity. Full article

The Yellow River, a critical water resource, faces challenges stemming from increasing water demand, which has led to detrimental effects on hydropower generation and ecological balance. This paper will address the complex task of balancing the interests of hydropower generation, water supply, and ecology within the context of cascade reservoirs, specifically Longyangxia and Liujiaxia reservoirs. Employing a systemic coupling coordination approach, we constructed a multi-objective synergetic model of the upper Yellow River in order to explore synergies and competitions among multiple objectives. The results reveal that there is a weak competitive relationship between hydropower generation and water supply, a strong synergy between hydropower generation and ecology, and a strong competitive relationship between water supply and ecology. The Pareto solution set analysis indicates a considerable percentage (59%, 20%, and 8% in wet, normal, and dry years, respectively) exhibiting excellent coordination. The probability of excellent coordination decreases with diminishing inflow. The optimization scheme with the highest coupling coordination demonstrates significant improvements in power generation, water supply, and ecological benefits in the upper Yellow River without compromising other objectives, fostering the sustainable operation of hydropower generation, water supply, and ecology in the upper Yellow River. Full article

The instability of the river channels has increased in response to the combined effects of global warming and human activity. This instability threatens the lives and property of people who live along river courses. This study takes the Pingluo section of the upper Yellow River, which is ~28 km long and ~400 m wide, as its research focus. We studied 11 periods of Landsat remote sensing images from 1973 to 2023 and analyzed the evolutionary characteristics of the Pingluo section over the past 50 years. The channel morphology indices included the channel braiding index (BI_T), the bar braiding index (BI_B), the average area of the bar (A_b), and the width of the wet channel area (B_W). The results showed that there was an overall shrinking trend in this section of the Yellow River; more particularly, fluctuations in indicators such as the river width and the braiding index highlighted an increasing–decreasing–increasing pattern of change. During the 1973–1986 period, the river showed a widening trend, with narrow anabranches cutting through the floodplain and both the river width and the braiding index increasing dramatically over a short period. Over the 1986–2018 period, the area of the wet channel continued to shrink to its lowest level for the past 50 years, the river’s branches were diverted and abandoned, and the channel tended to straighten out. Between 2018 and 2023, the river showed a slightly expanding trend. The evolution of the river channel appears to be related to regional human activity and climate change. For example, after the joint filling of the Longyangxia and Liujiaxia reservoirs in the upper reaches of the Pingluo section of the Yellow River in 1986, runoff and sediment load along this section decreased, flood events became less frequent, and the channel tended to contract. In addition, the increase in extreme precipitation events over the last five years has led to an increase in the magnitude and frequency of peak discharge values in the region, which is the main reason for the increase in the river braiding index and area. Full article

The source area of the Yellow River (SAYR) in China is an important water yield and water-conservation area in the Yellow River. Understanding the variability in rainfall and flood over the SAYR region and the related mechanism of flood-causing rainfall is of great importance for the utilization of flood water resources through the optimal operation of cascade reservoirs over the upper Yellow River such as Longyangxia and Liujiaxia, and even for the prevention of flood and drought disasters for the entire Yellow River. Based on the flow data of Tangnaihai hydrological station, the rainfall data of the SAYR region and NCEP-NCAR reanalysis data from 1961 to 2020, three meteorological conceptual models of flood-causing rainfall—namely westerly trough type, low vortex shear type, and subtropical high southwest flow type—are established by using the weather-type method. The mechanism of flood-causing rainfall and the corresponding flood characteristics of each weather type were investigated. The results show that during the process of flood-causing rainfall, in the westerly trough type, the mid- and high-latitude circulation is flat and fluctuating. In the low vortex shear type, the high pressures over the Ural Mountains and the Okhotsk Sea are stronger compared to other types in the same period, and a low vortex shear line is formed in the west of the SAYR region at the low level. The rain is formed during the eastward movement of the shear line. In the subtropical high southwest flow type, the low trough of Lake Balkhash and the subtropical high are stronger compared to other types in the same period. Flood-causing rainfall generally occurs in areas with low-level convergence, high-level negative vorticity, low-level positive vorticity, convergence of water vapor flux, a certain amount of atmospheric precipitable water, and low-level cold advection. In terms of flood peak increment and the maximum accumulated flood volume, the westerly trough type has a long duration and small flood volume, and the low vortex shear type and the subtropical high southwest flow type have a short duration and large flood volume. Full article

The Inner Mongolia section of the Yellow River is a primary alluvial segment of the main channel. The variations in water and sediment not only alter the cross-sectional morphology and flow capacity of the river but also impact the scheduling of upstream cascade reservoirs. Based on runoff and sediment load data and topographic information from typical hydrological stations, the characteristics of runoff and sediment load variations and the evolutionary pattern of siltation in the Inner Mongolia River section were analyzed via trend analysis methods, Mann–Kendall test methods, the sediment load transport rate method, and the water level–flow relationship. The results showed that the water and sediment loads at the hydrological stations in the Inner Mongolia River section significantly changed from the 1960s to after 2000, with runoff decreasing by approximately 22% to 32% and the sediment load decreasing by approximately 65% to 73%. Sedimentation in the river section generally increased, and the average annual siltation amount reached 0.144 billion t. The joint utilization of the Longyangxia and Liujiaxia reservoirs in 1987 was the main reason for the rapid increase in siltation, and siltation in the Inner Mongolia River section was slightly reduced after 2005. In addition, the critical sediment load coefficients of the Bayangaole–Sanhuhekou and Sanhuhekou–Toudaoguai River sections were 0.0073 and 0.0051 kg·s/m⁶, respectively, from 1952 to 1968, and 0.0053 and 0.0037 kg·s/m⁶, respectively, from 1969 to 2020. This study could provide technical support for river flood control and reservoir water sediment regulation in Inner Mongolia. Full article

The European Space Agency (ESA) developed the Sentinel-2 Multispectral Imager (MSI), which offers a higher spatial resolution and shorter repeat coverage, making it an important source for the remote-sensing monitoring of water bodies. Atmospheric correction is crucial for the monitoring of water quality. To compare the applicability of seven publicly available atmospheric correction processors (ACOLITE, C2RCC, C2XC, iCOR, POLYMER, SeaDAS, and Sen2Cor), we chose complex and diverse lakes in Qinghai Province, China, as the research area. The lakes were divided into three types based on the waveform characteristics of R_rs: turbid water bodies (class I lakes) represented by the Dabusun Lake (DBX), clean water bodies (class II lakes) represented by the Qinghai Lake (QHH), and relatively clean water bodies (class III lakes) represented by the Longyangxia Reservoir (LYX). Compared with the in situ R_rs, it was found that for the DBX, the Sen2Cor processor performed best. The POLYMER processor exhibited a good performance in the QHH. The C2XC processor performed well with the LYX. Using the Sen2Cor, POLYMER, and C2XC processors for classes I, II, and III, respectively, compared with the Sentinel-3 OLCI Level-2 Water Full Resolution (L2-WFR) products, it was found that the estimated R_rs from the POLYMER had the highest consistency. Slight deviations were observed in the estimation results for both the Sen2Cor and C2XC. Full article

The construction of Longyangxia Reservoir has altered the hydrogeological conditions of its banks. Infiltration and erosion caused by the periodic rise and fall of the water level leads to collapse of the reservoir banks and local deformation of the landslide. Due to heterogeneous topographic characteristics across the region, water level also varies between different location. Previous research on the influence of fluctuations in reservoir water level on landslide deformation has focused on single-point monitoring of specific slopes, and single-point water level monitoring data have often been used instead of water level data for the entire reservoir region. In addition, integrated remote sensing methods have seldom been used for regional analysis. In this study, the freely-available Landsat8 OLI and Sentinel-2 data were used to extract the water level of Longyangxia Reservoir using the NDWI method, and Sentinel-1A data were used to obtain landslide deformation time series using SBAS-InSAR technology. Taking the Chana, Chaxi, and Mangla River Estuary landslides (each having different reservoir water level depths) as typical examples, the influence of changes in reservoir water level on the deformation of three wading landslides was analyzed. Our main conclusions are as follows: First, the change in water level is the primary external factor controlling the deformation velocity and trend of landslides in the Longyangxia Reservoir, with falling water levels having the greatest influence. Second, the displacement of the Longyangxia Reservoir landslides lags water level changes by 0 to 62 days. Finally, this study provides a new method applicable other areas without water level monitoring data. Full article

The perennial storage water level (PL), the water level at the end of wet season (WL), and the water level at the end of dry season (DL) are three critical water levels for multiyear regulating storage (MRS) reservoirs. Nevertheless, the three critical water levels have not been paid enough attention, and there is no general method that calculates them in light of developing regulating rules for MRS reservoirs. In order to address the issue, three-parameter regulation (TPR) rules based on the coordination between the intra- and interannual regulation effects of MRS reservoirs are presented. Specifically, a long-term optimal scheduling (LTOS) model is built for maximizing the multiyear average hydropower output (MAHO) of a multireservoir system. The TPR rules are a linear form of rule with three regulation parameters (annual, storage, and release regulation parameters), and use the cuckoo search (CS) algorithm to solve the LTOS model with three regulation parameters as the decision variables. The approach of utilizing the CS algorithm to solve the LTOS model with the WL and DL as the decision variables is abbreviated as the OPT approach. Moreover, the multiple linear regression (MLR) rules and the artificial neural network (ANN) rules are derived from the OPT approach-based water-level processes. The multireservoir system at the upstream of Yellow River (UYR) with two MRS reservoirs, Longyangxia (Long) and Liujiaxia (Liu) reservoirs, is taken as a case study, where the TPR rules are compared with the OPT approach, the MLR rules, and the ANN rules. The results show that for the UYR multireservoir system, (1) the TPR rules-based MAHO is about 0.3% (0.93 × 10⁸ kW∙h) more than the OPT approach-based MAHO under the historical inflow condition, and the elapsed time of the TPR rules is only half of that of the OPT approach; (2) the TPR rules-based MAHO is about 0.79 × 10⁸ kW∙h more than the MLR/ANN rules-based MAHO under the historical inflow condition, and the TPR rules can realize 0.1–0.4% MAHO more than the MLR and ANN rules when the reservoir inflow increases or reduces by 10%. According to the annual regulation parameter, the PLs of Long and Liu reservoirs are 2572.3 m and 1695.2 m, respectively. Therefore, the TPR rules are an easy-to-obtain and adaptable LTOS rule, which could reasonably and efficiently to determine the three critical water levels for MRS reservoirs. Full article

Large-scale reservoirs have played a significant role in meeting various water demands and socio-economic development, while they also lead to undeniable impacts on the environment and ecology. The Longyangxia reservoir located on the Yellow River is the first large-scale reservoir on the upper Yellow River with a control area of 18% of the entire Yellow River Basin. Since it was put into operation in 1987, it has made great contributions to the national economy for over 30 years. In this study, the socio-economic benefits of the Longyangxia reservoir in power generation, water supply, flood control, and ice prevention are investigated. More importantly, its impacts on the ecology and environment are also presented and analyzed, such as the impacts on river morphology, flow regimes, peak flow, fish, phytoplankton, and zooplankton. It can be concluded that the construction of the Longyangxia reservoir contributes greatly to socio-economic benefits, the water area nearby has formed a new ecological environment, and the trophic level of the aquatic environment has probably increased. Full article

Satellite radar altimetry is an important technology for monitoring water levels, but issues related to waveform contamination restrict its use for rivers, narrow reservoirs, and small lakes. In this study, a novel and improved empirical retracker (ImpMWaPP) is presented that can derive stable inland lake levels from Cryosat-2 synthetic aperture radar interferometer (SARin) waveforms. The retracker can extract a robust reference level for each track to handle multi-peak waveforms. To validate the lake levels derived by ImpMWaPP, the in situ gauge data of seven lakes in the Tibetan Plateau are used. Additionally, five existing retrackers are compared to evaluate the performance of the proposed ImpMWaPP retracker. The results reveal that ImpMWaPP can efficiently process the multi-peak waveforms of the Cryosat-2 SARin mode. The root-mean-squared errors (RMSEs) obtained by ImpMWaPP for Qinghai Lake, Nam Co, Zhari Namco, Ngoring Lake, Longyangxia Reservoir, Bamco, and Dawa Co are 0.085 m, 0.093 m, 0.109 m, 0.159 m, 0.573 m, 0.087 m, and 0.122 m, respectively. ImpMWaPP obtains the lowest mean RMSE (0.175 m) over the seven lakes, indicating that it extracts lake levels well during icing and no-ice periods, and is more suitable for lakes frozen in winter. Full article