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Reparameterization Required After model Structure Changes From Carbon Only to Carbon-Nitrogen Coupling

JOURNAL OF ADVANCES IN modelING EARTH SYSTEMS 2022年第4期14卷 p1-15页

作者： Wang, Song Luo, Yiqi Niu, Shuli Chinese Acad Sci Key Lab Ecosyst Network Observat & Modeling Inst Geog Sci & Nat Res Beijing Peoples R China Univ Chinese Acad Sci Coll Resources & Environm Beijing Peoples R China No Arizona Univ Ctr Ecosyst Sci & Soc Flagstaff AZ 86011 USA

Prediction of carbon (C) sequestration in terrestrial ecosystems under climate change depends on C-nitrogen (N) interactions. While many newly developed C-N coupling models predict lower C storage than their C-only counterpart models, it has not been carefully examined whether or not such model predictions would be supported by real-world observations. This study is to retrieve knowledge on N cycle from one field warming experiment in an alpine meadow of China so that we can better predict land C sequestration. We estimated two sets of parameters with one C-only model and one C-N coupling model, respectively, with the data assimilation technique. Our results showed that estimated process rates (e.g., senescence and decomposition rates) of organic C from almost all pools except standing litter and leaf are higher with the C-N coupling model than those with the C-only model. The allocation coefficient of C to root estimated with the C-only model was 68.0% and 56.6% smaller than that with the C-N coupling model under the ambient and warming treatments, respectively. Both the C-only and C-N coupling models simulate similar C pool sizes as observed at either the ambient or warming treatment with their respective parameter estimates. Meanwhile, the warming treatment increased the slow soil organic matter (SOM) pool due to decrease in estimated decomposition rate of the slow SOM via parameter fitting and increase in the C input from surface litter. In general, our results suggest that reparameterization is required when we add N processes to a C cycle model to realistically predict the ecosystem dynamics in response to future changes in N availability.

关键词： Bayesian probabilistic inversion MCMC model structure model parameterization warming carbon and nitrogen cycles

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High-Fidelity model of Stand-Alone Diesel Electric Generator With Hybrid Turbine-Governor Configuration for Microgrid Studies

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IEEE ACCESS 2022年 10卷 110537-110547页

作者： Shah, Chinmay Wies, Richard W. Hansen, Timothy M. Tonkoski, Reinaldo Shirazi, Mariko Cicilio, Phylicia Univ Alaska Fairbanks Alaska Ctr Energy & Power Dept Elect & Comp Engn Fairbanks AK 99709 USA South Dakota State Univ Dept Elect Engn & Comp Sci Brookings SD 57007 USA South Dakota State Univ Dept Elect & Comp Engn Brookings SD 57007 USA

Diesel electric generators are an inherent part of remote hybrid microgrids found in remote regions of the world that provide primary frequency response (PFR) to restore system frequency during load or generation changes. However, with inverter-based resources (IBR) integration into microgrids, the IBR control provides a fast frequency response (FFR) to restore the system frequency. Hence, supplementing PFR with FFR requires a sophisticated control system and a high fidelity diesel electric generator model to design these control systems. In this work, a high-fidelity model of a diesel electric generator is developed. Its parameters are tuned using a surrogate optimization algorithm by emulating its response during a load change to a 400 kVA Caterpillar C-15 diesel generator, similar to those found in remote microgrids. The diesel electric generator model consists of a synchronous machine, DC4B excitation with V/Hz limiter, and a proposed modified IEEE GGOV1 engine-governor model (GGOV1D). The performance of the GGOV1D is compared with simple, Woodward DEGOV, and a standard IEEE GGOV1 engine-governor model. Results show that error in the diesel electric generator's response to load changes using the GGOV1D model is lower with an improved frequency response during the arresting and rebound period than the other engine-governor models.

关键词： Electric generators Load modeling Microgrids Frequency response Mathematical models Optimization Diesel engines Diesel generator modeling diesel governor power system dynamics power system stability frequency stability model parameterization microgrid

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Keeping up with the math: Advancing the ecological foundation of the Great Lakes Cladophora model

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ECOLOGICAL modelLING 2022年 473卷

作者： Kuczynski, Anika Auer, Martin T. Taylor, William D. Chapra, Steven C. Dijkstra, Marcel Natl Inst Water & Atmospher Res 10 Kyle St Riccarton Christchurch 8011 New Zealand Michigan Technol Univ Great Lakes Res Ctr Houghton MI 49931 USA Michigan Technol Univ Dept Civil & Environm Engn Houghton MI 49931 USA Univ Waterloo Dept Biol 200 Univ Ave West Waterloo ON N2L 3G1 Canada Tufts Univ Dept Civil & Environm Engn Medford MA 02155 USA Univ Wisconsin Sustainabil Inst Reg Transformat 800 Algoma Blvd Oshkosh WI 54901 USA

The nearshore waters of the Laurentian Great Lakes have historically suffered from beach fouling and clogged water intakes due to proliferation of the native, filamentous green alga Cladophora. A resurgence in nuisance growth of the alga has led to a demand for an improved model platform to better guide management. The Great Lakes Cladophora model (GLCM v3) predicts algal biomass (g dry matter m-2) and stored phosphorus content (P as % of dry matter) based on simulations forced by time series of incident light (I), water temperature (T) and water column soluble reactive phosphorus concentration (SRP, mu gP L-1). A particular strength of the GLCM v3 is its foundation in ecologically sound biokinetic mechanisms, supported by field and laboratory measurements. These measurements, advancing the credibility and reliability of the biokinetic framework, include improved characterization of the growth and respiration responses to light and temperature, addition of a self-shading algorithm replacing an overly deterministic carrying capacity term, a new treatment of phosphorus uptake based on radioisotope experiments, additional observational support for Droop-based simulation of growth as a function of stored P, and implementation of a new physiologically and physically driven sloughing function. Uncertainty associated with processes collectively termed "environmental friction" (the I, T, and P growth forcing functions) is reduced, leaving the model sensitive to the maximum specific growth rate and the coefficient for extinction of photosynthetically active radiation through the algal mat. The model was performance tested by multi-lake (Erie, Huron, Ontario, and Michigan) calibration employing a common set of biophysical coefficients. This common set of calibration coefficients provides enhanced corroboration that GLCM v3 is suitable for examining the phosphorus-Cladophora dynamic across the Great Lakes. In particular, it greatly strengthens the model's efficacy for establis

关键词： Cladophora Laurentian Great Lakes model parameterization Mechanistic modeling Calibration Growth rate Phosphorus uptake Sloughing Cross-site application Ecosystem management

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An improved drought-fire assessment for managing fire risks in tropical peatlands

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AGRICULTURAL AND FOREST METEOROLOGY 2022年 312卷 108738-108738页

作者： Taufik, Muh Widyastuti, Marliana Tri Sulaiman, Albertus Murdiyarso, Daniel Santikayasa, I. Putu Minasny, Budiman IPB Univ Dept Geophys & Meteorol Jalan Meranti Wing 19 Level 4 Darmaga Campus Bogor 16680 Indonesia Indonesian Sci Inst Res Ctr Phys Puspitek Serpong 15314 Tangerang Selat Indonesia Ctr Int Forestry Res CIFOR Bogor 16115 Indonesia Univ Sydney Sch Life & Environm Sci Sydney Inst Agr Sydney NSW 2006 Australia

Peatlands transformation in Indonesia has caused immense ecological and environmental degradation. Land use conversion has changed this natural carbon sink to a drought- and fire-prone ecosystem. Public awareness to tackle the drought and fire risk in peatlands has led to the development of drought-fire index. Current knowledge states that both climate and hydrology have a strong influence on drought-induced fire in tropical peatlands, yet the role of soil hydraulic properties in controlling the drying of peats remains unclear. This study develops an improved drought-fire index for tropical peatlands, called the Peat Fire Vulnerability Index, by incorporating groundwater and soil water retention information. We tested the new index on two peatland regions in Kubu Raya and Batanghari, Indonesia, to assess fire danger. We monitored daily rainfall, groundwater tables, and soil moisture from 2018 to 2019 on eight stations in the peatlands. Our model was calibrated against the observed drought index of two stations, and the results were verified with actual fire events through daily fire hotspots and fire burned areas in the other six stations. Results showed that soil-hydrological properties influenced the moistening and drying of peats through capillarity. Our model showed good performance in assessing fire danger during the calibration period, as indicated by three employed statistical metrics: the RMSE-standard deviation ratio (RSR = 0.57), Kling-Gupta Efficiency (KGE = 0.81), and percent bias (PBIAS = 1%). For verification, all observed fire events fell in high and extreme fire danger classes predicted by PFVI. Further, our findings revealed the importance of the groundwater table as a threshold of fire events. The high fire danger class was mostly found when groundwater table dropped below 40 cm, and burned areas only occurred when the groundwater table was below 60 cm. These findings suggest that our drought-fire index can be used as a peat fire risk management to

关键词： Ecohydrology fire danger Groundwater table model parameterization Peat moisture Water retention

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Dynamic parameterization of soil surface characteristics for hydrological models in agricultural catchments

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CATENA 2022年 214卷

作者： Grangeon, Thomas Vandromme, Rosalie Pak, Lai Ting Martin, Philippe Cerdan, Olivier Richet, Jean-Baptiste Evrard, Olivier Souchere, Veronique Auzet, Anne-Veronique Ludwig, Bruno Ouvry, Jean-Francois Bur Rech Geol & Minieres F-45060 Orleans France Cirad F-97285 Le Lamentin Martinique France Assoc Rech Ruissellement Eros & Amenagement Sol AR 2 Ave Foch F-76460 St Valery En Caux France Univ Paris Saclay INRAE AgroParisTech UMR SADAPT F-75005 Paris France Univ Paris Saclay Lab Sci Climat & Environm LSCE IPSL UMR 8212 CEACNRSUVSQ Gif Sur Yvette France Univ Paris Saclay UMR SADAPT INRAE AgroParisTech Ave Lucien Bretignieres F-78850 Thiverval Grignon France Univ Strasbourg ITES UMR 7063 F-67084 Strasbourg France LIOSE 71 Rue Crecy F-02000 Laon France

The detrimental impacts of surface runoff and soil erosion, particularly in cultivated areas, call for the use of distributed runoff and soil erosion models with a view to supporting adapted catchment management strategies. However, runoff model parameterization remains challenging in agricultural catchments due to the high spatial and seasonal variability of soil properties. Data acquisition is demanding and may not always be feasible. Therefore, model parameterization in such environments have been the subject of numerous research efforts. The combined analysis of land use management and soil surface state was proposed in literature to address this issue and demonstrated its potential for runoff analysis and modelling. However, these research findings were related to specific rainfall sequences and/or soil surface state. In this study, existing knowledge on soil surface state and its application to runoff model parameterization were synthetized and included in an easy-to-use parameterization software (PREMACHE), providing a framework for modelers lacking of means and/or data for modelling complex agricultural *** develop and evaluate the software, a dataset was acquired over 9 years on more than 110 plots in a 1045 ha agricultural catchment, including crop types, soil surface state, rainfall and runoff time series. Soil surface state dynamics was modeled based on crop types and daily rainfall. It was evaluated in the experimental catchment and validated in a nearby catchment. Soil hydrodynamic properties (e.g. infiltration capacity) were deduced from this framework and literature data at a daily time step, for each plots. Moreover, runoff events were measured when the modeled infiltration capacity was low, indicating that the parametrization adequately captured its temporal dynamics. The software developed in this study, as well as setup values deduced from the monitoring campaigns are provided with the manuscript for application in other ungauged catchm

关键词： Crops Soil properties Runoff Agricultural catchment model parameterization Soil infiltration capacity Tillage operations

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Effects of Choosing Different parameterization Data in Two-Phase Forest Inventories for Standing Stock Estimation

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FORESTS 2025年第2期16卷 259-259页

作者： Berger, Ambros Gschwantner, Thomas Austrian Res & Training Ctr Forests Nat Hazards & Inst Forest Inventory Seckendorff Gudent Weg 8 A-1131 Vienna Austria

The demands on national forest inventories to provide detailed information for small geographical regions are rising. Two-phase estimators are often employed to obtain forest resource estimates, yet there is little information on optimal training data selection. This study evaluates the impact of different training data on two-phase estimators, with a focus on small area estimators for standing stock and aims to develop guidelines on selecting appropriate training datasets. Linear regression models were parameterized using multiple datasets and subsets based on ecological and administrative boundaries. The models were then applied on varying scales, and their estimates and their confidence intervals were compared to each other as well as to the single-phase, purely terrestrial forest inventory. Results suggest that the different two-phase models generally yield comparable estimates but differ notably from single-phase estimates. Specifically, differences increase in smaller areas and with correspondingly smaller training datasets, suggesting a minimum of 100 data points. To ensure robust estimates, we recommend adapting training sets to local conditions and exercising caution with small training datasets and areas because implausible results may occur. Pooling appropriate datasets is the preferable solution.

关键词： national forest inventory model parameterization uncertainty small area estimation forest stock volume

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The individual-based forest landscape and disturbance model iLand: Overview, progress, and outlook

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ECOLOGICAL modelLING 2024年 495卷

作者： Rammer, Werner Thom, Dominik Baumann, Martin Braziunas, Kristin Dollinger, Christina Kerber, Jonas Mohr, Johannes Seidl, Rupert Tech Univ Munich Sch Life Sci Ecosyst Dynam & Forest Management Grp Freising Weihenstephan Germany Univ Vermont Gund Inst Environm Burlington VT USA Berchtesgaden Natl Pk Berchtesgaden Germany

Forest ecosystems are changing rapidly, and landscape-level processes such as disturbance and dispersal are key drivers of change. Consequently, forest landscape models are important tools for studying forest trajectories under changing environmental conditions and their impacts on ecosystem service provisioning. Here, we synthesize 12 years of development and application of the individual-based forest landscape and disturbance model iLand. Specifically, we describe the fundamental model logic and give an overview of model components introduced over the years. Additionally, we outline how to initialize, evaluate and parameterize the model for new applications. iLand is a process-based forest landscape model that simulates forest dynamics at the level of individual trees. It accounts for continuous processes (tree growth, mortality, and regeneration) as well as discontinuous disturbances (wind, wildfire, and biotic agents) and forest management. Simulations span multiple spatial and temporal scales, from individual trees to landscapes of 105 hectares, and from hourly disturbance dynamics to centuries of forest development. Environmental conditions are represented by daily climate data and high-resolution soil information. The model was designed for flexibly addressing a wide range of research questions, features a rich graphical user interface and comprehensive scripting support. The model is open source and comes with extensive online model documentation. iLand has hitherto been applied in 50 peer-reviewed simulation studies across three continents. Applications primarily focused on the effects of climate change, disturbances and forest management on forest dynamics, ecosystem service provisioning and forest biodiversity. Future model development could address the representation of belowground processes, biotic interactions, and landscape dynamics beyond forest ecosystems. We conclude that process-based simulation of landscape-scale forest dynamics at the level of i

关键词： Landscape modeling Agent-based modeling Simulation modeling Forest dynamics model development model initialization model parameterization model evaluation model application

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Full-waveform inversion of pure quasi-P waves in titled transversely isotropic media based on different parameterizations

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GEOPHYSICS 2024年第2期89卷 C57-C73页

作者： Ren, Zhiming Dai, Xue Wang, Lei Changan Univ Coll Geol Engn & Geomat Xian Peoples R China Natl Engn Res Ctr Offshore Oil & Gas Explorat Beijing Peoples R China

Full -waveform inversion (FWI) builds subsurface parameter models by minimizing the residuals between the modeled and observed data. Accounting for the effects of anisotropy is critical for high -resolution imaging of complex structures. We develop an acoustic anisotropic FWI method based on a pure quasi -P -wave (qP-wave) equation. The equation coefficients and their derivatives with respect to Thomsen's anisotropy parameters (epsilon and delta) are estimated by least -squares optimization. We derive and analyze the radiation patterns for six parameter classes: the velocity along the symmetry axis v, epsilon, and delta;the normal moveout velocity vnmo, the anisotropy parameter eta, and delta;the horizontal velocity vh, vnmo, and epsilon;vh,eta, and epsilon;vh, eta, and delta;and vh, vnmo, and delta. The parameterization [v, epsilon, delta] has significant trade-off between epsilon and delta at the intermediate and wide scattering angles. The anisotropy parameters epsilon and delta are resolvable at the short scattering angles for the parameterizations [vh, vnmo, epsilon] and [vnmo, eta, delta], respectively. The parameter crosstalk for the parameterizations [vh, eta,delta] and [vh, vnmo,delta] is more serious than that for other types of parameterizations. We perform FWI of pure qP-waves in vertical transversely isotropic (VTI) and titled transversely isotropic (TTI) media. Inversion results on the overthrust VTI model and the modified BP TTI model show that the velocity, anisotropy parameters, and tilt angle can be individually reconstructed when other parameters are sufficiently accurate. The multiparameter FWI cannot obtain reliable tilt angles for each type of parameterization. The inversion with the parameterization [vnmo, eta,delta] produces v, epsilon, and delta models with modest accuracy, whereas the parameterization [vh, vnmo, epsilon] helps to improve the accuracy of v and epsilon models.

关键词： acoustic anisotropy full-waveform inversion model parameterization pure quasi-P wave

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From field soil sampling to watershed model: Upscaling by integrating information entropy and interpolation method

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024年 360卷 121119页

作者： Chen, Lei Wang, Weichen Wang, Chengcheng Yan, Xiaoman Zhang, Yuhan Shen, Zhenyao Beijing Normal Univ Sch Environm State Key Lab Water Environm Simulat 19 Xinjiekouwai St Beijing 100875 Peoples R China Shanghai Invest Design & Res Inst Co Ltd Shanghai 200335 Peoples R China Beijing Normal Univ Sch Environm Beijing 100875 Peoples R China

Soil property data plays a crucial role in watershed hydrology and non-point source (H/NPS) modeling, but how to improve modeling accuracy with affordable soil samplings and the effects of sampling information on H/NPS modeling remains to be further explored. In this study, the number of sampling points and soil properties were optimized by the information entropy and the spatial interpolation method. Then the sampled properties were parameterized and the effects of different parameterization schemes on H/NPS modeling were tested using the Soil and Water Assessment Tool (SWAT). The results indicated that the required sampling points increased successively for soil bulk density (SOL_BD), soil saturated hydraulic conductivity (SOL_K) and soil available water capacity (SOL_AWC). Compared to the traditional database (Harmonized world soil database), the NSE and R2 performance by new scheme increased by 22.8% and 10.5%, respectively. The entropy-based optimization reduced the sampling points by 13.2%, indicating a more cost-effective scheme. Compared to hydrological simulation, sampled properties showed greater effects on NPS modeling, especially for nitrogen. This proposed method/framework can be generalized to other watersheds by upscaling field soil sampling information to the watershed scale, thus improving H/NPS simulation.

关键词： Soil sampling model parameterization Information entropy Nonpoint source pollution Soil and water assessment tool

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Connecting Agent-Based models with High-Dimensional Parameter Spaces to Multidimensional Data Using SMoRe ParS: A Surrogate modeling Approach

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BULLETIN OF MATHEMATICAL BIOLOGY 2024年第1期86卷 11-11页

作者： Bergman, Daniel R. Norton, Kerri-Ann Jain, Harsh Vardhan Jackson, Trachette Univ Michigan Dept Math 530 Church St Ann Arbor MI 48109 USA Bard Coll Comp Sci Program Computat Biol Lab 30 Campus Rd Hudson NY 12504 USA Univ Minnesota Duluth Dept Math & Stat 1117 Univ Dr Duluth MN 55812 USA

Across a broad range of disciplines, agent-based models (ABMs) are increasingly utilized for replicating, predicting, and understanding complex systems and their emergent behavior. In the biological and biomedical sciences, researchers employ ABMs to elucidate complex cellular and molecular interactions across multiple scales under varying conditions. Data generated at these multiple scales, however, presents a computational challenge for robust analysis with ABMs. Indeed, calibrating ABMs remains an open topic of research due to their own high-dimensional parameter spaces. In response to these challenges, we extend and validate our novel methodology, Surrogate modeling for Reconstructing Parameter Surfaces (SMoRe ParS), arriving at a computationally efficient framework for connecting high dimensional ABM parameter spaces with multidimensional data. Specifically, we modify SMoRe ParS to initially confine high dimensional ABM parameter spaces using unidimensional data, namely, single time-course information of in vitro cancer cell growth assays. Subsequently, we broaden the scope of our approach to encompass more complex ABMs and constrain parameter spaces using multidimensional data. We explore this extension with in vitro cancer cell inhibition assays involving the chemotherapeutic agent oxaliplatin. For each scenario, we validate and evaluate the effectiveness of our approach by comparing how well ABM simulations match the experimental data when using SMoRe ParS-inferred parameters versus parameters inferred by a commonly used direct method. In so doing, we show that our approach of using an explicitly formulated surrogate model as an interlocutor between the ABM and the experimental data effectively calibrates the ABM parameter space to multidimensional data. Our method thus provides a robust and scalable strategy for leveraging multidimensional data to inform multiscale ABMs and explore the uncertainty in their parameters.

关键词： Agent-based model Cancer model parameterization Parameter identifiability Surrogate model

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