Journal of Hydrology最新文献

{"title":"Identification of drought-flood abrupt alternation by a new non-stationary framework considering natural-social system impacts","authors":"Hao Cui ,&nbsp;Shanhu Jiang ,&nbsp;Liliang Ren ,&nbsp;Tianling Qin ,&nbsp;Qiuan Zhu ,&nbsp;Xiuqin Fang ,&nbsp;Chong-Yu Xu","doi":"10.1016/j.jhydrol.2025.132899","DOIUrl":"10.1016/j.jhydrol.2025.132899","url":null,"abstract":"<div><div>The drought-flood abrupt alternation (DFAA), defined as the phenomenon of flood (drought) following droughts (flood), magnifies the impact of individual flood and drought events yet has not been accurate assessment. Previous studies have used the stationary approach to identify DFAA events, where a fixed parameter is used to fit the SSI and then a threshold is determined to identify DFAA events. However, because changes in climate or human activities can induce significant variations in the underlying probability distributions of streamflow, the method’s usual assumption of stationarity should be questioned. In this study, a new non-stationary assessment framework considering natural-social systems is developed for identifying hydrological DFAA events. The framework was applied to the study of DFAA events at Huayuankou Station (HYK) in the Yellow River Basin (YRB) over the past 60 years (1961–2020). The main findings include: (1) The non-stationary test results demonstrate the emergence of non-stationary characteristics of streamflow at HYK station. The study period is divided into two periods, the base period (1961–1990) and the change period (1991–2020), based on the mutation test results. (2) the climate and anthropogenic factors screened based on the causal inference method can effectively improve the fitting performance of the non-stationary model of the streamflow at the HYK station, and better respond to the evolutionary characteristics under the changing environments of the extreme hydrological events; and a new sedimentation-based reservoir index (SDRI) considering reservoir siltation has been developed, which has less uncertainty than fitting reservoir index (RI) as a covariate. (3) The trends of DFAA events identified by non-stationary standardized streamflow index (NSSI) and standardized streamflow index (SSI) are consistent. However, the frequency and severity of DFAA events may be underestimated if the non-stationary characteristics of streamflow are not considered. (4) The frequency and severity of DFAA events at HYK station during the change period were higher than those during the base period. In conclusion, the above findings contribute to a better understanding of the effect of streamflow non-stationary on DFAA event identification and can provide valuable information for drought and flood management decisions in changing environments.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132899"},"PeriodicalIF":5.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143474264","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":"Generalization of an intelligent real-time flood prediction model based on CBT-BLSTM-RPA and QRGP-WGAN: A perspective considering the effect of drainage pipeline siltation","authors":"Danyang Di ,&nbsp;Hongyuan Fang ,&nbsp;Guangxin Liu ,&nbsp;Dehua Zhu ,&nbsp;Bin Sun ,&nbsp;Niannian Wang ,&nbsp;Bin Li","doi":"10.1016/j.jhydrol.2025.132892","DOIUrl":"10.1016/j.jhydrol.2025.132892","url":null,"abstract":"<div><div>Impeded drainage caused by siltation of drainage pipelines is one of the primary causes of urban flooding. Existing real-time flood prediction methods do not fully consider the impact of pipeline siltation on flood disaster and lack intelligent prediction models on a spatiotemporal scale. To solve these problems, combined with the Hardy-Cross method, hydrodynamic empirical formula, and momentum moment conservation equation of pipeline siltation, a calibration method of equivalent pipeline siltation coefficient in subcatchment area and subsurface infiltration rate is proposed. Then, a Wasserstein generative adversarial network based on quantile regression and gradient penalty is introduced to expand the sample set of numerical simulation results of urban flood with high accuracy. On this basis, an intelligent flood prediction model integrating multi-scale convolution, batch normalization, Tanh units, multi-channel bidirectional long short-term memory neural network, and improved relational perceptual attention mechanism is constructed. To overcome the problem of hyperparameter optimization easily falling into local optimal solutions, a two-layer hyperparameter optimization mechanism based on sequential model optimization, transfer learning, maximum entropy search, and Bayesian optimization is formulated. The results indicated that the prediction accuracy of urban flood prediction model reached 85.57 % on the spatial scale and the Nash-Sutcliffe efficiency coefficient (NSE) of flood prediction on the temporal scale was greater than 0.9. The proposed intelligent flood prediction model in this study had clear advantages in terms of accuracy, reliability, and robustness.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"655 ","pages":"Article 132892"},"PeriodicalIF":5.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488202","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":"Conceptualization and assessment of groundwater–seawater interactions on bedrock islands","authors":"Rong Gong ,&nbsp;Dongmei Han ,&nbsp;Yi Xiao ,&nbsp;Xianfang Song ,&nbsp;Wei Wang ,&nbsp;Yanling Cao","doi":"10.1016/j.jhydrol.2025.132886","DOIUrl":"10.1016/j.jhydrol.2025.132886","url":null,"abstract":"<div><div>Groundwater and seawater interactions (GSIs) in coastal areas are significantly influenced by climate change and anthropogenic activities. However, few studies have focused on GSIs on a bedrock island scale. Compiled literature data from global investigations shows that over 68 % of investigated bedrock islands and coasts worldwide have been seriously threatened by groundwater salinization and NO₃-N contamination. This study investigates the Changshan Islands in Shandong, China. Utilizing hydrogeological data, historical rainfall, long-term groundwater levels (2010–2021), and multi-period hydrochemical data (2015–2021) to analyze groundwater dynamics and hydrochemical processes. Results reveal severe NO₃-N contamination in groundwater, with concentrations peaking at 40 mg/L, primarily due to domestic wastewater discharge and tourism activities. Excessive groundwater extraction exacerbates NO₃-N migration into deeper aquifers. Seawater intrusion (SWI) and submarine groundwater discharge (SGD) rates were calculated using Darcy’s law, with Cl^- and NO₃-N fluxes estimated. SWI is more pronounced on the north island, with an average SWI rate of 0.3 m/d. The associated Cl^- and NO₃-N fluxes are on average 119187.6 and 69.6 mmol/(m²·d), respectively. The southern island, largely free of SWI, has an average SGD rate of 0.2 m/d, with Cl^- and NO₃-N fluxes averaging 3912.1 and 81.8 mmol/(m²·d), respectively. Key factors influencing GSIs are precipitation, heterogeneous structure, hydrogeological conditions, and groundwater extraction. Based on these findings, we proposed a conceptual model of GSIs for these islands. This study would be helpful to enhance the understanding of island-scale GSIs’ patterns and the scientific management of island groundwater resources.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"655 ","pages":"Article 132886"},"PeriodicalIF":5.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520644","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":"Mapping 100 m multi-depth soil moisture with WRF-Hydro over Tibetan Plateau","authors":"Yuan Gan ,&nbsp;Shuzhe Huang ,&nbsp;Chao Wang ,&nbsp;Wei Wang ,&nbsp;Nengcheng Chen","doi":"10.1016/j.jhydrol.2025.132884","DOIUrl":"10.1016/j.jhydrol.2025.132884","url":null,"abstract":"<div><div>The Tibetan Plateau (TP), a critical area impacting regional and global climate systems, faces significant hydrological changes due to global warming. Understanding these changes requires high solution soil moisture (SM) profiles, which are fundamental for analyzing water and energy exchanges. To achieve high-precision and high-resolution SM products over the TP, this study conducted long-term WRF-Hydro simulations based on a variety of input data, with the option of enabling or disabling lateral flow processes. Ultimately, the most suitable settings for the SM simulation in the TP were identified, leading to the development of region-specific SM datasets at both 100 m and 1 km spatial resolution. High-resolution, multi-depth SM data were generated for four distinct regions: Ali and Naqu (August 2010 to December 2018), Maqu (January 2009 to December 2018), and Pali (June 2015 to December 2016), each at 100-meter spatial resolution and hourly temporal resolution. By comparing these datasets with existing global SM products (SMAP L4, GLDAS Noah and ERA5-Land), we observed an average improvement in correlation by 0.22, 0.263 and 0.137, and a reduction in unbiased RMSE by 14 %, 21.82 % and 25.86 %, respectively. This research emphasizes the importance of using high-resolution models, incorporating lateral flow processes, and high-precision input to capture the complex hydrological dynamics of the TP. It offers valuable insights into regional hydrological processes, potentially aiding future climatological and hydrological forecasts. The resulting dataset is made publicly available for further research and applications.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132884"},"PeriodicalIF":5.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143474070","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":"Geochemical evolution and flow of groundwater impacted by long-term abstraction in the Mekong Delta, Vietnam","authors":"Karsten Osenbrück ,&nbsp;Anke Steinel ,&nbsp;Nelly Montcoudiol ,&nbsp;Le Van Manh ,&nbsp;Roland Bäumle","doi":"10.1016/j.jhydrol.2025.132881","DOIUrl":"10.1016/j.jhydrol.2025.132881","url":null,"abstract":"<div><div>In many large river deltas, growth in agricultural production and population has led to a continuous drop in groundwater levels of the often multi-layered delta aquifers. To investigate the impact on groundwater quality, a total of 119 groundwater samples from (semi-)confined aquifers were collected for hydrochemical and isotopic (δ¹³C_DIC, ¹⁴C_DIC) analysis from the Mekong Delta in Vietnam, one of the world’s largest river deltas. These aquifers are dominated by groundwater of the Na-Cl to Na-HCO₃ type showing a large variation in dissolved concentration (TDS of 0.4 to 30.8 g/L). Geochemical modeling confirmed that dissolution of reactive minerals (e.g., carbonates, pyrite), mixing with seawater, and cation exchange are the relevant hydrogeochemical processes. The highly saline groundwater component is probably due to an exchange with connate seawater in the marine sediments of the Delta. δ¹³C_DIC values indicate that high DIC concentrations (up to 14 mmol/L) result from different sources (soil CO₂, dissolution of carbonates, reduction of sulfate by organic matter, and the admixture of seawater DIC). Adjusted ¹⁴C_DIC groundwater ages range from approx. 3 to more than 30 thousand years, which suggests that the groundwater was recharged during low seawater levels in the Upper Pleistocene. Contrary to expectations, ¹⁴C_DIC ages do not show clear age trends along the presumed flow direction or depth of the groundwater. This provides evidence for vertical flow or leakage processes through natural or artificial hydraulic windows within the aquitards, presumably caused or intensified by the increasing groundwater abstraction over recent decades.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"655 ","pages":"Article 132881"},"PeriodicalIF":5.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143526952","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":"Improving representation of hydrological process heterogeneity in grid-Xin’anjiang model through a stepwise approach","authors":"Qinuo Zhang ,&nbsp;Ke Zhang ,&nbsp;András Bárdossy ,&nbsp;Yunping Li ,&nbsp;Nan Wu","doi":"10.1016/j.jhydrol.2025.132897","DOIUrl":"10.1016/j.jhydrol.2025.132897","url":null,"abstract":"<div><div>Conceptual models often fail to give sufficient representation of the hydrological processes. Reasonably increasing process complexity in these models based on available data may help to find a balance between model realism and simplicity. This study aims to enhance the process representation capability of the grid-Xin’anjiang (GXAJ) model, a distributed conceptual model with a spatially uniform structure. We stepwise increased the dominant runoff process heterogeneity in the GXAJ model, which produced three new models, namely, MGXAJ^A, MGXAJ^B and MGXAJ^C model. Thereinto, MGXAJ^A was developed based on a topography-based hydrological landscape classification method, which delineated the watershed into three response units, i.e., wetland, hillslope and plateau. Different model structures were assigned to the individual units to represent their dominant runoff processes, i.e., saturated overland runoff, subsurface runoff and deep percolation, respectively. On the basis of MGXAJ^A, MGXAJ^B and MGXAJ^C progressively introduce more temporal variability of dominant processes by accounting for saturated overland runoff process on hillslope and plateau cells that have transformed into a quasi-wetland cell. The dynamic transformation process from a hillslope or plateau cell to a quasi-wetland cell will be initiated when its soil water content reaches a specific threshold. This stepwise approach was tested in the humid Tunxi watershed. It was found that compared to GXAJ and MGXAJ^A, MGXAJ^B and MGXAJ^C are more capable of reproducing different aspects of the outlet discharge hydrograph. Furthermore, MGXAJ^B-C behave in a more hydrologically meaningful and realistic way by representing the runoff composition patterns more reasonably in regard to both runoff type and runoff source. MGXAJ^C model allows a most adequate runoff process representation, but only slightly outperforms MGXAJ^B. These results indicate that accounting for the dominant runoff generation processes and their spatiotemporal heterogeneity in a watershed is effective in improving the simulation accuracy and advancing the process realism of a conceptual model. Moreover, a stepwise model test is essential to find a suitable model setup and thus achieve a good tradeoff between model realism and simplicity.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"655 ","pages":"Article 132897"},"PeriodicalIF":5.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143509502","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":"Enhancing representation of data-scarce reservoir-regulated river basins using a hybrid DL-process based approach","authors":"Liangkun Deng ,&nbsp;Xiang Zhang ,&nbsp;Louise J. Slater","doi":"10.1016/j.jhydrol.2025.132895","DOIUrl":"10.1016/j.jhydrol.2025.132895","url":null,"abstract":"<div><div>River discharge estimation in regulated river basins requires the inclusion of specific reservoir operation modules. However, human impacts remain challenging to depict in regions where upstream operational information (such as inflow and storage observations) is not available. Here, we develop a hybrid deep learning (DL)-process based approach that couples a conceptual hydrological model with simplified generic reservoir operation schemes and uses embedded neural networks (ENNs) to parameterize the conceptual model and optionally replace its reservoir operation module. We assess the ability of ENNs to compensate for the structural inability of simplified operation schemes to capture complex human impacts, while maintaining the advantage of minimal upstream operational record requirements. The hybrid models were tested across 43 regulated basins in the Continental USA in terms of their ability to simulate reservoir outflow, and evaluated in terms of their physical interpretability. Results show that the hybrid models outperformed both the conceptual and the LSTM models for outflow simulations, achieving a median NSE (KGE) of 0.648 (0.700) compared to 0.426 (0.415) for the conceptual models and 0.581 (0.636) for the LSTM model, with percentage improvements of 52.47 % (68.67 %) and 11.53 % (10.06 %) respectively. The dynamic parameterization by the ENNs compensates for the structural limitations of the simplified operation schemes to reproduce different operational patterns. Beyond their superior accuracy, the hybrid models also preserve physical interpretability, producing meaningful untrained internal variables such as inflow and evapotranspiration, and coherent parameters. The physical operation modules, while not improving final output accuracy, play a key role in supporting the physical interpretation of internal inflow processes. This highlights the importance of evaluating hybrid models comprehensively, rather than relying solely on final output performance. Our study offers deeper insights into hybrid modeling and provides a promising solution for system representation of data-scarce regulated river basins.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"655 ","pages":"Article 132895"},"PeriodicalIF":5.9,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143508852","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":"Coupled convolutional neural network with long short-term memory network for predicting lake water temperature","authors":"Huajian Yang,&nbsp;Chuqiang Chen,&nbsp;Xinhua Xue","doi":"10.1016/j.jhydrol.2025.132878","DOIUrl":"10.1016/j.jhydrol.2025.132878","url":null,"abstract":"<div><div>Water temperature is critical to freshwater ecosystems and lake habitats, and it directly affects the growth, reproduction and habitat of aquatic organisms. In this study, a separable convolutional neural network (SCNN) and long short-term memory (LSTM) neural network are combined to propose a SCNN-LSTM model for lake temperature prediction with only temperature as model input. The proposed SCNN-LSTM model was constructed using 35,064 samples, including hourly measured lake water temperature at 12 different depths, air temperature, wind speed, and solar irradiance. To evaluate the performance of the hybrid SCNN-LSTM model, the model was compared with the extreme gradient boosting (XGBoost) and Air2water models, respectively. In addition, the SCNN-LSTM model that only considers temperature is compared with the SCNN-LSTM model that considers multiple factors. The results show that the SCNN-LSTM model is superior to the XGBoost and Air2water models in predicting lake water temperature, and the SCNN-LSTM model considering only temperature has certain competitiveness compared with the SCNN-LSTM model considering multiple meteorological factors such as temperature, wind speed and solar irradiance.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"655 ","pages":"Article 132878"},"PeriodicalIF":5.9,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488333","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":"The propagation from atmospheric flash drought to soil flash drought and its changes in a warmer climate","authors":"Feng Ma ,&nbsp;Xing Yuan","doi":"10.1016/j.jhydrol.2025.132877","DOIUrl":"10.1016/j.jhydrol.2025.132877","url":null,"abstract":"<div><div>Soil flash droughts (SFDs), characterized by a rapid decline in soil moisture during drought onset, occurred frequently in recent decades and raised great challenges to drought monitoring and forecasting. Similar to traditionally slow-developing droughts, SFDs could originate from atmospheric droughts, but whether there is a connection between atmospheric flash droughts (AFDs) and SFDs remains unexplored. In this study, we identified AFDs and SFDs using 15-day mean vapor pressure deficit (VPD) and 5-day mean soil moisture (SM) respectively, and examined their occurrence frequency and propagation relationships during the growing seasons over global vegetated lands. Results show that the frequency of AFDs displays minor regional differences while SFDs are more frequent in humid regions. The global mean fractions of AFDs that trigger SFDs and SFDs that follow AFDs are 15 % and 31 % respectively, with significant spatial variability. Semi-humid and humid regions show higher propagation relationships between AFDs and SFDs. Antecedent SM conditions play critical roles in the propagation from AFDs to SFDs. Medium antecedent SM conditions (∼52nd percentile) accompanied by significantly elevated evapotranspiration (ET) at the onset of AFDs favor the occurrence of SFDs. High (∼69th percentile) and low (∼26th percentile) SM conditions limit the propagation from AFDs to SFDs. In a warmer future, the occurrence of AFDs is projected to increase globally, with a mean increase rate of 52.7 ± 4.27 % under a moderate emission scenario. The SFDs are projected to increase by 15.4 ± 7.03 %, with a larger increase in semi-humid and humid regions. The fraction of SFDs that follow AFDs is projected to increase by 33.33 ± 2.97 %, indicating a stronger link between SFDs and AFDs in a warmer climate. These findings improve our knowledge in the complicated propagation relationship between AFDs and SFDs and imply the urgency for adapting to flash droughts under climate warming.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132877"},"PeriodicalIF":5.9,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465091","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":"An innovative framework to assess the human-water relationship in complex pluvial flooding system at urban meso-scales","authors":"Chenlei Ye ,&nbsp;Weihong Liao ,&nbsp;Zongxue Xu ,&nbsp;Xinyi Shu","doi":"10.1016/j.jhydrol.2025.132876","DOIUrl":"10.1016/j.jhydrol.2025.132876","url":null,"abstract":"<div><div>Urban pluvial flooding, exacerbated by intense rainstorms, has emerged as a growing risk to urban safety in the face of climate change and accelerated urban development. Integrated hydrological and hydrodynamic models have become widely adopted for simulating urban floods, enhancing the accuracy of pluvial flood prediction. However, existing research has primarily focused on modeling flooding, while always overlooking the modeling of social systems directly impacted by floods. Moreover, various flood control measures under human influence can partially reduce peak discharge and surface runoff, making it crucial to deeply analyze the human-water relationship. This involves coupling the surface inundation process with social systems under flood control, which is a crucial issue in flood management. This research proposes an innovative framework to assess the human-water relationship in complex pluvial flooding systems. Specifically, HWI-CEM (Human-water interaction, crowd evacuation model) was developed to simulate social behavior during crowd evacuation. The framework consists of three main components: (1) Based on hydrological and hydrodynamic models, a heuristic algorithm is used to optimize the composition and location of flood control infrastructure; (2) HWI-CEM adopts a bottom-up modeling approach, simulates the crowd evacuation process in urban floods, focusing on heterogeneous individual features and behavior rules, and analyzes the impacts of rainfall, development modes, and evacuation strategies; and (3) An uncertainty analysis of HWI-CEM is implemented using multithreaded parallel computing. The framework was applied in Jincheng, the results reveal: First, the multi-objective optimization of adaptive flood control measures (FCMs) effectively reduces flood impacts under various return periods, while the global evacuation mode (GEM) and zonal evacuation mode (ZEM) strategies significantly influence both evacuation efficiency and balance. FCMs, as decentralized flood control measures, enhance evacuation efficiency by regulating runoff and improving the balance of the evacuation process, although extreme events may require additional drainage capacity enhancement measures. Second, HWI-CEM successfully couples urban flooding processes with complex social systems. It effectively captures individual heterogeneity and interaction mechanisms in urban flooding scenarios. HWI-CEM demonstrates robustness and stability, with minor variations having minimal impact on its overall performance. The integrated framework proposed in this study for assessing the human-water relationship shows strong versatility and interpretability at urban meso-scales.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"655 ","pages":"Article 132876"},"PeriodicalIF":5.9,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143508855","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}