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Item Open Access Developments and applications of electromagnetic tomography in process engineering(Elsevier Ltd., 2024-08) Sharifi, M; Fourie, J; Heffernan, B; Young, BIn the processing industry, monitoring, control, development and optimization are major performance improving activities. In this industry multiphase mixtures flow within enclosed domains such as process vessels or pipelines, with sometimes complex and harsh process conditions, such as high standards of hygiene or high temperatures and pressures, and require to be monitored and analysed for the purpose of continuous improvements in process control. Electromagnetic Tomography (EMT) is a promising tomographic technique which employs contactless non-invasive inductive sensing coils to evaluate the passive electromagnetic properties of what exists within a sensing domain. Although the potential applications of EMT are widespread throughout various industries such as the medical, environmental, geological and mining industries, this paper focuses on evaluating research focused on applications of this promising technique to the processing arena, with the purpose of identifying research gaps for future evaluation. Research in this area has been divided into two groups based on their purpose: developments in the technique with the purpose of enhancing its capabilities, and exploring the technique's various applications. As one of the more recent tomography techniques, EMT still has a lot of potential remaining to be discovered which would come about with further advancements in its hardware, i.e., sensor unit and excitation unit, and also with improvements in the data processing unit, i.e., data reconstruction. Combining different modalities, which would expand the capabilities of the resulting unit, is an interesting area with high potential, requiring further exploration. EMT remains to be studied in the future on countless other processes, unit operations and media and for several objectives. The application of EMT to other areas such as Food, Dairy, Pulp and paper processes also remain to be developed.Item Open Access Active-distributed temperature sensing dataset beneath a braided river(Elsevier Inc., 2023-12) Sai Louie, AJ; Morgan, LK; Banks, EW; Dempsey, D; Wilson, SBraided rivers play a significant role in replenishing groundwater, but our understanding of how these recharge rates fluctuate over time remains limited. Traditional techniques for gauging groundwater recharge are ineffective for studying complex braided river systems due to their insufficient spatiotemporal resolution. To address this gap, active-distributed temperature sensing (A-DTS) was used. This method combines fiber optic temperature measurements with an active heat source, enabling quantification of groundwater fluxes. In this study, twelve consecutive A-DTS surveys were conducted on a 100 m long hybrid fiber optic cable to a depth of 5 m beneath the Waikirikiri Selwyn River. This experiment was conducted during a period of relatively stable river stage and flow, highlighting the effectiveness of using A-DTS to measure temporal changes in groundwater recharge.Item Open Access Conceptualising surface water-groundwater exchange in braided river systems(Copernicus Publications on behalf of the European Geosciences Union, 2024) Wilson, Scott R; Hoyle, Jo; Measures, Richard; Di Ciacca, Antoine; Morgan, Leanne K; Banks, Eddie W; Robb, Linda; Wöehling, ThomasBraided rivers can provide substantial recharge to regional aquifers, with flow exchange between surface water and groundwater occurring at a range of spatial and temporal scales. However, the difficulty in measuring and modelling these complex and dynamic river systems has hampered process understanding and the upscaling necessary to quantify these fluxes. This is due to an incomplete understanding of the hydrogeological structures that control river–groundwater exchange. In this paper, we present a new conceptualisation of subsurface processes in braided rivers based on observations of the main losing reaches of three braided rivers in Aotearoa / New Zealand. The conceptual model is based on a range of data, including lidar, bathymetry, coring, particle size distribution, groundwater level and temperature monitoring, radon-222, electrical-resistivity tomography and fibre-optic cables. The combined results indicate that sediments within the recently active river braidplain are distinctive, with sediments that are poorly consolidated and better sorted compared with adjacent deposits from the historical braidplain that become successively consolidated and intermixed with flood silt deposits due to overbank flow. A distinct sedimentary unconformity, combined with the presence of geomorphologically distinct lateral boundaries, suggests that a “braidplain aquifer” forms within the active river braidplain through the process of sediment mobilisation during flood events. This braidplain aquifer concept introduces a shallow storage reservoir to the river system, which is distinct from the regional aquifer system, and mediates the exchange of flow between individual river channels and the regional aquifer. The implication of the new concept is that surface water–groundwater exchange occurs at two spatial scales: the first is hyporheic and parafluvial exchange between the river and braidplain aquifer; the second is exchange between the braidplain aquifer and regional aquifer system. Exchange at both scales is influenced by the state of hydraulic connection between the respective water bodies. This conceptualisation acknowledges braided rivers as whole “river systems”, consisting of channels and a gravel aquifer reservoir. This work has important implications for understanding how changes in river management (e.g. surface water extraction, bank training and gravel extraction) and morphology may impact groundwater recharge (and potentially flow, temperature attenuation and ecological resilience) under dry conditions.Item Open Access Electrochemical oxidation of low-concentration methane on Pt/Pt and Pt/CP under ambient conditions(American Chemical Society, 2024-11) Wu, T; Rankin, DM; Golovko, VBMethane is a potent greenhouse gas, and its rapid conversion at low concentrations under ambient conditions is a challenging process where combustion is not an option. Herein, we report an electrochemical method to address this problem. It was achieved by applying an oxidation potential to electrochemically activate methane followed by conducting an anodic cyclic voltammogram to fully oxidize activated methane to carbon dioxide on platinized Pt mesh (Pt/Pt) and carbon paper (Pt/CP). This “dynamic potential” oxidation approach enabled methane conversion with low energy consumption, thanks to the low activation potential. Effects of various experimental conditions (applied potential, reaction time, and methane concentration) were investigated. Pure methane and methane/nitrogen gas mixtures containing a series of low concentrations of methane were tested. It was found that methane conversion is independent of its concentration on both Pt/Pt and Pt/CP. Compared to Pt/Pt electrocatalysis, Pt/CP displayed approximately 10 times higher catalytic activity, which can be attributed to the stronger binding of intermediate CO* to Pt, leading to easier CO* activation in the presence of a carbon substrate. Carbon dioxide was the only compound detected during the electro-oxidation phase for Pt/Pt, while for Pt/CP, carbon dioxide and a small amount of formic acid (after 15 h reaction) were observed. Electrocatalytic conversion of methane to carbon dioxide on Pt/CP using 0.5% methane was measured, giving a methane conversion rate of 7.5 × 10¯⁸ mol L¯¹ s¯¹ m¯², while the methane conversion rate on Pt/Pt with 1% methane was only 8.3 × 10¯⁹ mol L¯¹s¯¹ m¯².Item Open Access Characterising the decay of organic metal complexes in speleothem-forming cave waters(Elsevier B.V., 2024-05-15) Höpker, SN; Breitenbach, SFM; Grainger, M; Stirling, CH; Hartland, AOrganic metal complexes (OMCs) transport trace metals (e.g., Co, Ni, Cu) from surface soils, via the unsaturated zone, to sites of cave carbonate (speleothem) formation. OMCs clearly imprint on speleothem trace element chemistry, but the role of kinetic factors in the signal transfer process has yet to be elucidated. We investigated whether OMCs may viably link metal concentrations in stalagmites and local hydrology (i.e., drip rate), via their time-sensitive dissociation (or ‘decay’) in the speleothem water thin-film. We performed competitive ligand exchange experiments using water and soil samples from eight geographically diverse Aotearoa New Zealand caves, providing a first comparative characterisation of speleothem-specific OMC kinetics. Critically, this approach corroborated that NOM ligands limit transition metal availability at the dripwater-speleothem interface, exhibiting stabilities on the order Cu ≈ Co > Ni, whereas organic complexation of the alkaline earth metals Mg and Sr was virtually absent. Systematic variations of OMC stability with natural organic matter characteristics were not observed amongst water samples, whilst enhanced complexation was clearly evident in the comparably organic-rich soil extracts. Our results imply that the supply of transition metals to speleothems is inversely related to drip rate, increasing with drip interval via the decay of OMCs. This process appears most sensitive on time-scales relevant to typical speleothem-forming settings (<0 to ca. 40 drips min‾¹, corresponding to ca. <5.6 mL min‾¹), and therefore provides a general, mechanistic link to a quantitative proxy of palaeoclimatic cave drip rates.Item Open Access Elucidating phosphorus removal dynamics in a denitrifying woodchip bioreactor(Elsevier B.V., 2024-03-20) Perera, GN; Rojas, DT; Rivas, A; Barkle, G; Moorhead, Brian; Schipper, LA; Craggs, R; Hartland, ADenitrifying woodchip bioreactors (DBRs) are an established nitrate mitigation technology, but uncertainty remains on their viability for phosphorus (P) removal due to inconsistent source-sink behaviour in field trials. We investigated whether iron (Fe) redox cycling could be the missing link needed to explain P dynamics in these systems. A pilot-scale DBR (Aotearoa New Zealand) was monitored for the first two drainage seasons (2017–2018), with supplemental in−field measurements of reduced solutes (Fe²⁺, HS⁻/H₂S) and their conjugate oxidised species (Fe³⁺/SO₄²⁻) made in 2021 to constrain within-reactor redox gradients. Consistent with thermodynamics, the dissolution of Fe³⁺(s) to Fe²⁺(aq) within the DBR sequentially followed O₂, NO₃− and MnO₂(s) reduction, but occurred before SO²‾₄ reduction. Monitoring of inlet and outlet chemistry revealed tight coupling between Fe and P (inlet R² 0.94, outlet R² 0.85), but distinct dynamics between drainage seasons. In season one, outlet P exceeded inlet P (net P source), and coincided with elevated outlet Fe²⁺, but at ⁓50 % lower P concentrations relative to inlet Fe:P ratios. In season 2 the reactor became a net P sink, coinciding with declining outlet Fe²⁺ concentrations (indicating exhaustion of Fe³⁺(s) hydroxides and associated P). In order to characterize P removal under varying source dynamics (i.e. inflows vs in-situ P releases), we used the inlet Fe vs P relationship to estimate P binding to colloidal Fe (hydr)oxide surfaces under oxic conditions, and the outlet Fe²⁺ concentration to estimate in-situ P releases associated with Fe (hydr)oxide reduction. Inferred P-removal rates were highest early in season 1 (k = 0.60 g P m³ d⁻¹; 75–100 % removal), declining significantly thereafter (k = 0.01 ± 0.02 g P m³ d⁻¹; ca. 3–67 % removal). These calculations suggest that microbiological P removal in DBRs can occur at comparable magnitudes to nitrate removal by denitrification, depending mainly on P availability and hydraulic retention efficiency.Item Open Access Model simplification to simulate groundwater recharge from a perched gravel-bed river(Elsevier, 2024-11) Di Ciacca, A; Wilson, S; Durney, P; Stecca, G; Wöhling, TGravel-bed rivers are an important source of groundwater recharge in some regions of the world. Their interactions with groundwater are complex and highly variable in space and time, with considerable water storage in the riverbed sediments. In losing river sections, where most of the groundwater recharge occurs, the river can be separated from the regional groundwater system by an unsaturated zone (i.e., perched). The complexity of groundwater–surface water interactions in these environments calls for the use of 3D fully integrated hydrological models to represent them, but their computational intensity limits their practicality for parameter inference, uncertainty quantification and regional scale problems. On the other hand, the simple groundwater–surface water exchange functions currently implemented in regional scale groundwater models are not suited to represent complex gravel-bed river systems such as braided rivers. There is therefore a need for developing groundwater–surface water exchange functions tailored to gravel-bed rivers that can be used in regional scale models. To address this issue, we developed a model simplification framework that combines a 3D integrated surface and subsurface hydrological model, a 2D cross-sectional river-aquifer model and a 1D conductance-based analytical model. We aim at broadly simplifying the 3D model while ensuring the appropriate simulation of groundwater recharge. We demonstrate our modelling approach on the Selwyn River (New Zealand) using piezometric data and groundwater recharge estimates derived from field observations and satellite imagery. Our results indicates that groundwater recharge from this river can be simulated using a simple 1D analytical model, which can easily be implemented in regional groundwater models (e.g., MODFLOW models). However, to represent properly the time variability of groundwater recharge, it is essential to use the groundwater level in the shallow aquifer associated with the river as input to the regional groundwater model. Our approach is generally transferable to other gravel-bed rivers but requires some observations of river losses for proper calibration.Item Open Access Extending GLUE With multilevel methods to accelerate statistical inversion of hydrological models(Wiley on behalf of American Geophysical Union, 2024-10) Rudolph, MG; Wöhling, T; Wagener, T; Hartmann, AInverse problems aim at determining model parameters that produce observed data to subsequently understand, predict or manage hydrological or other environmental systems. While statistical inversion is especially popular, its sampling-based nature often inhibits its application to computationally costly models, which has compromised the use of the Generalized Likelihood Uncertainty Estimation (GLUE) methodology, for example, for spatially distributed (partial) differential equation based models. In this study we introduce multilevel GLUE (MLGLUE), which alleviates the computational burden of statistical inversion by utilizing a hierarchy of model resolutions. Inspired by multilevel Monte Carlo, most parameter samples are evaluated on lower levels with computationally cheap low-resolution models and only samples associated with a likelihood above a certain threshold are subsequently passed to higher levels with costly high-resolution models for evaluation. Inferences are made at the level of the highest-resolution model but substantial computational savings are achieved by discarding samples with low likelihood already on levels with low resolution and low computational cost. Two example inverse problems, using a rainfall-runoff model and groundwater flow model, demonstrate the substantially increased computational efficiency of MLGLUE compared to GLUE as well as the similarity of inversion results. Findings are furthermore compared to inversion results from Markov-chain Monte Carlo (MCMC) and multilevel delayed acceptance MCMC, a corresponding multilevel variant, to compare the effects of the multilevel extension. All examples demonstrate the wide-range suitability of the approach and include guidelines for practical applications.Item Open Access Modelling wine grapevines for autonomous robotic cane pruning(Elsevier, 2023-11) Williams, H; Smith, D; Shahabi, J; Gee, T; Nejati, M; McGuinness, B; Black, K; Tobias, J; Jangali, R; Lim, H; Duke, M; Bachelor, O; McCulloch, J; Green, R; O'Connor, M; Gounder, S; Ndaka, A; Burch, K; Fourie, J; Hsiao, J; Werner, A; Agnew, R; Oliver, R; MacDonald, BAAotearoa (New Zealand) has a strong and growing winegrape industry struggling to access workers to complete skilled, seasonal tasks such as pruning. Maintaining high-producing vines requires training agricultural workers that can make quality cane pruning decisions, which can be difficult when workers are not readily available. A novel vision system for an autonomous cane pruning robot is presented that can assess a vine to make quality pruning decisions like an expert. The vision system is designed to generate an accurate digital 3D model of a vine with skeletonised cane structures to estimate key pruning metrics for each cane. The presented approach has been extensively evaluated in a real-world vineyard as a commercial platform would be expected to operate. The system is demonstrated to perform consistently at extracting dimensionally accurate digital models of the vines. Detailed evaluation of the digital models shows that 51.45% of the canes were modelled entirely, with a further 35.51% only missing a single internode connection. The quantified results demonstrate that the robotic platform can generate dimensionally accurate metrics of the canes for future decision-making and automation of pruning.Item Open Access Warming drives dissolved organic carbon export from pristine alpine soils(Springer Nature, 2024-12) Pearson, AR; Fox, BRS; Hellstrom, JC; Vandergoes, MJ; Breitenbach, SFM; Drysdale, RN; Höpker, SN; Wood, CT; Schiller, M; Hartland, ADespite decades of research, the influence of climate on the export of dissolved organic carbon (DOC) from soil remains poorly constrained, adding uncertainty to global carbon models. The limited temporal range of contemporary monitoring data, ongoing climate reorganisation and confounding anthropogenic activities muddy the waters further. Here, we reconstruct DOC leaching over the last ∼14,000 years using alpine environmental archives (two speleothems and one lake sediment core) across 4° of latitude from Te Waipounamu/South Island of Aotearoa New Zealand. We selected broadly comparable palaeoenvironmental archives in mountainous catchments, free of anthropogenically-induced landscape changes prior to ∼1200 C.E. We show that warmer temperatures resulted in increased allochthonous DOC export through the Holocene, most notably during the Holocene Climatic Optimum (HCO), which was some 1.5–2.5 °C warmer than the late pre-industrial period—then decreased during the cooler mid-Holocene. We propose that temperature exerted the key control on the observed doubling to tripling of soil DOC export during the HCO, presumably via temperature-mediated changes in vegetative soil C inputs and microbial degradation rates. Future warming may accelerate DOC export from mountainous catchments, with implications for the global carbon cycle and water quality.Publication Open Access Testing the reproducibility of active-distributed temperature sensing for measuring groundwater specific discharge beneath a braided river(Elsevier B.V., 2024-04) Sai Louie, AJ; Morgan, LK; Banks, EW; Dempsey, D; Wilson, SBraided rivers are a major contributor of groundwater recharge, yet little is known about how recharge rates vary in time. Existing methods for estimating groundwater recharge from rivers (i.e., river loss) are inadequate for studying highly heterogeneous braided river systems at a sufficient spatiotemporal resolution. To do so, active-distributed temperature sensing (A-DTS) is employed, which combines fibre optic temperature measurements with an active heat source, enabling high-resolution quantification of water fluxes. In this study, twelve successive A-DTS surveys were conducted during a 24-hour experiment on a 100 m horizontal subsurface hybrid fibre optic cable installed at 5 m depth beneath a braided river. The experiment was carried out under conditions where the river stage and flow were relatively stable to demonstrate the reproducibility and effectiveness of the A-DTS method for measuring groundwater specific discharge. This foundational work will provide a high level of confidence in the method for future studies aimed at evaluating temporal variations in groundwater recharge. The median groundwater specific discharge values calculated over the 24-hour period had a very narrow range from 3.5 to 4.0 m d‾¹ across the wetted footprint of the river, which is within the measurement error of the installation (6 %), indicating relatively stable groundwater recharge during the experiment. This provides confidence in the repeatability of the A-DTS method as an effective technology for quantifying river loss over longer time periods, to understand seasonal variability of groundwater recharge in braided river systems.Publication Open Access Conceptualising surface water-groundwater exchange in braided river systems(Copernicus Publications, 2023-12-13) Wilson, Scott; Hoyle, Jo; Measures, Richard; Di Ciacca, Antoine; Morgan, Leanne K; Banks, Eddie W; Robb, Linda; Wohling, TBraided rivers can provide substantial recharge to regional aquifers, with flow exchange between surface water and groundwater occurring at a range of spatial and temporal scales. However, the difficulty of measuring and modelling these complex and dynamic river systems has hampered process understanding and the upscaling necessary to quantify these fluxes. This is due to an incomplete understanding of the hydrogeological structures which control river-groundwater exchange. In this paper, we present a new conceptualisation of subsurface processes in braided rivers based on observations of the main losing reaches of three braided rivers in New Zealand. The conceptual model is based on a range of data including: lidar, bathymetry, coring, particle size distribution, groundwater, temperature monitoring, radon-222, electrical resistivity tomography, and fibre optic cables. The combined results indicate that sediments within the recently active river braidplain are distinctive, with sediments that are poorly consolidated and better sorted compared to adjacent deposits from the historical braidplain, which become successively consolidated and intermixed with flood silt deposits due to overbank flow. A distinct sedimentary unconformity, combined with the presence of geomorphologically distinct lateral boundaries, suggests that a “braidplain aquifer” forms within the active river braidplain through the process of sediment mobilisation during flood events. This braidplain aquifer concept introduces a shallow storage reservoir to the river system, which is distinct from the regional aquifer system, and mediates the exchange of flow between individual river channels and the regional aquifer. The implication of the new concept is that surface water-groundwater exchange occurs at two spatial scales. The first is hyporheic and parafluvial exchange between the river and braidplain aquifer. The second is exchange between the braidplain aquifer and regional aquifer system. Exchange at both scales is influenced by the state of hydraulic connection between the respective water bodies. This conceptualisation acknowledges braided rivers as whole “river systems”, consisting of channels, and gravel aquifer. This work has important implications for understanding how changes in river management (e.g., surface water extraction, bank modification and gravel extraction) and morphology may impact groundwater recharge, and potentially river flow, temperature attenuation, and ecological resilience during dry conditions.Publication Open Access The potential of UAV and very high-resolution satellite imagery for yellow and stem rust detection and phenotyping in Ethiopia(Springer Nature, 2023-10-05) Blasch, G; Anberbir, T; Negash, T; Tilahun, L; Belayineh, FY; Alemayehu, Y; Mamo, G; Hodson, DP; Rodrigues, FAVery high (spatial and temporal) resolution satellite (VHRS) and high-resolution unmanned aerial vehicle (UAV) imagery provides the opportunity to develop new crop disease detection methods at early growth stages with utility for early warning systems. The capability of multispectral UAV, SkySat and Pleiades imagery as a high throughput phenotyping (HTP) and rapid disease detection tool for wheat rusts is assessed. In a randomized trial with and without fungicide control, six bread wheat varieties with differing rust resistance were monitored using UAV and VHRS. In total, 18 spectral features served as predictors for stem and yellow rust disease progression and associated yield loss. Several spectral features demonstrated strong predictive power for the detection of combined wheat rust diseases and the estimation of varieties’ response to disease stress and grain yield. Visible spectral (VIS) bands (Green, Red) were more useful at booting, shifting to VIS–NIR (near-infrared) vegetation indices (e.g., NDVI, RVI) at heading. The top-performing spectral features for disease progression and grain yield were the Red band and UAV-derived RVI and NDVI. Our findings provide valuable insight into the upscaling capability of multispectral sensors for disease detection, demonstrating the possibility of upscaling disease detection from plot to regional scales at early growth stages.Publication Open Access Determination of the oxidative stability of olive oil using an integrated system based on dielectric spectroscopy and computer vision(Elsevier on behalf of KeAi and China Agricultural University, 2019-03) Sanaeifar, A; Jafari, ADuring storage, olive oil may suffer degradation leading to an inferior quality level when purchased and consumed. Oxidative stability is one of the most important parameters for maintaining the quality of olive oil, which affects its acceptability and market value. The current methods of predicting the oxidative stability of edible oils are costly and time-consuming. The aim of the present research is to demonstrate the use of dielectric spectroscopy integrated with computer vision for determining the oxidative stability index (OSI) of olive oil. The most effective features were selected from the extracted dielectric and visual features for each olive oil sample. Three machine learning techniques were employed to process the raw data to develop an oxidative stability prediction algorithm, including artificial neural network (ANN), support vector machine (SVM) and multiple linear regression (MLR). The predictive models showed a great agreement with the results obtained by the Rancimat instrument that was used as a reference method. The best result for modelling the oxidative stability of olive oil was obtained using SVM technique with the R-value of 0.979. It can be concluded that this new approach may be utilized as a perfect replacement for quicker and cheaper assessment of olive oil oxidation.Publication Open Access Improving accuracy of quantifying nitrate removal performance and enhancing understanding of processes in woodchip bioreactors using high-frequency data(Elsevier, 2023-07-01) Rivas, A; Barkle, G; Sarris, T; Park, J; Kenny, A; Maxwell, B; Stenger, R; Moorhead, B; Schipper, L; Clague, JWoodchip bioreactors have gained popularity in many countries as a conservation practice for reducing nitrate load to freshwater. However, current methods for assessing their performance may be inadequate when nitrate removal rates (RR) are determined from low-frequency (e.g., weekly) concurrent sampling at the inlet and outlet. We hypothesised that high-frequency monitoring data at multiple locations can help improve the accuracy of quantifying nitrate removal performance, enhance the understanding of processes occurring within a bioreactor, and therefore improve the design practice for bioreactors. Accordingly, the objectives of this study were to compare RRs calculated using high- and low-frequency sampling and assess the spatiotemporal variability of the nitrate removal within a bioreactor to unravel the processes occurring within a bioreactor. For two drainage seasons, we monitored nitrate concentrations at 21 locations on an hourly or two-hourly basis within a pilot-scale woodchip bioreactor in Tatuanui, New Zealand. A novel method was developed to account for the variable lag time between entry and exit of a parcel of sampled drainage water. Our results showed that this method not only enabled lag time to be accounted for but also helped quantify volumetric inefficiencies (e.g., dead zone) within the bioreactor. The average RR calculated using this method was significantly higher than the average RR calculated using conventional low-frequency methods. The average RRs of each of the quarter sections within the bioreactor were found to be different. 1-D transport modelling confirmed the effect of nitrate loading on the removal process as nitrate reduction followed Michaelis-Menten (MM) kinetics. These results demonstrate that high-frequency temporal and spatial monitoring of nitrate concentrations in the field allows improved description of bioreactor performance and better understanding of processes occurring within woodchip bioreactors. Thus, insights gained from this study can be used to optimise the design of future field bioreactors.Publication Open Access Optimal sample size and composition for crop classification with Sen2-Agri’s random forest classifier(MPDI, 2023-02-01) Schulthess, Urs; Rodrigues Jr, Francelino; Taymans, Matthieu; Bellemans, Nicolas; Bontemps, Sophie; Ortiz-Monasterio, Ivan; Gérard, Bruno; Defourny, PierreSen2-Agri is a software system that was developed to facilitate the use of multi-temporal satellite data for crop classification with a random forest (RF) classifier in an operational setting. It automatically ingests and processes Sentinel-2 and LandSat 8 images. Our goal was to provide practitioners with recommendations for the best sample size and composition. The study area was located in the Yaqui Valley in Mexico. Using polygons of more than 6000 labeled crop fields, we prepared data sets for training, in which the nine crops had an equal or proportional representation, called Equal or Ratio, respectively. Increasing the size of the training set improved the overall accuracy (OA). Gains became marginal once the total number of fields approximated 500 or 40 to 45 fields per crop type. Equal achieved slightly higher OAs than Ratio for a given number of fields. However, recall and F-scores of the individual crops tended to be higher for Ratio than for Equal. The high number of wheat fields in the Ratio scenarios, ranging from 275 to 2128, produced a more accurate classification of wheat than the maximal 80 fields of Equal. This resulted in a higher recall for wheat in the Ratio than in the Equal scenarios, which in turn limited the errors of commission of the non-wheat crops. Thus, a proportional representation of the crops in the training data is preferable and yields better accuracies, even for the minority crops.Publication Open Access Diverse approaches to learning with immersive Virtual Reality identified from a systematic review(Elsevier, 2023-04) Won, Mihye; Ungu, Dewi Ayu Kencana; Matovu, Henry; Treagust, David F; Tsai, Chin-Chung; Park, J; Mocerino, Mauro; Tasker, RoyTo investigate how learning in immersive Virtual Reality was designed in contemporary educational studies, this systematic literature review identified nine design features and analysed 219 empirical studies on the designs of learning activities with immersive Virtual Reality. Overall, the technological features for physical presence were more readily implemented and investigated than pedagogical features for learning engagement. Further analysis with k-means clustering revealed five approaches with varying levels of interactivity and openness in learning tasks, from watching virtual worlds passively to responding to personalised prompts. Such differences in the design appeared to stem from different practical and educational priorities, such as accessibility, interactivity, and engagement. This review highlights the diversity in the learning task designs in immersive Virtual Reality and illustrates how researchers are navigating practical and educational concerns. We recommend future empirical studies recognise the different approaches and priorities when designing and evaluating learning with immersive Virtual Reality. We also recommend that future systematic reviews investigate immersive Virtual Reality-based learning not only by learning topics or learner demographics, but also by task designs and learning experiences.Publication Open Access Simulating water and nitrogen runoff with APSIM(Elsevier, 2023-03) Vogeler, I; Cichota, R; Langer, S; Thomas, S; Ekanayake, D; Werner, ATo determine the impact of potential reductions of terrain-targeted nitrogen (N) fertilisation rates on N losses a simulation study was carried out using the Agricultural Production Systems Simulator (APSIM). To simulate N runoff a simple approach was used, in which runoff is based on the N concentration in the soil solution and an extraction coefficient. Firstly, APSIM parameters that have the largest effect on runoff of water and N were determined for terrains with different slopes for a poorly drained silt loam. A sensitivity analysis was then conducted to assess the effect of soil hydraulic properties and soil organic carbon content on runoff losses. Finally, APSIM was set up to simulate pasture production and water and N dynamics (including pasture N uptake, leaching and N runoff) for a farm on rolling hills in South Canterbury, New Zealand. Two different fertilisation approaches were used, either scheduled or based on the aboveground N concentration of the pasture. For the poorly drained silt loam, the rainfall intensity and the surface conductance had the highest effect on the amount of water lost by runoff. Soil hydraulic conductivity at saturation and field capacity, as well as plant available water content also controlled runoff of water and N, while the organic carbon content of the topsoil had less effect on N runoff. Both the extraction coefficient and the depth considered to exchange N with the runoff water affected the amount of N lost via runoff. Using the aboveground pasture N concentration prior to fertilisation had positive effects on pasture yield and reduced N runoff losses.Publication Open Access Deriving transmission losses in ephemeral rivers using satellite imagery and machine learning(Copernicus Publications on behalf of the European Geosciences Union, 2023) Di Ciacca, A; Wilson, S; Kang, J; Wöhling, TTransmission losses are the loss in the flow volume of a river as water moves downstream. These losses provide crucial ecosystem services, particularly in ephemeral and intermittent river systems. Transmission losses can be quantified at many scales using different measurement techniques. One of the most common methods is differential gauging of river flow at two locations. An alternative method for non-perennial rivers is to replace the downstream gauging location by visual assessments of the wetted river length on satellite images. The transmission losses are then calculated as the flow gauged at the upstream location divided by the wetted river length. We used this approach to estimate the transmission losses in the Selwyn River (Canterbury, New Zealand) using 147 satellite images collected between March 2020 and May 2021. The location of the river drying front was verified in the field on six occasions and seven differential gauging campaigns were conducted to ground-truth the losses estimated from the satellite images. The transmission loss point data obtained using the wetted river lengths and differential gauging campaigns were used to train an ensemble of random forest models to predict the continuous hourly time series of transmission losses and their uncertainties. Our results show that the Selwyn River transmission losses ranged between 0.25 and 0.65 m³ s‾¹ km‾¹ during most of the 1-year study period. However, shortly after a flood peak the losses could reach up to 1.5 m³ s‾¹ km‾¹. These results enabled us to improve our understanding of the Selwyn River groundwater-surface water interactions and provide valuable data to support water management. We argue that our framework can easily be adapted to other ephemeral rivers and to longer time series.Publication Open Access Bayesian modelling of phosphorus content in wheat grain using hyperspectral reflectance data(BMC, 2023-01-20) Pacheco-Gil, Rosa Angela; Velasco-Cruz, Ciro; Pérez-Rodríguez, Paulino; Burgueño, Juan; Pérez-Elizalde, Sergio; Rodrigues, Francelino; Ortiz-Monasterio, Ivan; del Valle-Paniagua, David Hebert; Toledo, FernandoBackground: As a result of the technological progress, the use of sensors for crop survey has substantially increased, generating valuable information for modelling agricultural data. Plant spectroscopy jointly with statistical modeling can potentially help to assess certain chemical components of interest present in plants, which may be laborious and expensive to obtain by direct measurements. In this research, the phosphorus content in wheat grain is modeled using reflectance information measured by a hyperspectral sensor at different wavelengths. A Bayesian procedure for selecting variables was used to identify the set of the most important spectral bands. Additionally, three different models were evaluated: the first model assumes that the observations are independent, the other two models assume that the observations are spatially correlated: one of the proposed models, assumes spatial dependence using a Conditionally Autoregressive Model (CAR), and the other through an exponential correlogram. The goodness of fit of the models was evaluated by means of the Deviance Information Criterion, and the predictive power is evaluated using cross validation. Results: We have found that CAR was the model that best fits and predicts the data. Additionally, the selection variable procedure in the CAR model reveals which wavelengths in the range of 500–690 nm are the most important. Comparing the vegetative indices with the CAR model, it was observed that the average correlation of the CAR model exceeded that of the vegetative indices by 23.26%, − 1.2% and 22.78% for the year 2010, 2011 and 2012 respectively; therefore, the use of the proposed methodology outperformed the vegetative indices in prediction. Conclusions: The proposal to predict the phosphorus content in wheat grain using Bayesian approach, reflect with the results as a good alternative.