Hasil untuk "River protective works. Regulation. Flood control"

Yanjie Sun, Xiaolong Song, Haijue Xu et al.

The Yellow River Estuary (YRE) in China has transitioned to a complex multi-channel regime since 2013, making understanding terminal channel morphodynamics crucial for effective water and sediment management. The current study investigates the controls on channel evolution in both non-estuarine and estuarine reaches of YRE, differentiated by bifurcation locations, using a multi-method approach. For the non-estuarine reach, wavelet analysis was applied to satellite-derived river centerlines (2003–2022) to quantify channel migration and its relation with fluvial forcing. In the estuarine reach, the interplay between fluvial and marine processes and their influence on channel migration were assessed. The analysis was complemented by scaled physical modeling experiments. The results indicate that in the non-estuarine reach, the erodibility of the channel, primarily governed by the median grain size of the bed material, exerts a dominant control on channel migration, with higher discharge consistently enhancing mobility by providing the necessary erosive energy. The concentration of incoming suspended sediment plays a secondary role, as much of it can be transported through the reach without causing significant local morphological change. The estuarine reach exhibits three distinct morphological states: limited mouth oscillation, minor bifurcation, and major bifurcation/avulsion. River discharge is the primary driver of these changes, while marine forces exert a stabilizing influence. Crucially, both physical modeling and field data indicate that local bed material characteristics—shaped by selective sediment transport and deposition—significantly influence estuarine morphodynamics, more so than upstream sediment supply parameters alone. Effective management of the YRE requires an integrated approach considering the spatial variability of bed material and the temporal dynamics of hydraulic conditions. The current study emphasizes the importance of distinguishing between bed material properties and suspended load characteristics for predicting morphodynamic responses in sediment-rich, highly managed river systems.

Muhammad Ishfaq, Farzana Noor, A. A. Bhat

ABSTRACT This article develops a two‐component mixture model combining the weighted Inverse Rayleigh (WIR) distribution and Gumbel Type‐II distribution for the estimation and prediction of flood events. The study utilizes 29 years (1990–2018) of flood data from the Federal Flood Commission (FFC) of Pakistan for the Jhelum River, using two gauging stations (Mangla and Rasul) across two catchments (U/S and D/S). Two distinct approaches, Annual Maximum series (AMS) and Peak over threshold (POT), are used for the estimation of parameters of the mixture models in a Bayesian context. Bayesian analysis is performed using the Square Error Loss Function (SELF) and Quadratic Loss Function (QLF) with gamma and beta priors. Bayes estimators and their posterior risks for both the Weighted Inverse Rayleigh and Gumbel Type‐II distributions are derived. For the Gumbel type‐II distribution, both the shape and scale parameters are treated as random. A comprehensive simulation study is conducted to examine the behavior of derived Bayes estimators and their posterior risks. The study also compares various loss functions and aims to explore a well‐fitted distribution. Additionally, it aims to determine return periods for accurate flood event predictions.

Ömer Faruk Karaca, Kadri Yürekli

In studies on water resources planning and management, regular and complete hydrological data such as streamflow and sediment data are needed. Since the existing data generally do not fully reflect the entire process, the process needs to be modeled in order to make more reliable decisions. The aim of this study is to investigate the possibilities of estimating the sediment amount with the ANN technique, which can be used in many areas today, with the streamflow and sediment measured from 20 sediment gauging stations (SGS) established by State Hydraulic Works (SHW) in the Euphrates-Tigris Basin and to try to determine the most appropriate network structure. The ANN structures to be used were determined as the most commonly used Radial Basis Artificial Neural Network (RBANN), Feed Forward Back Propagation Artificial Neural Network (FFBP) and Multilayer Artificial Neural Network (MLP). The obtained results were compared with the Multiple Linear Regression (MLR) method. The highest R2 values obtained were determined as 0.9683 and 0.9969 in the RBANN model, 0.9546 and 0.9820 in the MLP model, 0.9735 and 0.9732 in the FFBG model with the CG and LM algorithms, respectively. When only the mean values of the test values according to the ANN models were examined, the highest value was again obtained as 0.8507 in the RBANN and LM algorithms. In terms of sediment estimation, the highest R2 value in the ANN analysis was found in the RBANN model LM algorithm as 0.9804 in the train phase, 0.9969 in the testing phase and 0.9970 in the cross-validation phase.

Filipe Chaves Gonçalves, Joaquin Ignacio Garcia Bonnecarrère

ABSTRACT In light of the increasing adoption of sustainable urban drainage measures for flood control, driven by advances in the urban drainage field and, particularly, in downtown São Paulo, by the significant challenge associated with implementing large detention reservoirs due to the scarcity of open spaces within the watershed, this study investigates the hydrologic and hydraulic parameters that influence the rainfall–runoff simulation in urban areas using the PCSWMM model. Real‐time telemetry data, including measurements from meteorological radar, rainfall gauges, and fluviometric stations, were employed for model calibration and validation. Historical images of São Paulo from the 1930s were used to assess the potential impact of promoting permeable surfaces within the basin on current design hydrographs and flood‐prone area extents. Two future scenarios incorporating sustainable urban drainage strategies for flood mitigation were analyzed to evaluate their effectiveness, complemented by a sensitivity analysis to identify the parameters with the greatest influence on the simulated hydrographs. Results indicate that, even though sustainable measures significantly reduce flood‐prone area extents, their performance is highly dependent on rainfall duration and return period. Consequently, an integrated approach combining conventional and sustainable strategies is recommended for managing design storms with longer durations and higher return periods.

Zenghui Wang, Junqiang Xia, Chengzheng Yu et al.

Retrogressive erosion, a critical process impacting river engineering structures, channel geomorphology, and reservoir sediment management, manifests primarily in two distinct forms: rotating and stepped bed deformation. The former type is dominated by sediment entrainment, whereas the latter is dominated by mass failure. Simulating these processes accurately, particularly predicting which form will dominate, poses significant challenges for existing numerical models. This study addresses this gap by developing and validating a numerical model capable of simulating both rotating and stepped retrogressive erosion with automatic adjustment between the two types. The model integrates governing equations for unsteady nonuniform flow and nonequilibrium sediment transport with specialized modules for each erosion type. The rotating erosion module incorporates sediment entrainment theories suitable for high flow velocities and steep slopes, accounting for shear dilatancy effects. The stepped erosion module employs force equilibrium analysis to predict the critical horizontal erosion distance at the step toe to induce mass failure. A key feature is the implementation of a criterion based on the ratio of shear stresses at the top and bottom of the overfall relative to the critical shear stress, allowing the model to adapt the simulation approach on the basis of evolving hydrodynamic conditions. The hydrodynamic and sediment transport equations are solved at each time step, and the criterion is applied to determine whether the rotating or stepped erosion model is used to further solve bed deformation. Model calibration and verification were performed via laboratory flume data covering various inflow discharges, initial step heights, and bed material properties. For rotating-type erosion simulations, the model demonstrated high accuracy, with Nash–Sutcliffe efficiencies (NSEs) for water surface and bed elevation calculations generally exceeding 0.9. The calculated cumulative erosion amounts also agreed well with the measurements, with relative errors mostly less than 10 % in the later stages. The maximum Froude number, which was located at the end of the foreset reach, increased from 1.72 to 3.40 during the entire test. The maximum sediment concentration was almost constant. For stepped erosion, the model successfully replicated the characteristic headcut migration, although the results were sensitive to the erodibility coefficient. The errors of predicted overall migration rate were within 12.5 % of the measured values. The developed model provides a robust tool for predicting retrogressive erosion dynamics and is uniquely capable of handling both rotating and stepped forms.

Changjiang Ma, Yang-Guang Gu, Richard W. Jordan et al.

Freshwater lakes in China face increasing environmental pressures due to rapid urbanization and industrialization, with metal pollution emerging as a significant concern. Despite this, the ecological risk assessment of metal mixtures in lake sediment remains limited. The current study addresses this gap by utilizing the diffusive gradients in thin films (DGT) technique to investigate the distribution and ecological risk of metals and arsenic in surface sediment of Hongze Lake, China. Substantial variations in metal concentrations were found across sampling sites, with average values of manganese (Mn) (1,730.56 μg/L) and iron (Fe) (930.58 μg/L) being notably high. The ecological risk quotient (RQ) values for Mn and Fe exceeded 1 at all sites, indicating substantial ecological risks, while copper (Cu) and arsenic (As) had RQ values near or above 1 at most sites. A joint probabilistic risk assessment using the species sensitivity distribution (SSD) method revealed a 30.31% probability of concurrent toxic effects on aquatic organisms. These results highlight the pressing need for proactive measures to mitigate metal contamination risks in Hongze Lake. The current study provides critical insight into the ecological risks associated with metal pollution and underscores the importance of effective environmental management to preserve the lake's ecosystem.

Marina Bier, Ramian Fathi, Christiane Stephan et al.

Abstract In the response of the flood disaster in Germany 2021 a vast number of spontaneous volunteers (SVs) participated. They organized coordinating services, developed emergent forms of SVs and thus hold the potential to improve existing flood managing capacities. This raises the need for in‐depth knowledge about SVs and organization, the use of information and communication technologies (ICT), social and individual aspects. This article analyzed results of an online survey (n = 2636) with the aim to discuss challenges and potentials to develop SVs as social innovations in flood risk management. As a result, SVs are strong value‐based motivated, can be psychologically stressed and travel long distances, especially when they got aware of helping possibilities via social media. Disaster relief organizations rarely cooperate with or integrate SVs, but when they collaborate, SVs' satisfaction with authorities increases significantly. Based on the results, this article derives preplanning of useful concepts consider safety aspects, ICT utilization, foster mutual respect between SVs and authorities and supporting sense of community as key results for development of social innovations. Especially in light of pandemics, social crisis like refugee movements, and climate change‐related disasters, the requirement rises for engaging SVs.

Koji Ikeuchi, Daiki Kakinuma, Yosuke Nakamura et al.

ABSTRACT Owing to the increased frequency of short‐duration extreme rainfall events caused by climate change, peak flood flows are expected to increase substantially in small and medium‐sized rivers (SMRs) with a short time of concentration for a catchment (Tc). Accurate flood forecasts and corresponding evacuation are effective in reducing the number of casualties caused by flash floods in SMRs. Currently, flood forecasting using observed rainfall in SMRs has a short lead time, which often delays the issuance of evacuation orders by local governments. Moreover, the large number of SMRs necessitates a system that can be widely used by local governments for disaster response tasks, such as issuing evacuation orders. Therefore, we developed a system that can accurately predict when river water levels will reach the Flood Risk Level (FRL). This forecasting approach uses the rainfall–runoff–inundation (RRI) model and the H–Q equation. The parameters in the RRI model were optimized using the Shuffled Complex Evolution algorithm developed at the University of Arizona (SCE‐UA) to reduce the required time and effort. The system uses real‐time water level observation data to sequentially modify the basin state quantities in the RRI model using the particle filter method to improve the water level forecast accuracy. The system was implemented in 200 rivers in Japan with diverse rainfall and geological characteristics and was tested during the flood season. Accuracy verification was conducted when the forecasted water levels were operated within a range of ± 50 cm. The results showed that 75% of the flood events could be forecasted more than 2 h before reaching the FRLs. Furthermore, 89% of the flood events could be predicted with a lead time (LT; time that water levels reach the FRL—time of first forecast) of 2 h or more or a lead time equal to the Tc or more. These findings show that this system has the potential to enhance and strengthen flood warning and evacuation systems.

Jean Hounkpè, Bruno Merz, Félicien D. Badou et al.

Abstract Floods are among the most devastating natural disasters and are expected to become more severe with changing climate and population growth. Flood forecasting is one of the key components of flood risk reduction. The potential for seasonal flood forecasting through climate indexes has not been studied for West Africa so far. This work investigates how climate indicators can be used to predict in advance, one to several months ahead of the flood season, above or below normal flood discharge in West Africa. Six global and regional climate indexes were screened for their potential to predict flood discharge of 56 river gauging stations across West Africa. Forecasting models are developed, based on simple and multiple linear regressions between climate indexes and annual maximum discharge, and evaluated using the relative operating characteristics and the relative operating levels scores. The western dipole mode index is the most skillful individual climate index for above normal flood prediction. Combining climate indexes via multiple linear regressions outperforms individual climate indexes for both above and below normal flood prediction. The models show forecasting skills for up to 4 months prior to the flood season. Hence, this study opens promising possibilities for seasonal flood forecasting in West Africa. This may help alert disaster reduction agencies of entering a period of an increased chance of flooding and may trigger adequate mitigation measures.

Hyeon‐Tae Moon, Sun‐Kwon Yoon, Jong‐Suk Kim et al.

Abstract Estimating potential changes in future flood patterns based on anticipated changes in hydrological characteristics within the basin is crucial for mitigating flood damage and managing flood risk. In this study, nonparametric probability models are used to estimate future rainfall patterns in Seoul under the GCM‐based climate change scenarios (CCS), and the estimated future daily rainfall data was temporally downscaled to hourly units using the KNNR‐GA technique. Changes in flood hazard and runoff characteristics of the target area based on the estimated future rainfall data are quantitatively assessed. The results highlight that under CCS, flood runoff may increase further into the future, resulting in more significant changes in flood patterns and accelerating the increase in flood hazard. The delta change factor of flood risk indicators increased relatively significantly in more severe CCS. This study also proposed a process to estimate future flood runoff and mitigation effects according to CCS by reflecting various flood mitigation measures in the urban drainage system model. These findings can offer valuable insights for setting the direction of current and future mitigation measures.

علی رضا واعظی, اولدوز بخشی راد

مقدمه زمان تمرکز حوزه‌های آبخیز، یکی از مهم‌ترین و متداول‌ترین ویژگی‌‌های مؤثر در مطالعات هیدرولوژیکی به‌‌ویژه تعیین دبی جریان برای طرح‌های آبخیزداری است. اغلب حوزه‌های آبخیز دنیا و همچنین ایران، فاقد ایستگاه‌های اندازه‌گیری جریان هستند و مجریان طرح‌ها ناگزیر به استفاده از مدل‌های تجربی برآورد زمان تمرکز هستند. بررسی مطالعات پیشین نشان می‌‌دهد که مدل‌‌های تجربی برآورد زمان تمرکز به‌دلیل تغییر شرایط محیطی در خارج از محل ارائه مدل نتایج نامطلوبی دارند. از سوی دیگر اطلاعات کافی در مورد کارایی مدل‌‌های تجربی برآورد زمان تمرکز در بسیاری از حوزه‌‌های آبخیز در ایران و به‌ویژه در مناطق نیمه‌‌خشک وجود ندارد. هدف از این مطالعه ارزیابی دقت برخی مدل‌های تجربی برآورد زمان تمرکز در زیرحوضه‌‌های منطقه نیمه‌‌خشک شمال غرب کشور و شناسایی عوامل تعیین‌کننده آن است.   مواد و روش‌ها این پژوهش در هشت زیرحوضه شامل آلانق، اردکلو، شکرعلی‌چای، شیرامین، کرجان، کلاله و لیوار از حوضه‌های دریاچه ارومیه و رود ارس در شمال غرب ایران انجام گرفت. داده‌های هواشناسی و هیدرومتری از اداره کل منابع طبیعی آذربایجان شرقی و ایستگاه‌های متعلق به وزارت نیرو اخذ شد. ویژگی‌های حوضه‌ مانند مساحت، طول، شیب، ارتفاع و شکل از راه مطالعات میدانی و رسم نقشه‌‌ها در بستر GIS تعیین شد و زمان تمرکز با استفاده از هیدروگراف جریان‌‌ها در دوره آماری 30 سال (از سال 1367 تا 1397) محاسبه شد و از طریق شش مدل تجربی شامل کرپیچ (1940)، کربای (1959)، چاو (1962)، سازمان هوانوردی امریکا (1972)، برانسبی-ویلیامز (1980) و ونتورا (2007) برآورد شد. بررسی رابطه میان زمان تمرکز و ویژگی‌‌های حوزه آبخیز به روش ماتریس همبستگی با استفاده از معیار پیرسون انجام گرفت. برای ارزیابی دقت مدل‌ها از ضریب کارایی نش-ساتکلیف، میانگین خطا و ریشه میانگین مربعات خطا استفاده شد.     نتایج و بحث بر اساس نتایج مشاهده‌ای حاصل از روش هیدروگراف، زیرحوضه شکرعلی‌چای کوتاه‌‌ترین (66 دقیقه) و کلاله طولانی‌‌ترین زمان تمرکز (132 دقیقه) را دارد. مدل برانسبی-ویلیامز کمترین خطا (6.8 درصد) و بیشترین ضریب کارایی (73) را داشت؛ درحالی‌که بیشترین خطای برآورد (2/36 درصد) و کمترین ضریب کارایی (14.4-) در مدل سازمان هوانوردی آمریکا بود. شیب، مهم‌ترین عامل مؤثر بر زمان تمرکز برآوردی در مدل کرپیج (0.83-=r)، چاو (0.82-=r) و برانسبی-ویلیامز (0.73-=r) بود. مدل سازمان هوانوردی امریکا (1972) و مدل ونتورا (2007) در زیرحوضه‌های با شیب زیاد، برآورد ضعیف‌‌تری دارند و برای مناطق کوهستانی مناسب نیستند.   نتیجه‌گیری  نتایج نشان داد که از میان ویژگی‌های فیزیکی حوضه، مساحت، شیب و طول زیرحوضه در تغییرات زمان تمرکز نقش مهم‌تری دارند. این مطالعه نشان داد درصد شیب حوضه مهم‌ترین عامل کاهش زمان تمرکز و دبی اوج و افزایش سرعت سیلابی شدن در زیرحوضه‌های مورد بررسی است. بنابراین پیشنهاد می‌شود، برای زیرحوضه‌هایی که درصد شیب بالاتری دارند، از طرح‌های حفاظت خاک به‌منظور افزایش زمان تمرکز استفاده شود. ارزیابی مدل‌‌های برآورد زمان تمرکز در هشت زیرحوضه آبخیز نشان داد که مدل برانسبی-ویلیامز (1980) با میانگین خطا 6.80 درصد و ضریب کارایی نش- ساتکلیف 73 درصد مطلوب‌ترین برآورد را ارائه می‌کند، لذا، استفاده از این مدل در حوضه‌های مشابه که فاقد ایستگاه‌های اندازه‌گیری هستند، پیشنهاد می‌شود.

Kumudu Madhawa Kurugama, So Kazama, Yusuke Hiraga et al.

Abstract Identifying flood‐prone areas is essential for preventing floods, reducing risks, and making informed decisions. A spatial database with 595 flood inventory and 13 flood predictors were used to implement five boosting algorithms: gradient boosting machine (GBM), extreme gradient boosting, categorical boosting, logit boost, and light gradient boosting machine (LGBM) to map flood susceptibility in Rathnapura while evaluating trained model's generalizing ability and assessing the feature importance in flood susceptibility mapping (FSM). The model performance was evaluated using the F1‐score, kappa index, and area under curve (AUC) method. The findings revealed that all the models were effective in identifying the overall flood susceptibility trends while LightGBM model had superior results (F1‐score = 0.907, Kappa value = 0.813 and AUC = 0.970), securing the top scores across all performance metrics compared to the other models (for testing dataset). Based on kappa evaluation, most of the models had finer performance (AUC min = 0.737) while LightGBM had moderate performance for predictions beyond the training region. According to the results, regions with lower altitudes and topographic roughness values, moderate rainfall, and proximity to rivers are more susceptible to flooding. This framework can be adapted for rapid FSM in data‐deficient regions.

سید احمد حسینی

بندهای رسوب‌گیر، با اهداف چند منظوره مشتمل بر کنترل سیلاب، فرسایش، رسوب و تغذیه آبخوان احداث می‌شوند. این بندها، با هدف کنترل رسوب از انتقال بخشی از آن به مخازن سدها در پایین‌دست جلوگیری و با ایجاد تاخیر در رواناب سطحی، بخشی از سیل را کنترل و آبخوان منطقه را نیز تغذیه می‌کنند. طراحی نامناسب و یا عدم اجرای بهینه این سازه‌ها، سبب کاهش عمر مفید و گاهی تخریب زودهنگام این سازه‌ها می‌شود. ارزیابی کارکرد و عملکرد فنی چنین طرح‌هایی با هدف اصلاح و مدیریت سامانه از اهمیت ویژه‌ای برخوردار است. به همین دلیل، در این مقاله، تعدادی از بندهای رسوب‌گیر اجرا شده در شهرستان آبدانان استان ایلام مورد بررسی و ارزیابی قرار گرفتند. این پژوهش، در قالب مقایسه و شبیه‌سازی هیدرولیکی وضع موجود با شرایط قبل از اجرای طرح، در بازه‌ای از آبراهه به طول حدود هفت کیلومتر انجام شد. گفتنی است در این بازه، تعداد شش بند سنگ و ملاتی طی یک دهه گذشته احداث شده است. نتایج شبیه‌سازی هیدرولیکی سیلاب آبراهه و سازه‌های احداث شده نشان داد، با استناد به دبی با دوره بازگشت 100 ساله، به‌طور متوسط عرض سرریز بندهای احداثی حدود 25 درصد بزرگ‌تر از مقدار مورد نیاز و طول حوضچه‌های آرامش حدود 40 درصد کمتر از مقدار مورد نیاز اجرا شده است. به­‌طورکلی، در تمامی بندهای احداثی طول حوضچه آرامش به‌درستی انتخاب نشده است، به‌طوری‌که کم بودن طول حوضچه آرامش باعث شده است، پرش هیدرولیکی از حوضچه خارج شود و یا در قسمت پایانی آن تشکیل شود. به‌واسطه بالا بودن سرعت جریان در محدوده پرش هیدرولیکی، فرسایش و تخریب در ناحیه انتهایی حوضچه آرامش تشدید شده، که به مرور تخریب‌ها به سمت بالادست و سازه اصلی بند رسوب‌گیر کشیده شده است. با استناد به شبیه‌سازی هیدرولیکی سیلاب و مقایسه نسبی نتایج در شرایط قبل و پس از احداث بندها، مشخص شد که بندهای احداثی به‌طور متوسط بر روی پارامترهای سرعت جریان، قدرت جریان و تنش برشی جریان که همگی از عوامل تشدید فرسایش در آبراهه هستند، تاثیر مثبت داشته‌اند. به‌طوری‌که برای دبی با دوره بازگشت 25 ساله پارامترهای سرعت، قدرت و تنش ‌برشی جریان در طول بازه مورد پژوهش، به‌ترتیب حدود 23، 29 و 27 درصد کاهش پیدا کرده است. لذا، میزان متوسط کاهش این پارامترها به­‌صورت موضعی و در محل احداث بندهای شش‌گانه، به­‌ترتیب برابر با 73، 85 و 82 درصد برآورد شد. به‌طورکلی، با توجه به بازدیدهای میدانی و بررسی‌‌های به‌عمل آمده، اجرای طرح در کنترل سیل و رسوب موثر بوده است و در صورت حفاظت و ترمیم سالانه، تاثیرات آن مضاعف خواهد شد.

Tobias Sieg, Sarah Kienzler, Viktor Rözer et al.

Abstract Flood risk assessments require different disciplines to understand and model the underlying components hazard, exposure, and vulnerability. Many methods and data sets have been refined considerably to cover more details of spatial, temporal, or process information. We compile case studies indicating that refined methods and data have a considerable effect on the overall assessment of flood risk. But are these improvements worth the effort? The adequate level of detail is typically unknown and prioritization of improvements in a specific component is hampered by the lack of an overarching view on flood risk. Consequently, creating the dilemma of potentially being too greedy or too wasteful with the resources available for a risk assessment. A “sweet spot” between those two would use methods and data sets that cover all relevant known processes without using resources inefficiently. We provide three key questions as a qualitative guidance toward this “sweet spot.” For quantitative decision support, more overarching case studies in various contexts are needed to reveal the sensitivity of the overall flood risk to individual components. This could also support the anticipation of unforeseen events like the flood event in Germany and Belgium in 2021 and increase the reliability of flood risk assessments.

Sarah L. Collins, Anne Verhoef, Majdi Mansour et al.

Abstract In the United Kingdom, woodland planting and soil and crop management are being promoted as approaches to tackling flooding. Although evidence is limited, it is thought tree planting and regenerative agriculture practices such as crop–herbal ley pasture rotations increase infiltration, soil water storage and evapotranspiration, potentially reducing flooding. A process‐based soil–water–vegetation model was coupled with a semi‐distributed groundwater model to explore the impact of these interventions on peak and low flows in a large, groundwater‐dominated catchment. Land use change and management were found to have limited potential to reduce flooding in this setting. Herbal ley–crop rotations produced a <1% reduction in flow for return periods >2 years, and levels of woodland planting judged to be the realistic maximum produced reductions of 0.2%–2.6%, depending on tree species. Broadscale spruce planting was the only scenario to produce significant reductions in peak flow (16.0%–24.7% at return periods 1–15 years); however, the level of spruce planting required to achieve these reductions was estimated to reduce Q95 flow by ~39%, which would likely have negative implications for water security and ecological river flows. The impact of land‐based natural flood management interventions for flood prevention in large, permeable catchments should not be overstated.

کیومرث روشنگر, صادق عبدل زاد

مقدمهپیش‌بینی تغییرات بیشینه دما، بسیار مهم است و به‌دلیل تاثیرات زیادی که بر منابع آبی، کشاورزی و محیطی دارد، اهمیت فزاینده‌ای پیدا کرده است. با پیش‌بینی دما، می‌توان از تغییرات آینده آگاه شد و تمهیدات لازم برای تعدیل اثرات منفی آن بر منابع آبی، کشاورزی و محیطی را انجام داد. بنابراین، مدلسازی و پیش‌بینی بیشینه دما می‌تواند، به‌عنوان یک ابزار مهم در برنامه‌ریزی و مدیریت منابع طبیعی، اقتصادی و صنعتی مورد استفاده قرار گیرد.مواد و روش‌‌هادر این پژوهش، بیشینه دما با استفاده از روش نوین حافظه طولانی-کوتاه‌-مدت (LSTM) بر پایه روش‌‌های پیش‌پردازنده تبدیل موجک گسسته (DWT) و تجزیه مد تجربی کامل (CEEMD) در دو اقلیم متفاوت (مرطوب و نیمه‌خشک) مدلسازی شد. برای این منظور، از داده‌‌‌‌‌های دمای بیشینه، دمای کمینه، بارش و تابش خورشیدی به‌صورت روزانه مربوط به دوره 2001 تا 2020 ایستگاه‌های سینوپیک واقع در سیاه‌بیشه شهرستان آمل در استان مازندران و فرودگاه شهرستان ارومیه در استان آذربایجان غربی، استفاده شد. مشخص شد که در منطقه نیمه‌‌خشک، پارامترهای دمای بیشینه و کمینه دو روز قبل و دمای بیشینه و کمینه یک روز قبل و‌ دمای کمینه و تابش خورشیدی همان روز و در منطقه مرطوب، پارامترهای دمای بیشینه دو روز قبل و دمای بیشینه و کمینه یک روز قبل و دمای کمینه و تابش خورشیدی همان روز، به‌عنوان مدل برتر شناخته شده است.نتایج و بحثنتایج حاصل از تحلیل مدل‌ها، قابلیت و کارایی بالای روش به‌کار رفته در تخمین بیشینه دما را به ‌خوبی نشان داد. از طرف دیگر، روش‌های پیش‌پردازنده باعث بهبود نتایج شدند. در بررسی‌های صورت گرفته مشاهده شد که نتایج حاصل از تجزیه بر اساس تبدیل موجک، منجر به نتایج بهتری می‌شود، به‌طوری‌ که معیار ارزیابی DC برای مدل برتر در منطقه نیمه‌خشک شهرستان ارومیه، از 0.965 به 0.993 و در منطقه مرطوب شهرستان آمل از 0.926 به 0.970، افزایش یافت و معیار RMSE در فرودگاه ارومیه از 1.943 به0.896 و در سیاه‌بیشه از 2.595 به 1.648، کاهش یافته است.نتیجه‌گیرینتایج بررسی نشان از افزایش معیار ارزیابی DC و کاهش RMSE برای ایستگاه سینوپتیک فرودگاه ارومیه به‌ترتیب 2.74 و 53.87 درصد و برای ایستگاه سینوپتیک سیاه‌بیشه آمل به‌ترتیب 4.80 و 35.50 درصد شد. این نتایج نشان می‌‌دهد، تبدیل موجک بیشترین تاثیر را در بهبود عملکرد مدل LSTM دارد و مدل‌های‌‌ منتخب، قابلیت و کارایی بالایی در تخمین میزان دمای بیشینه را دارند. با توجه به نتایج تحلیل حساسیت مشخص شد، پارامتر دمای یک روز قبل، تاثیرگذارترین پارامتر در تخمین بیشینه دمای روزانه برای دو منطقه با اقلیم متفاوت مرطوب و نیمه‌خشک است.

Gábor Ungvári, András Kis

Abstract Between 1998 and 2006 a series of extreme flood events took place on the Tisza River and its tributaries. In Hungary, this triggered the development of flood‐peak polders as a more cost‐efficient solution of defense compared to raising the dikes. The recent analysis applies Monte‐Carlo simulation‐based quantified risk calculations with a cost–benefit type comparison. Results indicate that compared to the originally planned, 100‐year return frequency flood that threats to topple the levees, lower flood levels already provide economic justification for polder use. Apart from the optimal timing of opening the floodgates, the controlled inundation of polders requires the consideration of its cost–benefit effects as well. The development of the economic decision‐support system for the controlled use of the flood‐peak polders along the Tisza River provides an insight into the efficiency gains that a more informed, quantitative economic analysis can offer in risk reduction. The analysis reveals the potential for more efficient management of flood polders. The decision support of controlled polder inundation includes all the necessary information elements for the cross‐sectoral comparability of impacts that is the foundation for any multi‐purpose land management scheme that enables nature‐based solutions.

Marcela Rojas

Philipp Babcicky, Sebastian Seebauer

Abstract Damage and disruption caused by floods do not just arise from the characteristics of physical structures, but also from the characteristics of residents inhabiting these structures. Social vulnerability analyses typically employ socio‐demographic proxy indicators that do not address the risk attitudes, beliefs and agency of those living in areas at risk. To close this gap, this article introduces a range of indicators from psychological risk research. Physical, social and psychological indicators are compared for their influence on vulnerability outcomes such as building damage or emotional distress. Based on survey data of 456 Austrian at‐risk households, hierarchical regression models confirm the added value of psychological indicators for measuring vulnerability above and beyond traditional physical and social indicators. Our findings show that psychological indicators are particularly important for explaining health impacts and distress. General intentions for flood preparedness, fear of flooding and self‐efficacy are most relevant. For a more holistic view of vulnerability, measurement instruments should incorporate psychological indicators. Disaggregated household‐level data is necessary to fully capture the variability between households living in the same flood‐prone area. Indicators perform differently depending on the other indicators included, and the considered outcome; therefore, we caution against pooling indicators to composite indices of overall vulnerability.

Ahmad Sharafati, Zaher Mundher Yaseen, Shamsuddin Shahid

Abstract This study presents a novel stochastic simulation–optimization approach for optimum designing of flood control dam through incorporation of various sources of uncertainties. The optimization problem is formulated based on two objective functions, namely, annual cost of dam implementation and dam overtopping probability, as those are the two major concerns in designing flood control dams. The nondominated solutions are obtained through a multi‐objective particle swarm optimization (MOPSO) approach. Results indicate that stochastic sources have a significant impact on Pareto front solutions. The distance index (DI) reveals the rainfall depth (DI = 0.41) as the most significant factor affecting the Pareto front and the hydraulic parameters (DI = 0.02) as the least. The dam overtopping probability is found to have a higher sensitivity to the variability of stochastic sources compared to annual cost of dam implementation. The values of interquartile range (IQR) indicate that the dam overtopping probability is least uncertain when all stochastic sources are considered (IQR = 0.25%). The minimum annual cost of dam implementation (2.79 M$) is also achieved when all stochastic sources are considered in optimization process. The results indicate the potential of the proposed method to be used for better designing of flood control dam through incorporation of all sources of uncertainty.