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

Dina Pirone, Roberta Padulano, Giuseppe Del Giudice

ABSTRACT Urban flood modelling allows for developing effective strategies for mitigating flood risks and improving urban resilience. Different urban models can be selected according to the desired objective, ranging from simplified frameworks to more sophisticated numerical models. While several studies explored the advantages and limitations of existing model types, very few publications address the urban flood modelling issue based on data availability and data collection. Urban data regarding digital elevation models, sewer networks, and small‐scale features can vary significantly. Thus, the availability and resolution of available data strongly influence urban flood modelling. This study reviews existing approaches to achieve satisfactory urban flood modelling according to the available data and desired objectives. We explored the advantages and limitations of data‐rich environments and the benefits of the simplifications. We identified two primary objectives most concerned with ongoing urban flood simulation research: flood modelling for preliminary flood susceptibility assessment and flood hazard mapping. For each category, we investigated how previous authors approached data collection tasks and which resolution they considered sufficiently high to retain their objectives achieved. This study provides valuable guidance for scientists, engineers, and decision‐makers, promoting a more informed and mindful approach to urban flood modelling.

Yiping Wang, Yongjun Lu, Huaixiang Liu et al.

The estuarine reach of the Yellow River (YRE), located within the core zone of the Yellow River Delta Reserve, serves as a critical zone where the conservation and restoration of fish biodiversity constitute essential elements for achieving high-quality development in the Yellow River Basin. However, the fish population in this area is subject to multiple disturbances (especially water‒sediment regime changes), and because of the year-round fishing ban, relevant data are lacking. By integrating historical fish species records with water‒sediment phases classified via Bayesian mutation analysis and key drivers identified via principal component analysis, this study elucidates the reasons for the evolution of fish biodiversity. The results revealed mutation points of the annual runoff (2001) and sediment load (2004) in the YRE during 1950–2023, with a marked declining trend preceding these shifts (P < 0.05), accompanied by fluctuations in fish taxonomic diversity and obvious changes in the dominant fish ecological types. Moreover, the key water–sediment factors influencing fish biodiversity were associated primarily with fish reproduction and migration during the investigation periods, including the proportion of monthly mean discharge relative to the natural baseline phase, minimum daily ecological flow guarantee rate, and annual flow cessation days in zero-flow years. We emphasize that these findings are based on empirical observations from implemented water regulations, but the causal relationship requires rigorous testing via process-based models or controlled experimental studies. Nevertheless, this study still provides the necessary empirical data and initial hypotheses for subsequent research, which can serve as a reference for optimizing protection measures for the YRE.

Bugrayhan Bickici, Beste Hamiye Beyaztas, Zaher Mundher Yaseen et al.

ABSTRACT Streamflow (Qflow) process is one of the complex stochastic processes in the hydrology cycle owing to its associated non‐linearity and non‐stationarity characteristics. It is an essential hydrological process to address the complex time series nonlinear phenomena. In this research, a novel approach was proposed by integrating an autoregressive conditionally heteroscedastic (ARCH) method with bootstrap model to predict future Qflow intervals. For this purpose, two Qflow series located at the Eastern Black Sea basin (Turkey) were subjected to the application of the proposed methodology. Among other regression and machine learning (ML) models, which are suitable for Qflow modeling, the autoregressive integrated moving average (ARIMA), seasonal autoregressive integrated moving average (SARIMA), and artificial neural network (ANN) were selected for modeling validation in this study. A group of three numerical metrics and graphical presentations were used for the modeling evaluation and assessment. The proposed ARCH approach performed a superior mathematical model to address the Qflow interval prediction. Remarkable prediction accuracy was shown against the benchmark models. Overall, the approach of coupling the bootstrap procedure with the ARCH model exhibited a robust modeling strategy for predicting Qflow intervals suggested as a new analysis tool.

Saad Sh. Sammen, Reza Mohammadpour, Karam AlSafadi et al.

ABSTRACT Rainfall and runoff are considered the main components of the hydrological cycle, and their forecasting is of great significance in water resource management, particularly for reservoir operation. Developing an accurate model to capture the dynamic connection between rainfall and runoff remains problematic and challenging in water resource management due to the nonstationary characteristics of hydrologic processes and the effects of noise. In this study, data‐driven techniques, such as the group method of data handling (GMDH), extreme learning machine (ELM), and two hybrids of artificial neural network (ANN) with Cuckoo search algorithm (ANN + Cuckoo) and genetic algorithm (ANN + GA) were used to model the rainfall–runoff relationship. For a comprehensive analysis, four scenarios were examined based on the different input combinations to test and select the best scenario and best model performance. The results indicated that the performance of ELM and GMDH in predicting runoff was more accurate than that of ANN + Cuckoo and ANN + GA. Although the GMDH predicts runoff with higher accuracy, ELM provides reliable performance in simulating both low and high values. The models' performance can be ranked based on the testing data in the following order: GMDH, ELM, ANN + GA, and ANN + CUKOO. The root mean squared error (RMSE) was recorded as 56.7 and 69.7 m3/s for the GMDH and ELM models, respectively. These low RMSE values highlight the potential of these models in effectively addressing the challenges associated with the complexity of rainfall–runoff simulations. Moreover, the results demonstrate that the machine learning models could be used as a simple, rapid, and inexpensive approach for timely and reliable runoff prediction that is expected to benefit reservoir management.

Andrea Lammer, Rolf Rindler, Michael Tritthart et al.

Temporal and spatial variability and a wide range of measured transport rates at comparable flow rates are well-known characteristics of the bedload transport process but represent substantial difficulties in practice and for load calculation. The possibility of measuring the bedload transport process has increased in recent years through the use of technically advanced methods. Since 2011, an integrative bedload monitoring system has been operating on the Urslau River in Austria and has been continuously observing the transport process. This long-term integrative dataset provides the basis for comparing calculation results from commonly used bedload transport formulae with measured data. On the basis of 27 high sediment transport efficiency events, as well as 75 events with reduced sediment availability and 34 events with low sediment availability, this study compares the measured and calculated bedload volumes. In addition, a wide range of measured bedload transport rates are presented for comparable discharges, and values in this range are represented by the formulae shown. The performance of the transport equations is improved by considering measured data from integrative bedload monitoring and by classifying bedload events. The results presented here indicate that, depending on the question considered and by selecting the appropriate formula, it is possible to achieve improved calculation results for practice that are comparable to the measured values.

Brian R. Cook, Isabel Cornes, Paula Satizábal et al.

Abstract Responding to societal challenges requires an understanding of how institutional change happens or does not happen. In the context of flood risk reduction, a central impediment of transformational change is a struggle over how public participation is understood and practiced. Risk institutions are often portrayed as resistant to change, which overlooks the individuals within institutions who struggle to implement innovative power‐sharing approaches/arrangements. Using two rounds of qualitative interviews spread over 5 years, this research identifies factions within the risk sector—those who view participation as awareness raising and those who are struggling to make participation part of a wider commitment to power‐sharing: a group that, for the purpose of this analysis, we call “mavericks.” Through focus on how mavericks struggle for change, this analysis uncovers tensions that arise as individuals attempt to alter prevailing knowledge‐practices. The findings highlight the importance of experiential learning, active listening, and the alteration of space. By applying a relational conceptualisation, we explore how mavericks advocate for relationship building, which alters spaces of public participation and, in that way, lays the foundation for transformational social innovations. The conclusions offer flood risk researchers perspective on the institutional struggles that preconfigure how frontrunner projects are or are not able to facilitate the community participation needed to successfully implement societal transformations.

Mousumi Ghosh, Supantha Paul, Subimal Ghosh et al.

ABSTRACT Climate change, urbanization, and anthropogenic activities have intensified rainfall and urban flooding, especially along coastlines. The high spatiotemporal variability and erratic pattern of rainfall highlight the incompetency of independent application of statistical forecasting techniques, especially over the tropics, and demand the incorporation of physics‐based numerical weather prediction models along with urban feedback for improved forecasting. The current study utilizes a physics‐based numerical weather prediction model, Weather Research and Forecasting (WRF) model, for rainfall forecasting, provided as an input to a 2‐way coupled hydrodynamic flood modeling framework, considering streamflow, overland flow, and tidal impact. The influence of three urban canopy scenarios, i.e., not coupled, coupled with a single layer, and multiple layer urban canopy model, is assessed over rainfall, and subsequently the flood inundation and risk pattern, by utilizing this framework. Comparisons have been made between flood maps developed for three scenarios using WRF forecasted rainfall and maps developed using observed rainfall data. An investigation has been conducted into the extent to which the scenarios can replicate the observed pattern and extent of flooding for the comprehensive flood forecasting network. This study signifies that considering urban signatures with other meteorological parameters for rainfall forecasting is highly essential to improve the accuracy of flood risk forecasts.

Fateme Sedaghatkish, Safoora Asadi Kapourchal, Misagh Parhizkar

Biochar, as a viable substrate and soil amendment, has the potential to improve the physical and chemical properties of soils, consequently affecting soil erosion. However, few studies have explored the impacts of different types of biochar on soil detachment rates in the hillslope rill erosion process due to overland flow in deforested areas. To fill this knowledge gap, this study evaluated the soil detachment capacity (Dc) and rill erodibility (Kr) of soil samples amended with four different biochars (wood, rice, olive, and almond shells) collected from deforested hillslopes in northern Iran. Dc was measured via a hydraulic flume at three-bed slopes (8.5%, 16.9%, and 25.4%) and five flow discharges (0.21, 0.32, 0.43, 0.55, and 0.63 L/(m·s)). Moreover, key properties of the amended soils and the control soil, including organic matter (OM), aggregate stability (MWD), bulk density (BD), and cation exchange capacity (CEC), were measured. Compared with the control treatment, the application of the four types of biochar significantly (p < 0.01) decreased the Dc (with at least a 41% reduction). The application of almond shell and rice biochars significantly increased the OM and MWD, thus effectively decreasing Dc (−76% compared with that of wood biochar) and (−47% compared with that of olive biochar). The correlation analysis revealed significant associations between OM, MWD, and BD on the one hand and Dc on the other hand. Overall, the soils treated with almond shell and rice biochars could be distinguished from the other soils into distinct groups via principal component analysis. The linear relationship between Dc and shear stress was used to reflect the relationship between the dependent and independent variables (coefficient of determination, R2 > 0.71). The multiple regression equation developed to estimate Dc from the OM, MWD, and BD data was also accurate (R2 > 0.83). This study demonstrated that almond shells and rice biochars can be effective factors in controlling and reducing Dc and Kr on deforested and steep hillslopes. The findings of this study can help land managers select the most effective organic substrate for soil conservation purposes as well as hydrologists to support the estimation of rill erosion on steep hillslopes.

James H. Williams, Huong Ngan Vu, Ryan Paulik et al.

ABSTRACT Flood impact assessment is limited by a scarcity of damage curves for critical infrastructure network components. This study presents a judgement‐based methodology for developing critical infrastructure network component flood damage curves. The 12 semi‐structured workshops record responses for estimated minimum and maximum damage ratios at 0.5, 1, 2 and 3 m water depths. The 46 responses, weighted by participant expertise level, are aggregated into a discrete minimum and maximum damage curve for each component. Damage curves are presented for 34 infrastructure network components across the transportation, energy, water, and telecommunication sectors. These damage curves are benchmarked against relevant flood damage curves from previous studies, providing insight on how flood damage models compare internationally and across methods. While the synthesised flood damage curves allow for nationally consistent risk assessments, this study highlights the need for flood damage curves that represent local risk contexts for infrastructure network components to facilitate locally applicable risk assessments that inform risk management.

طاهر فرهادی نژاد, ایرج ویس کرمی, مهران زند

مقدمهخشکسالی، می‌تواند اثرات منفی جدی بر کیفیت آب مورد نیاز برای کشاورزی آبی داشته باشد. سازندهای زمین‌شناسی منطقه باعث افزایش غلظت عناصر جزیی و کمیاب سمی در آب‌ها می‌‌شود و از طرف دیگر، فعالیت‌های انسان منجر به آلودگی آب در مناطق مجاور می‌‌شود. در این پژوهش، به بررسی اثر خشکسالی بر کیفیت آب‌های سطحی، اثر عوامل مختلف از جمله سازندهای زمین‌‌شناسی و کاهش یا افزایش بارندگی و دمای هوا بر کیفیت منابع آب، چگونگی تغییرات کیفی آب، تعیین محدودیت‌‌های مصرف آب در بخش شرب و کشاورزی پرداخته شود. مواد و روش‌هاحوضه رودخانه تیره، با مساحت 3243.6 کیلومتر مربع به‌عنوان یکی از زیرحوضه‌های رودخانه دز و زیرمجموعه‌ای از حوضه کارون محسوب می‌شود. برای بررسی تاثیر خشکسالی بر کیفیت منابع آب سطحی، ابتدا شاخص‌های بارندگی استاندارد (SPI)، شاخص استاندارد جریان‌های رودخانه‌ای (SSI) و شاخص دهک‌ها (DI) محاسبه شد و سپس روابط آن‌ها با عناصر و ترکیبات هدایت الکتریکی (EC)، کل جامدات محلول (TDS)، pH و آنیون‌های کلر (Cl-)، سولفات (SO42-) ، بی‌کربنات (HCO3-)، کاتیون‌های سدیم (Na)، کلسیم (Ca) و منیزیم (Mg) مورد بررسی قرار گرفت. برای ترسیم الگوی خشکسالی‌ها سه ایستگاه هیدرومتری تنگ محمد حاجی (بالادست)، رحیم‌آباد سیلاخور (میانه‌) و ایستگاه تیره-درود (خروجی) مورد بررسی قرار گرفته‌اند. نتایج و بحثنتایج نشان داد که شدیدترین خشکسالی‌های هیدرولوژیک با تداوم دو ساله و کمینه SSI به مقدار 1.23- در ایستگاه تنگ محمد حاجی در سال‌های آبی 87 و 88 و ایستگاه تیره–درود با تداوم چهار ساله (1.19-) و ایستگاه رحیم‌آباد سیلاخور با تداوم سه ساله (1.16-) برای سال‌های آبی 91، 92، 93 و 94 رخ داده است. بررسی داده‌های دبی و بارش زیرحوضه‌های تیره نشان داد که بین دبی و بارش (SPI و SSI) ایستگاه‌های تنگ محمدحاجی و رحیم‌آباد دارای همبستگی متوسط مثبت در سطح معنی‌داری 0.05 بوده (0.526 =R2). بررسی روابط دبی سالانه و پارامترهای کیفیت آب نشان داد که برای بیشتر پارامترها مثل TDS، هدایت الکتریکی، کلر و مجموع آنیون‌ها و کاتیون‌ها همبستگی منفی بوده، به‌طوری‌که بیشینه تمرکز غلظت پارامترهای کیفیت در خشکسالی‌ها رخ داده است. در ایستگاه تنگ محمدحاجی بیشترین درصد تغییرات مربوط به سدیم و کلر به‌ترتیب با 62.55 و 39.70 درصد در سال‌های خشک نسبت به میانگین بلندمدت است. نتایج این پژوهش نشان داد که در ایستگاه‌های مورد بررسی در حوضه رودخانه تیره، درصد تغییرات مربوط به کلسیم، منیزیم و سدیم و آنیون‌های کربنات و کلر در سال‌های خشک نسبت به میانگین بلندمدت افزایش پیدا کرده است. همه ایستگاه‌های حوضه تیره دوره خشکسالی هیدرولوژیک نسبتا خشک (0.84- تا 1.28-) را گذرانده، هیچ‌کدام متحمل خشکسالی هیدرولوژیک شدید نشده‌اند.نتیجه‌‌گیریبررسی داده‌های دبی و بارش زیرحوضه‌های تیره نشان می‌دهد که بین دبی و بارش (SPI و  SSI) ایستگاه تنگ محمد حاجی که یک زیرحوضه بالادستی تیره است، دارای همبستگی متوسط مثبت در سطح معنی‌داری 0.05 بوده، در ایستگاه رحیم‌‌آباد که در میانه حوضه تیره قرار دارد، نیز از نظر پیرسون در سطح معنی‌داری 0.05 دارای همبستگی است. در ایستگاه خروجی حوضه تیره بین متغیرهای دبی و بارش همبستگی معنی‌دار مشاهده نمی‌شود که می‌تواند ناشی از بارش برف و ماندگاری برف در ارتفاعات از سال آبی قبل، احداث سد مروک در بالادست حوضه و همچنین آب‌گیری تالاب بیشه‌دالان سیلاخور در خشکسالی‌ها و برداشت فراوان آب از رودخانه تیره برای کشاورزی باشد. حوضه‌ بالادست ایستگاه‌ تنگ محمدحاجی کاملا آهکی بوده که باعث تغییر در پارامترهای کلسیم، TDS، EC و غیره شده است. در ایستگاه رحیم‌آباد سیلاخور و خروجی تیره نیمی از مساحت حوضه اختصاص به سنگ‌های نفوذی مثل گرانیت و گرانودیوریت که باعث افزایش پتاسیم و کلسیم می‌شود. در ایستگاه‌های مورد بررسی در حوضه رودخانه تیره درصد تغییرات مربوط به کلسیم، منیزیم و سدیم و آنیون‌های کربنات و کلر در سال‌های خشک نسبت به میانگین بلندمدت افزایش پیدا کرده است. به‌طور کلی، می‌توان نتیجه‌گیری کرد که خشکسالی می‌تواند اثرات منفی بر پارامترهای کیفی آب در حوضه رودخانه تیره داشته باشد.

نرگس کریمی‌نژاد, حمیدرضا پورقاسمی, محسن حسینعلی زاده et al.

مقدمه زمین‌لغزش‌ها و فروچاله‌ها به زیرساخت‌های اجتماعی، اقتصادی و طبیعی آسیب می‌زنند. این فرایندها تأثیرات مستقیم و غیرمستقیم بر زیرساخت‌های مهم، از جمله مناطق مسکونی دارند و بر تغییر کاربری اراضی و مهاجرت از روستا به شهر تأثیرگذارند. یکی از اهداف اصلی در مدیریت پایدار اراضی، شناسایی و کنترل بلایای طبیعی است که از یک‌سو سبب ارتقاء کمی و کیفی تولید در طولانی‌مدت شده و از سوی دیگر، علاوه بر حفظ کیفیت خاک از تخریب خاک جلوگیری می‌کند. به‌منظور مدیریت بهتر و پایدارتر، آگاهی از نحوه تغییر‌پذیری و شناسایی شکل‌های مختلف فرسایشی مانند فروچاله‌ها و زمین‌لغزش‌ها ضروری به‌نظر می‌رسد.   مواد و روش‌ها با پیشرفت‌های اخیر در استفاده از تصاویر پهپاد (UAV) و روش‌های یادگیری عمیق (DL)، امکان ارائه روش‌های نیمه‌خودکار برای شناسایی واحدهای اراضی در مناطق مختلف با دقت مکانی بسیار خوب فراهم شده است. در این پژوهش، توانمندی دو مدل یادگیری عمیق پیشرفته، یعنی مدل U-Net و مدل U-Net با نظارت عمیق (ADSMS) که بر روی تصاویر به‌دست آمده از پهپاد اعمال شده است، برای نقشه‌برداری زمین‌لغزش‌ها و فروچاله‌ها در بخشی از نهشته‌های لسی استان گلستان مورد بررسی قرار گرفته است.   نتایج و بحث عملکرد مدل U-Net در زمینه زمین‌لغزش‌ها نشان می‌دهد که مدل دارای مقادیر مثبت کاذب کمتری است، اما هم‌زمان، بسیاری از سلول‌های زمین‌لغزش را از دست داده است. درعین‌حال، مدل ADSMS U-Net در تشخیص سلول‌های زمین‌لغزش عملکرد بهتری داشته، اما موارد زیادی را به پیش‌بینی‌های نادرست نسبت داد (که با امتیاز پایین دقت توضیح داده شده است). بهترین امتیاز F1  به مقدار 0.68 برای مدل ADSMS U-Net به‌دست آمده است. برای همه ترکیب باندها در تشخیص فروچاله‌ها، عملکردهای ADSMS U-Net نسبت به مدلU-Net  سنتی بهتر است. بهترین امتیازات کلی توسطADSMS U-Net  زمانی به‌دست آمد که بر روی داده‌های ALL، آموزش داده شد. در مورد اثربخشی مختلف ترکیب‌های ارزیابی‌شده در این پژوهش، می‌توان رفتار متناقض مدل‌ها را مشاهده کرد. U-Net سنتی، بهترین عملکرد را با استفاده از ترکیب نوری RGB به‌دست می‌آورد، درحالی‌که ADSMS U-Net  می‌تواند از اطلاعات مشتقات توپوگرافی و داده‌های نوری بهره برده و با ترکیبALL  بهترین نتایج را نشان دهد. علاوه بر این، واضح است که داده‌های DSHC به‌تنهایی برای هر دو مدل بدترین نتایج را ارائه می‌دهد. به طور کلی نتایج نشان داد که قابلیت ADSMS U-Net برای پیش‌بینی زمین‌لغزش‌ها در مقایسه با U-Net به واقعیت زمین نزدیک‌تر است. این مدل اغلب زمین‌لغزش‌های موجود در قسمت‌های آزمون را شناسایی می‌کند. همچنین، برای همه ترکیب باندهای فروچاله‌ها، عملکرد ADSMS U-Net نسبت به مدل U-Net بهتر است. بهترین امتیازات کلی توسط ADSMS U-Net زمانی به‌دست آمده است که بر روی داده‌های ALL آموزش داده شده‌اند.   نتیجه‌گیری از آنجایی‌که فروچاله‌ها منشأ اصلی برخی از فرسایش‌های عمده دیگر ازجمله شروع و گسترش آبکند محسوب می‌شوند، استفاده از ابزارها و فناوری جدید نظیر پهپاد و یادگیری عمیق، بسیار مهم است. با استفاده از مدل‌های مورداستفاده در این پژوهش، زمین‌لغزش‌ها با امتیاز قابل‌قبول ٪69=F1 نقشه‌برداری شدند. همچنین، مشتقات توپوگرافیکی به‌دست آمده از مدل رقومی ارتفاع مبتنی بر پهپاد، توانایی نقشه‌برداری فروچاله‌ها و زمین‌لغزش‌ها با داده‌های موجود را دارا هستند. تحقیقات بعدی می‌توانند استفاده از چنین رویکردی را برای نقشه‌برداری از زمین‌لغزش‌ها و فروچاله‌ها در طول زمان مورد بررسی قرار داده تا تغییرات مبتنی بر زمان بر روی شکل‌گیری و گسترش مخاطرات طبیعی را ارزیابی کنند.

Frank denHeijer, Jeroen Rijke, Marian Bosch‐Rekveldt et al.

Abstract Flood defences are in practice often multi‐used, multi‐managed and multi‐financed. Flood defence asset management contains technical, organizational and spatial complex issues involving multiple organizations. In the literature, little attention has been given to the conditions for successful cooperation between organizations in flood defence asset management. This paper elaborates on this aspect of mature asset management from a practical point of view. Although the importance of a fit‐for‐purpose cooperation seems trivial, practice shows that the shape of cooperation is often the coincidental result of implicit or ad‐hoc choices and is not deliberately designed. This paper reports on empirical data gathered in a case consisting of five different situations related to collaboration in flood defence management. The management context consists of three main tasks: performance assessment, reinforcement and daily management, and three decision levels: strategic, tactical and operational, resulting in nine different management environments and related interfaces. For effectively achieving desired outcomes, the shape of cooperation has to be explicitly chosen dependent on the complexity of content and organizational context, and relevant external circumstances: situational cooperation.

Johann Jacob, Pierre Valois, Maxime Tessier et al.

Abstract Given that flooding episodes are occurring at a greater rate due to climate change, individuals must adopt certain adaptation behaviors to prevent or mitigate the anticipated or negative impact of such events. However, few studies have assessed if and how households and individuals have actually taken action in this regard. Because some individual beliefs can be linked to facilitating factors and barriers to action, a better understanding of the adoption of adaptive behaviors requires a combined analysis of individual psychosocial factors. The purpose of this study was to develop a better understanding of the reasons underlying the adoption of behaviors related to structural adaptation to flooding by people living in or near flood‐prone areas in the Province of Québec (Canada). Results of a series of structural equation modeling showed that behavioral, normative and control beliefs were all significant predictors of the respondents' intention to adopt structural flood protective behaviors, with normative beliefs being the strongest. By identifying the best psychosocial predictors of the adoption of such behaviors, the results of this study provide valuable insights regarding the most effective factors to be used in public health messages to promote the adoption of behaviors related to structural adaptation to flooding.

Rongrong Li, L. Xiong, Cong Jiang et al.

Parthkumar A. Modi, Jonathan A. Czuba, Zachary M. Easton

Abstract An increase in heavy precipitation associated with climate change has exacerbated flooding in the Eastern U.S. To assess regional flood risk with changing climatic conditions, we demonstrate the application of a novel hydrologic modeling framework that integrates climate projections with a coupled Noah‐MP land surface model and a two‐dimensional HEC‐RAS hydrodynamic model. We employ this framework along a 41 km reach of the Susquehanna River near Harrisburg, Pennsylvania, where recent flood damages exceeded $2 billion (2011 Irene and Lee floods). Historical and future 30‐year and 100‐year peak‐discharge estimates were compared to assess how flood risk might be altered due to climate change. Results indicate that precipitation increases from climate change do not always lead to increases in flood risk, because interplay of hydrological components in the watershed, which are considered by Noah‐MP, largely controls flooding severity. However, climate change is expected to increase the severity of extreme events; if a 50‐year flood (the recurrence interval of Tropical Storm Lee) occurred toward the end of the 21st century in the worst‐case emission scenario, then flood volume would increase by 40% and flood extent by 15%, due to an increase in soil moisture from a wetter overall climate.

Paul Samuels

Abirham Cherinet, Sadnur Worku

Flood is one of the natural hazards that have negative impacts on peoples and property. It occurs in lowland areas without any sign when excessive rains fall in adjacent highland areas. Since flood is unavoidable natural phenomena, adopting protective mechanisms are crucial. This study was conducted in Jigjiga town, Eastern Ethiopia with main objective of delineating flood risk areas. For the purpose of flood risk mapping preparation, hydrology and hydraulics models have been used. Besides, land use /cover change detection analysis has been carried out between the year 2003 and 2017. Soil Conservation System (SCS) Curve Number method was used as hydrology model. Satellite and field data have been collected, filtered and finally a geo-database has been developed in GIS environment. Flow data and river geometry data, which obtained from hydrology model and prepared using HEC-GeoRAS was used as inputs for HEC-RAS model. Before running steady flow analysis, correction of geometry data has been carried out in HEC-RAS environment. From the study, it was found that, expansion of built up area and agricultural land at the cost of open area. Flood inundation extent maps show that increasing in aerial coverage as return period increases but the variation in area between consecutive periods are small. The flood extent obtained by applying structural flood control mechanism shows that the measure reduces the flood extent considerably but it also exhibits some part of the town is still in undated in all return periods. From the analysis it was observed that the increases in built up area and agricultural land may lead to increase flooding. Besides, among the LULC classes fall under high risk zone at different return periods, built up area and agricultural land consist a considerable proportion. It also observed that, flood risk areas increase as return period increases but the variation between the periods is small. The flood risk map can be used for planning control measures for future flood.

Víctor M. Santos, Thomas Wahl, Robert Jane et al.

Abstract Compound flooding may result from the interaction of two or more contributing processes, which may not be extreme themselves, but in combination lead to extreme impacts. Here, we use statistical methods to assess compounding effects from storm surge and multiple riverine discharges in Sabine Lake, TX. We employ several trivariate statistical models, including vine‐copulas and a conditional extreme value model, to examine the sensitivity of results to the choice of data pre‐processing steps, statistical model setup, and outliers. We define a response function that represents water levels resulting from the interaction between discharge and surge processes inside Sabine Lake and explore how it is affected by including or ignoring dependencies between the contributing flooding drivers. Our results show that accounting for dependencies leads to water levels that are up to 30 cm higher for a 2% annual exceedance probability (AEP) event and up to 35 cm higher for a 1% AEP event, compared to assuming independence. We also find notable variations in the results across different sampling schemes, multivariate model configurations, and sensitivity to outlier removal. Under data constraints, this highlights the need for testing various statistical modelling approaches, while the choice of an optimal approach remains subjective.

K. Hlavčová, M. Danáčová, S. Kohnová et al.

Abstract The paper focuses on the generation of floods as a principal soil threat and on soil erosion as an additional soil threat on arable lands of hillslope areas. As the most important component of floods causing the degradation of soils on arable lands, surface runoff is analysed in this study. The protective effect of crop management on the generation of surface runoff and sediment transport on arable lands is estimated on a plot and slope scale. The site of the case study, which is located in the Myjava river basin in western Slovakia, is a hilly agricultural field with an area of 29 ha; it is characterised by arable soil, extreme erosion processes, and muddy floods. Field rainfall simulation experiments were combined with physically-based modelling for studying the formation of surface runoff under various soil covers. The field experiments consisted of simulating runoff generation from artificial rainfalls using the Eijkelkamp rainfall simulator on experimental plots with a focus on estimating the volume of surface runoff, the mass of sediments transported by the surface runoff, and the time to runoff. The volumes of the surface runoff and the values of the time to runoff have been applied in the parameterisation of the SMODERP physically-based hydrological model. The hydrological modelling of the surface runoff on the selected slope profile quantified the protective effect of various soil covers on reducing surface runoff. The outcome of the modelling was the maximum allowed lengths of the slope that represent the crucial values for flood and erosion control. When exceeding these critical values, protective measures, e.g., vegetation strips, should be proposed.

Shida Gao, Pan Liu, Zhengke Pan et al.

Abstract Assessing flood frequency is pivotal for hydrology, with implications for many fields ranging from river science to the insurance industry. Reservoir regulation may alter the characteristics of the flood frequency distribution function. This paper incorporates reservoir impacts as an inherent variable to derive an analytical solution of outflow peaks and proposes new flood frequency distributions. Steps are as follows: (1) the original flood without reservoir impacts is assumed to follow a Pearson type III distribution, (2) linear and nonlinear reservoir models, including numerical integration and triangular area calculation methods, are proposed to simulate the relationships between inflow and outflow peaks, and (3) the flood frequency distributions resulting from reservoir impacts are derived. Derived equations are applied to the Shuibuya and Wuqiangxi reservoirs in China. Results show that: (1) although the numerical integration method with the nonlinear model is comparable with the reservoir flood routing, the triangle area calculation method with the nonlinear model is recommended for its accuracy and simplicity, (2) the reservoir regulation changes the flood frequency distribution function entirely in the nonlinear reservoir model, while only change the parameter in the linear reservoir model, and (3) downstream flood’s CV can be increased or decreased, which depends on the reservoir regulating capacity. It is indicated that altering the parameters of the flood frequency distribution is not sufficient to characterize watershed under reservoir control. This paper proposes the analytical solution about inflow and outflow peaks, which can point out the possible changes in the watershed with reservoir construction in plan.