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

HUANG Ziyuan, ZHAO Yinjun, TONG Kai et al.

To explore the trends in sediment variation in the Nanliu River estuary, a two-dimensional hydrodynamic–sediment transport coupled model was established using the MIKE 21 modeling system. Utilizing this model, the spatial distribution of suspended sediment, erosion–deposition alterations, and seabed evolution characteristics in the Nanliu River estuarine region were simulated and analyzed. The modeling method integrates hydrodynamic processes with sediment transport processes, enabling a systematic investigation of sediment movement and morphological response under the combined influence of river discharge and tidal forcing. The simulation results demonstrate the following characteristics of sediment dynamics in the Nanliu River estuary. ① Tidal currents and river runoff jointly govern the distribution of suspended sediment in the estuarine region. Generally, suspended sediment concentrations exhibit a decreasing tendency from the estuary towards the open sea, as well as from the northeast to the southwest. Regions with high suspended sediment concentrations are primarily distributed within the seaward river channel and along the coastal zones. This spatial pattern reflects the influence of upstream sediment supply and hydrodynamic transport along the channel, while sediment concentrations gradually decline as sediment disperses towards offshore areas. ② Regarding erosion and deposition characteristics, the Nanliu River estuary is predominantly characterized by sedimentation overall. Deposition areas are mainly concentrated in narrow channel sections, the downstream reaches of the main channel, and areas adjacent to the estuary mouth. Conversely, mild erosion occurs in the upstream section of the seaward channel and in the near-mouth frontal zone. The offshore area tends towards a state of erosion–deposition equilibrium, with relatively minor net changes in bed elevation. Collectively, these processes lead to a distinct spatial differentiation of erosion and deposition patterns across the estuarine area. ③ The processes of sediment transport and morphological change in the Nanliu River estuary are jointly regulated by river runoff, tidal dynamics, and topographic conditions. Under the combined effects of these factors, sediment movement in the estuary displays a characteristic pattern described as "high upstream input—alternating erosion and deposition at the estuary mouth—erosion-deposition equilibrium in the offshore area." This pattern reflects the role of the estuary as a transitional zone where fluvial sediment input interacts with tidal processes and coastal dynamics. Overall, this study reveals the spatiotemporal differentiation of sediment transport and erosion–deposition changes in the Nanliu River estuary on a monthly scale. The results provide a scientific foundation for comprehending sediment dynamics in the estuarine system and offer valuable references for estuarine ecological environmental management and protection.

Jannes Malanowski

Democracy relies on making collective decisions through voting. In addition, voting procedures have further applications, for example in the training of artificial intelligence. An essential criterion for determining the winner of a fair election is that all alternatives are treated equally: this is called neutrality. The established Ranked Pairs voting method cannot simultaneously guarantee neutrality and be computationally tractable for election with ties. River, the recently introduced voting method, shares desirable properties with Ranked Pairs and has further advantages, such as a new property related to resistance against manipulation. Both Ranked Pairs and River use a weighted margin graph to model the election. Ties in the election can lead to edges of equal margin. To order the edges in such a case, a tiebreaking scheme must be employed. Many tiebreaks violate neutrality or other important properties. A tiebreaking scheme that preserves neutrality is Parallel Universe Tiebreaking (PUT). Ranked Pairs with PUT is NP-hard to compute. The main result of this thesis shows that River with PUT can be computed in polynomial worst-case runtime: We can check whether an alternative is a River PUT winner, by running River with a specially constructed ordering of the edges. To construct this ordering, we introduce the semi-River diagram which contains the edges that can appear in any River diagram for some arbitrary tiebreak. On this diagram we can compute the River winners, by applying a variant of Prims algorithm per alternative. Additionally, we give an algorithm improve the previous naive runtime of River from $\mathcal{O}(n^4)$ to $\mathcal{O}(n^2 \log n)$, where n is the number of alternatives.

Xiangyi Chen, Wenbo Huang, Jiaqi Leng

This study develops a water-level management model for the Great Lakes using a predictive control framework. Requirement 1: Historical data (pre-2019) revealed consistent monthly water-level patterns. A simulated annealing algorithm optimized flow control via the Moses-Saunders Dam and Compensating Works to align levels with multi-year benchmarks. Requirement 2: A Water Level Predictive Control Model (WLPCM) integrated delayed differential equations (DDEs) and model predictive control (MPC) to account for inflow/outflow dynamics and upstream time lags. Natural variables (e.g., precipitation) were modeled via linear regression, while dam flow rates were optimized over 6-month horizons with feedback adjustments for robustness. Requirement 3: Testing WLPCM on 2017 data successfully mitigated Ottawa River flooding, outperforming historical records. Sensitivity analysis via the Sobol method confirmed model resilience to parameter variations. Requirement 4: Ice-clogging was identified as the most impactful natural variable (via RMSE-based sensitivity tests), followed by snowpack and precipitation. Requirement 5: Stakeholder demands (e.g., flood prevention, ecological balance) were incorporated into a fitness function. Compared to Plan 2014, WLPCM reduced catastrophic high levels in Lake Ontario and excessive St. Lawrence River flows by prioritizing long-term optimization. Key innovations include DDE-based predictive regulation, real-time feedback loops, and adaptive control under extreme conditions. The framework balances hydrological dynamics, stakeholder needs, and uncertainty management, offering a scalable solution for large freshwater systems.

Maximilian Zoch, Edward Holmberg, Pujan Pokhrel et al.

This work investigates the feasibility of using Physics-Informed Neural Networks (PINNs) as surrogate models for river stage prediction, aiming to reduce computational cost while maintaining predictive accuracy. Our primary contribution demonstrates that PINNs can successfully approximate HEC-RAS numerical solutions when trained on a single river, achieving strong predictive accuracy with generally low relative errors, though some river segments exhibit higher deviations. By integrating the governing Saint-Venant equations into the learning process, the proposed PINN-based surrogate model enforces physical consistency and significantly improves computational efficiency compared to HEC-RAS. We evaluate the model's performance in terms of accuracy and computational speed, demonstrating that it closely approximates HEC-RAS predictions while enabling real-time inference. These results highlight the potential of PINNs as effective surrogate models for single-river hydrodynamics, offering a promising alternative for computationally efficient river stage forecasting. Future work will explore techniques to enhance PINN training stability and robustness across a more generalized multi-river model.

Georgi Markov, Jon G. Hall, Lucia Rapanotti

Many organisational problems are addressed through systemic change and re-engineering of existing Information Systems rather than radical new design. In the face of widespread IT project failure, devising effective ways to tackle this type of change remains an open challenge. This work discusses the motivation, theoretical foundation, characteristics and evaluation of a novel framework - referred to as POE-$Δ$, which is rooted in design and engineering and is aimed at providing systematic support for representing, structuring and exploring change problems of a socio-technical nature, including implementing their solutions when they exist. We generalise an existing framework of greenfield design as problem solving for application to change problems. From a theoretical perspective,POE-$Δ$ is a strict extension to its parent framework, allowing the seamless integration of greenfield and brownfield design to tackle change problems. A Design Science Research methodology was applied over a decade to define and evaluate POE-$Δ$, with significant case study research conducted to evaluate the framework in its application to real-world change problems of varying criticality and complexity. The results show that POE-$Δ$ exhibits desirable characteristics of a design approach to organisational change and can bring tangible benefits when applied in practice as a holistic and systematic approach to change in socio-technical contexts.

Sebastian Baltes, Florian Angermeir, Chetan Arora et al.

Large Language Models (LLMs) are now ubiquitous in software engineering (SE) research and practice, yet their non-determinism, opaque training data, and rapidly evolving models threaten the reproducibility and replicability of empirical studies. We address this challenge through a collaborative effort of 22 researchers, presenting a taxonomy of seven study types that organizes the landscape of LLM involvement in SE research, together with eight guidelines for designing and reporting such studies. Each guideline distinguishes requirements (must) from recommended practices (should) and is contextualized by the study types it applies to. Our guidelines recommend that researchers: (1) declare LLM usage and role; (2) report model versions, configurations, and customizations; (3) document the tool architecture beyond the model; (4) disclose prompts, their development, and interaction logs; (5) validate LLM outputs with humans; (6) include an open LLM as a baseline; (7) use suitable baselines, benchmarks, and metrics; and (8) articulate limitations and mitigations. We complement the guidelines with an applicability matrix mapping guidelines to study types and a reporting checklist for authors and reviewers. We maintain the study types and guidelines online as a living resource for the community to use and shape (llm-guidelines$.$org).

Oliver Karras

In the last two decades, several researchers provided snapshots of the "current" state and evolution of empirical research in requirements engineering (RE) through literature reviews. However, these literature reviews were not sustainable, as none built on or updated previous works due to the unavailability of the extracted and analyzed data. KG-EmpiRE is a Knowledge Graph (KG) of empirical research in RE based on scientific data extracted from currently 680 papers published in the IEEE International Requirements Engineering Conference (1994-2022). KG-EmpiRE is maintained in the Open Research Knowledge Graph (ORKG), making all data openly and long-term available according to the FAIR data principles. Our long-term goal is to constantly maintain KG-EmpiRE with the research community to synthesize a comprehensive, up-to-date, and long-term available overview of the state and evolution of empirical research in RE. Besides KG-EmpiRE, we provide its analysis with all supplementary materials in a repository. This repository contains all files with instructions for replicating and (re-)using the analysis locally or via executable environments and for repeating the research approach. Since its first release based on 199 papers (2014-2022), KG-EmpiRE and its analysis have been updated twice, currently covering over 650 papers. KG-EmpiRE and its analysis demonstrate how innovative infrastructures, such as the ORKG, can be leveraged to make data from literature reviews FAIR, openly available, and maintainable for the research community in the long term. In this way, we can enable replicable, (re-)usable, and thus sustainable literature reviews to ensure the quality, reliability, and timeliness of their research results.

Mehrdad Sabetzadeh, Chetan Arora

Natural Language Processing (NLP) is now a cornerstone of requirements automation. One compelling factor behind the growing adoption of NLP in Requirements Engineering (RE) is the prevalent use of natural language (NL) for specifying requirements in industry. NLP techniques are commonly used for automatically classifying requirements, extracting important information, e.g., domain models and glossary terms, and performing quality assurance tasks, such as ambiguity handling and completeness checking. With so many different NLP solution strategies available and the possibility of applying machine learning alongside, it can be challenging to choose the right strategy for a specific RE task and to evaluate the resulting solution in an empirically rigorous manner. In this chapter, we present guidelines for the selection of NLP techniques as well as for their evaluation in the context of RE. In particular, we discuss how to choose among different strategies such as traditional NLP, feature-based machine learning, and language-model-based methods. Our ultimate hope for this chapter is to serve as a stepping stone, assisting newcomers to NLP4RE in quickly initiating themselves into the NLP technologies most pertinent to the RE field.

Ali Morshedi

Introduction In determining the evapotranspiration (ET) of a crop species, factors such as type, crop density, growth stage, climate of the region, physicochemical characteristics and soil fertility, have a significant effect. Therefore, it has a significant complexity. In recent years, new technologies are used to estimate ET, such as surface energy balance algorithm for land (SEBAL), which estimates actual evapotranspiration, using satellite data and some ground data. The purpose of this research is to estimate the actual ET and water requirement of Rosa damascena using SEBAL during three crop growth years in a part of the Shahrekord high plain. Materials and Methods The studied farm with an area of 16.38 ha is located in the Shahrekord plain, Karoun watershed. The remote sensing data included 42 cloud-free images of Landsat 7 and Landsat 8 satellites (2017, 2018, and 2019). The growth period lasted from the beginning of April to the end of November of each crop year. Images were processed in ERDAS Imagine 2015 software for radiometric correction and subsequent calculations using SEBAL algorithm. In order to estimate the actual evapotranspiration, the energy balance equation is used. For this purpose, all energy fluxes such as, Rn: the net incoming radiation flux to the considered surface, H: the sensible heat flux, G0: the soil heat flux and lET: the latent heat flux of evapotranspiration should be taken into account. The first step in the SEBAL process is to calculate the net radiation flux of the Rn. The second, soil heat flux G0 that is the rate of heat capacity in the soil and vegetation resulting from heat conduction or heat energy used to heat or cools the volume of the soil mass. The third is to calculate sensible heat flux (H) is the rate of heat loss to the air by conduction and convection phenomena, which is caused by the thermal difference. In SEBAL process, two "anchor" pixels are used to create boundary conditions for energy balance. These include as "cold (wet)" and "warm (dry)" pixels that are determined in the study area. A cold pixel is selected at the surface of open water or the surface covered by a well-watered alfalfa crop. It is assumed that the temperature of the surface and the temperature of the air near the surface are the same in this pixel. The "warm" pixel is selected in dry agricultural lands and its ET is considered zero. It is necessary for SEBAL model to establishing a linear equation between the surface temperature (Ts) and the air-surface temperature difference (dT) for each pixel using hot (dry) and cold (wet) pixels. Results and Discussion Based on the results of three years of research in a 16.38 hectare Golmohammadi farm in the Shahrekord plain, using the Sabal algorithm and the number of 42 images on the days of Landsat 7 and Landsat 8 satellites passing, as well as using the modified Penman-Mantith-Fao mathematical relationship. It was found that the amount of evaporation and transpiration of hollyhocks in the studied area was on average 1043.8 mm during the growth period. According to the results of other researchers, which have been conducted using lysimeter data and field studies, it necessarily requires higher costs than remote sensing methods. In this research, the ability of the Sabal algorithm (as one of the best remote sensing algorithms) to estimate evaporation And the actual transpiration and determination of the water requirement of the chrysanthemum plant with a low cost and an easy method compared to the results of other researchers, which were done with difficult and expensive lysimetric methods, were proved and it is suitable to be used for other plant species and in other geographical areas. Results showed that actual evapotranspiration value of rose crop (ETC) obtained from the SEBAL during the three years of experiment were 1089.4, 1021.3, and 1020.6 mm per growth period. In the same period, reference crop evapotranspiration (ET0) values were 1214.8, 1100.5, and 1135.5 mm during the growth period, respectively. In other words, average value for ETC was 1043.8 mm in growth period. ConclusionBased on the results of three years of research in a 16.38 hectare Golmohammadi farm in the Shahrekord plain, using the Sabal algorithm and the number of 42 images on the days of Landsat 7 and Landsat 8 satellites passing, as well as using the modified Penman-Mantith-Fao mathematical relationship. It was found that the amount of evaporation and transpiration of hollyhocks in the studied area was on average 1043.8 mm during the growth period. According to the results of other researchers, which have been conducted using lysimeter data and field studies, it necessarily requires higher costs than remote sensing methods. In this research, the ability of the Sabal algorithm (as one of the best remote sensing algorithms) to estimate evaporation And the actual transpiration and determination of the water requirement of the chrysanthemum plant with a low cost and an easy method compared to the results of other researchers, which were done with difficult and expensive lysimetric methods, were proved and it is suitable to be used for other plant species and in other geographical areas.

Akosua Kyerewaa Awuah, Sabine Stuart-Hill, Dayle Trotter-Boardman

The uMngeni catchment in KwaZulu-Natal faces numerous challenges that threaten the availability and quality of water resources. To understand the prevalent issues, the purpose of the study was to assess the institutional aspects that may or may not have facilitated Integrated Water Resource Management (IWRM). Twenty-one semi-structured interviews were conducted, and development planning and environmental management tools were analysed. Water User Associations (WUAs) are statutory bodies and have not been established at the local level. Moreover, an operational Catchment Management Agency (CMA) at the regional level is non-existent. Consequently, the implementation of IWRM has been very limited. The establishment of the uMngeni Ecological Infrastructure Partnership (UEIP) has facilitated the integration of role-players in the absence of an operational CMA. Most of the spatial planning and environmental management tools feature water resource planning except for the integrated waste management plans. As a result, poor solid waste management contributes to the poor water quality in the uMngeni catchment. The challenges remaining are the poor implementation of plans due to a lack of human and financial resources. Therefore, the gap created by a non-existent operational CMA means catchment management activities will continue to negatively affect water resources and the degree to which water resource management is integrated. HIGHLIGHTS The uMngeni catchment is a critical water resource area in South Africa and faces numerous challenges.; The institutional landscape is indicative of IWRM; however, lacks key institutions for integrative water management.; Increased coordination and partnership have reduced the gap created by non-existent institutions at the local and regional levels.;

Angeliki Koutsimpela, Michail Loulakis

We consider the stochastic control problem of the shallow lake and continue the work of G. T. Kossioris, Loulakis, and Souganidis (2019) in three directions. First, we generalise the characterisation of the value function as the viscosity solution of a well-posed problem to include more general recycling rates. Then, we prove approximate optimality under bounded controls and we establish quantitative estimates. Finally, we implement a convergent and stable numerical scheme for the computation of the value function to investigate properties of the optimally controlled stochastic shallow lake. This approach permits to derive tail asymptotics for the invariant distribution and to extend results of Grass, Kiseleva, and Wagener (2015) beyond the small noise limit.

G. Mazzolani, F. G. Ciliberti, L. Berardi et al.

Water Supply Systems are essential infrastructures for the socio-economic life of urban cities. To improve their reliability, water utilities undertake several short- and long-term operational tasks based on technical and economic constraints. These activities are motivated by many factors, including increasing leakage rates due to infrastructure aging, increased consumer demands and need for sustainable use of water and energy. European and national regulatory bodies have promoted investment programs for allowing water utilities to reach common standards of reliability and quality of service among countries. Targets of management and operational achievements are usually measured using specific performance indicators. The Italian Regulatory Authority for Energy, Networks and Environment (ARERA) recently introduced the Regulation of the technical performances of water utilities. Performances on leakage management and investment plans of the utilities are thus based on two indicators named M1a (linear leakage index) and M1b (percentage leakage index). This paper analyzes in details the inconsistencies of the percentage leakage index (M1b), mainly due to its mathematical formulation and the ambiguity of defining water consumption as part of the total system inflow. The discussion is supported by a real case study, where both indicators have been calculated to assess their impact on management decisions and investment plans. The inconsistencies of the percentage leakage index are further demonstrated for various layouts of water supply systems.

Hongzhen Ni, Jing Zhao, Xiujian Peng et al.

In response to rapidly growing energy demands, Chinese authorities plan to invest more in hydropower development. However, there are concerns about the possible effects on macroeconomy. This paper uses SinoTERM, a dynamic multi-regional computable general equilibrium model (CGE) of the Chinese economy, to analyze the economic impact of large hydropower development projects. The model features regional labor market dynamics and an electricity subdivision module with substitutability between various types of electricity generation. The results suggest that hydropower development will boost economic growth in the project region. Most sectors in the project region will benefit from the hydropower development such as other services, health, and education, while some sectors will suffer a loss in output because of the substantial increase in real wages. For the national, every 10,000 yuan investment can drive the national GDP growth of 1,000 yuan, and the cost is expected to be recovered in ten years. By the end of 2040, the real national wage will be around 0.16% higher than the baseline scenario. The project could only be justified if net environmental benefits outweigh this loss. HIGHLIGHTS This paper used the SinoTERM model to assess the regional and national economic impacts of a large hydropower development project.; This SinoTERM model is dynamic through labor and capital year-by-year adjustments and accumulation. So this model could simulate long-term costs and benefits associated with dam development.;

Juan-juan Fang, Yun-ping Yang, Meng-lin Jia et al.

Hydrological, sediment, and bathymetric data of the Shashi Reach in the middle Yangtze River for the period of 1975–2018 were collected, and the characteristics of low water level changes and their impacts on utilization of water depth for navigation were investigated. The results showed that, during the study period, the Shashi Reach riverbed was significantly scoured and incised, with cross-sectional profiles showing overall narrowing and deepening. This indicated a strong potential to improve the water depth of the channel. The analysis of the temporal variation of in-channel topographical features showed that the Taipingkou diara underwent siltation and erosion, with its head gradually scoured and relocated downstream after 2008, and the Sanbatan diara continued to shrink and migrate leftwards. Low water levels with the same flow rate over the study period decreased. For instance, from 2003 to 2020, the water level at the Shashi hydrological station decreased to 1.37 m with a flow rate of 6 000 m3/s. Furthermore, the designed minimum navigable water level of the Shashi Reach was approximately 2.11 m lower than the recommended level. In terms of utilization of the channel water depth, continuous scouring of the river channel is expected to result in a reduction in discharge at the Taipingkou mouth, which will improve the water depth conditions of the channel during the dry season in the Shashi Reach. With several channel regulation projects, the 3.5-m depth of the Shashi Reach would basically be unobstructed. This promotes utilization of the shipping route from the Taipingkou south branch to the Sanbatan north branch as the main navigation channel during the dry season. Considering the factors of current water depth and the clear width limitation of the navigation hole at the Jingzhou Yangtze River Bridge, this route can still be favored as the main navigation channel with a 4.5-m depth during the dry season.

Seyed Mohammad Tajbakhsh, Zahra Gohari, Asadollah Mahmoodzadeh Vaziri

Introduction Watershed management projects with different objectives require some kinds of prioritization due to the natural condition prevailing in the watershed, including socio-economic issues, technical and financial constraints. The main purpose of the paper is to provide and apply the concept and techniques of multi-criteria decision-making (MCDM) under a fuzzy environment in the prioritization and selection of projects in portfolio management. In order to priority watershed management practices and evaluate the ecological potential of Ferizi and Rig-Sefid watersheds (Chenaran city, Khorasan Razavi province), the Fuzzy-TOPSIS method has been used as a powerful tool in multi-criteria decision making.Materials and Methods In this study, the preference weights of the criteria were identified using fuzzy AHP. Then, the weights are embraced in fuzzy-TOPSIS to improve the gaps of projects (alternatives) to achieve the organizational objectives as well as interactions between projects. The hybrid Fuzzy-AHP and Fuzzy TOPSIS methods made it more systematic and helpful for the decision maker to choose the best alternative from watershed management practices. In this respect, there are three phases performed in this study, the first phase of data is collected via questionnaire by experts. Next, determining criteria weights via Fuzzy-AHP was the main purpose of the second phase. In the third phase, the output obtained from Fuzzy-AHP with regard to criteria weights is used as input to be applied in fuzzy-TOPSIS for defining the optimal alternative and capturing the complex relationships between the assessment criteria and alternatives.Results and DiscussionThe comparison of the prioritization with the Fuzzy-TOPSIS method in this study and studies in 2010 indicate their similarity to some items, while in the second category priorities, the differences are more than the third and fourth priorities. The results indicate that multi-criteria decision models suggest the best location due to the usage of several criteria quantitatively and qualitatively with respect to objectives. In addition, it can be provided valuable information on prioritizing executive operations for integrated watershed management. It is also revealed that in the Fuzzy-TOPSIS technique, calculating the weights of criteria is essential and they can adjust the rating for other projects. Therefore, Fuzzy-TOPSIS will additionally help to select the optimal management project for the decision-making process.Conclusion It was found that many researchers applied many kinds of MCDM methods to help the decision makers understand and have more concentration on the high rank of criteria and also provide the ranking of the best alternatives in different problems and situations.

Kimbugwe Ceaser, Davis Tim, Goff Fraser et al.

Water, sanitation, and hygiene (WASH) are fundamental human rights, of critical importance to health, education, wellbeing, and economic prosperity. To fulfil these human rights and drive progress towards universal and sustainable access to WASH services, government service-level monitoring processes and data use are vital for effective decision-making and accountability. Despite increasing sector efforts to improve WASH data access, there is limited evidence of this translating into effective data use to inform effective planning for equitable access and budgeting and of the factors affecting this. Four case studies where WaterAid has worked with national government and sector stakeholders to strengthen WASH monitoring processes in Uganda, Cambodia, Papua New Guinea (PNG), and Myanmar were analysed through an analytical framework to understand the impact of different factors and related system-strengthening activities towards outcomes of increased data coordination, timely and relevant data availability and data use to inform decision-making in WASH service delivery. The analysis highlighted that strengthening activities aiming at improving indicators, data collection and analysis, and the type of data collection and visualisation technology have a direct impact on improving WASH sector coordination and timely data availability. However, to ensure strengthening activities support data use for decision-making, they need to be developed from within and adapt to the on-going wider political economy systems evolution, including formal processes such as decentralisation and evolving informal political drivers. HIGHLIGHTS Analysis of factors leading to improvements to WASH data availability and data use.; Indicators, data analysis, data needs mapping, ICT, sector coordination platforms are strategic entry points for strengthening country-led monitoring system.; Approach to strengthening WASH monitoring requires recognition of the wider WASH system and political economy.;

Yixin Li

In this study, a mathematical model is developed for the drought problem of Lake Mead. First, a polynomial fitting of the elevation of Lake Mead to the area of the lake is done by the least-squares method, and the volume of Lake Mead is approximated by the numerical integration of the product of the height and the area solved by the trapezoidal rule. The accuracy of the fitting reached more than 96%at all four different locations. Second, the minimum and maximum water levels were transformed into volume numbers by the above method, and the historical data of Lake Mead were classified into three classes of water resources by sequential clustering. According to these data, the optimal cut point of the most recent drought period was 2008 and has continued until now. Finally, two prediction models were constructed using ARIMA(2,2,2) and ARIMA(3,2,2) to study the water level data from 2008 to 2020 and 2005 to 2020, respectively, to predict the water level data of Lake Mead from 2022 to 2050, and to compare and analyze them.

Hauwa Mohammed Mustafa, Gasim Hayder

The objective of this research was to ascertain the best conditions for efficient applications of water lettuce, giant salvinia and water hyacinth in improving the quality of low strength domestic wastewater. Water quality assessment of the wastewater samples before (influent) and after treatment (effluent) with effect to retention times (6, 12 and 24 h) was analysed. The outcome of the study at 6 h retention showed that water lettuce (6.8–7.0 pH, 50.5% colour, 46.7% biochemical oxygen demand (BOD) and 37.8% chemical oxygen demand (COD)), giant salvinia (6.9–7.1 pH, 40.5% colour, 60% BOD and 43.2% COD) and water hyacinth (6.7–6.9 pH, 45.5% colour, 53% BOD and 35.1% COD) reduction values were achieved. At 12 h retention, water lettuce (6.6–7.0 pH, 57.2% colour, 77.1% BOD and 74.6% COD), giant salvinia (6.4–6.8 pH, 81.1% colour, 66.7% BOD and 72.2% COD) and water hyacinth (6.4–6.7 pH, 61.9% colour, 70% BOD and 61.1% COD) reduction values were achieved. Similarly, for 24 h retention, water lettuce (6.6–7.0 pH, 76.7% colour, 53.2% BOD and 70.3% COD), giant salvinia (6.6–7.0 pH, 91.4% colour, 74.7% BOD and 81.0% COD) and water hyacinth (6.4–6.9 pH, 74% colour, 58% BOD and 67.2% COD) reduction values were achieved. These findings indicated that the retention times of 12 and 24 h provided suitable conditions to break down the organic contaminants present in the shallow ponds. HIGHLIGHTS Determine the ideal conditions for efficient applications of macrophytes in phytoremediation of treated domestic wastewater.; The reduction rate of pollutants progressively increased, as the retention time and sampling period increased.; The developed hydroponic ponds provided simple, cheap, and sustainable technology for tertiary treatment of wastewater within a short time.;

Silverio Martínez-Fernández, Justus Bogner, Xavier Franch et al.

AI-based systems are software systems with functionalities enabled by at least one AI component (e.g., for image- and speech-recognition, and autonomous driving). AI-based systems are becoming pervasive in society due to advances in AI. However, there is limited synthesized knowledge on Software Engineering (SE) approaches for building, operating, and maintaining AI-based systems. To collect and analyze state-of-the-art knowledge about SE for AI-based systems, we conducted a systematic mapping study. We considered 248 studies published between January 2010 and March 2020. SE for AI-based systems is an emerging research area, where more than 2/3 of the studies have been published since 2018. The most studied properties of AI-based systems are dependability and safety. We identified multiple SE approaches for AI-based systems, which we classified according to the SWEBOK areas. Studies related to software testing and software quality are very prevalent, while areas like software maintenance seem neglected. Data-related issues are the most recurrent challenges. Our results are valuable for: researchers, to quickly understand the state of the art and learn which topics need more research; practitioners, to learn about the approaches and challenges that SE entails for AI-based systems; and, educators, to bridge the gap among SE and AI in their curricula.