Dam Management Research Articles

A Novel Seepage Behavior Prediction and Lag Process Identification Method for Concrete Dams Using HGWO-XGBoost Model

Seepage monitoring is a vital task in the risk management of concrete dams. Considering the lag effect of input factors, this paper presents a novel seepage monitoring model for concrete dams and proposes an effective identification method of lag process. Firstly, extreme gradient boosting (XGBoost) were adopted to predict the dam seepage. Hybridizing grey wolf optimization (HGWO) which integrates differential evolution (DE) into grey wolf optimization (GWO) and five-fold cross validation were utilized to optimize the hyper-parameters of XGBoost. Secondly, under the same search range and four evaluation indicators, the models optimized respectively by HGWO and three other algorithms were compared to confirm the global optimization capability of HGWO. Six state-of-art methods were also introduced to verify the effectiveness and feasibility of the proposed model. Then, based on the computation method of factor importance in decision tree models, we evaluated the relative importance of each component in the proposed model. Finally, according to the factor importance, the lag process of upstream water level and rainfall was identified, meanwhile a new equivalent water level calculation method is proposed. Monitoring data from three piezometric tubes on a concrete dam were taken as the experimental object. The results show that the improved HGWO has stronger global optimization ability, and the HGWO-XGBoost model achieves satisfactory prediction for seepage in concrete dams. Compared with the traditional trial-and-error method, the lag process computation method proposed in this paper provides a better recognition effect, which is of great value to the seepage monitoring and control of concrete dams.

Risk factor analysis for beef calves requiring assisted vaginal delivery in Great Britain.

Dystocia has serious consequences for both mother and offspring. This study therefore aimed to identify risk factors for dystocia in vaginally delivered spring born beef calves in Great Britain (GB). Information on calving assistance, calf sex, birthweight, breed, twinning, dam parity and body condition score (BCS) was collected from 1131 calves across 84 GB farms. Variables were modelled against calving assistance as a binary response variable. Twins (Odds Ratio [OR] = 5.45), Charolais calves (OR = 3.24), calves from primiparous dams (OR = 5.75) and male calves (OR = 1.75) were at significantly increased risk of requiring calving assistance across all models. Calves born to cows classed as thin (BCS < 2.5/5) were identified in the univariate analysis and in one of the multivariate models (OR = 1.92) as having an increased likelihood of dystocia. Most beef herds have limited scope to manage cows on the basis of fetal gender and number. However, calf breed, dam body condition and management of primiparous dams can be manipulated to reduce the risk of dystocia and improve supervision. Poor body condition is a novel risk factor for dystocia in beef cows and worthy of further investigation.

Utilization of Displacement Monitored by GPS for Safety Management of Rockfill Dams

Utilization of Displacement Monitored by GPS for Safety Management of Rockfill Dams

Mineralogical and Geochemical Characterization of Gold Mining Tailings and Their Potential to Generate Acid Mine Drainage (Minas Gerais, Brazil)

For more than 30 years, sulfide gold ores were treated in metallurgic plants located in Nova Lima, Minas Gerais, Brazil, and accumulated in the Cocoruto tailings dam. Both flotation and leaching tailings from a deactivated circuit, as well as roasted and leaching tailings from an ongoing plant, were studied for their acid mine drainage potential and elements’ mobility. Detailed characterization of both tailings types indicates the presence of fine-grain size material hosting substantial amounts of sulfides that exhibit distinct geochemical and mineralogical characteristics. The samples from the ongoing plant show high grades of Fe in the form of oxides, cyanide, and sulfates. Differently, samples from the old circuit shave higher average concentrations of Al (0.88%), Ca (2.4%), Mg (0.96%), and Mn (0.17%), present as silicates and carbonates. These samples also show relics of preserved sulfides, such as pyrite and pyrrhotite. Concentrations of Zn, Cu, Au, and As are higher in the tailings of the ongoing circuit, while Cr and Hg stand out in the tailings of the deactivated circuit. Although the obtained results show that the sulfide wastes do not tend to generate acid mine drainage, leaching tests indicate the possibility of mobilization of toxic elements, namely As and Mn in the old circuit, and Sb, As, Fe, Ni, and Se in the tailings of the plant that still works. This work highlights the need for proper management and control of tailing dams even in alkaline drainage environments such as the one of the Cocoruto dam. Furthermore, strong knowledge of the tailings’ dynamics in terms of geochemistry and mineralogy would be pivotal to support long-term decisions on wastes management and disposal.

Digital Asset Management: A Lowdown on Intricacies of Digital Rights and Permissions

The adaptability of digital asset management has prevailed enormous businesses and individuals who desire to manage information effectively. The criteria of this paper will revolve around the in-depth intricacies of digital asset management, its functions, significance, and categories of DAM. The introduction of digital rights and permissions aligned with highlighted copyright permission. Initializing from manual asset management and proceeding towards digital asset management, media asset management, and finalizing at massive content management, these terms seem to be striving to explain a unified thing. However, each domain of asset management has separate aspects of managing information. Every organization will opt for its criteria of approach for managing the assets that rely upon the environmental, current cultural, and financial state of the company.

Efficient dam management using SQL and GIS

This paper discusses use of SQL and GIS tools in nowadays dam management. Dam management requires the use of a highly-sophisticated measuring, monitoring and general management tools, since it is not only economical aspect of importance of these projects, but also about the security risks that require the highest possible caution and a precisely-developed control systems. Therefore, SQL and GIS are tools to be considered and implemented. GIS is widely used in spatial planning and connected management processes - because it allows easy way of storage, processing, analysis, modelling and display of spatial data. It has a wide range of features and is used in many areas. Structured Query Language (SQL) is a programming language for databases, written to be easy to understand and to use. SQL provides integration and presentation of data, optimization, easy reporting and analysis. In hand of trained professional analysts, SQL can make database search efficient and flexible, which is the key feature in demanding management processes as dam management).

Can science-informed, consensus-based stakeholder negotiations achieve optimal dam decision outcomes?

Integrating science and decision-making in dam management is needed to address complex tradeoffs among environmental, economic, and social outcomes across varied geographic scales and diverse stakeholder interests. In this study, we introduce an approach that integrates system dynamics modeling (SDM) and role-play simulation (RPS) to facilitate use of the best available knowledge in dam decision-making. Using a hypothetical dam decision context in the New England region of the United States, this research investigates: (1) How do science-informed, negotiated outcomes compare to Pareto-optimal outcomes produced by a scientific model that balance selected system performance tradeoffs?; and (2) How do science-informed, negotiated outcomes compare to the status quo outcome? To our knowledge, this research is the first effort to combine SDM and RPS to support dam decisions and compare science-informed, consensus-based outcomes and optimized system outcomes. Our analyses show Pareto-optimal solutions usually involve a multi-dam management approach with diversified management options. Although all negotiated outcomes produced a net loss compared with at least one of the Pareto-optimal solutions balanced across tradeoffs, some yielded benefits close to or better than specific Pareto-optimal solutions. All negotiated outcomes yielded improvements over the status quo outcome. Our findings highlight the potential for science-informed, stakeholder-engaged approaches to inform decision-making and improve environmental and economic outcomes.

147 Nutritional advances in fetal and neonatal development: Mineral nutrition

Abstract Mineral nutrition during pregnancy has long been known to impact fetal growth and development. This is evidenced by a multitude of mineral deficiency-related causes for embryonic loss, abortion, stillbirth, or neonatal death, including poor or inappropriate fetal development that can be either reversible or irreversible postnatally. Both macro and trace mineral needs of the dam are known to increase with the fetal growth of advancing gestation due to greater metabolic stress and demand, as well as tissue development and deposition in the fetus. Fetal deposition of many trace minerals is especially important for neonatal use while consuming milk with low mineral concentrations and facing a multitude of immune challenges. In the last 2 decades, many laboratories have focused on “developmental programming,” or the effects of maternal nutrition on fetal and neonatal development and ultimately long-term health and productivity of livestock. Despite this, the role of macro and trace minerals in short-and long-term consequences of developmental programming is still unclear for many minerals and species. Taken together, research in ruminants and swine demonstrate that mineral intake and source during pregnancy can have a large effect on fetal growth and development that lasts into the neonatal and pre-weaning periods. Some studies suggest that supra-nutritional mineral intake may have a positive benefit during gestation or neonatal periods. Moreover, some data suggest that mineral requirements may be greater than currently thought to accommodate the rapid fetal growth and preparation for lactation that occurs during late gestation. Continued research is necessary to determine mineral requirements of livestock during pregnancy, especially when considering their long-reaching subsequent effects on offspring. Additionally, increased understanding of perinatal transfer of trace minerals can aid in our management of pregnant dams and their offspring.

Effect of Dam Construction to Land Use and Land Cover Changes Using Remote Sensing: A Case of Hulu Terengganu Hydroelectric Dam

Increase demand of electricity has driven the exploration of Hulu Terengganu hydroelectricity dam as an option to generate electric power supply. Therefore, as a way to monitor the landscape changes, spectral indices were used to study on the spatial-temporal changes over the Hulu Terengganu catchment area. Spectral indices technique was applied on satellite images which acquired on three different years to describe the changes before the construction phase, during the construction phase and post-construction phase. Satellite images used in this study are SPOT-5 and Landsat 7 for year 2006, SPOT-5 and Landsat 8 for year 2014 and Spot-7 and Sentinel 2 for year 2018. Alteration of the land use and land cover has recorded degradation of the forest area by -5.53% during the dam construction phase (2014) and -8.35% during post-construction phase (2018). It also found that water body has remarkable change of 10,141% increase from 2014 to 2018. The result from this study would be useful as an overview for future planning, decision making and dam management activity related to the Hulu Terengganu hydroelectric dam operation

Developing reservoir evaporation predictive model for successful dam management

Evaporation is a primary component of the hydrological cycle, water resources management and forward planning. The succeed management for the dam system is based on the accurate prediction of the reservoir evaporation magnitude. Physical models applied in the prediction of evaporation can encounter obstacles in respect to accurate estimations of evaporation due to the inherent challenges in respect to the mathematical procedure that could fail to address the natural processes and initial conditions that drive the evaporation patterns. To address these limitations, the present study aims to design a new model using the modified Coactive Neuro-Fuzzy Inference System (CANFIS) algorithm to improve feature extraction process in a purely data-driven model. The new approach comprised of the adjustments made to the back-propagation algorithm, allowing the automatic updating of the membership rules and hence, providing the center-weighted set rather than the global weight sets for input-target feature mapping. The predictive ability of the modified CANIFIS model is benchmarked in respect to the conventional ANFIS, SVR and RBF-NN model by statistical performance metrics. To explore its efficiency, the modified CANFIS method is applied for evaporation prediction in two diverse climatic environments. The results revealed the superiority of the modified CANFIS model for evaporation prediction in both Aswan High Dam (AHD) and Timah Tasoh Dam (TTD). The statistical indicators supported the better performance of the modified CANFIS model, which significantly outperforms other proposed models to attain relative error value less than (23% for AHD, 20% for TTD), MAE (12.72 mm month−1 for AHD, 7.63 mm month−1 for TTD), RMSE (15.42 mm month−1 for AHD, 8.53 mm month−1 for TTD) and a relative large coefficient of determination (0.96 for AHD, 0.91 for TTD).

Water Constraints and Flood-Recession Agriculture in the Senegal River Valley

Flood recession farming practiced in flood-prone areas and on the banks of rivers and lakes in arid or semi-arid environments essentially depends on the soil water stock after the flood has receded. During these last few decades, this coveted agriculture is increasingly challenged by severe water constraints, due to increased hydrological hazards and development projects aimed at controlling floods. These challenges are difficult to anticipate, and are the subject of a great deal of uncertainty regarding the sustainability of development projects in the concerned areas. In this study, recent hydraulic data of the Senegal River were analyzed to understand the constraints related to the river management in flood-prone areas. Satellite imagery analysis techniques were used to estimate flooded areas and establish relationships with the river regime. Agricultural practices implemented by farmers were also analyzed to evaluate the resilience of this cropping system to the risk of water stress. The results confirmed many constraints of different importance related to the objectives assigned to the management of dams under multiple water use context. It clearly came out that the water resource management rules relegate flood-recession agriculture to the lowest priorities. In addition, there are safety issues related to unexpected effects of flooding on the water structures and in the nearby inhabited localities of flood-prone areas. Knowing some characteristics of the flooding and of the river’s levels and their relationships can be useful within the framework of an organized climate service that would help farmers and communities to better anticipate constraints.

In search of the good dam: contemporary views on dam planning in Latin America

Dam planning and construction is notoriously difficult. It is highly complex, involving a multitude of social, environmental, economic and technological questions that often become politicised in the process; negative impacts are often concentrated on small, vulnerable groups within society, while the benefits are typically spread in a much more diffuse pattern; it requires changing riverine ecosystems, often irreversibly so; and it takes a very long time, with often harsh consequences if mistakes are made. These challenges have generated decades of debate around dams and development, yet it is not clear how dam planning and management can be improved. To address this question, the present study used Q methodology to analyse the views of social and environmental researchers on dams in Latin America on the principles that should guide dam development. The Q analysis rendered three idealised viewpoints: The first suggested that defending the rights of vulnerable people should be the main priority, as a counterbalance to the natural bias towards economically and politically powerful actors within the political economy of dam construction. The second implied adoption of a holistic and scientific vision towards dam decision-making and a focus of efforts on perfecting formal procedures and participatory processes to build better dams in the future. The third called into question the need for dams altogether and concentrated attention on invisible and overlooked aspects of dam decision-making, particularly past injustices, and the rights of indigenous communities to determine their own model of development. Each viewpoint represents an alternative vision for future dam planning and clarifies the choices available to policy-makers and development actors. Moreover, viewpoints give insights into the motivations of those who seek to inform debates on dams and development. While they were identified in the context of dam-decision making, our findings may also be relevant to other fields of sustainable development.

Improvement of Forecasting Method of Recession Characteristics of River Flow Rate into a Dam by using Estimation of Steady State

This paper describes an application of neural networks for forecasting the flow rate upper district of dams for hydropower plants. The forecasting of recession characteristics of the river flow after rainfalls is important with respect to system operation and dam management. We present a method for improving the precision of forecasting flow rate upper district of dams by utilizing steady-state estimation and recession time constant of the river flow. A case study was carried out on the upper district of the Yahagi River in Central Japan. It is found from our investigations that the forecasting accuracy is improved to 18.6% from 25.8% with a forecasted error of the total amount of river flow by using steady-state estimation.

Environmental Flow Releases for Wetland Biodiversity Conservation in the Amur River Basin

Flow regulation by large dams has transformed the freshwater and floodplain ecosystems of the Middle Amur River basin in Northeast Asia, and negatively impacted the biodiversity and fisheries. This study aimed to develop environmental flow recommendations for the Zeya and Bureya rivers based on past flow rate records. The recommended floodplain inundation by environmental flow releases from the Zeya reservoir are currently impracticable due to technical reasons. Therefore, the importance of preserving the free-flowing tributaries of the Zeya River increases. Future technical improvements for implementing environmental flow releases at the Zeya dam would improve dam management regulation during large floods. The recommendations developed for environmental flow releases from reservoirs on the Bureya River should help to preserve the important Ramsar wetlands which provide habitats for endangered bird species while avoiding flooding of settlements. The results emphasize the importance of considering environmental flow during the early stages of dam planning and the need to enhance the role of environmental flow in water management planning.

Lessons learned during Covid-19 from engineering asset management of dams

Public and private owners of critical infrastructures all over the world are taking high-quality standards to face the consequences of pandemics, particularly critical infrastructure such as dams that needs more attention to maintain and operate during coronavirus disease (Covid-19) pandemics. In this study, critical strategies have been identified through literature review and with the support of experts’ opinions. The rough Decision-making Trial and Evaluation Laboratory and interpretive structural modelling methods were integrated to determine the most important strategies that were identified by literature review and experts’ opinions. Moreover, the methodology was used to find the relationships, cause and effect between the critical strategies. Interviews were completed with professional managers and experts in the field of dam operation and maintenance to help in finding the influence degree between these critical strategies. Among 11 initial strategies, six critical strategies were selected for this study from the experts’ points of view. By applying Matriced Impacts Croisés Multiplication Appliquée á un Classement analysis, driving and dependence powers were also determined and classified for these strategies. The outcomes indicate that the strategy of reviewing emergency action plans and planning for how routine and unplanned work will be implemented during pandemic staffing restrictions is the most driving among these strategies in dam asset management in Canada during pandemics.

Mine tailings as a raw material in alkali activation: A review

The mining industry produces billions of tons of mine tailings annually. However, because of their lack of economic value, most of the tailings are discarded near the mining sites, typically under water. The primary environmental concerns of mine tailings are related to their heavy metal and sulfidic mineral content. Oxidation of sulfidic minerals can produce acid mine drainage that leaches heavy metals into the surrounding water. The management of tailing dams requires expensive construction and careful control, and there is the need for stable, sustainable, and economically viable management technologies. Alkali activation as a solidification/stabilization technology offers an attractive way to deal with mine tailings. Alkali activated materials are hardened, concrete-like structures that can be formed from raw materials that are rich in aluminum and silicon, which fortunately, are the main elements in mining residues. Furthermore, alkali activation can immobilize harmful heavy metals within the structure. This review describes the research on alkali activated mine tailings. The reactivity and chemistry of different minerals are discussed. Since many mine tailings are poorly reactive under alkaline conditions, different pretreatment methods and their effects on the mineralogy are reviewed. Possible applications for these materials are also discussed.

Hydrological Risk Valuation on The Design of Sukamahi Dry Dam, Bogor, West Java

The flooding risk has always been considered as an important factor ofthe risk safety management of dams. The extreme flooding in the downstream of a dam could be either due to dam failure or sometimes without failure. In both cases, they give serious risks to people and property in the downstream of the dam.Sukamahi dry dam at Cisukabirus River is a part of the upper Ciliwung Watershed, located in Bogor regency. Sukamahi dry dam was design for flood reduction purpose especially for the downstream regione.g. Bogor City, Bogor Regency, Depok City and Jakarta. Sukamahi dam has a capacity in flood reduction of 13.53 m3/s with probability exceeded 2 %, and time to concentration (tc) of peak discharge (Qp) at least 4 hours longer than the existing condition. Construction of dry dam might increase the magnitude of flood prone risk especially on the dam breach caused by spillway capacity failure case, although with lower probability. Simulation using HEC RAS 4.1 and an ex-antehydrological risk valuation Xrisk model wereperformed with three scenarios, i.e. normal risk, risk averse and risk takers, with simplified option value and option risk calculation. Risk valuation can be used by decision makers to evaluate the technical and risk feasibility of Sukamahi dry dam construction.

Flood Prediction and Warning System using Dam Data Monitoring

Flood is one of the most devastating natural calamities affecting parts of the state from past few years. The recurring calamity necessitates an efficient early warning system since anticipation and preparedness play a key role in mitigating the impact. Though heavy and erratic rainfall has been marked as one of the main reasons for flood in several places, flood witnessed by various regions of Kerala was the result of sudden opening of reservoirs indicating poor dam management. The unforeseen flow of water often provided less time for evacuation. Prediction thus plays key role in avoiding loss of life and property, followed by such calamities. The vast benefits and potentials offered by Machine Learning makes it the most promising approach. The developed system is a model by taking Malampuzha Dam as reference. Support Vector Machine (SVM) is used as machine learning method for prediction and is programmed in python. The idea has been to create early flood prediction and warning system by monitoring different weather parameters and dam-related data. The feature vectors include current live storage, current reservoir level, rainfall and relative humidity from the period 2016-2019. Based on the analysis of these parameters, the open/closure of shutters of the dam is predicted. Release of shutters has varied impacts in the nearby regions and is measured by succeeding prediction, by mapping regions on grounds of level warning to be issued. Warning is issued through Flask-based server, by identifying vulnerable areas based on flood hazard reference for regions. The dam status prediction model delivered highest prediction accuracy of 99.14% and associated levels of warning has been generated in the development server, thus preventing unexpected release.

Seismic and structural health monitoring of Cabril dam. Software development for informed management

Nowadays, the management and safety control of large dams is generally based on automatic monitoring, including the so-called seismic and structural health monitoring systems (SSHM), using the latest technology for automatic data measurement, acquisition and transmission. These systems should include software for automatic management and analysis of continuous monitoring data and software for numerical simulation of the dam dynamic behavior using 3D finite element models. This software should be designed to provide useful and reliable information to meet the needs and expectations of stakeholders, and to support the studies of researchers and engineers responsible for structural health monitoring. This paper is focused on the experience gathered from the SSHM system of Cabril dam, a 132 m high-arch dam, in Portugal, that has been under continuous dynamic monitoring since 2008. The importance of the software specifically developed for automatic modal identification, automatic detection of seismic vibrations (distinct from vibrations due to the operation of discharge gates and power groups), and automatic comparison between experimental data and computed results from a reference finite element model of the dam-reservoir-foundation system, is highlighted. This software includes: (1) the generation of graphics with the evolution of the identified natural frequencies over time and the comparison with calculated frequencies using different hypothesis for concrete damage evolution; and (2) a service to automatically send emails summarizing key dynamic monitoring results to stakeholders to provide the necessary support for informed management and engineering decision making. The main results from SSHM of Cabril dam are presented, namely regarding the evolution of modal parameter over time, considering the influence of water level variations, and the measured response during an earthquake event.

Climatic and anthropogenic impacts on the decrease of sediment discharge to the Mediterranean coast from the largest river of Maghreb

The current study focuses on the issue of the decrease in sediment discharge to the Mediterranean Sea by the largest river in Algeria, the Wadi Cheliff (i.e. Cheliff River). This study clarifies the effect of climatic and anthropogenic factors on the changes in the sedimentary dynamics of the Cheliff River discharging to the sea. The data used (rainfall, water discharge, and sediment discharge) concern the Sidi Bel Attar gaging station on the Cheliff River, only 18 km from discharge to the Mediterranean Sea. A power-type statistical regression model was used to fill the 74.2% gap in Suspended Solids (SS) measurements in the establishment of a SS database for the period 1951–2012. The study results show that the transport of suspended sediment discharged to the sea is about 487 t/km2/yr. Statistical tests of breaks highlight that rainfall decreased by 26% and that water and sediment input to the sea declined from 74% to 63% for the period of 1981–2012. The correlation analysis shows a decrease in the contribution of rainfall on sediment and water input at the outlet equal to 77.9% and 77.8%, respectively, during the period of 1980–2012, compared to the period of 1968–1980. However, the double mass method reflects the contribution of factors other than rainfall to the decrease of sediment input to the sea. These other factors mainly include large dams, which intercepted about 71% of the total volume of sediment discharged to the sea during the period of 1968–2010. In addition the contribution of large dams to the reduction of sedimentary input to the sea is more important than that of the decrease in rainfall. The management of large dams also contributes to the increase in the sediment deficit to the sea through the prioritization of interception of sediment at the expense of releases, for socio-economic purposes, 68.4% of the Cheliff River discharge is diverted for human use. This has led to an increase in the mean water bed level at bankfull downstream, where the Cheliff River gave up 51% of its width to the floodplain between 1996 and 2009. In the light of the scarcity of sediment transport data in North Africa and in many other areas, the current study provides a reference framework for other studies: providing useful information for the study of the transfer of sediment from land to sea, and the links with the socio-economic needs.