Hasil untuk "River, lake, and water-supply engineering (General)"

Mayuranath SureshKumar, Hanumanthrao Kannan

Classic problem-space theory models problem solving as a navigation through a structured space of states, operators, goals, and constraints. Systems Engineering (SE) employs analogous constructs (functional analysis, operational analysis, scenarios, trade studies), yet still lacks a rigorous systems-theoretic representation of the problem space itself. In current practice, reasoning often proceeds directly from stakeholder goals to prescriptive artifacts. This makes foundational assumptions about the operational environment, admissible interactions, and contextual conditions implicit or prematurely embedded in architectures or requirements. This paper addresses that gap by formalizing the problem space as an explicit semantic world model containing theoretical constructs that are defined prior to requirements and solution commitments. These constructs along with the developed axioms, theorems and corollary establish a rigorous criterion for unambiguous boundary semantics, context-dependent interaction traceability to successful stakeholder goal satisfaction, and sufficiency of problem-space specification over which disciplined reasoning can occur independent of solution design. It offers a clear distinction between what is true of the problem domain and what is chosen as a solution. The paper concludes by discussing the significance of the theory on practitioners and provides a dialogue-based hypothetical case study between a stakeholder and an engineer, demonstrating how the theory guides problem framing before designing any prescriptive artifacts.

Maria Kalista Hadia Sabu, Doddi Yudianto, Obaja Triputera Wijaya

Accuracy of rainfall data is very important in hydrological analysis, especially in areas with limited data such as Labuan Bajo City, Indonesia. Global climate data generated from satellite observations and assimilation products, which are freely available, have great potential for use in data scarce areas. However, this data needs to be evaluated to measure its accuracy in rainfall estimates. This research aims to evaluate the accuracy of eight global rainfall data products, namely Global Precipitation Measurement (GPM), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks – Cloud Classification System (PERSIANN-CCS), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Climate Data Record (PERSIANN-CDR), Precipitation Data Integration and Retrieval - Now (PDIR-Now), European Reanalysis for the 5th Generation (ERA5), European Reanalysis for the 5th Generation Land (ERA5-LAND), and Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) at two temporal scales: monthly and 15-daily. Evaluation is carried out using an assessment matrix which includes Root Mean Square Error (RMSE), Nash-Sutcliffe Efficiency (NSE), correlation (r), and Relative Bias (RB). The evaluation results show that on a monthly scale, ERA5, PERSIANN, and GPM provide the best results, with ERA5 being the top. On a 15-daily scale, ERA5 also shows the best performance, followed by GPM and ERA5-LAND. These findings confirm that ERA5 is the main choice for monitoring rainfall in Labuan Bajo City, which is very important for water resource management in areas with limited direct observation data.

GAO Lihua, PAN Hongzhou, HE Yingqing et al.

Quantitative assessment of the impact of marine construction projects on suspended sediment transport and diffusion in estuaries is crucial for flood control, post-project evaluations, and estuarine ecological protection. This paper proposed a technical framework of "remote sensing inversion, path extraction, and phase comparison" and a zonal and block-optimized computational methodology, which accounted for variations in hydrodynamic conditions and differences in suspended sediment diffusion, effectively reducing cross-interference. This paper focused on the Shenzhen-Zhongshan Link as a case study. Using multi-temporal Landsat and Sentinel-2 satellite imagery, the paper employed remote sensing quantitative inversion to retrieve suspended sediment concentration (SSC), and an analysis method based on geometric features of SSC contours was applied to extract information about sediment plumes. In the study area, the suspended sediment diffusion was compressed by the freshwater discharge from the Shiziyang, resulting in a sharp gradient in the concentration isolines at the diffusion boundary. Concurrently, the diffusion exhibited anisotropy under flow action, characterized by downstream-dominated transport and outwardly convex isolines. Based on these characteristics, the plume front position was extracted to determine the diffusion extent. Furthermore, the geometric center of the isolines was computed, and a weighted principal component analysis was employed to derive the principal axis direction, thereby identifying the overall diffusion direction. The spatial extent and direction of suspended sediment diffusion before and after the project's construction were extracted from six satellite images captured at typical tidal levels (covering 2014-2016 pre-construction and 2020-2024 post-construction) along with DEM topographic data from 2011 to 2019. A comparative analysis of the extraction results was conducted. Key findings reveal enhanced southeastward diffusion intensity and expanded plume extent at Hengmen, Hongqimen, and Jiaomen's southern extension, increased diffusion angle south of the project with a south-eastward directional bias, and distinct morphological changes in sediment plume geometry post-construction. Following the completion of the project, a net increase exceeding 12 square kilometers in suspended sediment dispersion area is observed, accompanied by a northward deflection in the dispersion pattern of approximately 23 degrees. This research provides critical technical support for ecological impact assessment and integrated management of major engineering projects in the Pearl River Estuary.

Neha Pandey, Chandrakant Thakur, Nayna Agarwal et al.

Electrochemical reactors play a vital role in scaling up wastewater treatment processes, with efficiency influenced by electrode material, reactor geometry, flow dynamics, power supply, and operational mode. This study investigated the continuous electrocoagulation treatment of paper mill wastewater using a reactor equipped with four aluminum electrodes. The effects of flow rate (0.1–0.6 L/min) and retention time on pollutant removal efficiency were examined. Effluent was continuously fed into the reactor via a peristaltic pump, ensuring controlled inflow and uniform distribution for optimal treatment conditions. Experimental results demonstrated that 80% removal of total dissolved solids, total organic carbon, chemical oxygen demand, and color was achieved under optimal conditions: a pH value of 5.0, a conductivity of 7.59 mS/cm, an electrode gap of 1.38 cm, a current density of 10.72 mA/cm2, a retention time of 120 min, and a flow rate of 0.1 L/min. The sludge generated during treatment was characterized using scanning electron microscopy, energy dispersive X-ray spectroscopy, X-ray diffraction, and Fourier transform infrared spectroscopy to assess its composition and potential for reuse or safe disposal. Additionally, the pollutant removal mechanism using aluminum electrodes was elucidated. This study provides a novel contribution by exploring a continuous-flow electrocoagulation system for pulp and paper mill wastewater treatment, an area with limited prior research, and by integrating detailed sludge characterization to evaluate treatment performance and resource recovery potential. These results underscore the effectiveness of continuous electrocoagulation for treating paper mill effluents, advancing sustainable wastewater management practices.

Kevin Hermann, Sven Peldszus, Jan-Philipp Steghöfer et al.

Software security is of utmost importance for most software systems. Developers must systematically select, plan, design, implement, and especially, maintain and evolve security features -- functionalities to mitigate attacks or protect personal data such as cryptography or access control -- to ensure the security of their software. Although security features are usually available in libraries, integrating security features requires writing and maintaining additional security-critical code. While there have been studies on the use of such libraries, surprisingly little is known about how developers engineer security features, how they select what security features to implement and which ones may require custom implementation, and the implications for maintenance. As a result, we currently rely on assumptions that are largely based on common sense or individual examples. However, to provide them with effective solutions, researchers need hard empirical data to understand what practitioners need and how they view security -- data that we currently lack. To fill this gap, we contribute an exploratory study with 26 knowledgeable industrial participants. We study how security features of software systems are selected and engineered in practice, what their code-level characteristics are, and what challenges practitioners face. Based on the empirical data gathered, we provide insights into engineering practices and validate four common assumptions.

Filipe R. Cogo, Gustavo A. Oliva, Ahmed E. Hassan

The rapid advancement of AI-assisted software engineering has brought transformative potential to the field of software engineering, but existing tools and paradigms remain limited by cognitive overload, inefficient tool integration, and the narrow capabilities of AI copilots. In response, we propose Compiler.next, a novel search-based compiler designed to enable the seamless evolution of AI-native software systems as part of the emerging Software Engineering 3.0 era. Unlike traditional static compilers, Compiler.next takes human-written intents and automatically generates working software by searching for an optimal solution. This process involves dynamic optimization of cognitive architectures and their constituents (e.g., prompts, foundation model configurations, and system parameters) while finding the optimal trade-off between several objectives, such as accuracy, cost, and latency. This paper outlines the architecture of Compiler.next and positions it as a cornerstone in democratizing software development by lowering the technical barrier for non-experts, enabling scalable, adaptable, and reliable AI-powered software. We present a roadmap to address the core challenges in intent compilation, including developing quality programming constructs, effective search heuristics, reproducibility, and interoperability between compilers. Our vision lays the groundwork for fully automated, search-driven software development, fostering faster innovation and more efficient AI-driven systems.

Martin Obaidi, Marc Herrmann, Elisa Schmid et al.

Sentiment analysis is an essential technique for investigating the emotional climate within developer teams, contributing to both team productivity and project success. Existing sentiment analysis tools in software engineering primarily rely on English or non-German gold-standard datasets. To address this gap, our work introduces a German dataset of 5,949 unique developer statements, extracted from the German developer forum Android-Hilfe.de. Each statement was annotated with one of six basic emotions, based on the emotion model by Shaver et al., by four German-speaking computer science students. Evaluation of the annotation process showed high interrater agreement and reliability. These results indicate that the dataset is sufficiently valid and robust to support sentiment analysis in the German-speaking software engineering community. Evaluation with existing German sentiment analysis tools confirms the lack of domain-specific solutions for software engineering. We also discuss approaches to optimize annotation and present further use cases for the dataset.

Paris Avgeriou, Nauman bin Ali, Marcos Kalinowski et al.

Increasingly, courses on Empirical Software Engineering research methods are being offered in higher education institutes across the world, mostly at the M.Sc. and Ph.D. levels. While the need for such courses is evident and in line with modern software engineering curricula, educators designing and implementing such courses have so far been reinventing the wheel; every course is designed from scratch with little to no reuse of ideas or content across the community. Due to the nature of the topic, it is rather difficult to get it right the first time when defining the learning objectives, selecting the material, compiling a reader, and, more importantly, designing relevant and appropriate practical work. This leads to substantial effort (through numerous iterations) and poses risks to the course quality. This chapter attempts to support educators in the first and most crucial step in their course design: creating the syllabus. It does so by consolidating the collective experience of the authors as well as of members of the Empirical Software Engineering community; the latter was mined through two working sessions and an online survey. Specifically, it offers a list of the fundamental building blocks for a syllabus, namely course aims, course topics, and practical assignments. The course topics are also linked to the subsequent chapters of this book, so that readers can dig deeper into those chapters and get support on teaching specific research methods or cross-cutting topics. Finally, we guide educators on how to take these building blocks as a starting point and consider a number of relevant aspects to design a syllabus to meet the needs of their own program, students, and curriculum.

Assiya Ansabayeva, Zhanetta Issayeva, A. Sarsembayeva et al.

One of the key priorities in the development of the country’s agro-industrial complex is the management of pasture resources, with a particular emphasis on their rational use. In Kazakhstan, characterized by its arid climate, there are two main approaches to pasture irrigation. The first relies on open water sources (streams, springs, rivers, and lakes), which can supply only 30–32 million hectares of pastureland (1/5 of the total area). The second involves the extraction and delivery of groundwater to the surface through engineering structures located near settlements. The regulation of pasture use is particularly critical in Zhambyl region, where agricultural land covers more than 4.5 million hectares, 65% of which (2.9 million hectares) are pastures. Notably, over 5,000 agricultural entities in the region possess pastureland but keep no livestock, while most livestock is owned by the rural population, who in turn lack access to pastures. Against this background, this study aimed to develop scientific approaches to the rational use of pasture resources, using the example of remote grazing in the Kordai district of the Zhambyl region. The research was carried out on the land of the Batyr peasant farm. Its pastures are divided into five independent plots located across three geographical zones: foothill-steppe (950 ha), foothill dry steppe (1,370 ha), and foothill semi-desert (1,880 ha), with a total area of 4,200 ha.

Mikhail M. Trofimchuk

Assessment of the biological systems’ state in case of anthropogenic impact is the most important aspect of monitoring of the surface waters’ state and pollution. The state of more than 100 water bodies of the European territory of Russia and Siberia was assessed in various natural and climatic zones with different levels of pollution and different mineralization, as one of the significant environmental factors of natural origin.

Binnur Görer, Fatma Başak Aydemir

Elicitation interviews are the most common requirements elicitation technique, and proficiency in conducting these interviews is crucial for requirements elicitation. Traditional training methods, typically limited to textbook learning, may not sufficiently address the practical complexities of interviewing techniques. Practical training with various interview scenarios is important for understanding how to apply theoretical knowledge in real-world contexts. However, there is a shortage of educational interview material, as creating interview scripts requires both technical expertise and creativity. To address this issue, we develop a specialized GPT agent for auto-generating interview scripts. The GPT agent is equipped with a dedicated knowledge base tailored to the guidelines and best practices of requirements elicitation interview procedures. We employ a prompt chaining approach to mitigate the output length constraint of GPT to be able to generate thorough and detailed interview scripts. This involves dividing the interview into sections and crafting distinct prompts for each, allowing for the generation of complete content for each section. The generated scripts are assessed through standard natural language generation evaluation metrics and an expert judgment study, confirming their applicability in requirements engineering training.

Marvin Wyrich, Justus Bogner

LinkedIn is the largest professional network in the world. As such, it can serve to build bridges between practitioners, whose daily work is software engineering (SE), and researchers, who work to advance the field of software engineering. We know that such a metaphorical bridge exists: SE research findings are sometimes shared on LinkedIn and commented on by software practitioners. Yet, we do not know what state the bridge is in. Therefore, we quantitatively and qualitatively investigate how SE practitioners and researchers approach each other via public LinkedIn discussions and what both sides can contribute to effective science communication. We found that a considerable proportion of LinkedIn posts on SE research are written by people who are not the paper authors (39%). Further, 71% of all comments in our dataset are from people in the industry, but only every second post receives at least one comment at all. Based on our findings, we formulate concrete advice for researchers and practitioners to make sharing new research findings on LinkedIn more fruitful.

Sonja Hyrynsalmi, Ella Peltonen, Fanny Vainionpää et al.

In the extant literature, there has been discussion on the drivers and motivations of minorities to enter the software industry. For example, universities have invested in more diverse imagery for years to attract a more diverse pool of students. However, in our research, we consider whether we understand why students choose their current major and how they did in the beginning decided to apply to study software engineering. We were also interested in learning if there could be some signs that would help us in marketing to get more women into tech. We approached the topic via an online survey (N = 78) sent to the university students of software engineering in Finland. Our results show that, on average, women apply later to software engineering studies than men, with statistically significant differences between genders. Additionally, we found that marketing actions have different impacts based on gender: personal guidance in live events or platforms is most influential for women, whereas teachers and social media have a more significant impact on men. The results also indicate two main paths into the field: the traditional linear educational pathway and the adult career change pathway, each significantly varying by gender

D. S. Yucel, A. Baba

This study focuses on the Koru and Tesbihdere Pb-Zn mining districts, located at the upstream areas of the Umurbey dam basin. Mining activities in Koru, one of the longest operated mines in NW Turkey, date back to the beginning of the 1900s. The purpose of the study is to (1) determine the hydrochemical properties of the water resources and to assess the potential environmental consequences of mining activities in the Koru and Tesbihdere mining districts, and (2) investigate the effects caused by mining activities on the water resources and sediment quality in the Umurbey dam basin. Concentrations of As, Cd, Cu, Fe, Mn, Pb, and Zn in river sediments downstream of the Tesbihdere and Koru mining district, and in the Umurbey dam sediments were higher than the world average for river sediments. The geoaccumulation index and enrichment factor revealed that sediments were strongly polluted with Pb and Zn, moderately to strongly polluted with Cd and moderately polluted with Cu. The chemical analyses of water resources revealed that the maximum Fe, Zn, Pb, Mn, and Cu concentrations reached 2890 μg/l, 1785 μg/l, 1180 μg/l, 984 μg/l, and 419 μg/l, respectively. The Koru River is classifi ed as polluted water according to Turkish inland water quality regulations. The environmental contamination problems in the local drainage system are caused by leakage from past and current tailing ponds into the Koru River. 20 D.S. Yucel, A. Baba basaltic andesite lava, andesitic tuff, rhyodacite and dacitic lava, and tuff. In the upper layers, as well as pyroclastic volcanic rocks, limestone bands are found (Bozkaya and Gokce 2009). This unit is unconformably overlain by Adadagi pyroclastics. Pyroclastic rocks contain agglomerates and tuffs of trachytic, trachyandesitic, dacitic, rhyolitic, and rhyodacitic composition, and andesitic and dacitic lavas containing agglomerates, lapilli stone, and ash tuffs with lava interlayers. Adadagi pyroclastics are exposed in a wide area around the Koru and Tesbihdere mining districts. The corresponding parts of the upper levels of this unit are in the form of layers, silica rich zones, as well as areas with Pb-Zn mineralization and alteration with common brecciation. Adadagi pyroclastics are heavily altered by hydrothermal fl uids; silicifi cation, kaolinization, alunitization, and chloritization are widespread (Bozkaya et al. 2007, Bozkaya and Gokce 2009). Cicek and Oyman (2016) reported that mineralization in Koru and Tesbihdere is commonly observed in the Adadagi pyroclastics, which includes rhyolitic lava-domes and tuffs (Figure 2b). Basalt is the youngest volcanic rock in the form of basaltic lavas and agglomerates, and is represented by the Karaomerler basalt. Karaomerler basalt is composed of basaltic lavas with a hypo-hyaline porphyritic texture, and agglomerate. The basalt unconformably overlies Akcaalan andesite and Adadagi pyroclastics in the northern part of the study area. Alluvium unconformably overlies all the earlier units and is composed of fragments of volcanic and volcano-sedimentary origin, of heterogeneous size, with no diagenesis. Alluvium is generally located along the Koru River. The elevation in the study area has a range of 50–500 m. The Koru and Tesbihdere mining districts have an approximate elevation of 180 m and 370 m above mean sea level, respectively. The Koru and Tesbihdere underground operated mining districts are located at the upstream areas of the Koru River. The Koru River is a tributary of the Umurbey River, which fl ows across the Umurbey plain and eventually fl ows into the Sea of Marmara. Mining activities have caused changes in the hydrology, land cover and land use of mine site. The Koru River is one of the major sources of water for the Umurbey dam. The total length of the Umurbey River is 22 km, the average fl ow rate is 16.777 m3/s, and the river basin area of the Umurbey dam is 279 km2 (Sasi and Berber 2012). Using Pleiades satellite image in December 2016, the dam lake area was calculated to be 1.39 km2. The Umurbey-Koru River confl uence is at a height of 873 m. The Umurbey River has its source in the Dede and Kaplan mountains (Ilgar, 2015). The Umurbey dam is situated along the Umurbey River’s fl ow path. Drinking water for several residential areas is supplied from wells drilled within the fl ood plain of the Umurbey River, including Umurbey village and Lapseki County. The Umurbey dam was established to increase the effi ciency of intensive agriculture in the Umurbey plain area, and to meet the irrigation water requirements of the region. The Umurbey plain is one of the most important areas in Turkey for peach, nectarine, cherry, plum, and apple production. The high quality of the fruit produced provides a large business advantage for both domestic and foreign markets (Ilgar 2015). The water quality in the Umurbey dam and its tributaries is important for providing safe drinking water to the local residents. The aim of this study is to (1) determine the hydrochemical properties of the water resources (the Umurbey dam and its tributaries) and to assess the potential environmental consequences of the mining activities in the Koru and Tesbihdere mining districts and (2) investigate the effects caused by mining activities on the water resources and sediment quality in the Umurbey dam basin. Materials and methods Two water sampling campaigns were conducted (one in the dry season and one in the wet season) to observe seasonal variations. A total of 30 water sampling points from springs, surface water, groundwater, and tailing ponds were selected to determine hydrochemical composition (Figure 3). The discharge rates of springs and surface water were also measured during sampling. Static groundwater levels were measured using an electric sounding device (Eijkelkamp, 30 m) from wells. Groundwater samples were collected using a bailer sampler (Eijkelkamp, 250 ml). Values for pH, temperature and electrical conductivity were recorded by means of a portable multi-parameter fi eld meter (WTW 340i multiparameter). All probes were calibrated at each sampling site before sampling using standard calibrating solutions. Water samples were fi ltered into polyethylene bottles Fig. 1. Location map of Koru and Tesbihdere mine districts and Umurbey dam basin on Google Earth view (December, 2016) Determining water and sediment quality related to lead-zinc mining activity 21 (50 ml*2) using disposable cellulose acetate syringe fi lters of 0.45 μm. Water samples taken for measuring the dissolved phase of metal concentrations were acidifi ed (nitric acid 65% Suprapure®, MERCK, Germany) to pH Fe> Zn> Mn> Pb> Cu> As> Cd, with the following concentration values: Al

M. Bolgov, A. I. Belyaev

The article presents an overview of the main hydrological and water management tasks and problems that have arisen in recent decades on the Lower Volga because of the construction and operation of the Volga-Kama cascade of reservoirs, anthropogenic changes in runoff as a result of economic activity, and the consequences of poorly predictable climatic changes. It is shown that the hydrological regime in the lower reaches of the Volga River has undergone significant changes, both as a result of regulation of runoff by reservoirs and due to climatic changes. The observed changes in flow fluctuations have led to serious changes in the aquatic environment and the entire ecosystem of the river. A number of negative consequences were predicted during the development of reservoir cascade projects, and the construction and operation processes were accompanied by the implementation of a set of compensatory measures of a fisheries’ nature. Nevertheless, the functioning of a complex water management system and insufficient attention to environmental problems led to the emergence of new environmental, technical, and scientific problems that required an integrated approach for their solution, and the effectiveness of the planned measures turned out to be insufficient. The study of the consequences of seasonal regulation of runoff by reservoirs, changes in the estimates of water resources, the involvement of new methods of studying the hydrological system, including multi-arm channels, and the analysis of anthropogenic-altered river sections allowed to obtain new results but at the same time to formulate a block of unresolved scientific problems. Among such problems, there is a need to solve such engineering and hydrological tasks as increasing the feasibility of forecasts of inflow to reservoirs, long-term forecasting of long-term fluctuations in runoff under conditions of ongoing climate change, obtaining up-to-date estimates of negative processes—deformation of riverbeds under anthropogenic impact. The latter is very important for the downstream of the Volgograd Hydroelectric Power Station. In terms of predicting the behavior of the ecosystems of the Lower Volga, with an assessment of their stability, further development of methods for assessing permissible impacts, the development of monitoring systems for their condition is required. The management of the Volga-Kama cascade of reservoirs is a complex scientific and technical task. Today, this management is carried out on the basis of dispatching rules dating back more than a dozen years. It is shown that modern management should be based on a coordinated system of priorities, including environmental criteria. The required optimization formulation of the task of finding optimal cascade control can be based, for example, on the search for a compromise solution at the level of agreement of the parties. A set of environmental and water management problems unsolvable for decades has been formed in the northern part of the Volga-Akhtuba floodplain as well as in the zone of the Western-subtidal ilmens (system of lakes in the Volga River Delta). To solve these problems, new methods of studying ecological systems under severe anthropogenic stress and appropriate engineering approaches that allow a comprehensive approach to achieving sustainable water resources management are considered. The problem of poorly predictable fluctuations in the level of the Caspian Sea and the problem of water resource management in the region in conditions of conflicting interests of users are touched upon. The main measures are discussed, whose implementation will mitigate the consequences of flow regulation for the ecosystem of the Lower Volga. Among the important system principles, the need for a basin approach is noted, which involves, at a minimum, the development of a General Scheme for the Use of Water Resources of the Volga River.

LI Ming

CHEN Xuanxuan, WANG Lina

Water yield is one of the important service functions of the urban ecosystem,and land use change has a certain influence on regional water yield change.Therefore,it is of great significance to analyze the correlation between water yield and land use change.With Guangdong Province as the research object,the influence of land use change on water yield was explored by comprehensively applying tools such as InVEST,ArcGIS,and SPSS.The results showed that from 1980 to 2020,the variation range of the average water yield depth in the whole province was 974~1 375 mm.Spatially,it showed the spatial distribution characteristics of higher water yield in the central cities of Guangdong Province and lower water yield in the northeast and southwest.The increase in urban and rural land areas had a certain positive correlation with the increase in water yield.The increase in the area of cultivated land,forest land,grassland,and water area had a certain negative correlation with the water yield.

Peter Borgen Sørensen, Anders Nielsen

Valid mass load predictions of nutrients, in particular nitrogen (N) and phosphorus (P), are needed for the limnological understanding of single lake ecosystems as well as larger river/lake ecosystems. The mass of N and P that enters a lake will determine the ecological state of the lake, and the mass release from the lake will determine the ecological state of downstream ecosystems. Hence, establishing sound quantifications of the external load is crucial and e.g. contributes to the foundation of assessments of necessary management interventions to improve or preserve the ecological integrity of lakes. The external load of N and P is an integral of several pathways, each having different contributions to the total mass load. Around the world, balances of N and P have been derived for decades to support both lake water quality monitoring and research, but it can be difficult and, thus, costly to make detailed and sufficiently covering measurement campaigns in all tributaries (surface as well as groundwater) in the watershed of the N and P load including seasonality and temporal change from year to year. Thus, load prediction is facing challenge of uncertainty due to unmeasured loads, which can be a consequence of limited resources available for the water flow recordings and water concentration measurements in inlets around the lake, or simply due to invisible water flow taking place through the lake bottom. The lake outlet will typically take place in one single river, so the outlet recording seems easier to measure than inlets, however, the outlet may also have unmeasured parts in cases where water is leaching out though the lake bottom. In this paper, we propose a method that applies incomplete data sets (incomplete in the sense of temporal frequency and percentage of gauged watershed) to generate time series that predict the N and P loads entering and leaving the lake.

Marcel Grote, Justus Bogner

Today, many systems use artificial intelligence (AI) to solve complex problems. While this often increases system effectiveness, developing a production-ready AI-based system is a difficult task. Thus, solid AI engineering practices are required to ensure the quality of the resulting system and to improve the development process. While several practices have already been proposed for the development of AI-based systems, detailed practical experiences of applying these practices are rare. In this paper, we aim to address this gap by collecting such experiences during a case study, namely the development of an autonomous stock trading system that uses machine learning functionality to invest in stocks. We selected 10 AI engineering practices from the literature and systematically applied them during development, with the goal to collect evidence about their applicability and effectiveness. Using structured field notes, we documented our experiences. Furthermore, we also used field notes to document challenges that occurred during the development, and the solutions we applied to overcome them. Afterwards, we analyzed the collected field notes, and evaluated how each practice improved the development. Lastly, we compared our evidence with existing literature. Most applied practices improved our system, albeit to varying extent, and we were able to overcome all major challenges. The qualitative results provide detailed accounts about 10 AI engineering practices, as well as challenges and solutions associated with such a project. Our experiences therefore enrich the emerging body of evidence in this field, which may be especially helpful for practitioner teams new to AI engineering.

Eduardo A. Oliveira, Leon Sterling

This paper describes how motivational models can be used to cross check agile requirements artifacts to improve consistency and completeness of software requirements. Motivational models provide a high level understanding of the purposes of a software system. They complement personas and user stories which focus more on user needs rather than on system features. We present an exploratory case study sought to understand how software engineering students could use motivational models to create better requirements artifacts so they are understandable to non-technical users, easily understood by developers, and are consistent with each other. Nine consistency principles were created as an outcome of our study and are now successfully adopted by software engineering students at the University of Melbourne to ensure consistency between motivational models, personas, and user stories in requirements engineering.