Karel J Keesman

Wageningen University, Mathematical and Statistical Methods - Biometris, Faculty Member

Wageningen University, Agrotechnology & Food Sciences Group, Faculty Member

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Dr Karel J Keesman has a personal chair at the Mathematical and Statistical Methods group (Biometris), Wageningen University & Research. He was PhD student (Twente University, Enschede) under the supervision of Prof G. van Straten, Prof J.E. Rijnsdorp (Chemical Technology) and Prof H. Kwakernaak, Prof A. Bagchi (Applied Mathematics) from May 1985 - Jan 1989. The title of the PhD thesis was: "Set-membership identification and prediction of ill -defined systems, with application to a water quality system". After completion of the PhD project he became Post-doc at the Process Control Group, Chemical Technology, Twente University. In 1991 he was appointed as Assistant Professor and in 1998 as Associate Professor at the Systems & Control group, Wageningen University. Since 2017 he holds a personal chair.
His main research interests focus on identification, modelling and control of uncertain dynamic systems, such as bioreactors, food storage facilities, biobased economic and environmental systems and the Food-Water-Energy nexus in urban-rural regions with more than 250 papers in international journals and refereed proceedings. In 2011 he published the book, entitled: “System Identification: an Introduction”, Springer Verlag, UK, ISBN: 0857295217.

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Andrej Dujella

University of Zagreb

Hemin Koyi

Uppsala University

Jana Javornik

University of East London

Graham Martin

University of Leicester

Gwen Robbins Schug

University of North Carolina at Greensboro

Gabriel Gutierrez-Alonso

University of Salamanca

John Sutton

Macquarie University

Eros Carvalho

Universidade Federal do Rio Grande do Sul

Kevin Arbuckle

Swansea University

Jesper Hoffmeyer

University of Copenhagen

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Papers by Karel J Keesman

How greenhouse horticulture in arid regions can contribute to climate-resilient and sustainable food security

Global Food Security

Onsite anaerobic treatment of tomato plant waste as a renewable source of energy and biofertilizer under desert conditions

Bioresource Technology Reports

Carbon dynamics and energy recovery in a novel near-zero waste aquaponics system with onsite anaerobic treatment

Science of The Total Environment

Aquaponics is gaining renewed interest to enhance food security. This study aimed to investigate ... more Aquaponics is gaining renewed interest to enhance food security. This study aimed to investigate the performance of a novel off-grid aquaponics system with near-zero water and waste discharge, focusing on the carbon cycle and energy recovery that was achieved by the addition of onsite anaerobic treatment of the solid waste streams. Following a stabilization stage, the system was closely monitored for four months. Fish tank water was recirculated via solid and nitrification reactors, from which 66% was recycled to the fish tank directly and 34% indirectly through the hydroponically grown plants. Fish solid waste was anaerobically treated, energy was recovered, and the nutrient-rich supernatant was recycled to the plants to enhance production. Plant waste was also digested anaerobically for further recovery of energy and nutrients. Fish stocking density was 15.3 and over time reached approximately 40 kg/m3 where it was maintained. Feed (45% protein content) was applied daily at 2% of body weight. Typical fish performance was observed with a survival rate >97% and feed conversion ratio of 1.33. Lettuce production was up to 5.65 kg/m2, significantly higher than previous reports, largely because of high nutrients reuse efficiency from the anaerobic supernatant that contained 130 and 34 mg/L N and P, respectively. Of the feed carbon, 24.5% was taken up by fish biomass. Fish solid wastes contained 38.2% carbon, of which 91.9% was recovered as biogas (74.5% CH4). Biogas production was 0.84 m3/kg for fish sludge and 0.67 m3/kg for dry plant material. CO2 sequestration was 1.4 higher than the feed carbon, which reduced the system's carbon footprint by 64%. This study is the first to demonstrate highly efficient fish and plant production with near-zero water and waste discharge and with energy recovery that can potentially supply the system's energy demand.

Onsite anaerobic treatment of aquaponics lettuce waste: digestion efficiency and nutrient recovery

Aquaculture International, 2020

Aquaponics plant waste, such as the non-edible parts of many vegetable crops, can be a source of ... more Aquaponics plant waste, such as the non-edible parts of many vegetable crops, can be a source of environmental pollution, while its treatment might cause an economic burden. Therefore, efficient use of this waste would be advantageous. This study aimed at investigating anaerobic digestion of aquqponic lettuce waste to recover nutrients and energy through biogas production. A 700 L commercial anaerobic system was used to treat lettuce wastes from an aquaponic farming system that operated under desert climate and steady-state conditions. Digestion efficiency of the lettuce waste was 90.1% by weight, producing a maximum biogas volume of 0.65 m 3 /kg dry weight per day. Biogas composition contained on average 59.2% methane and 38.9% CO 2 with only negligible hydrogen sulfide content. Moreover, the supernatant from the anaerobic digester contained elevated nutrient concentrations (N, P, K, Ca, and Fe), which can potentially be used onsite as a fertilizer. Onsite anaerobic digestion of lettuce plant waste from the aquaponic system under summer desert conditions is demonstrated for the first time to efficiently reduce pollution burden, produce high-quality biogas, and recover nutrients.

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Gebruikershandleiding van het simulatiemodel voor de waterbalans van een met een gewas begroeid oppervlak gekoppeld aan een model voor het oppervlaktewaterbeheer : Swatre (Swatre-Drenthe)

ïS£S££* *t* Ï.Ü* tvo t& \feO' r «v& a ** && ^00* ^S £.ee ST&' atv» V*' .3.^' ia« 1 î,aV-e \ i^ :v... more ïS£S££* *t* Ï.Ü* tvo t& \feO' r «v& a ** && ^00* ^S £.ee ST&' atv» V*' .3.^' ia« 1 î,aV-e \ i^ :v*' ,tf> e<v Vve^ Itv' .©tV tvi 1 !& ot^cr etv *»::**«?: * e ^r^* u " .*&**sift* .ü* '<#.#&£•• t e^ \v^ ItvS f^ -0> et vo' o* iet-\>v± nor. ,.yv3 \M 't ILLISTRATIEF VOORBEELD VAN COMMANDO-PROCEDURE TBV. HET DOORREKENEN VAN MEERDERE PEILBEHËERSINGSALTERNATIEVEN OVER MEERDERE JAREN MBV. HET COMPUTERPROGRAMMA SUADRE C0DE=0 HS IS KEPT AT PHASE(O) C0DE=1 ONLY CONSERVATION C0DE=2 CONSERVATION AND WATER SUPPLYi ACAP=0.075 MM/D C0DE=3 CONSERVATION AND WATER SUPPLY» ACAP=0.150 MM/D C0DE=4 CONSERVATION AND WATER SUPPLY» ACAP=0.250 MM/D C0DE=5 CONSERVATION» WATER SUPPLY (ACAP=0.250 HM/D) AND SPRINKLER IRRIGATION ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ * CODE * 1 * CROP t*= POT * NEXT! $ JRST = 1982 * JREND = 1983 * JAAR = JRST * CREATE OUTPUT.DAT * COPY INVOER'CODE'.'CROP' INPUT.DAT * COPY BODEM.'CROP' HN21.DAT * COPY GWLB.DAT GWLA.DAT •! **** METEO-FILES EELDE19**.DAT AT SUBDIRECTORY C.METE03 **** * NAME := C.METE03EELDE * TYPE := .DAT * LOOP: * COPY 'NAME''JAAR "TYPE' METE0.DAT * RUN SWADRE t JAAR = JAAR + 1 * IF JAAR .LE, JREND THEN GOTO LOOP * REN OUTPUT.DAT UITVOER'CODE'.'CROP' * REN PROUT.DAT TABUITVR'CODE'.'CROP' $ CODE = CODE + 1 * IF CODE .LE. 2 THEN GOTO NEXT $ EXIT Hierin bevatten INVOER1.POT en INVOER2.POT de plaatsafhankelijke invoergegevens. De file BODEM.POT bevat de bodemkarakteristieke informatie, GWLB.DAT de initiële grondwaterstand en EELDE1982.DAT de meteorologische gegevens uit 1982 van het meteo-station Eelde.

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Proceedings of the 67th European Study Group Mathematics with Industry, Wageningen, The Netherlands, 26-30 January, 2009

Rolling of a ship is a swinging motion around its length axis. In particular vessels transporting... more Rolling of a ship is a swinging motion around its length axis. In particular vessels transporting containers may show large amplitude roll when sailing in seas with large head waves. The dynamics of the ship is such that rolling interacts with heave being the motion of the mass point of the ship in vertical direction. Due to the shape of the hull of the vessel its heave is influenced considerably by the phase of the wave as it passes the ship. The interaction of heave and roll can be modeled by a mass-spring-pendulum system. The effect of waves is then included in the system by a periodic forcing term. In first instance the damping of the spring can be taken infinitely large making the system a pendulum with an in vertical direction periodically moving suspension. For a small angular deflection the roll motion is then described by the Mathieu equation containing a periodic forcing. If the period of the solution of the equation without forcing is about twice the period of the forcing then the oscillation gets unstable and the amplitude starts to grow. After describing this model we turn to situation that the ship is not anymore statically fixed at the fluctuating water level. It may move up and down showing a motion modeled by a damped spring. One step further we also allow for pitch, a swinging motion around a horizontal axis perpendicular to the ship. It is recommended to investigate the way waves may directly drive this mode and to determine the amount of energy that flows along this path towards the roll mode. Since at sea waves are a superposition of waves with different wavelengths, we also pay attention to the properties of such a type of forcing containing stochastic elements. It is recommended that as a measure for the occurrence of large deflections of the roll angle one should take the expected time for which a given large deflection may occur instead of the mean amplitude of the deflection.

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Modeling and Control of Flows

Switching control for post-harvest food storage

Uncertainty propagation and speculation in projective forecasts of environmental change: A lake-eutrophication example

Journal of Forecasting, 1991

The issue of whether models developed for current conditions can yield correct predictions when u... more The issue of whether models developed for current conditions can yield correct predictions when used under changed control, as is often the case in environmental management, is discussed. Two models of different complexity are compared on the basis of performance criteria, but it appears that good performance at the calibration stage does not guarantee correctly predicted behavior. A requirement for the detection of such a failure of the model is that the prediction uncertainty range is known. Two techniques to calculate uncertainty propagation are presented and compared: a stochastic first‐order error propagation based on the extended Kalman filter (EKF), and a newly developed and robust Monte Carlo set‐membership procedure (MCSM). The procedures are applied to a case study of water quality, generating a projective forecast of the algal dynamics in a lake (Lake Veluwe) in response to management actions that force the system into a different mode of behavior. It is found that the forecast from the more complex model falls within the prediction uncertainty range, but its informative value is low due to large uncertainty bounds. As a substitute for time‐consuming revisions of the model, educated speculation about parameter shifts is offered as an alternative approach to account for expected but unmodelled changes in the system.

Modelling and control in agriculture, horticulture and post-harvest processing (Agricontrol 2000) : a proceedings volume from the 1st IFAC International Conference, Wageningen, The Netherlands, 10-12 July 2000

Published for the International Federation of Automatic Control by Pergamon eBooks, 2001

Section Headings. Agricultural production technology and robotics. Animal production. Protected c... more

Concise encyclopedia of environmental systems

Automatica, Feb 1, 1996

Optimal input design for model discrimination

IFAC Proceedings Volumes, Jul 1, 2012

The paper presents a methodology for an optimal input design for model discrimination. To allow a... more The paper presents a methodology for an optimal input design for model discrimination. To allow analytical solutions, the method, using Pontryagin's maximum principle, is developed for non-linear single-state systems that are affine in their joint input. The method is demonstrated on a fed-batch reactor case study with first-order and Monod kinetics.

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Uncertainty analysis of agroforestry models

HAL (Le Centre pour la Communication Scientifique Directe), Jun 27, 2004

International audienceModels for productivity and resource use in agroforestry systems are needed... more International audienceModels for productivity and resource use in agroforestry systems are needed for land use explorations and support of management decisions by farmers and policy makers in European agriculture. Alternative or complementary avenues for building predictive models are available, ranging from parameter-sparse models, containing not more than some dozens of parameters and only few dynamic equations, to parameter-rich models with hundreds of parameters, based on detailed descriptions of ecophysiological processes and covering many pages of code. The strength of parameter-sparse models lies in their transparency and amenability to mathematical techniques for reduction of uncertainty and improvement of predictive capacity. The strength of parameter-rich models is their biological realism and suitability for studying intricate trade-offs in agroforestry systems at short temporal and detailed spatial scales. In both classes of models, problems are faced in parameterization and the containment of uncertainties in model predictions. Parameter-sparse models require long-term data sets for model calibration and evaluation of uncertainty. Such data sets are rare. Parameter-rich models contain many parameters that do not have a significant impact on long-term model predictions; moreover, they are cumbersome to develop and maintain, understand and document. This presentation will focus on how these problems are being dealt with in a European-wide research project aiming at evaluation of possibilities of agroforestry systems as a rediscovered component of sustainable land use in Europe

Set-membership approach to identification and prediction of lake eutrophication

Water Resources Research, 1990

Generally, ecosystems modeling is obstructed by the problem of sparse and unreliable data, and la... more Generally, ecosystems modeling is obstructed by the problem of sparse and unreliable data, and lack of knowledge about processes dominating the system. Under these circumstances, set theoretic uncertainty models are an appropriate alternative to probabilistic models. The only requirement is that the uncertainty is pointwise bounded. A newly developed set membership identification procedure is presented and demonstrated by an application to the modeling of shallow lake eutrophication. First, a set of parameter vectors is identified. Analysis of the set reveals a dominant direction spanned by four algal growth and death parameters. Second, on the basis of additional fuzzy set theoretic assumptions, a formal min-max estimation is performed to obtain information about the model validity. If the model appears to be (partially) invalid, the degree of invalidity, affecting the model prediction uncertainty, can be represented by an estimate of the model structure error in addition to the uncertainty contained in the identified set of parameter vectors. INTRODUCTION An important problem in lake water quality management is eutrophication. Due to excessive nutrient loadings from point sources (sewage plants, inlets, and so forth) and nonpoint sources (from agriculture), algae blooms occur in spring and summer. From the viewpoint of recreation, fisheries, and drinking water supply, these blooms must be prevented. Lake Veluwe, created in 1956/1957 during the reclamation of Eastern Flevoland in the Netherlands, is an example of a lake that has suffered from excessive algae blooms since 1970. The restoration of the lake started in 1972, when phosphates were removed from the effluent of one of the sewage plants. This pollution control activity aimed at diminishing the external phosphorous load. In addition, since 1979 phosphorus-poor and calcium-rich water from the polder was used to flush the lake during the winter periods. Without mathematical modeling, it is virtually impossible to predict the effects of this kind of human interference in a system. In model building, a balance must be found between the complexity needed to mimic the systems behavior and the practical requirement of identifiability [Beck, 1981]. Only relatively simple models can be calibrated by formal parameter estimation against field data. The calibration process should not merely result in "optimal" parameter estimates, but also in an analysis of the associated residuals in order to obtain information on model validity. In addition, it is also desirable to properly identify the uncertainty in parameter estimates and model structure from the field data. Uncertainties are of major importance in model predictions, because predicting effects just from a single trajectory associated with an "optimal" parameter vector can be quite misleading. Even when the model and the associated uncertainties are identified from the data, the results will still contain some subjective elements. Against this background, Fedra et al. [1981] proposed a method (based on the work of Spear and Hornberger [1980]) that explicitly takes into account the

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Optimal control of N-removal in ASPs

Water Science and Technology, Aug 1, 1998

Optimisation of the operation strategy of N•removing activated sludge processes (ASPs) contribute... more Optimisation of the operation strategy of N•removing activated sludge processes (ASPs) contributes to improved effluent quality and/or costll savings. Thispaper deals with the development of an aeration strategy yielding optimal N-removal in continuously mixed, continuously fed ASPs. First, optimal control theory is applied to the generally accepted ASM DO. I model (Henze et al., 1987). This study reveals that, from an Nremoval point of view, both alternating nittificationldenitrificatioD and simultaneous nitrificationldenittification at limiting DO-levels might be optimal, depending on the uncertain oxygen half• saturation constants of autotrophic and heterotrophic biomass. Hence, taking into consideration the risk of sludge bulking at limiting Do-Ievels, an alternating anoxic/aerobic strategy is favoured. A Receding Horizon Optimal Control (RHOC) strategy using NH. and NO, measurements is developed, enabling feedback control of the alternation between anoxic and aerobic phases with the explicit objective of optimal Nremoval. Simple rules are given for straightforward tuning of this controller. The controller successfully passed several tests both in simulation and in application to a pilot plant continuously fed with presettled domestic wastewater.

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Integrated Hydroponics Systems with Anaerobic Supernatant and Aquaculture Effluent in Desert Regions: Nutrient Recovery and Benefit Analysis

Sensor data fusion in electrochemical applications: An overview and its application to electrochlorination monitoring

Computers & Chemical Engineering

Removal of small elemental sulfur particles by polysulfide formation in a sulfidic reactor

Water Research

Clean and Safe Drinking Water Systems via Metagenomics Data and Artificial Intelligence: State-of-the-Art and Future Perspective

Frontiers in Microbiology

The use of next-generation sequencing technologies in drinking water distribution systems (DWDS) ... more The use of next-generation sequencing technologies in drinking water distribution systems (DWDS) has shed insight into the microbial communities’ composition, and interaction in the drinking water microbiome. For the past two decades, various studies have been conducted in which metagenomics data have been collected over extended periods and analyzed spatially and temporally to understand the dynamics of microbial communities in DWDS. In this literature review, we outline the findings which were reported in the literature on what kind of occupancy-abundance patterns are exhibited in the drinking water microbiome, how the drinking water microbiome dynamically evolves spatially and temporally in the distribution networks, how different microbial communities co-exist, and what kind of clusters exist in the drinking water ecosystem. While data analysis in the current literature concerns mainly with confirmatory and exploratory questions pertaining to the use of metagenomics data for the...

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Assessing the flexibility potential of the residential load in smart electricity grids — A data-driven approach

2017 14th International Conference on the European Energy Market (EEM), 2017

This paper proposes a framework for assessing the sensitivity of the performance of a hypothetica... more This paper proposes a framework for assessing the sensitivity of the performance of a hypothetical demand response (DR) program to consumers' preferences, should they enable DR and become prosumers. The proposed framework contains a data analytics module and a DR simulation module. The data analytics module, processes the historical data to select informative subsets and define simulation scenarios to investigate the performance of the DR module. The DR module is, in essence, an optimization problem that seeks to meet the objective of the distribution system operator (DSO); it minimizes active power losses, by utilizing the potential flexibility prosumers can provide. The optimization problem is solved subject to physical and economic constraints. It considers the fact that cost of energy for the prosumers, after implementing DR, remains less than or equal to its value before that. We defined six scenarios to investigate the sensitivity of the performance of DR on prosumers pref...

How greenhouse horticulture in arid regions can contribute to climate-resilient and sustainable food security

Global Food Security

Onsite anaerobic treatment of tomato plant waste as a renewable source of energy and biofertilizer under desert conditions

Bioresource Technology Reports

Carbon dynamics and energy recovery in a novel near-zero waste aquaponics system with onsite anaerobic treatment

Science of The Total Environment