Automated modelling of lakes from data and expert knowledge: evaluation of applications

Ecological models of lakes are useful tools for a better understanding of the ecosystem behaviour, lake management, policy making, as well as testing and accepting engineering solutions. Setting such model is a difficult task due to the complexity of these ecosystems. Therefore it is reasonable to use as many approaches as possible to construct a reliable model of the observed domain. In this paper the evaluation of an automated modelling method, called Lagramge, that combines the two basic approaches, i.e. data-driven (inductive) approach and knowledge-driven (deductive) approach, is given. The method supports the introduction of domain knowledge in the procedure of equation discovery from measured data, where the domain modelling knowledge is introduced in a form of modelling knowledge library. Four applications of the method, i.e. Lake Glumsø, Lake Bled, Lake Kasumigaura, and Greifensee, comprise different modelling tasks for Lagramge, each of them resulting in a specific model of the observed domains. The models are evaluated in terms of their descriptive power and their performance (goodness of fit to the measurements). Although faced with some constraints, the method can be successfully used in complex domains. It can be used successfully for model discovery as well as for other scientific discoveries, such as identifying dynamic patterns in the observed system, i.e. dynamic structure of the ecosystem

Preparation and use of the domain expert knowledge for automated modelling of aquatic ecosystems\ud

This thesis is concerned with automated modelling (AM) of aquatic ecosystems. The method used here integrates the two basic principles of modelling, i.e., empirical or data-driven in theoretical or modelling by using the expert background knowledge. The integration of empirical in theoretical modelling is based on the use of the background knowledge in the procedure of model induction from measured data. The theoretical knowledge that guides the process of model induction includes a knowledge library of generalised knowledge from a specific domain in a task specification of the observed system.\ud \ud The thesis is divided into two parts. The first part deals with elaboration of knowledge library in the domain of modelling of aquatic ecosystems. The library includes knowledge about food web modeling by following the mass conservation principle. The knowledge is formalized in terms of (1) taxonomy of variable types, (2) basic processes that govern the behavior of aquatic ecosystems, (3) alternative models of the basic processes, and (4) knowledge how to combine models of individual processes into a model of the entire ecosystem. We evaluated the generality of the knowledge in the library through reconstruction of three wellknown models of different complexity. Thus, we showed that such formalization of the modelling knowledge provides a solid unifying framework for both handcrafting ecological models as well as their automated induction from measured data.\ud \ud In the second part we applied the developed library in the AM method on four real world domains. Using the measurements and the background knowledge we constructed models for each domain. The models were evaluated according to their accuracy and transparency. We tackled the following domains: Lake Glumsoe (Danmark), Lagoon of Venice (Italy), Lake Kasumigaura (Japan), and Lake of Bled (Slovenia). The quality of the models is above all dependant on (1) the knowledge in the library, (2) the quality of the measurements, (3) ecosystem complexity, and (4) the expert knowledge introduced in the induction procedure

Performance Assessment of Wastewater Treatment Plant with Machine Learning Tools

Uređaji za pročišćavanje otpadnih voda (UPOV) s aktivnim muljem su dinamični i složeni sustavi čije se upravljanje može poboljšati primjenom različitih pristupa modeliranju i predviđanja njihova rada. U ovom radu je korišten alat strojnog učenja (modelska stabla) za izradu modela koncentracije kemijske potrošnje kisika (KPK) na izlazu pročišćene otpadne vode iz UPOV-a s aktivnim muljem. Za modeliranje su korišteni mjereni podaci na ulazu i izlazu otpadne vode iz UPOV-a. U izradi modela koncentracije KPK su korišteni programski alat Weka i algoritam za izradu modelskih stabala M5P. Model dobiven alatom strojnog učenja ima veliku opisnu moć i koeficijent korelacije te se zato može primijeniti u modeliranju koncentracije KPK. Time se u ovom radu ukazuje i na prednosti primjene alata strojnog učenja u izradi modela UPOV-a.Wastewater treatment plants (WWTPs) with activated sludge are complex and dynamic systems whose management can be improved by using different modelling and prediction approaches to their work. A machine learning tool for the development of model trees was used in this paper in order to develop a model for chemical oxygen demand (COD) in the wastewater effluent from the WWTP with activated sludge. The data measured in both the influent and the effluent of WWTP were used for modelling. For the COD model the machine learning tool Weka and the algorithm for the development of model trees M5P were used. The obtained model has a high descriptive power and correlation coefficient and thus can be used for modelling purposes. Also, the purpose of this paper is to show the benefits of using machine learning tools for developing WWTP models

Performance Assessment of Wastewater Treatment Plant with Machine Learning Tools

Uređaji za pročišćavanje otpadnih voda (UPOV) s aktivnim muljem su dinamični i složeni sustavi čije se upravljanje može poboljšati primjenom različitih pristupa modeliranju i predviđanja njihova rada. U ovom radu je korišten alat strojnog učenja (modelska stabla) za izradu modela koncentracije kemijske potrošnje kisika (KPK) na izlazu pročišćene otpadne vode iz UPOV-a s aktivnim muljem. Za modeliranje su korišteni mjereni podaci na ulazu i izlazu otpadne vode iz UPOV-a. U izradi modela koncentracije KPK su korišteni programski alat Weka i algoritam za izradu modelskih stabala M5P. Model dobiven alatom strojnog učenja ima veliku opisnu moć i koeficijent korelacije te se zato može primijeniti u modeliranju koncentracije KPK. Time se u ovom radu ukazuje i na prednosti primjene alata strojnog učenja u izradi modela UPOV-a.Wastewater treatment plants (WWTPs) with activated sludge are complex and dynamic systems whose management can be improved by using different modelling and prediction approaches to their work. A machine learning tool for the development of model trees was used in this paper in order to develop a model for chemical oxygen demand (COD) in the wastewater effluent from the WWTP with activated sludge. The data measured in both the influent and the effluent of WWTP were used for modelling. For the COD model the machine learning tool Weka and the algorithm for the development of model trees M5P were used. The obtained model has a high descriptive power and correlation coefficient and thus can be used for modelling purposes. Also, the purpose of this paper is to show the benefits of using machine learning tools for developing WWTP models

Studija utjecaja omjera TIN/PO4 na pojavu cvjetanja mora u sjevernom Jadranu upotrebom regresijskih stabala

The north-western part of the northern Adriatic (NA) exhibits eutrophic to mesotrophic characteristics with recurrent algal blooms and quite unpredictable mucilage events. To contribute to the understanding of the mucilage events in the NA a machine learning algorithm for induction of regression trees was applied on a long-term data-set comprising physical, chemical and biological parameters, measured at six stations on the profile from the Po River delta (Italy) to Rovinj (Croatia). A model describing the connection between the TIN/PO4 ratio, considered as a necessary factor and sometimes even a trigger for mucilage events, and the environmental conditions in NA, was elaborated. The model for TIN/PO4 ratio confirmed the assumption that the mucilage events are connected with this ratio, e.g. mucilage events coincides with its high values. This finding indicates that at certain levels of phosphorus limitation (from TIN/PO4 ratio) mucilage event frequency increases. The model also reveals that salinity and temperature are responsible for the changes of the TIN/PO4 ratio and gives an insight on their threshold values which lead to high values of this ratio, further related to mucilage events.Sjevero-zapadni dio sjevernog Jadrana (SJ) pokazuje eutrofne do mezotrofne karaktaristike sa čestim pojavama cvjetanja algi te prilično nepredvidljivim cvjetanjima mora. Kako bi se doprinjelo razumijevanju cvjetanja mora u SJ upotrijebljen je algoritam strojnog učenja za izradu regresijskih stabala na skupu podataka koji sadrži fizičke, kemijske i biološke parametre mjerene na šest postaja na profile od delte rijeke Po (Italija) do Rovinja (Hrvatska). Upotrebom strojnog učenja izrađen je model koji opisuje vezu između omjera TIN/PO4 koji se smatra neophodnim, a ponekad i glavnim okidačem za pojave cvjetanja mora te ekoloških uvjeta u SJ. Dobiveni model za omjer TIN/PO4 potvrđuje pretpostavku da su pojave cvjetanja mora povezane sa danim omjerom, tj. pojave cvjetanja mora se podudaraju sa visokim vrijednostima tog omjera. Ovo otkriće ukazuje da se na određenim razinama ograničenja fosforom (vidljivo iz omjera TIN/PO4) pojava frekvencije cvjetanja mora povećava. Model također otkriva da su salinitet i temperatura odgovorni za promjene omjera TIN/PO4 te daje uvid u njihove granične vrijednosti koje dovode do visokih vrijednosti ovog omjera, a koji je dalje povezan sa pojavom cvjetanja mora

Implementing nature-based solutions for creating a resourceful circular city

Resource depletion, climate change and degradation of ecosystems are challenges faced by cities worldwide and will increase if cities do not adapt. In order to tackle those challenges, it is necessary to transform our cities into sustainable systems using a holistic approach. One element in achieving this transition is the implementation of nature-based solutions (NBS). NBS can provide a range of ecosystem services beneficial for the urban biosphere such as regulation of micro-climates, flood prevention, water treatment, food provision and more. However, most NBS are implemented serving only one single purpose. Adopting the concept of circular economy by combining different types of services and returning resources to the city, would increase the benefits gained for urban areas. The COST Action Circular City aims to establish a network testing the hypothesis that: ‘A circular flow system that implements NBS for managing nutrients and resources within the urban biosphere will lead to a resilient, sustainable and healthy urban environment’. In this paper we introduce the COST Action Circular City by describing its main objectives and aims. The paper also serves as introduction to the review papers of the Action's five Working Groups in this Special Issue

Towards a Cross-Sectoral View of Nature-Based Solutions for Enabling Circular Cities

A framework developed by the COST Action Circular City (an EU-funded network of 500+ scientists from 40+ countries; COST = Cooperation in Science and Technology) for addressing Urban Circularity Challenges (UCCs) with nature-based solutions (NBSs) was analyzed by various urban sectors which refer to different fields of activities for circular management of resources in cities (i.e., reducing use of resources and production of waste). The urban sectors comprise the built environment, urban water management, resource recovery, and urban farming. We present main findings from sector analyses, discuss different sector perspectives, and show ways to overcome these differences. The results reveal the potential of NBSs to address multiple sectors, as well as multiple UCCs. While water has been identified as a key element when using NBSs in the urban environment, most NBSs are interconnected and also present secondary benefits for other resources. Using representative examples, we discuss how a holistic and systemic approach could facilitate the circular use of resources in cities. Currently, there is often a disciplinary focus on one resource when applying NBSs. The full potential of NBSs to address multifunctionality is, thus, usually not fully accounted for. On the basis of our results, we conclude that experts from various disciplines can engage in a cross-sectoral exchange and identify the full potential of NBSs to recover resources in circular cities and provide secondary benefits to improve the livelihood for locals. This is an important first step toward the full multifunctionality potential enabling of NBSs