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

D. Petsch, V. Cionek, S. Thomaz et al.

Jae-In Lee, Chang-Hee Lee, Chang-Gu Lee et al.

This study investigated the potential application of dredged sediments as a medium for cultivating landscape plants, assessing plant performance in contaminated dredged sediment (CDS) and remediated dredged sediment (RDS), using commercial horticultural soil as a control. Three ornamental plant species, Korean lawn grass (KLG), Aster arenarius Nemoto, and English poppy, were grown under distinct soil conditions both with and without the addition of organic and biochar-based amendments. Soil quality indices and responses in plant growth were measured to determine the influence of sediment remediation and amendment application. The findings demonstrated that RDS created a more suitable substrate for plant development compared to CDS, with KLG exhibiting the most pronounced growth improvement, especially when supplemented with wood-derived biochar and soil conditioner (SC). Incorporating SC into CDS markedly improved KLG biomass, with dry weight increases of 7.4 % and 136.9 % at 2 % and 5 % SC, respectively. Significant correlations (p < 0.05) were observed between soil and leaf Ni concentrations. Additionally, the study analyzed how soil properties impacted heavy metal(loid) accumulation in KLG, showing that soil pH, electrical conductivity, and cation exchange capacity exerted significant effects on Pb and Zn levels in plant tissues. Overall, these results indicate that adequately remediated and amended RDS has the potential to be utilized as a sustainable medium for landscape plant production and may play a role in environmental restoration initiatives.

Muhammad Waqas, Basir Ullah, Afed Ullah Khan et al.

ABSTRACT Floods are among the most destructive natural disasters, presenting significant challenges due to their unpredictability and complex behavior. This study develops a robust flood prediction framework for the Chakdara monitoring station on the Swat River, Pakistan, by integrating traditional statistical methods with advanced machine learning (ML) models. Four statistical distributions—Log‐Normal, Gumbel, General Extreme Value (GEV), and Log‐Pearson Type III (LP‐III)—were evaluated for flood frequency analysis. Among these, the LP‐III distribution demonstrated the best performance with an R2 value of 0.78. To enhance prediction accuracy, two ML models—Artificial Neural Network (ANN) and multilayer neural network (MLNN)—were employed. The MLNN model outperformed all others, achieving R2 values of 0.96 for training and 0.93 for testing, confirming its high reliability for streamflow prediction. Furthermore, the trained MLNN was adapted to future climate conditions using downscaled and bias‐corrected CMIP6 projections under SSP245 and SSP585 scenarios. This allowed for reliable discharge forecasting under changing precipitation and temperature trends. The proposed hybrid approach not only improves the accuracy of flood predictions but also supports long‐term planning for flood risk mitigation. These findings provide essential insights for policymakers, engineers, and disaster management agencies to design adaptive infrastructure and implement proactive flood management strategies in the Swat River basin.

Yanan Zhu, Yibao Lou, Wenlong Wang et al.

Dump slopes have experienced severe rill erosion and threaten the safety of the ecological environment. Although vegetation restoration has improved the ecological environments of mining areas, because dump slopes have unique soil properties, the mechanism by which roots impact rill erosion on dump slopes remains unclear. Based on the in-situ runoff scouring experiment of the dump slope and the use of bare land as the control (CK), the influence of roots on rill erosion characteristics (RECs) of the dump slopes were analyzed for three root types of vegetation, specifically, tap root–Artemisia ordosica (AO), fibrous root–Elymus dahuricus (ED) and tap + fibrous root–Artemisia ordosica + Elymus dahuricus (AE). The results indicated that, compared to the CK, the roots reduced the rill erosion rate (Ts) by 75.61%–86.64% and the rill depth (Rd) by 64.62%–81.06% on the dump slopes. However, they increased the runoff depth (h) and Reynolds number (Re) by 2.02%–37.14% and 36.1%–172.0%. Among them, AO significantly increased Manning roughness coefficient (n), Darcy–Weisbach friction factor (f) and shear stress (τ), whereas ED and AE were most effective in reducing h and Ts, respectively. 59.9% of the RECs of dump slopes were explained by roots and hydraulic characteristics together. Furthermore, PLS-SEM analysis revealed that roots affect hydraulic characteristics by changing surface roughness and runoff friction resistance, ultimately leading to differences in the RECs of dump slopes, which explained 98.5% of the RECs on dump slopes with a 72.2% goodness-of-fit. The above results further enhance the understanding of the role of roots in controlling rill erosion on dump slopes.

Min Li, Jing Ou, Zhihe Chen

The aggregation of microplastics (MPs) with sediments in natural water plays a crucial role in the general deposition and transport of plastic particles. However, the effect of salinity changes on the settling behavior of aggregates remains unclear. In this study, the aggregation and settling processes of sediment particles with spherical MPs were investigated using a settling tube and a microphotography device, in deionized water (pH 8.0) with 10–35 practical salinity units (PSU). Two-particle and three-particle aggregates were most commonly observed in the experiments. Increasing the salinity promoted the aggregation of MPs, reaching the largest average particle size at 25 PSU, but the mean Corey shape factor values exhibited minimal variations at different salinities. Meanwhile, the settling velocity of the aggregates was directly proportional to their particle size, and thus the average settling velocity also reached a maximum at 25 PSU. Although the settling velocity can be predicted with high correlation coefficients using existing formulas developed for static conditions, dynamic flow may reduce the settling velocity of aggregates and cause overestimation. Herein, a reduction coefficient was used to revise the settling velocity formula and predict the measured values with higher accuracy. This study provides insights into the aggregation and settlement of MPs in estuarine environments with varying salinity, which affect the fate and distribution of plastic particles in natural waters.

Michael H. Gardner, Nina Stark, Kevin Ostfeld et al.

ABSTRACT Flood hazards pose a significant threat to communities and ecosystems alike. Triggered by various factors such as heavy rainfall, storm surges, or rapid snowmelt, floods can wreak havoc by inundating low‐lying areas and overwhelming infrastructure systems. Understanding the feedback between local geomorphology and sediment transport dynamics in terms of the extent and evolution of flood‐related damage is necessary to build a system‐level description of flood hazard. In this research, we present a multispectral imagery‐based approach to broadly map sediment classes and how their spatial extent and relocation can be monitored. The methodology is developed and tested using data collected in the Ahr Valley in Germany during post‐disaster reconnaissance of the July 2021 Western European flooding. Using uncrewed aerial vehicle‐borne multispectral imagery calibrated with laboratory‐based soil characterization, we illustrate how fine and coarse‐grained sediments can be broadly identified and mapped to interpret their transport behavior during flood events and their role regarding flood impacts on infrastructure systems. The methodology is also applied to data from the 2022 flooding of the Yellowstone River, Gardiner, Montana, in the United States to illustrate the transferability of the developed approach across environments. Here, we show how the distribution of soil classes can be mapped remotely and rapidly, and how this facilitates understanding their influence on local flow patterns to induce bridge abutment scour. The limitations and potential expansions to the approach are also discussed.

Hulan Badde Gedara Dilshan Madubhashana Padminda Ekanayaka, Nimal Shantha Abeysingha, Tusita Amarasekara et al.

Soil erosion is a significant environmental threat, impacting water quality and the siltation of the productive capacity of reservoirs. To prioritize soil conservation areas for sustainable land management, quantitative spatial assessment of soil erosion is essential, particularly in the catchment of a reservoir. The current study aims to evaluate the soil erosion severity and sediment generation in the closer catchment of a proposed reservoir, the lower Malwathu Oya Reservoir in Sri Lanka. Erosion modeling has proven cost-effective in assessing the spatial distribution of soil erosion severity. This current study utilized the Integrated valuation of ecosystem services and tradeoffs sediment delivery ratio (InVEST-SDR) model to analyze the spatial distribution of soil erosion and sediment export. A digital elevation model (30 m × 30 m), 22 years of rainfall data, land use and land cover data, soil map, and cropping factors were used as model inputs. The results revealed an average annual soil loss ranging from 0 to 15.55 t/(ha·y) in the catchment and a mean annual sediment export of 0.016 t/(ha·y). Erosion severity was classified into four hazard classes, i.e., insignificant (<0.5 t/(ha·y)), weak (0.5–3 t/(ha·y)), considerable (3–12 t/(ha·y)), and severe (12 < t/(ha·y)). A critical 0.12% area was identified as a considerable soil erosion hazard area, necessitating urgent measures for erosion control. High-risk areas were at Galpottegama, Asirikgama, Puleliya, Navodagama, and Thuppitiyawa Grama Niladari. These findings provide valuable insight for formulating and implementing soil conservation practices in the catchment to reduce the siltation of the proposed lower Malwathu Oya reservoir. The study is an example of using InVEST-SDR to evaluate the sedimentation of a proposed reservoir.

Hyun‐il Kim, Se‐Dong Jang, Hehun Choi et al.

ABSTRACT Accurate flood level prediction is crucial for mitigating flood damage caused by typhoons or localized heavy rainfall. However, predicting flood levels is challenging due to changes in river environments and external factors, such as dam or weir operations. To address these challenges, this study proposes a methodology for constructing an optimal combination of input data using basic hydrological information and predicting flood levels in real time through a deep learning model. The study focuses on identifying the best input data combination tailored to each river basin's characteristics, considering both natural runoff rivers and those influenced by dam discharges. The Long Short‐Term Memory (LSTM) model, known for its superior performance in time‐series forecasting, was employed. The results demonstrate high accuracy in flood level prediction, particularly within a 3‐h lead time.

Ajith G. Nair, R. Kiran

ABSTRACT Three clustering algorithms, K‐means clustering analysis (KCA), fuzzy cluster analysis (FCA), and density‐based spatial clustering of applications with noise (DBSCAN), are applied to classify the 13 subbasins of the Mahe River, southwest India, based on 13 morphometric parameters of each. Suitable validation indices, such as Davies–Bouldin and Calinski–Harabasz indices, have been used to select the optimal number of clusters using KCA and FCA techniques. All three analyses have yielded three clusters, with subbasins 3–8 forming the first one. These constitute 23% of the total basin area of the Mahe. SW 12 forms a grouping of its own. The rest, SW 1–2, 9–11, and 13, form the third cluster. The first cluster corresponds to the subbasins identified as most susceptible to flooding. Cluster 3 encompasses the subbasins falling in the “Moderate” and “Least” categories with respect to the risk of flooding. The subbasin 12 (< 1 km2) exhibits a deviant morphometric pattern likely due to its specific topographical and network characteristics. The study reveals that cluster algorithms are effective in ranking and prioritizing subbasins of a river based on their potential for natural hazards like flooding. Moreover, the DBSCAN averts the use of cluster validation indices to determine the optimum clusters without compromising the results. All these methods would be beneficial in chalking out suitable management measures for different subbasins of a river based on their potential for any given hazard.

Hong-wei Fang

Maaz Ashhar, Venkata Reddy Keesara, Venkataramana Sridhar

ABSTRACT Floods are among the most common natural disasters in India, causing significant socio‐economic and environmental impacts. This study focuses on a frequently flooded stretch of the Godavari River in Telangana, India, to analyze the flood event that occurred between 14th July 2022 and 20th July 2022. Sentinel‐1 SAR data from 6th July 2022 to 20th July 2022 were used to perform flood inundation mapping. Various machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Tree (GBT), and Classification and Regression Tree (CART), were employed. The analysis revealed that out of the total study area of 1,556,544 ha, SVM classified 59,823 ha, RF classified 60,088 ha, GBT classified 57,497 ha, and CART classified 58,374 ha as flooded areas. In contrast, Otsu's Thresholding technique identified a significantly larger flooded area of 359,253 ha. For validation, 70 flooded and 30 non‐flooded points were randomly selected from the flood map provided by the National Remote Sensing Center (NRSC). The RF algorithm achieved the best performance, correctly classifying 58 flooded points and 26 non‐flooded points, resulting in an overall accuracy of 84%. The findings highlight the effectiveness of machine learning algorithms, particularly Random Forest, in flood inundation mapping.

J. Hesson, M.L. Schäfer, J.O. Lundström

Floodwater mosquitoes cause extreme nuisance and are the target for mosquito control in several European countries. In Forshaga municipality, western Sweden, high abundance of the floodwater mosquito Aedes sticticus has been reported in past years. This study describes mosquito abundances in Forshaga before and after initiation of mosquito control using VectoBac G®, a larvicide based on the pre-toxins of Bti, administered by helicopter. Adult mosquitoes were collected with CDC-miniature light traps baited with carbon dioxide, and larval counts were performed in flooded areas. Both EU and Swedish national regulations determine when mosquito control can be used, and in 2019 abundance of adult mosquitoes reached the national requirement to initiate mosquito control the following year. In 2020 and 2021, flooding caused by the spring-flood in river Klarälven and rainfall induced hatching of floodwater mosquito larvae. In both years larval abundance reached the requirement to perform a mosquito control action. Both control actions were successful with >97% decrease in larval abundance and <1,000 adult mosquitoes collected per trap-night. The Bti-applications did not affect the abundance of non-floodwater mosquitoes; thus, it controlled the extreme nuisance without impact on mosquito community as a whole.

Rian Dinata, Deva Foster Haroldas Swasto

Abstrak: Proyek pengendalian banjir perkotaan merupakan salah satu upaya mitigasi risiko banjir perkotaan, dan diharapkan dapat mengurangi dampak bencana banjir di perkotaan. Sebagai proyek mitigasi banjir yang tetap memperhatian aspek berkelanjutan; baik secara berkelanjutan dalam pengurangan banjir maupun berkelanjutan pada dataran banjir seperti aspek sosial, ekonomi, lingkungan dan kelembagaan, oleh karena itu mitigasi risiko banjir melalui proyek pengendalian banjir perkotaan tidak hanya tentang mengurangi banjir saja tetapi diharapkan mempertimbangkan dampak proyek pada dataran banjir untuk mencapai proyek mitigasi banjir yang berkelanjutan. Penelitian ini bertujuan untuk mengukur kepuasan masyarakat atas kinerja / dampak proyek pada proyek normalisasi sungai di DAS Bendung Kota Palembang. 22 variabel terkait aspek mitigasi banjir berkelanjutan digunakan untuk mengevaluasi kinerja / dampak proyek dari sudut pandang masyarakat. Analisis kepuasan yang dilakukan dalam penelitian ini menggunakan tiga metode, yaitu metode indeks kepuasan masyarakat (Community satisfaction index), analisis kesenjangan (gap analysis), dan metode analisis kinerja kepentingan (Importance Performance Analysis). Hasil analisis menunjukkan nilai indeks kepuasan pelanggan (CSI) sebesar 69,23%, dan skor rata-rata untuk tingkat kepuasan adalah 3,44 (skala 1-5). Selanjutnya dari metode IPA variabel yang menjadi prioritas utama untuk perbaikan guna meningkatkan kepuasan masyarakat, meliputi 4 variabel kinerja yaitu pemindahan paksa, tempat / peluang rekreasi, partisipasi penduduk setempat, dan pemeliharaan proyek Secara keseluruhan dapat disimpulkan bahwa masyarakat telah puas dengan kinerja proyek.Abstract: The urban flood control project is one of the efforts in urban flood risk mitigation, and is expected to reduce the impact of flood disasters in cities. As sustainable flood mitigation project that involves both sustainable in flood reduction and sustainable on the floodplain such as social, economic, environmental and institutional aspects, therefore flood risk mitigation through urban flood control project is should not about reducing flood only but expected to consider impacts of the project on the floodplain for achieving sustainable flood mitigation project. This study aims to measure community satisfaction on project performance/impacts at river normalization project in Bendung watershed Palembang City. 22 variables related to sustainable flood mitigation aspects are used to evaluate project performance/impacts from points of view of community satisfaction. Analysis carried out in this research using three methods, namely the community satisfaction index (CSI), gap analysis, and importance performance analysis (IPA) method. The analysis results reveal that the customer satisfaction index (CSI) value was 69.23%, and the average score for the level of satisfaction was 3.44 (1-5 scale). Furthermore, from the IPA method, variables which are the main priority to be improved in order to increase community satisfaction, includes 4 performance variables namely; involuntary displacement, recreational place/opportunities, participation of locals, and project maintenance. Overall it can be concluded that community have been satisfied with project performances.

Z. Kundzewicz, Buda Su, Yanjun Wang et al.

Abstract Despite massive flood protection efforts in China, undertaken since the ancient times, disastrous floods continue to plague the country. In this paper, we discuss changes in flood hazard and flood risk in China. First, we review published results (including our own works) on change detection in observed records of intense precipitation, high river flow and flood damage in China. We provide information on essential features of extreme floods in last decades – floods on large rivers, urban floods, and flash floods. Next, we review available projections for the future (including our own results), related to intense precipitation, high river flow and flood damage in China. We try to interpret the difference in flood hazard projections obtained in various publications. Since the spread of river flood hazard projections is large, projections have to be interpreted with caution, because of the impact on decisions related to climate change adaptation, flood risk reduction, and water resources management. We review flood risk reduction strategies in China, focusing on the present situation and division of responsibilities. China has embarked upon an ambitious and vigorous task to improve flood preparedness, by both structural (“hard”) defences, such as: dikes, dams and flood control reservoirs, and diversions, as well as non-structural (“soft”) measures: spatial planning and zoning; watershed management (source control), flood forecasting and warning systems; and awareness raising. The strategy of flood mitigation includes flood retention and urban water management to alleviate the burden of flash and urban flooding.

Juan Velandia, Leonardo Alfonso

Abstract Flood risk management faces challenging decisions to balance between reducing disastrous flood consequences and different societal goals such as development. The inherent complexity and limited data often lead to significant uncertainties in decision‐making, potentially resulting in suboptimal resource allocation. Consequently, there may be value in aiming to reduce uncertainty, minimizing the possibility of selecting deemed efficient decisions because of deficiencies in the current knowledge. To address this, a novel methodology is proposed, integrating Bayesian uncertainty with value of information concepts, commonly employed in healthcare economics. This methodology assesses the implications of current uncertainty and identifies worthwhile sources for resolution prior making decisions. Validation in a synthetic case study and application in a real case (Zapayan wetland in the Magdalena River, Colombia) demonstrate the method's efficacy. Results show that the proposed method can help apprising if the available information is enough to make a decision, or if more information should be obtained. For example, for the synthetic case, resolving the sources of uncertainty with extra information does not significantly improve the expected utility, so a decision could be made based on existing information. For the real case, reducing the uncertainty related to the exposed assets should be targeted first, by an information gathering activity, before deciding.

قباد رستمی زاد, مجتبی پاک پرور, پرویز عبدی نژاد et al.

مقدمه تبخیر و تعرق (ET)، یکی از مهم‌ترین عوامل موثر در چرخه هیدرولوژیکی است و تعیین‌کننده اصلی معادلات انرژی در سطح زمین است. برآورد تبخیر و تعرق برای هیدرولوژی، آبیاری، جنگل و مرتع و مدیریت منابع آب مهم است. تبخیر و تعرق، بیلان آب و انرژی خاک را که عمدتا در مدل‌های گردش عمومی و مدلسازی آب و هوا مورد استفاده قرار می‌گیرد، تحت تاثیر قرار می‌‌دهد. در نتیجه، پیش‌بینی جریان آب رودخانه، پیش‌بینی عملکرد محصول، سامانه‌های مدیریت آبیاری، کیفیت آب رودخانه/دریاچه همگی به سطوح تبخیر و تعرق بستگی دارند. به همین دلیل، برآورد دقیق بیلان آب ضروری است. مدل‌‌های متعددی برای تخمین تبخیر و تعرق با استفاده از روش‌‌های سنجش از دور توسعه یافته است. بررسی تحقیقات اخیر نشان می‌‌دهد که سنجش از دور و استفاده از تصاویر ماهواره‌‌ای توانایی بالایی در تخمین میزان تبخیر و تعرق واقعی دارد. مواد و روش‌‌ها هدف از این پژوهش، واسنجی الگوریتم METRIC در تخمین تبخیر و تعرق دشت سهرین-قره‌‌چریان است که تحت تاثیر پخش سیلاب قرار گرفته است. این روش به‌وسیله بسیاری از محققان در سراسر جهان برای تخمین تبخیر و تعرق استفاده شده است. از سوی دیگر، برآورد تبخیر و تعرق واقعی در دشت‌‌های متاثر از سیلاب، به‌ویژه پخش سیلاب بر آبخوان دشت سهرین- قره‌‌چریان از اهمیت بالایی برخوردار است. لذا، این پژوهش با هدف تخمین تبخیر و تعرق با استفاده از الگوریتم متریک در دشت سهرین-قره‌چریان به منظور مدیریت بهینه منابع آب در منطقه و مناطق با شرایط مشابه انجام شد. در این پژوهش، از داده‌‌های هواشناسی روزانه و ساعتی ایستگاه سینوپتیک فرودگاه زنجان از سال 2020 تا 2021 استفاده شد که این داده‌‌ها شامل کمینه و بیشینه دما، کمینه و بیشینه رطوبت، میانگین سرعت باد، ساعات آفتابی و فشار هوا بود. برای بررسی کاربرد الگوریتم متریک، تصاویر Landsat 8 برای سال آبی 1400–1399 دانلود و پیش‌‌پردازش و پردازش‌‌های لازم بر روی آن‌‌ها انجام شد. تصاویر Landsat در فواصل 16 روزه با وضوح مکانی 30 متر و از سایت سازمان زمین‌‌شناسی ایالات متحده (http://glovis.usgs.gov) به‌دست آمد. پس از پردازش تصاویر، شار خالص تشعشع سطح زمین و شار حرارتی زمین با استفاده از شارهای تشعشعی ورودی-خروجی از آلبدو، گسیل‌‌مندی، دمای سطح زمین و شاخص‌های گیاه به‌دست آمد. سپس، شار حرارتی محسوس با تعیین پیکسل‌‌های سرد و گرم محاسبه و در  آخر، نقشه‌‌های تبخیر و تعرق استخراج شد. نتایج و بحث نتایج نشان داد، با افزایش تراکم پوشش گیاهی، تبخیر و تعرق روزانه نیز افزایش می‌‌یابد. در ابتدای دوره رشد، دامنه تبخیر و تعرق بین 0.08 تا 4.97 میلی‌‌متر در روز تخمین زده شد در حالی که این مقدار در اواسط و اواخر فصل رشد به‌ترتیب در محدوده 0.086 تا 5.56 و 0.59 تا 9.57 میلی‌‌متر در روز تخمین زده شد. بر اساس نتایج، این پژوهش تبخیر و تعرق حاصل از مدل بیلان آب خاک و مدل متریک به‌ترتیب معادل 24115 و 25648 متر مکعب در سال برآورد شد. اعتبارسنجی نتایج مقدار تبخیر و تعرق حاصل از مدل متریک با مقدار تبخیر و تعرق واقعی حاصل از مدل بیلان آب خاک مقایسه شد که ضریب خطا معادل 5.97 درصد به‌دست آمد. نتیجه‌‌گیری با توجه به نتایج این پژوهش، مشخص شد استفاده از مدل‌‌های بیلان انرژی با بهره‌‌گیری از علم سنجش از دور امکان برآورد تبخیر و تعرق را به‌صورت منطقه‌‌ای فراهم می‌‌کند. از طرفی، درصد خطای محاسباتی نشان می‎دهد الگوریتم متریک برای برآورد ET در منطقه مورد مطالعه از دقت لازم برخوردار است.

Hossein Hamidifar, Faezeh Yaghoubi, Pawel M. Rowinski

Abstract Effective management of flood risks requires the prioritization of appropriate flood control solutions. This study aims to prioritize structural flood control options using multi‐criteria decision‐making (MCDM) methods. Four MCDM methods, namely analytic hierarchy process, technique for order preference by similarity to ideal solution, multi‐criteria optimization and compromise solution, and Fuzzy‐VIKOR are employed to assess and rank the flood control options based on multiple criteria. Field surveys, interviews with local authorities and experts, and on‐site assessments of existing flood control structures constituted the primary data collection methods. The findings demonstrate the effectiveness of reservoir dams, retention basins, and levees as viable solutions. Conversely, flood control gates and the no‐project options were assigned lower priorities. The findings highlight the importance of considering multiple MCDM methods to account for variations in rankings. The study provides valuable insights into the decision‐making process for prioritizing flood control options in the study area. These findings can assist policymakers and stakeholders in effectively allocating resources and implementing appropriate structural flood control measures to mitigate flood risks.

Zhiyi Chen, Harshal Maske, Devesh Upadhyay et al.

This paper presents a modeling-control synthesis to address the quality control challenges in multistage manufacturing systems (MMSs). A new feedforward control scheme is developed to minimize the quality variations caused by process disturbances in MMSs. Notably, the control framework leverages a stochastic deep Koopman (SDK) model to capture the quality propagation mechanism in the MMSs, highlighted by its ability to transform the nonlinear propagation dynamics into a linear one. Two roll-to-roll case studies are presented to validate the proposed method and demonstrate its effectiveness. The overall method is suitable for nonlinear MMSs and does not require extensive expert knowledge.

Afreen Islam, Guido Herrmann, Joaquin Carrasco

In this paper, the solvability of the Inverse Optimal Control (IOC) problem based on two existing minimum principal methods, is analysed. The aim of this work is to answer the question regarding what kinds of trajectories, that is depending on the initial conditions of the closed-loop system and system dynamics, of the original optimal control problem, will result in the recovery of the true weights of the reward function for both the soft and the hard-constrained methods [1], [2]. Analytical conditions are provided which allow to verify if a trajectory is sufficiently conditioned, that is, holds sufficient information to recover the true weights of an optimal control problem. It was found that the open-loop system of the original optimal problem has a stronger influence on the solvability of the Inverse Optimal Control problem for the hard-constrained method as compared to the soft-constrained method. These analytical results were validated via simulation.

Antonio Oliva, Jorge Olcina

Historical cartography is one of the principal tools used in correct flood adaptation and management based on territorial planning. In fact, Directive 2007/60/EC on the assessment and management of flood risks includes the analysis and inventory of historical floods in a river basin for assessing the flood hazard and risk existing in a geographical space. This study seeks to analyse the largest flood registered in the Segura basin, occurring on 14–15 October 1879, which attracted enormous interest on a national and international level. The methodology applied is based on the consultation of historical sources and historical cartography, and the elaboration of maps using GIS, enabling comparisons to be made with current flood zones. The results show that the Santa Teresa flood was very similar to the Spanish National Cartographic Systems for Flood Areas (SNCZI) map for a 500-year return period. Furthermore, it allows the identification of the sensitive points along the course of the river or those prone to burst banks or overflowing, which practically coincide with the current maps and modelling conducted by the official bodies. Furthermore, the buildings in the floodable area in the historical cartography have been counted and reconstructed on a GIS map and the SNCZI. Massive anthropic occupation through the construction of settlements and infrastructures (hospitals, schools, centers for the elderly, roads and railways) in the Guadalentín valley and the Segura River increases the risk of flooding in the study area, despite the numerous control and regulation works carried out in the Segura River basin.