Journal of Hydrology最新文献

{"title":"Improving joint identification of groundwater contaminant source and non-Gaussian distributed conductivity field using a deep learning-based ensemble smoother","authors":"Lei He ,&nbsp;Huan Cheng ,&nbsp;Zhengnian Nan ,&nbsp;Yiqing Gong ,&nbsp;Huifang Guo ,&nbsp;Jingqiao Mao ,&nbsp;Jiangjiang Zhang","doi":"10.1016/j.jhydrol.2025.133202","DOIUrl":"10.1016/j.jhydrol.2025.133202","url":null,"abstract":"<div><div>Accurate simulation of groundwater flow and solute transport is crucial for effective risk assessment and targeted pollution remediation. The inherent complexity of groundwater systems, characterized by elusive contamination sources and heterogeneous aquifer structures, introduces significant uncertainty into model simulations and predictions. Given the difficulty in directly measuring these unknown parameters, their estimation often relies on utilizing indirect observational data (e.g., hydraulic head and solute concentration) with data assimilation (DA) techniques. Traditional DA methods such as Markov chain Monte Carlo (MCMC) and ensemble smoother with multiple DA (ESMDA) struggle with high dimensionality and non-Gaussianity issues, leading to suboptimal performance in calibrating complex groundwater models. In this study, we introduce an innovative DA approach that integrates ensemble smoother (ES) with deep learning (DL), termed ESDL, designed for joint identification of contaminant source and heterogeneous conductivity field represented by high-dimensional and non-Gaussian distributed parameters. ESDL leverages DL’s robust capabilities in fitting non-linear relationships and discerning complex (including non-Gaussian) features to extract valuable insights from observational data. We systematically evaluate the efficacy of ESDL and ESMDA through three case studies involving 3,329 unknown model parameters with non-Gaussian spatial characteristics (multi-facies and channels, respectively). The impact of biased prior assumptions on identification performance is also investigated. Across these cases, ESDL exhibits superior performance in characterizing non-Gaussian conductivity fields and matching the observations, while ESMDA excels in estimating contaminant source parameters. Both methods demonstrate distinct strengths, underscoring the potential for future research to integrate these approaches for enhanced performance.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133202"},"PeriodicalIF":5.9,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climate change and ENSO significantly enhances seasonal flood occurrence in the Ganges-Brahmaputra-Meghna basin","authors":"Shahab Uddin ,&nbsp;Dai Yamazaki ,&nbsp;Anna Lintern ,&nbsp;Menaka Revel ,&nbsp;Prakat Modi","doi":"10.1016/j.jhydrol.2025.133207","DOIUrl":"10.1016/j.jhydrol.2025.133207","url":null,"abstract":"<div><div>Seasonal hydrological dynamics have profound socio-economic implications for communities in the Ganges-Brahmaputra-Meghna (GBM) River basin. Climate change and El Niño-Southern Oscillation (ENSO) phase are known to impact extreme flood magnitude in GBM River, however how they affect seasonal flooding pattern is not revealed. Utilizing large ensemble climate data (comprising 6000 years of non-warming and warming climate scenarios) and the global hydrodynamic model CaMa-Flood, we assess the influence of climate change and ENSO on seasonal hydrological patterns specially focusing on maximum river flow. The quantitative effects of La Niña and El Niño are calculated utilizing the Fractional Attribution Risk (FAR) method, separately for non-warming and historical climate scenarios. We assess climate change’s impact on flooding by contrasting historical and non-warming climate conditions using the FAR method. Climate change has substantially increased the maximum river flow for all seasons. In the monsoon season, climate change amplifies the likelihood of flooding with a 10-year return period of 34 %, 46 %, and 31 % at the Hardinge Bridge, Bahadurabad, and Bhairab Bazar gauge stations of the Ganges, Brahmaputra, and Meghna Rivers, respectively. The influence of ENSO still remains significant even with the influence of climate change.<!--> <!-->ENSO influence presents a nuanced picture, exhibiting variations both between seasons and across different rivers within the GBM basin. The relationship between ENSO and seasonal flood occurrence in the GBM basin can be effectively elucidated by the upward movement of moisture through vertical wind velocity, which serves as a large-scale controlling factor for flood variation.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133207"},"PeriodicalIF":5.9,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel inverse model insensitive to initial guesses for estimating parameters of continuous time random walk-truncated power law model","authors":"Behrouz Mehdinejadiani","doi":"10.1016/j.jhydrol.2025.133206","DOIUrl":"10.1016/j.jhydrol.2025.133206","url":null,"abstract":"<div><div>This study introduces a new, user-friendly inverse model based on the teaching learning-based optimization (TLBO) algorithm for estimating the parameters of the continuous time random walk-truncated power law (CTRW-TPL) model, including normalized transport velocity (<span><math><mrow><msub><mi>v</mi><mi>φ</mi></msub></mrow></math></span>), normalized dispersion coefficient (<span><math><mrow><msub><mi>D</mi><mi>φ</mi></msub></mrow></math></span>), power law exponent (β), and time scale of <span><math><mrow><msub><mi>t</mi><mn>2</mn></msub></mrow></math></span>. A sensitivity analysis revealed that the β has the most effect on the results of the CTRW-TPL model, followed by the <span><math><mrow><msub><mi>v</mi><mi>φ</mi></msub></mrow></math></span>, <span><math><mrow><msub><mi>D</mi><mi>φ</mi></msub></mrow></math></span>, and <span><math><mrow><msub><mi>t</mi><mn>2</mn></msub></mrow></math></span>, respectively. The sensitivity of the proposed inverse model (CTT) to initial parameter guesses was significantly lower compared to the CTRW MATLAB toolbox (CMT). Performance comparisons of the CTT using synthetic, experimental, and direct numerical simulation (DNS) breakthrough curves (BTCs) demonstrated that it provides more accurate estimates for the parameters β, <span><math><mrow><msub><mi>v</mi><mi>φ</mi></msub></mrow></math></span>, and <span><math><mrow><msub><mi>D</mi><mi>φ</mi></msub></mrow></math></span> compared to the CMT. In a nutshell, the CTT is an efficient and robust tool for estimating the CTRW-TPL parameters in both porous and fractured media.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133206"},"PeriodicalIF":5.9,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seasonal freeze-thaw CO2 sink 'midday rest' phenomenon in lakes: A case study of the largest freshwater lake in the Yellow River Basin","authors":"Yue Sun ,&nbsp;Xiaohong Shi ,&nbsp;Ruli Kang ,&nbsp;Zhaoxia Yang ,&nbsp;Shengnan Zhao ,&nbsp;Guohua Li ,&nbsp;Yanjun Wang ,&nbsp;Jussi Huotari","doi":"10.1016/j.jhydrol.2025.133208","DOIUrl":"10.1016/j.jhydrol.2025.133208","url":null,"abstract":"<div><div>The transition between ice-covered and non-ice-covered periods in lakes is continuous. However, the scarcity of comparative CO₂ flux studies between these periods in large plateau lakes of mid-latitude regions represents a significant gap in our knowledge. This study is the first to use an eddy covariance system to directly measure year-round CO₂ flux (May 2018 to April 2019) at Lake Wuliangsuhai, the largest freshwater lake on the Inner Mongolia Plateau in the Yellow River Basin. Results indicated that Lake Wuliangsuhai was a CO₂ sink throughout the observation period. During the ice-covered period, the lake absorbed significant amounts of CO₂ (−0.82 ± 0.26gCm⁻²d⁻¹), about half the rate observed during the non-ice-covered period (−1.61 ± 1.23gCm⁻²d⁻¹). In the non-ice-covered period, the net CO₂ exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RECO) were −382.26 gCm⁻², −519.02 gCm⁻², and 146.98 gCm⁻², respectively. Significant diurnal variations were observed between the two periods. A “midday rest” phase, attributed to stomatal closure in emergent plants, characterized the non-ice-covered period. Carbon source activity was more intense during the non-ice-covered period, showing an unimodal pattern. Monthly, NEE and GPP followed a bimodal pattern. As the lake transitioned from the non-ice-covered to the ice-covered period, daytime meteorological factors influencing CO₂ absorption decreased by nearly half, while nighttime driving forces increased substantially. Eutrophication reduced CO₂ absorption during the non-ice-covered period but enhanced it during the ice-covered period, with CO₂ flux changes showing a delayed response. Lake Wuliangsuhai demonstrated a stronger CO₂ sink capacity than other lakes during both periods.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133208"},"PeriodicalIF":5.9,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Responses of leaf-level physiological traits and water use characteristics to drought of a xerophytic shrub in northern China","authors":"Lei Wang ,&nbsp;Ying Ma ,&nbsp;Yue Li ,&nbsp;Di Wang ,&nbsp;Jinxia An ,&nbsp;Yiming Shao ,&nbsp;Guangyao Gao","doi":"10.1016/j.jhydrol.2025.133204","DOIUrl":"10.1016/j.jhydrol.2025.133204","url":null,"abstract":"<div><div>Frequent drought distinctly affects the water use characteristics and physiological responses of xerophytic shrubs, which has significantly altered the regional water cycle in drylands. It is essential to explore the coordination between leaf-level physiological traits and root water uptake patterns of xerophytic shrubs to adapt drought. In this study, the soil water dynamics in 0–200 cm, sap flow, leaf-level physiological traits, and stable isotopes (δ²H, δ¹⁸O, and δ¹³C) of <em>Salix psammophila</em> were observed over three different hydrological years (2019–2021) in the semi-arid Loess Plateau of China, and the responses of water use patterns and physiological traits to drought were investigated. Results showed that in wet (2019) and normal (2020) years, <em>S. psammophila</em> mainly utilized soil water in shallow layer (0–40 cm) with proportion of 46.0 ± 12.3 % and had a higher transpiration rate and intrinsic water use efficiency (iWUE). In dry year (2021), the main soil water source shifted to the middle layer (40–120 cm) with proportion of 51 ± 1.5 % and utilization of soil water in deep layer (120–200 cm) also increased, while iWUE decreased by 10 %. During the three years, an average of 39.4 % and 40.2 % of transpiration were provided by soil water in shallow and middle layers, respectively. <em>S. psammophila</em> could not completely alleviate drought stress by utilizing deep soil water due to persistent deep soil desiccation. In contrast, <em>S. psammophila</em> regulated leaf-level physiological traits (such as reducing leaf water potential and leaf area index) to reduce transpiration for adapting drought in dry year. The findings highlight that deep soil water is not a sustainable water source for xerophytic shrubs during drought, and deep soil water desiccation is the main threat for xerophytic shrub mortality. This study deepens understanding of drought resistance mechanisms of xerophytic shrubs, thereby providing essential insights for shrub ecosystem management to adapt global warming in drylands.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133204"},"PeriodicalIF":5.9,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time-varying mechanisms of hydraulic properties of root-soil composites under plant root decay","authors":"Suyun Meng,&nbsp;Tongyun Zhang,&nbsp;Guoqing Zhao,&nbsp;Shiwei Hou","doi":"10.1016/j.jhydrol.2025.133192","DOIUrl":"10.1016/j.jhydrol.2025.133192","url":null,"abstract":"<div><div>The hydraulic effect of plant roots reduces precipitation infiltration and enhances shallow slope stability. However, after root death and decay, soil permeability increases while water-retention capacity decreases. The time-varying mechanisms governing the hydraulic properties of root-soil composites after root decay remain unclear. This study examines the evolution of soil pore structure following root decay. A time-varying soil water retention curve (SWRC) model was developed to characterize changes in water-retention capacity. Additionally, a time-varying saturated infiltration coefficient model and a permeability coefficient prediction model were established to describe variations in hydraulic properties. A one-dimensional soil column infiltration test was conducted on root-soil composites at different stages of root decay to investigate the time-dependent changes in hydraulic properties. The reliability of the proposed models was validated using experimental results.</div><div>The findings indicate the following: After root death, root biomass, diameter, length, and number decreased with increasing decay time, stabilizing after four months. Root decay led to a reduction in root volume ratio, which altered soil structure and enhanced the permeability of root-soil composites. Longer decay periods increased soil porosity, modifying the soil water characteristic curve and reducing water-retention capacity. Creeping roots decayed more significantly than fibrous roots due to their distinct morphological traits, making changes in hydraulic properties more pronounced in the topsoil. Therefore, plant root decay negatively affects soil hydraulic properties by continuously altering soil pore structure. These findings provide a crucial foundation for understanding the time-dependent mechanisms of hydraulic property variations in root-soil composites during plant root decay.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133192"},"PeriodicalIF":5.9,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the use of structure-from-motion photogrammetry to monitor eroding banks of the black vermillion river in northeast Kansas","authors":"Michael E. McNair ,&nbsp;Howard D. Hahn ,&nbsp;Timothy D. Keane","doi":"10.1016/j.jhydrol.2025.133194","DOIUrl":"10.1016/j.jhydrol.2025.133194","url":null,"abstract":"<div><div>Remote sensing techniques, such as terrestrial laser scanner (TSL), airborne light detection and ranging (LiDAR), and Structure-from-Motion Photogrammetry (SfM), can be used to survey riverbanks having three-dimensional complexity. This research focuses on SfM, which has comparable accuracies to LiDAR and TLS but with lower costs and shorter data collection times. SfM was used to monitor selected banks of the Black Vermillion River (BVR) in Northeast Kansas typified by seasonally varying amounts of herbaceous bank vegetation and high, vertical banks. Data was collected six times between December 2020 and July 2022. Newly established vegetation was removed from the SfM point clouds leaving voids, and volume change was calculated with empty and interpolated voids. Comparison of each study bank’s leaf-off to leaf-off-condition point cloud pair in both the typical vertical and horizontal directions, showed an 18 % increase in net erosion, 13 % increase in model overlap, yet 4.9-mm increase in error, when horizontal was specified. All banks (822 m) experienced an estimated −1,729 m³ of net erosion during the study; however, one study bank experienced net deposition of 10.74 m³. Study banks with the highest amounts of net erosion (−409 m³, and –233 m³) experienced mass-wasting erosional processes. The data suggest SfM is better at monitoring actively eroding banks where vegetation did not establish, as interpolated voids led to the overestimation of deposition. Understanding rates of sediment production will inform the management of Tuttle Creek Reservoir, which is downstream of the BVR and has lost approximately 50 % of its capacity from sedimentation.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133194"},"PeriodicalIF":5.9,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lake-water-temperature regulation under diurnal and annual cycles of environmental forcing, Agamon Hula, Israel","authors":"Guy Tau ,&nbsp;Yehouda Enzel ,&nbsp;Hamish McGowan ,&nbsp;Vladimir Lyakhovsky ,&nbsp;Nadav G. Lensky","doi":"10.1016/j.jhydrol.2025.133142","DOIUrl":"10.1016/j.jhydrol.2025.133142","url":null,"abstract":"<div><div>Lake-water temperature regulation responds to annual and diurnal cycles of environmental forcing (radiation, wind speed, and air properties) through heat exchange, balancing stored heat with incoming and outgoing fluxes. Given the critical role of temperature response in influencing the ecological resilience and biogeochemical cycles of lakes, it requires precise mathematical expression based on direct observation. Here, this is addressed by accurately determining the equilibrium temperature, achieved when changes in stored heat are negligible, and its dependence on environmental forcing. Water temperature gradually approaches equilibrium, with a certain response time that depends on lake depth and wind velocities. The dynamics between water and equilibrium temperature and their corresponding surface heat fluxes are controlled by the ratio between the lake’s thermal response time to the environmental forcing timescale. The unique role of this ratio was examined using two years of continuous direct measurements from an eddy covariance tower at Agamon Hula, a shallow lake in northern Israel. Our results reveal that the lakes thermal response time is ∼1 day. Consequently, water temperature closely follows the equilibrium temperature at the intra-annual cycle, and deviates from equilibrium under the diurnal cycle. This agrees well with the measured heat fluxes, where under the intra-annual cycle, incoming radiation is balanced mainly by evaporation and changes in stored heat are negligible, as opposed to large oscillations in heat storage under the diurnal cycle. We leverage the results to study expected annual water temperatures under different environmental scenarios, and the role lake depth has on diurnal water temperatures.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133142"},"PeriodicalIF":5.9,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncertainty pattern and an integration strategy in flood susceptibility modeling: Limited sample size","authors":"Jun Liu,&nbsp;Xueqiang Zhao,&nbsp;Yangbo Chen,&nbsp;Huaizhang Sun,&nbsp;Yu Gu,&nbsp;Shichao Xu","doi":"10.1016/j.jhydrol.2025.133184","DOIUrl":"10.1016/j.jhydrol.2025.133184","url":null,"abstract":"<div><div>Flood is one of the most destructive natural disasters occurring across the globe. Employing machine learning models to construct flood susceptibility maps has emerged as an effective strategy in disaster prevention and management. Sample size is one of the primary sources of uncertainty in machine learning model, posing significant challenges to the flood susceptibility in data-scarce regions. However, the understanding of uncertainty patterns and effective methods to improve modeling accuracy under limited sample conditions are still evolving. Here, we applied uncertainties analysis theory to clarify this pattern for seven base machine learning models. Further, an integration strategy was developed by coupling geographical similarity, semi-supervised learning and active learning method. The analysis of uncertainty pattern indicates that each base machine learning model exhibits varying degrees of tolerance to changes in sample size. Specifically, a threshold exists below which the accuracy of model declines sharply, leading to significant changes in the distribution patterns of predicted flood susceptibility maps. The proposed integration strategy can enhance the accuracy and stability of models operating with limited sample sizes. Applying the ensemble strategy and increasing the number of labeled samples from 10 to 500, the average AUC values for the models improved as follows: RF ranged from 0.76 to 0.85, SVM from 0.46 to 0.86, MLP from 0.77 to 0.86, NB from 0.75 to 0.86, KNN from 0.72 to 0.83, DT from 0.65 to 0.78, and LR from 0.70 to 0.86.The insights into uncertainty pattern derived from this study can help guide the balancing of sample collection costs with model accuracy. Moreover, the proposed integration strategy is expected to improve flood susceptibility prediction in areas with limited samples.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133184"},"PeriodicalIF":5.9,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimized scheduling of cascade hydropower stations with advance risk control in dynamic operations","authors":"Yalin Zhang ,&nbsp;Haizheng Wang ,&nbsp;Guohua Fang ,&nbsp;Ziyu Ding ,&nbsp;Xianfeng Huang","doi":"10.1016/j.jhydrol.2025.133196","DOIUrl":"10.1016/j.jhydrol.2025.133196","url":null,"abstract":"<div><div>The uncertainty in forecasting runoff can lead to operational scheduling risks in the scheduling of cascade hydropower stations, potentially impacting power generation efficiency and supply quality. This study proposes an optimized method for formulating scheduling decisions by implementing advance risk control in the dynamic scheduling process for cascade hydropower stations. Firstly, the improved VMD method is proposed to reduce the noise in forecasting runoff errors, followed by an LSTM model to predict these errors, enabling the correction of the forecasted runoff. Next, the CVaR method is utilized to dynamically quantify the risks of insufficient power generation and water surplus associated with the scheduling strategy of cascade hydropower stations. Finally, an optimized scheduling model is established to formulate a scheduling strategy that considers both power generation benefits and scheduling risks. A case study in the Wujiang River Basin demonstrates that the forecasting runoff correction method effectively reduces the Mean Relative Error (MRE) in forecasting runoff. The proposed optimized scheduling model improves the accuracy of scheduling decisions for the Dahuashui and Geliqiao hydropower stations during flood seasons by 1.04% and 0.17%, respectively, and reduces actual water surplus by 1.18% and 0.28%. In dry seasons, it increases the accuracy of scheduling decisions by 6.21% and 8.48%, respectively. This model ensures power generation efficiency while reducing operational scheduling risks and enhancing decision accuracy across varying seasonal conditions.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133196"},"PeriodicalIF":5.9,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}