Journal of Hydrology最新文献

{"title":"Low-Cost Autonomous 3D-Printed Mini Disk Infiltrometer","authors":"Jan-František Kubát ,&nbsp;Francesco Zanna ,&nbsp;Martin Mildner ,&nbsp;Michal Sněhota","doi":"10.1016/j.jhydrol.2025.134212","DOIUrl":"10.1016/j.jhydrol.2025.134212","url":null,"abstract":"<div><div>Hydraulic conductivity on the surface of the soil is crucial to address many hydrological and environmental issues. This study presents the development and validation of a low-cost Autonomous Mini Disk Infiltrometer (AMDI), fabricated using fused deposition modeling (FDM) 3D printing. AMDI integrates a transparent PET-G Mariotte chamber and a TDT-based TMS-4 sensor to allow automated measurement of cumulative infiltration under controlled pressure head levels. Calibration was performed using polynomial regression (cubic) to relate the readings of the TDT sensor to changes in water volume. Laboratory infiltration experiments on loamy Chernozem soil compared AMDI with a commercially available, manually operated minidisk infiltrometer (MDI) at pressure head levels of h0 = −6, −3 and −1 cm. The results of ANOVA did not show significant differences between AMDI and MDI in higher pressure heads (p greater than 0.05), with notable discrepancies at −1 cm (p less than 0.05) likely attributed to differences in the porous sintered stainless-steel disks, despite the hydraulic conductivity of the CTU disk being significantly higher than that of the soil. The influence of the porous disk was tested using MDI alone, which clearly demonstrated its effect on infiltration. This aspect should be further investigated to better define the impact of the disk on infiltration measurements. Moreover, despite the inherent porosity of FDM prints, air leakage was minimized through optimized printing parameters, allowing for reliable operation without post-processing or specialized equipment. The AMDI offers a functional, cost-effective (approximately € 218), and customizable alternative to traditional MDIs, with potential for broader adoption, including in citizen science applications. Further field testing is needed in diverse soil types and environmental conditions.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134212"},"PeriodicalIF":6.3,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145009300","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 monitoring ability for extreme disasters in North China using a novel hydrometeorology-combined drought–flood severity index","authors":"Tengfei Feng ,&nbsp;Yunzhong Shen ,&nbsp;Fengwei Wang ,&nbsp;Jianli Chen ,&nbsp;Bin Liu ,&nbsp;Weilong Rao","doi":"10.1016/j.jhydrol.2025.134206","DOIUrl":"10.1016/j.jhydrol.2025.134206","url":null,"abstract":"<div><div>The heterogeneous triggering conditions of droughts and floods make it difficult for existing monitoring indices to balance the detection of extreme drought and flood events. To overcome this limitation, a hydrometeorology-combined drought-flood severity index (HDSI) is developed by integrating GRACE-based terrestrial water storage (TWS) and precipitation, and the time lag effect between two elements is reasonably handled using a weighting potential water storage model. The performance of the HDSI is evaluated in a typical ecologically fragile region: North China. The results show that the HDSI exhibits favorable spatial and temporal consistency compared with four commonly used indices, implying the effectiveness of the HDSI. With real-documented extreme events as benchmarks, the HDSI demonstrates significant accuracy superiority over the TWS-based monitoring index in capturing flood peak periods and outperforms indices based solely on meteorological elements in identifying drought intensity, which contributes to more profound understanding of extreme disasters under the combined impacts of turbulent climate change and intensive anthropogenic interference. Moreover, detailed investigations on two representative drought and flood events confirm that the HDSI can not only accurately identify the intensifying drought severity induced by water storage deficits in the context of reduced precipitation and growing water use, but also provide timely feedback in the case of emergency flooding due to increased precipitation; thus, it is an important complement to extreme disaster monitoring and early warning systems and can aid in facilitating rational disaster preparedness and decision-making.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134206"},"PeriodicalIF":6.3,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020230","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":"A nonlinear autoregressive recurrent forward harmonic network for rainfall forecasting","authors":"Shelendra Pal ,&nbsp;S. Palaniyandi ,&nbsp;Amal Al-Abri ,&nbsp;Robinson Joel ,&nbsp;G. Bhuvaneswari ,&nbsp;G. Manikandan","doi":"10.1016/j.jhydrol.2025.134208","DOIUrl":"10.1016/j.jhydrol.2025.134208","url":null,"abstract":"<div><div>Rainfall plays a crucial role in the Earth’s hydrological cycle. Changes in rainfall patterns adversely affect the climatic conditions and crop productivity. Rain prediction finds application in various domains, such as flood forecasting, agriculture, water management, and so on. Nevertheless, accurate rainfall prediction is regarded as a challenging mission due to the significant variability and intricate characteristics of the atmospheric data. Therefore, the novel technique, namely Nonlinear Autoregressive Recurrent Forward Harmonic Network (NARFH-Net), is developed for forecasting rainfall. Initially, the time series data is gathered from the dataset. After that, the extraction of rainfall indicators is accomplished. Then, feature fusion is performed by the Deep Neural Network (DNN) with Hamming distance. Finally, the developed NARFH-Net is used for the prediction of rainfall. The NARFH-Net is introduced by the integration of Gated Recurrent Unit (GRU), Harmonic Analysis, and Nonlinear Auto-Regressive models with the eXogenous (NARX) model. Here, the GRU can effectively handle sequential data, which captures long-term dependencies and helps the model to maintain complex temporal patterns in time series data. The Harmonic Analysis helps to handle the periodic patterns in rainfall. The NARX can capture the nonlinear relationship between past observations and external influencing variables. This hybrid structure enables the model to effectively learn complex, nonlinear and seasonal characteristics of rainfall data. The In addition, the effectiveness of the presented NARFH-Net is analyzed by utilizing various metrics and the value attained for Mean Absolute Squared Error (MASE) is 0.093, Weighted Absolute Percentage Error (WAPE) is 0.197, Mean Square Error (MSE) is 0.154, Root Mean Square Error (RMSE) is 0.392, Mean Absolute Error (MAE) is 0.253, Mean Absolute Percentage Error (MAPE) is 0.160, Relative Absolute Error (RAE) is 0.250, and R-squared is 0.928.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134208"},"PeriodicalIF":6.3,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096106","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":"Study of the effects of urban elements on traffic access in flooding at the neighbourhood scale","authors":"Meimei Wu ,&nbsp;Yushan Xin ,&nbsp;Wei Ge ,&nbsp;Zening Wu ,&nbsp;Huiliang Wang ,&nbsp;Shanyu Mei ,&nbsp;Mengjie Li","doi":"10.1016/j.jhydrol.2025.134207","DOIUrl":"10.1016/j.jhydrol.2025.134207","url":null,"abstract":"<div><div>Traffic congestion caused by urban flooding poses a notable threat to public safety and property and the factors influencing traffic flow exhibit pronounced spatial heterogeneity. At the neighbourhood scale, the complexity of layout and diversity of infrastructure result in distinct challenges. Investigating the impact of urban elements on traffic flow at the neighbourhood scale is a key issue in urban flood management. We adopted a neighbourhood-level perspective, based on the composition of urban elements, to analyse the natural environmental, structural, and social element indicators associated with traffic conditions under the influence of urban flooding disasters. Leveraging the advantages of the hierarchical Bayesian network (HBN) model in quantifying uncertainty relationships, we analysed indicator sensitivity to determine the impact of urban elements on traffic conditions during peak and off-peak periods at different floodwater depths at the neighbourhood scale. The results were validated using Zhengzhou City, China, as an example, and they indicated that at the neighbourhood scale, the social elements of regional population density (PD) and regional per capita GDP (GDP pc) had the highest impact on traffic conditions during urban flooding at different travel times and flood depths, with values of 0.34 and 0.25, respectively; structural elements had a relatively lower impact on traffic conditions during urban flooding. Among them, the proportion of commercial land (CLP) and the proportion of road area (RAP) had the highest impact on traffic conditions during urban flooding disasters under different travel times and flood depths, with values of 0.043 and 0.057, respectively; all indicators had a higher impact on traffic conditions during urban flooding disasters during peak periods than that during off-peak periods.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134207"},"PeriodicalIF":6.3,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145009301","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":"Interplay of Climate Change, Policy, and Human Behavior in Lake Basins: Identifying Key Factors and Future Climate Hotspots (Case Study: Urmia Lake Basin, Iran)","authors":"Mohammad Reza Mohammadi ,&nbsp;Razieh Taraghi Delgarm ,&nbsp;Hamid Farahmand ,&nbsp;Zahir Nikraftar ,&nbsp;Sahar Badiezadeh ,&nbsp;David López-Carr ,&nbsp;Massoud Tajrishy","doi":"10.1016/j.jhydrol.2025.134197","DOIUrl":"10.1016/j.jhydrol.2025.134197","url":null,"abstract":"<div><div>Climate change, government policy, and human behavior pose unprecedented challenges to the sustainability of lakes worldwide, necessitating a nuanced understanding of their ecosystem impacts. This study focuses on Lake Urmia in Iran as a case study, unraveling the complex interplay between climate change, management strategies, and local farmer behaviors in shaping the lake’s fate. Through comparative analysis with Van Lake in Turkey, we identify anthropogenic drought as a key driver of Lake Urmia’s shrinkage, underscoring the need for proactive policy interventions. First, climate change in the region is measured using high-resolution climate data derived from five Earth System Models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) analyzing 20 dimensions (5 indicators x 4 seasons) for each grid cell to identify Climate Change Hotspots (CCHs) and assess their potential impact on the Urmia and Van Lake basins. Second, semi-structured interviews and thematic analysis reveal the economic priorities of farmers in the Mahabad Plain region, representing farmers in the basin, and highlighting a critical gap in water conservation attitudes. Our findings advocate for government intervention in promoting crops with low water needs and incentivizing sustainable water management practices. Additionally, we identify climate change hotspots in the Urmia Lake Basin, providing vital insights for policymakers to prioritize mitigation measures. We propose targeted information campaigns and workshops to foster environmental responsibility among farmers, particularly in vulnerable regions. Ultimately, this study advocates for a comprehensive approach to sustainable water management, offering valuable lessons for preserving fragile ecosystems like Lake Urmia in the face of climate change.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134197"},"PeriodicalIF":6.3,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060504","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":"A catchment management optimization approach to mitigate rainfall induced pesticide contamination in water supply systems","authors":"Vaida Suslovaite,&nbsp;Vanessa Speight,&nbsp;James D. Shucksmith","doi":"10.1016/j.jhydrol.2025.134123","DOIUrl":"10.1016/j.jhydrol.2025.134123","url":null,"abstract":"<div><div>Surface water resources are under increasing strain from non-point pollution such as pesticides. Simulation based spatial land use optimization can be used to prioritize mitigation interventions within catchments. However, currently available methods rely on simulations at relatively coarse temporal scales which may not be appropriate when considering implications for water supply/abstraction systems. This paper develops an event-based distributed simulation and genetic algorithm optimization methodology which is compatible with fully distributed models accounting for high resolution, sub daily acute rainfall driven impacts. This is enabled by the use of a novel methodology to efficiently sample rainfall events for optimization purposes. Within the case study catchment, the methodology is used to identify targeted interventions of up to 5% of the catchment area to reduce the duration that the target pesticide remains above the threshold target for UK/EU drinking water. The proposed intervention is then evaluated based on historical rainfall records and compared against alternate intervention strategies, reducing the duration above threshold by 7.7% and significantly outperforming alternate random and clustered intervention strategies. The outputs demonstrate the complexities of the interactions between water quality dynamics, objective function and target thresholds at this temporal scale. It is anticipated the proposed approach may be utilized by catchment managers to effectively target catchment interventions to reduce pesticide contamination risks to water resource systems.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134123"},"PeriodicalIF":6.3,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027523","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 water conservation capacity in the Yellow River water conservation area integrating ecological model and machine learning","authors":"Jianglei Zhang ,&nbsp;Shaohui Chen","doi":"10.1016/j.jhydrol.2025.134202","DOIUrl":"10.1016/j.jhydrol.2025.134202","url":null,"abstract":"<div><div>Accurately assessing the Water Conservation Capacity (WCC) of the Water Conservation Area (WCA) in the Yellow River Basin (YRB) is imperative for regional ecological security, yet it remains challenging because of the intricate interplay among climatic and anthropogenic drivers. This study proposes a novel integrated framework that couples the process-based InVEST model with a data-driven Random Forest (RF) algorithm to evaluate the spatiotemporal dynamics of WCC from 2000 to 2022 using annual water yield and Water Conservation Quantity (WCQ). Results reveal that annual water yield and WCQ range from 80.17 to 218.68 mm and 3.56 to 10.99 mm, and optimal Grade I WCC is predominantly concentrated in the central-southern Yellow River Source Area (YRSA), the Southern Mountain Tributary Area of the Wei River (SMTAWR), and the western Yiluo River Basin (YLRB). RF-based factor importance analysis indicates that climatic factors (precipitation, potential evapotranspiration) and anthropogenic factors (NDVI, population, GDP, flow velocity coefficient) are the primary drivers of WCC, while natural structural factors (soil depth, slope, saturated hydraulic conductivity, plant available water content) exert relatively minor effects. By quantitatively disentangling the relative contributions of climatic, natural structural, and anthropogenic factors to WCC, the proposed InVEST-RF framework advances watershed WCC assessment. Moreover, it provides a transferable methodological tool for ecohydrological evaluations in global watersheds, particularly under the context of changing climate and evolving land use trajectories.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134202"},"PeriodicalIF":6.3,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027562","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 integrated model of water–sediment-energy simulation and its application in the Xiaolangdi reservoir","authors":"Xianziyi Zhang ,&nbsp;Junqiang Xia ,&nbsp;Yifei Cheng ,&nbsp;Meirong Zhou ,&nbsp;Zenghui Wang ,&nbsp;Cuixia Chen","doi":"10.1016/j.jhydrol.2025.134131","DOIUrl":"10.1016/j.jhydrol.2025.134131","url":null,"abstract":"<div><div>The Xiaolangdi (XLD) Reservoir stands as a pivotal reservoir for the water–sediment regulation and power generation in the Yellow River Basin. The coexistent process of water–sediment-energy during the pre-flood period causes the competition among multi-objectives: power generation, water supply, deposition reduction in the reservoir area and the downstream channel. To balance the trade-off between reservoir sustainability and utility value, a model framework is proposed in this study, following the route of “scheme design-model simulation-scheme evaluation”. The framework integrates a reservoir operation module, a hydrodynamic-based water–sediment-energy simulation module, and a benefit evaluation method based on the Fuzzy Neural Network (FNN). Firstly, the water–sediment-energy simulation module was validated against the 2013 and 2014 water–sediment regulation events, showing good agreement with the field measurements. Subsequently, by altering two key scheduling parameters of CWL (connecting water level) and RWL (refilled water level) based on the 2014 water–sediment regulation event, different operation schemes were evaluated based on the comprehensive performance of VS (vented sediment amount from reservoir), TV (total volume of discharge greater than 2600 m³/s), PG (power generation amount), and SC (final storage capacity) with the trained FNN. The proposed optimal values of CWL and RWL were 217 m and 211 m, with the relative membership degrees of 0.750 and 0.754, respectively. This finding suggests that maintaining a continuous low pool level in the XLD Reservoir is optimal for securing higher comprehensive benefits in case of insufficient water inflow, with the effect of deposition reduction being a notable advantage.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134131"},"PeriodicalIF":6.3,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145046429","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":"Unraveling the mechanistic interplay of carbon cycle and nitrogen transport within deep reservoirs: A perspective of δ13CDIC analysis","authors":"Yufei Bao ,&nbsp;Yuchun Wang ,&nbsp;Qian Zhang ,&nbsp;Xiaobo Liu ,&nbsp;Peng Hu ,&nbsp;Meng Sun ,&nbsp;Xiaodong Qu ,&nbsp;Jie Wen ,&nbsp;Shanze Li ,&nbsp;Bing Lin ,&nbsp;Jialong Huang","doi":"10.1016/j.jhydrol.2025.134195","DOIUrl":"10.1016/j.jhydrol.2025.134195","url":null,"abstract":"<div><div>In the Lancang River Watershed (LRW), the establishment of substantial reservoirs has been implicated in the perturbation of biogeochemical carbon-nitrogen cycles, as well as their environmental repercussions, across both temporal and spatial dimensions. This work involved the procurement of water samples from various points within the Nuozhadu Reservoir (NZD). During the rainy season, pronounced alterations in stratification were observed: the surface mixed layer ranging from 0 to 5 m in depth; the thermocline layer extended from 5 to 40 m; and the profundal zone, spanning from 40 m to the riverbed, was designated as the stagnant temperature layer. The spatiotemporal heterogeneity of dissolved inorganic carbon (DIC) and its isotopic composition (δ¹³C_DIC) was pronounced, with δ¹³C_DIC values spanning from −9.04 ‰ to −3.00 ‰. Spatially, the concentrations of DIC exhibited an increment with increasing depth across various vertical profiles. This variation was attributed to the thermal stratification within reservoirs, which modulated the intensity of photosynthetic carbon fixation. The nitrogen content exhibited a parallel trend to DIC concentration, with lower values in the upper layers and elevated levels in the deeper strata. This work revealed that photosynthesis and carbonate sedimentation might be an important carbon sequestration process in the large reservoir. Future research endeavors should focus on elucidating the migratory and transformational dynamics of carbon and nitrogen elements, to enhance the management and environmental surveillance strategies for deep reservoirs.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134195"},"PeriodicalIF":6.3,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145009281","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":"Geoelectrical monitoring of natural attenuation process in an organic contaminated site including artificial insulating films","authors":"Siyuan Qiang ,&nbsp;Wenyi Xie ,&nbsp;Xiaoqing Shi ,&nbsp;Shaopo Deng ,&nbsp;Tao Long ,&nbsp;Xueyuan Kang ,&nbsp;Yalin Song ,&nbsp;Jichun Wu","doi":"10.1016/j.jhydrol.2025.134161","DOIUrl":"10.1016/j.jhydrol.2025.134161","url":null,"abstract":"<div><div>Hydrogeophysical methods such as electrical resistivity tomography (ERT) have been increasingly employed in the investigation of organic contaminated sites. However, their applicability during monitored natural attenuation (MNA) of organic pollutants (OPs) remains highly site dependent, owing to the variable and often contradictory electrical responses associated with OP migration and degradation. In addition, artificial structures introduced by common remediation efforts (e.g., insulating films) can significantly complicate the interpretation of electrical data, yet their potential influence on geoelectrical measurements has not been systematically evaluated. To assess the feasibility of applying geoelectrical methods in the context of MNA, we conducted a one-year time-lapse surface and cross-borehole ERT monitoring at an OP-contaminated site. After obtaining the geoelectrical data, an effective correction methodology was first developed to mitigate the signal distortions caused by subsurface insulating films. Then, based on long-term hydrochemical sampling at this study site, we confirmed that the subsurface electrical conductivity showed no significant correlation with the concentration of dissolved OPs in groundwater (as opposed to the free phase) due to their lack of ionic charge carriers. Meanwhile, through a variety of hydrochemical indicators related to biodegradation, we demonstrated the correlations between high-conductivity anomalies delineated by ERT and the biodegradation byproduct plumes of OPs, where metabolic compounds such as chloride and carbon dioxide lead to increases in groundwater electrical conductivity. These findings highlight the potential of geoelectrical methods to provide spatiotemporal insights into OP degradation, which is particularly essential for MNA-based remediation strategies.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134161"},"PeriodicalIF":6.3,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989233","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}