Journal of Hydrology最新文献

{"title":"Nitrogen dynamic transport processes shaped by watershed hydrological functional connectivity","authors":"Ming Lei ,&nbsp;Yu Long ,&nbsp;Taoxi Li ,&nbsp;Yichun Ma ,&nbsp;Guangjie Zhang ,&nbsp;Bo Peng ,&nbsp;Zhongwu Li ,&nbsp;Yaojun Liu","doi":"10.1016/j.jhydrol.2024.132218","DOIUrl":"10.1016/j.jhydrol.2024.132218","url":null,"abstract":"<div><div>Nitrogen (N) pollution is the major type of non-point pollution in watersheds. The nitrogen transport process is significantly controlled by the watershed hydrological connectivity under different rainfall conditions. Changes in hydrological connectivity were controlled by extreme rainfall events, resulting in a more uncertain response mechanism for dynamic nitrogen transport. In this study, four typical rainfall events were selected based on long-term positional monitoring of a small watershed using high-frequency sampling (long duration rainfall events E1, E2; short duration rainfall events E3, E4). Characterizing spatial and temporal changes in hydrological connectivity under different types of rainfall events. Revealing how hydrological connectivity shape the nitrogen dynamic processes. The results showed that the hydrological functional connectivity was better for long duration rainfall events than for short duration rainfall events as influenced by rainfall events (E1, E2: 4.58, 5.5; E3, E4: 5.25, 5.18). The difference in hydrological connectivity not only made the average and peak nitrogen concentration load under the long duration rainfall events higher than that under the short duration rainfall events. It also resulted in different nitrogen source composition, with soil nitrogen (SN) and manure &amp; sewage (M&amp;S) being the main sources under long duration rainfall events (SN: 28.3%, 25.5%; M&amp;S: 41%, 53%), whereas M&amp;S dominated under short duration rainfall events (37%, 67%). The antecedent precipitation index (API) also constrained the timing of onset of hydrological functional connectivity, in addition to rainfall events influencing watershed hydrological connectivity. The landscape characteristics of the watershed also affected the spatial and temporal characteristics of hydrological connectivity, which shaped the nitrogen source-sink transition relationship in the watershed. Based on the differences in the response of nitrogen transport characteristics to hydrological connectivity under different rainfall events. Considering hydrological connectivity dimensions and intervention can help to achieve precise management of nitrogen in the watershed.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132218"},"PeriodicalIF":5.9,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554655","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":"Untangling the coupling effect of water quality and quantity on lake algal blooms in Lake Hulun from a dual perspective of remote sensing and sediment cores","authors":"Hao Zhang ,&nbsp;Yu Li ,&nbsp;Bo Yao ,&nbsp;Yuqi Huang ,&nbsp;Shengrui Wang ,&nbsp;Shouqing Ni","doi":"10.1016/j.jhydrol.2024.132141","DOIUrl":"10.1016/j.jhydrol.2024.132141","url":null,"abstract":"<div><div>Algal blooms and sediment diatoms are crucial indicators of lake water ecology, influenced by water quantity and quality. However, the coupled effects of water quality and quantity changes on algal blooms are still unclear, especially for lakes in cold and arid regions. This study assessed the long-term variations in algal blooms in Hulun Lake using a novel approach combining remote sensing and sediment core samples for diatom analysis. Two mutation points from the structural change test were identified in approximately 2000 and 2010 for algal bloom area (MBE) and sediment diatom richness, indicating asynchronous algal blooms. A structural equation model (SEM) demonstrated that water level (WL) changes were the dominant influencing factor, co-driving the variations in algal blooms and sediment diatoms in conjunction with total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD). The results revealed nonlinear relationships between the lake WL, TN, Chla, and COD. The water level of 543 m emerged as a critical threshold affecting the relationship between water quality and quantity. Distinct differences in this relationship were observed when water levels were above or below this threshold. These variations became particularly pronounced during periods of high and low water levels. The results provide novel insights into the dynamics of algal blooms and can further support lake ecosystem conservation and management.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132141"},"PeriodicalIF":5.9,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663517","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-guided convolutional neural networks for spatiotemporal urban flood modelling","authors":"Ze Wang ,&nbsp;Heng Lyu ,&nbsp;Guangtao Fu ,&nbsp;Chi Zhang","doi":"10.1016/j.jhydrol.2024.132250","DOIUrl":"10.1016/j.jhydrol.2024.132250","url":null,"abstract":"<div><div>Urban flood modelling is key to understand flood risks and develop effective interventions in flood management. Deep learning (DL), known for its robust and automatic feature extraction capabilities, has been applied for urban flood predictions. However, the hybrid spatiotemporal structure of conventional DL-enabled urban flood models is limited in terms of accuracy and efficiency. To address this gap, this study develops a new DL model guided by time information. This model uses a classic CNN (Convolution Neural Network) architecture, Unet, as its backbone. Time information is integrated into inputs via an extra channel to specify the desired prediction time, facilitating the simulation of the spatiotemporal flood process. Additionally, a modified loss function is formulated to tackle the sample imbalance problem between flooded and non-flooded sites. The model performance is assessed in an urban area in Dalian, China with a total of 18 rainfall events of varying return periods. The model attains average precision and recall values of 0.90 and 0.81, respectively, across different time steps during various events. Furthermore, the model exhibits transferability in ungauged regions where a high influence of surrounding environments on local flood processes is identified by Grad-CAM (Gradient-weighted Class Activation Mapping) analysis. The results show that the new Unet model has great promise in efficiently providing accurate spatiotemporal flood simulations. The time-guided Unet model can serve as practical tools for rapid flood simulation in urban areas.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132250"},"PeriodicalIF":5.9,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554653","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 generalization of the Exner law for sediment nonlocal transport at bedform scale","authors":"ZhiPeng Li ,&nbsp;Zhenyang Peng ,&nbsp;Mehrdad Kiani-Oshtorjani ,&nbsp;Mengyang Liu ,&nbsp;Fuxin Zhang ,&nbsp;Yilin Chen ,&nbsp;Yantao Zhu","doi":"10.1016/j.jhydrol.2024.132236","DOIUrl":"10.1016/j.jhydrol.2024.132236","url":null,"abstract":"<div><div>Recent researches have highlighted the significance of nonlocal processes in understanding the morphodynamics and sediment transport across landscapes. Nonlocal processes in sediment transport refer to the influence of landscape properties beyond the immediate vicinity of a given point on the sediment flux. Existing nonlocal models, employing fractional operators, aim to capture global correlated nonlocality using a global convolution operator. Nevertheless, such models tend to disregard nonlocal phenomena occurring at regional scales, potentially resulting in substantial inaccuracies due to an inadequate representation of sediment transport processes at these scales. This study presents a novel and more comprehensive mathematical formulation of the nonlocal Exner law, leveraging the peridynamic differential operator (PDDO). The proposed regional nonlocal model incorporates nonlocal sediment transport processes by utilizing a pre-defined weight function and interaction domain within the framework of the PDDO. The novel regional nonlocal model effectively bridges the gap between local and global models by integrating both short-range and long-range interactions in sediment transport. Application reveals that the regional nonlocal model provides a significantly enhanced accuracy in depicting profiles at the bedform scale compared to the local and the global models.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132236"},"PeriodicalIF":5.9,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572120","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":"Random fractional kinematic wave equations of overland flow: The HPM solutions and applications","authors":"Ninghu Su ,&nbsp;Fengbao Zhang","doi":"10.1016/j.jhydrol.2024.132234","DOIUrl":"10.1016/j.jhydrol.2024.132234","url":null,"abstract":"<div><div>This paper presents new findings from analyses of a random fractional kinematic wave equation (rfKWE) for overland flow. The rfKWE is featured with orders of temporal and spatial fractional derivatives and with the roughness parameter, the effective rainfall intensity and infiltration rate as random variables. The new solutions are derived with the aid of a numerical method named the homotopy perturbation method (HPM) and approximate solutions are presented for different situations. The solutions are evaluated with data from overland flow flumes with simulated rainfall in the laboratory. The results suggest that on an infiltrating surface the temporal nonlocality of overland flow represented by the temporal order of fractional derivatives diminishes over time while the spatial nonlocality manifested by the spatial order of fractional derivatives continue if there is overland flow. It shows that the widely used unit discharge-height relationship is a special case of the solution of the rfKWE. Procedures are demonstrated for determining the fractional roughness coefficient, <span><math><mrow><msub><mi>n</mi><mi>f</mi></msub></mrow></math></span>, the order of spatial fractional derivatives, <span><math><mrow><mi>ρ</mi></mrow></math></span>, and the steady-state infiltration rate during the overland flow, <span><math><mrow><msub><mi>A</mi><mi>s</mi></msub></mrow></math></span>. The analyses of the data show that the mean spatial order of fractional derivatives is <span><math><mrow><mi>ρ</mi><mo>=</mo><mn>1.25</mn></mrow></math></span>, the mean flow pattern parameter <span><math><mrow><mi>m</mi><mo>=</mo><mn>1.50</mn></mrow></math></span>, and the mean fractional roughness coefficient is <span><math><mrow><msub><mi>n</mi><mi>f</mi></msub><mo>=</mo><mn>0.002</mn></mrow></math></span> which is smaller than the conventional roughness coefficient, <span><math><mrow><mi>n</mi><mo>=</mo><mn>0.108</mn></mrow></math></span>. With these average values of the parameters and their standard deviations, simulations were performed to demonstrate the use of the methods, which is also a comparison of the classic KWE and rfKWE models.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132234"},"PeriodicalIF":5.9,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594174","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":"Causes for overestimation of the moisture recycling in an alpine meadow ecosystem of the Shule River Basin, Tibetan Plateau, China","authors":"Hang Liu ,&nbsp;Liangju Zhao ,&nbsp;Ninglian Wang ,&nbsp;Zihan Zhang ,&nbsp;Cong Xie ,&nbsp;Xiying Dong ,&nbsp;Xiaohong Liu ,&nbsp;Lixin Wang","doi":"10.1016/j.jhydrol.2024.132226","DOIUrl":"10.1016/j.jhydrol.2024.132226","url":null,"abstract":"<div><div>Terrestrial moisture recycling is an essential hydrological component and a significant source of the atmosphere’s humidity budget in arid and semi-arid inland regions. Investigations on moisture recycling using the stable hydrogen and oxygen isotopes is currently a focal point in hydrologic research. However, the direct quantification of recycling ratio based on isotopic composition of evapotranspiration vapor is lacking. So, this causes challenges to compare studies, based in the same region and time period but with different methodologies. In this study, we measured the isotopic compositions of evapotranspiration vapor (δ¹⁸O<em>_ET</em>/δD<em>_ET</em>) from June to September 2018 in an alpine meadow ecosystem at the Shule River Basin by combining the Keeling plot model and in-situ chamber measurement. Using this data, the moisture recycled rate (<em>mrr</em>) was assessed based on the two-component (Model A) and three-component isotopic mixing models (Model B), respectively. Based on Model A and δ¹⁸O<em>_ET</em>, the analysis revealed that the mean recycled rate for the entire observation period was 35 %, while it was 26 % during the westerly period (the months dominated by the north branch of prevailing westerlies) and 44 % during the monsoon period (when subtropical moisture from the Indian monsoon penetrated the region). The recycled rate based on Model A and δD<em>_ET</em> was slightly larger with a mean value of 41 % during the entire observation period. The recycled rate based on Model B was also significantly higher in comparison with Model A, while the causes for this difference could be the assumption of substituting xylem water for transpiration vapor and the plant water source δD offset. The contribution of recycled moisture was notable lower for heavy rainfall comparing with light rainfall. Our findings provided a new perspective for the investigations of alpine meadow ecosystem hydrological processes.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132226"},"PeriodicalIF":5.9,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142561066","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":"Modeling the transport and mixing of suspended sediment in ecological flows with submerged vegetation: A random displacement model-based analysis","authors":"Jiao Zhang,&nbsp;Penghao Wang,&nbsp;Zhanbin Li,&nbsp;Peng Li,&nbsp;Guoce Xu,&nbsp;Kunxia Yu,&nbsp;Wen Wang,&nbsp;Mengjing Guo","doi":"10.1016/j.jhydrol.2024.132210","DOIUrl":"10.1016/j.jhydrol.2024.132210","url":null,"abstract":"<div><div>Aquatic vegetation in rivers influences the flow structure, impacting the sediment transport in the river and further changing the ecosystem and geomorphologic evolution of the river. In this paper, an improved random displacement model (RDM) is proposed to investigate the concentration of suspended sediment (CSS) in flows with flexible submerged vegetation. Considering the effect of sediment resuspension on sediment transport, a probability model of sediment resuspension is embedded into the RDM so that the simulation process is more consistent with the natural cases. For the streamwise development of flow with flexible submerged vegetation, the flow is divided into a flow adjustment region and a fully developed region in the longitudinal direction. The vertical distributions of the flow velocity and turbulence diffusion coefficient were analyzed in these two regions, and they were incorporated into the RDM to simulate the along-flow development of the CSS. The simulated concentrations were compared with the experimental data. The mean relative errors (MREs) were below 15%, the root mean square errors (RMSEs) were below 0.20, and the Nash–Sutcliffe efficiencies (NSEs) ranged from 0.71 to 0.99, indicating that the improved RDM is plausible and reliable. In addition, the along-flow distribution of the sediment transport rate (STR) was analyzed. The rate exhibited a decreasing trend during the flow adjustment region and tended to stabilize during the fully developed region. This study provides a new way of thinking for research on sediment transport in rivers with aquatic vegetation, which is of great significance for achieving the sustainable development of river ecosystems and the optimal design of river channels.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132210"},"PeriodicalIF":5.9,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594170","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":"Can the young water fraction reduce predictive uncertainty in water transit time estimations?","authors":"Arianna Borriero ,&nbsp;Tam V. Nguyen ,&nbsp;Stefanie R. Lutz ,&nbsp;Jan H. Fleckenstein ,&nbsp;Andreas Musolff ,&nbsp;Rohini Kumar","doi":"10.1016/j.jhydrol.2024.132238","DOIUrl":"10.1016/j.jhydrol.2024.132238","url":null,"abstract":"<div><div>Transit time distributions (TTDs) of streamflow are informative descriptors of catchment hydrological functioning and solute transport mechanisms. Conventional methods for estimating TTDs generally require model calibration against extensive tracer data time series, which are often limited to well-studied experimental catchments. We challenge this limitation and propose an alternative approach that uses the young water fraction (F_yw^obs), an increasingly used water age metric which represents the proportion of streamflow with a transit time younger than 2–3 months, and that can be robustly estimated with sparsely measured tracer data. To this end, we conducted a proof of concept study by modeling TTDs using StorAge Selection (SAS) functions with oxygen isotopes (<span><math><msup><mrow><mi>δ</mi></mrow><mrow><mn>18</mn></mrow></msup></math></span>O) measurements for 23 diverse catchments in Germany. In a Monte-Carlo approach, we computed the (averaged) marginal TTDs of a prior parameter distribution and derived a model-based F_yw (F_yw^sim). We compared F_yw^sim with F_yw^obs, obtained from <span><math><msup><mrow><mi>δ</mi></mrow><mrow><mn>18</mn></mrow></msup></math></span>O measurements, and constrained the prior SAS parameters distribution. Subsequently, we derived a posterior distribution of parameters and resulting model simulations. Our findings showed that using F_yw^obs to constrain the model effectively reduced parameter equifinality and simulation uncertainty. However, the value of F_yw^obs on reducing model uncertainty varied across sites, with larger values (F_yw^obs<span><math><mo>≥</mo></math></span>0.10) leading to simulations with a narrower uncertainty band and higher model efficiency, whilst smaller values (F_yw^obs<span><math><mo>≤</mo></math></span>0.05) had limited influence on reducing model output uncertainty. We discussed the potential and limitations of combining SAS functions with F_yw^obs, and considered broader implications of this approach for enhancing our understanding of catchment functioning and water quality status.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132238"},"PeriodicalIF":5.9,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594106","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":"Data-driven forecasting framework for daily reservoir inflow time series considering the flood peaks based on multi-head attention mechanism","authors":"Fugang Li ,&nbsp;Guangwen Ma ,&nbsp;Chengqian Ju ,&nbsp;Shijun Chen ,&nbsp;Weibin Huang","doi":"10.1016/j.jhydrol.2024.132197","DOIUrl":"10.1016/j.jhydrol.2024.132197","url":null,"abstract":"<div><div>Accurate and reliable daily reservoir inflow forecast plays an essential role in several applications involving the management and planning of water resources, such as hydroelectric generation, flood control, water supply, and basin ecological dispatching. Runoff usually exhibits strong non-linearity, high uncertainty, and spatial and temporal variability. Existing techniques fail to capture complete dynamics change processes effectively. A data-driven forecasting framework for daily reservoir inflow time series considering the flood peaks based on a multi-head attention mechanism was developed, referred to as the GWOCS-VMD-CNN-Transformer (GCVCT). First, the model utilize Grey Wolf Optimizer coupled with Cuckoo Search (GWO-CS) algorithms to optimize parameters in variational mode decomposition model (VMD). This approach helps obtain highly correlated intrinsic mode function (IMF) components, enhancing the frequency resolution of the input dataset. The proposed method overcomes the bottleneck of other available methods by decomposing the time series to capture the main long-term and short-term properties of hydrological processes. Second, the convolution neural network and Transformer (CNN-Transformer) are based on a multi-head attention mechanism as the objective predictive method. Finally, six evaluation indicators verify the performance of the proposed approach. The approach’s reliability was evaluated using the historical daily reservoir inflow data from the Xiluodu (XLD) and Wudongde (WDD) reservoirs in the Jinsha River Basin, China. Several single and hybrid models were developed for comparative analysis. The results indicate that the proposed ensemble approach fits better than other developed model methods. The GCVCT model showed excellent performance in forecasting the inflows of XLD and WDD reservoirs, with NSE values of 0.985 and 0.984, respectively. Furthermore, the GCVCT framework forecast capacity for peak inflow was further verified through discussion and analysis of the 48 peak flows during the validation period, consistently outperforming other models in predicting peak flow for both study reservoirs. This framework provides an effective method for the scientific optimal scheduling of hydropower reservoirs, enabling more sustainable and efficient management practices. It also demonstrates the potential of powerful deep-learning models in intelligent hydrological forecasting.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132197"},"PeriodicalIF":5.9,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554606","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":"Enhanced 2D-models as alternative to dual-drainage systems for urban flood simulation","authors":"Michael Oberauer,&nbsp;Boris Lehmann","doi":"10.1016/j.jhydrol.2024.132198","DOIUrl":"10.1016/j.jhydrol.2024.132198","url":null,"abstract":"<div><div>As research in the field of analysing urban flood rainfall events progresses, it is evident that dual-drainage models remain the standard for producing the most realistic results of flood extension and water depth. However, the development of these sophisticated models is contingent upon the availability of comprehensive data sets that can be used to simulate runoff behaviour on the surface and account for hydraulic processes within the sewer network. The aim of this study is to demonstrate that comparable outcomes can be achieved through the modification of 2D surface models, which require less data and are more straightforward to set up. In order to test the efficacy of different methodologies for the enhancement of 2D models, two distinct approaches were implemented in two study areas with disparate rainfall loads in a city in south-west Germany. The results were then compared with those of a 1D/2D model. The findings of this study demonstrate that the methodologies tested are effective in improving the accuracy of 2D models, and that they are capable of producing results that closely align with those of dual-drainage models.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132198"},"PeriodicalIF":5.9,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554656","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}