Field Experimental Data Research Articles

Multiscale characterisation of chimneys/pipes: Fluid escape structures within sedimentary basins

Evaluation of seismic reflection data has identified the presence of fluid escape structures cross-cutting overburden stratigraphy within sedimentary basins globally. Seismically-imaged chimneys/pipes are considered to be possible pathways for fluid flow, which may hydraulically connect deeper strata to the seabed. The properties of fluid migration pathways through the overburden must be constrained to enable secure, long-term subsurface carbon dioxide (CO2) storage. We have investigated a site of natural active fluid escape in the North Sea, the Scanner pockmark complex, to determine the physical characteristics of focused fluid conduits, and how they control fluid flow. Here we show that a multi-scale, multi-disciplinary experimental approach is required for complete characterisation of fluid escape structures. Geophysical techniques are necessary to resolve fracture geometry and subsurface structure (e.g., multi-frequency seismics) and physical parameters of sediments (e.g., controlled source electromagnetics) across a wide range of length scales (m to km). At smaller (mm to cm) scales, sediment cores were sampled directly and their physical and chemical properties assessed using laboratory-based methods. Numerical modelling approaches bridge the resolution gap, though their validity is dependent on calibration and constraint from field and laboratory experimental data. Further, time-lapse seismic and acoustic methods capable of resolving temporal changes are key for determining fluid flux. Future optimisation of experiment resource use may be facilitated by the installation of permanent seabed infrastructure, and replacement of manual data processing with automated workflows. This study can be used to inform measurement, monitoring and verification workflows that will assist policymaking, regulation, and best practice for CO2 subsurface storage operations.

Field testing of multi-variable individual pitch control on a utility-scale wind turbine

The ongoing increase in size of modern wind turbines creates the demand of better control algorithms to counteract the increased loads acting on them. Individual blade pitch control (IPC) algorithms to alleviate blade loads are becoming a crucial part of current wind turbine control systems. The state-of-the-art individual blade pitch load reduction controller mostly relies on multiple single-input single-output (SISO) designs. This approach, however, constrains the achievable bandwidth of the controller as relevant couplings in the dynamics are ignored. These couplings become more pronounced for bigger turbines. Model-based multiple-input multiple output (MIMO) control designs can be used to account for these couplings and hence reduce loads for future, larger turbines. In this article we present the results of an intensive field test campaign of an H∞-design based MIMO IPC. This controller is designed for and tested on the utility-scale 2.5 MW Clipper Liberty research turbine operated by the University of Minnesota. The article guides the reader through the turbine’s open loop dynamics, the IPC design and the relevant implementation steps on the turbine. Finally, the developed H∞-based IPC is compared using experimental field data against no IPC (collective blade pitch control) and a classical IPC based on decoupled SISO loops.

Aerodynamic modeling of wind turbine loads exposed to turbulent inflow and validation with experimental data

The present paper is intended to assess the ability of the state-of-the-art computational fluid dynamics (CFD) and blade element momentum (BEM) approaches for accurate load predictions on a 2.3 MW wind turbine rotor. Three different cases are considered, a steady uniform inflow condition, a turbulent uniform inflow condition and a turbulent inflow case in combination with shear and yaw. The CFD computations employ a delayed-detached eddy simulation (DDES) approach in combination with a high order (5th) WENO method for flux discretization. The BEM calculations apply several correction factors including recently developed dynamic stall and yaw models. Furthermore, a well established procedure at IAG to set-up BEM calculations consistent to CFD will be presented and verified. The results are compared with the field experimental data of the turbine for these three different flow conditions. The studies show that both CFD and BEM results are in a very good agreement with the experimental data not only on the mean load levels but also with regards to the load fluctuations. The differences between BEM, CFD and experimental data for most radial stations are less than 10%.

Modeling water consumption, N fates, and rice yield for water-saving and conventional rice production systems

Quantifying water consumption, nitrogen (N) fates, and crop yield is crucial in developing the best management practices for rice production systems. A 2-year field experiment was conducted in Taihu Lake region, China. The experiment consisted of water-saving controlled and conventional flooding irrigation regimes that are factorially combined with two N management practices (farmers’ N fertilization and site-specific N management). A simple surface ponding water layer component was incorporated into the original WHCNS (soil water heat carbon nitrogen simulator) model to simulate and comprehensively evaluate water consumption, N fates, and rice yield for water-saving and conventional rice production systems. Field experiment data, including surface water ponding depth, soil water content, runoff, runoff N loss, crop N uptake, and yield, was measured to test the improved model. Results showed agreement between the measured and simulated values of surface ponding water depth, soil water content, runoff, N runoff loss, ammonia volatilization, crop N uptake, and yield and simulated values agreed well, with average relative root mean squared error values of 24.0%, 9.3%, 26.1%, 20.9%, 21.3%, 7.9%, and 4.6%, respectively. Crop yield showed no significant difference under different water and N management practices. Compared with conventional flooding system, controlled irrigation saved 34.1% of irrigation water and greatly reduced nonproductive water consumption (evaporation + runoff + deep percolation) by 16.9%–20.0%, thus increasing the water use efficiency (WUE). Site-specific N management substantially reduced N losses from ammonia volatilization, leaching, denitrification, and runoff by 50.1%, 33.8%, 13.3%, and 42.7%, respectively, compared with those of the farmers’ N fertilization practice. These results indicated that the combination of controlled irrigation regime and site-specific N management regime reduced the water consumption, N losses, and N2O emission and increased WUE and N use efficiency.

Underwater channel estimation exploiting multipath feature morphology.

Real-time accurate channel estimation has been an ongoing challenge because of diverse oceanic events that cause rapid fluctuations of high-energy multipath activity across the delay spread. This work leverages current compressed sensing and sparse optimization techniques with topological signal processing to improve estimation time and localize channel estimation to salient parts of the delay spread. This work improves the estimation time by tracking the channel as a union of overlapping multipath and other scattering events, which are modeled as "feature braids" in the delay-time domain. A channel feature braid may be intuitively visualized as the topologically connected trajectory of a group of channel delay taps, which represent the support of dominant or persistent scattering events, e.g., surface bounce multipath scattering. We present algorithms that harness support-constrained mixed norm optimization techniques to track the evolving support of channel feature braids. We validate our channel feature tracking algorithm independently in experimental field data as well as BELLHOP channel simulations across a diversity of oceanic conditions. This work shows that braiding used in estimation can improve estimation time and track high-energy events that develop within the delay vs time channel representation.

Microwave Sensing for Estimating Cranberry Crop Yield: A Pilot Study Using Simulated Canopies and Field Measurement Testbeds

We present the results of an experimental and computational pilot study of cranberry crop yield prediction using low-power microwave sensing and machine learning. We simulated backscattered radiation from cranberry canopies using plane-wave illumination with frequency content from 300 to 2400 MHz. The computational canopy domains allowed for variable soil moisture and cranberry yield in terms of cranberry mass per 1 ft <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of canopy surface area. We collected experimental field data with a prototype open-ended waveguide sensor operating between 600 and 1300 MHz. We measured experimental microwave signals by placing our sensor directly on top of cranberry-crop bed canopies in central Wisconsin and recording reflection coefficients across the operating band. We implemented a machine learning approach to map the microwave reflection coefficients to yield. The mapping procedure involves dimensionality reduction with principal component analysis, supervised learning with linear discriminant analysis, and error-correcting output codes. The idealized computational results demonstrate the feasibility of discriminating three cranberry volume fractions that are representative of central Wisconsin field conditions, at frequencies below 2 GHz. Performance evaluations of the machine learning algorithm applied to the measured field data indicated that, in 81% of test cases, the predicted crop yield had less than 8% error. Most importantly, the average yield prediction error was less than 1.3%. These pilot study results provide strong evidence that machine learning enables accurate cranberry yield estimation when trained with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> (field) microwave backscattered signals.

Does moderate weight loss affect subjective health perception in obese individuals? Evidence from field experimental data

This paper analyzes whether moderate weight reduction improves subjective health perception in obese individuals. Besides simple regression models, in a simultaneous equation framework we use randomized monetary weight loss incentives as instrument for weight change, to address possible endogeneity bias. In contrast to related earlier work that also employed instrumental variables estimation, identification does not rely on long-term, between-individuals weight variation, but on short-term, within-individual weight variation. Yet, our result does not suggest that the simple regressions suffer from much endogeneity bias, since instrumental variables estimation yields similar—though far noisily estimated and statistically insignificant—estimates. In qualitative terms, our results do not contradict previous findings pointing to weight loss in obese individuals resulting in improved subjective health. Our results suggest that a reduction of body weight by one BMI unit is associated with an increase in the probability of reporting self-rated health to be ‘satisfactory’ or better by 3 to 4 percentage points. This finding may encourage obese individuals in their weight loss attempts, since they are likely to be immediately rewarded for their efforts by subjective health improvements.

Acquisition of object-robbing and object/food-bartering behaviours: a culturally maintained token economy in free-ranging long-tailed macaques

The token exchange paradigm shows that monkeys and great apes are able to use objects as symbolic tools to request specific food rewards. Such studies provide insights into the cognitive underpinnings of economic behaviour in non-human primates. However, the ecological validity of these laboratory-based experimental situations tends to be limited. Our field research aims to address the need for a more ecologically valid primate model of trading systems in humans. Around the Uluwatu Temple in Bali, Indonesia, a large free-ranging population of long-tailed macaques spontaneously and routinely engage in token-mediated bartering interactions with humans. These interactions occur in two phases: after stealing inedible and more or less valuable objects from humans, the macaques appear to use them as tokens, by returning them to humans in exchange for food. Our field observational and experimental data showed (i) age differences in robbing/bartering success, indicative of experiential learning, and (ii) clear behavioural associations between value-based token possession and quantity or quality of food rewards rejected and accepted by subadult and adult monkeys, suggestive of robbing/bartering payoff maximization and economic decision-making. This population-specific, prevalent, cross-generational, learned and socially influenced practice may be the first example of a culturally maintained token economy in free-ranging animals.This article is part of the theme issue ‘Existence and prevalence of economic behaviours among non-human primates'.

Broad or exact? Search Ad matching decisions with keyword specificity and position

In paid search advertising firms need to make decisions on a matching strategy between broad match and exact match to target their current and prospective customers. Broad match broadens the scope of targeting while exact match provides more accurate targeting. This paper investigates the relative effectiveness of matching decisions using both secondary data and a field experiment data. Both studies show that compared to exact match, broad match leads to lower advertising performance. Moreover, the negative effect of broad match on CTR is more prominent for more specific or lower (better)-position keywords, and the effects of broad match on CR, revenue and profits are less negative for higher (worse)-position keywords. These results suggest that managers of paid search advertising campaigns should take into account keyword specificity and position in making optimal matching strategy decisions for their keyword portfolios.

Significance of active speleothem δ18O at annual-decadal timescale——A case study from monitoring in Furong Cave

Stalagmites are the product of the combined effects of the surface environment and the cave environment, and their stable carbon and oxygen isotope ratios (δ18O and δ13C) have been widely used as proxies for palaeoclimatic and palaeoenvironmental reconstructions. Modern cave monitoring is essential for the accurate interpretation of multiple-proxies in stalagmites. However, the interpretation of the climatic and environmental signals indicated by the carbon and oxygen stable isotopes in stalagmites remains controversial. Based on the ongoing monitoring work of Furong Cave in Southwest China over 12 years (2008-2019 AD) involving a combination of field monitoring and experimental data, the following conclusions were drawn. (1) On the interannual scale, the isotopic fractionation of oxygen in active speleothems (AS) exhibits equilibrium fractionation. On the seasonal scale, the crystallization of a mixture of calcite and aragonite minerals is one of the reasons for the deviation of oxygen isotopic composition from the value expected under equilibrium fractionation. (2) There was a significantly positive correlation between δ18O and δ13C values in the AS, which may have been controlled by climate change rather than dynamic fractionation. (3) Mainly because of the mixing effect in the 300–500 m of bedrock overlying Furong Cave, the δ18O value of the drip water reflected the annual average δ18O value of precipitation. (4) The AS δ18O (δ18OAs) values over the 12-year monitoring records did not show significant seasonal variations but exhibited multiyear trend, which might reflect changes in the external atmospheric circulation and “amount effect” on decadal and longer timescales. Consequently, speleothem δ18O values in Furong Cave can be used for isotope-based palaeoclimate reconstruction.

МОДЕЛИРОВАНИЕ УСТАЛОСТНОЙ ДОЛГОВЕЧНОСТИ КОНСТРУКЦИОННЫХ СПЛАВОВ ПРИ ДВУХЧАСТОТНОМ НАГРУЖЕНИИ

The processes of fatigue life of polycrystalline structural alloys under the combined action of low- and high-cycle fatigue mechanisms are considered. From the standpoint of damaged medium mechanics (DMM), a mathematical model has been developed that describes the processes of plastic deformation and the accumulation of fatigue damage. The DMM model consists of three interrelated parts: relations that determine the cyclic elastoplastic behavior of the material, taking into account the dependence on the fracture process; equations describing the kinetics of fatigue damage accumulation; criterion for the strength of the damaged material. Variant of the constitutive relations for elastoplasticity is based on the concept of a microplastic loading surface in the von Mises form and the principle of the gradient of the plastic strain rate vector to the surface at the loading point. This version of the equations of state reflects the main effects of the process of cyclic plastic deformation of the material for arbitrary complex loading trajectories. A variant of the kinetic equations for the accumulation of fatigue damage is based on the introduction of a scalar damage parameter, is based on energy principles and takes into account the main effects of the formation, growth and fusion of microdefects under arbitrary complex loading conditions. A unified form of the evolutionary equation for the accumulation of fatigue damages for low-cycle and high-cycle fatigue is proposed. As a criterion for the strength of the damaged material, the condition for reaching the critical value of the damage is used. To assess the reliability and determine the limits of applicability of the constitutive relations of the DMM, numerical studies of the processes of accumulation of fatigue damage by cyclic inelastic deformation and fatigue failure of steel 20 and 08Х18Н12Т were carried out under single-frequency loading of the upper frequency and two-frequency loading with different amplitude ratios. And the comparison of the obtained numerical results with the data of field experiments is carried out. The results of comparing the calculated and experimental data showed that the developed model of the damaged environment reliably describes the durability of structures under the action of low- and high-cycle fatigue mechanisms.

ЧИСЛЕННОЕ ИССЛЕДОВАНИЕ ПРОЦЕССА ВЫСОКОТЕМПЕРАТУРНОЙ ПОЛЗУЧЕСТИ И ДЛИТЕЛЬНОЙ ПРОЧНОСТИ КОНСТРУКЦИОННЫХ СПЛАВОВ ПРИ ОДНООСНОМ РАСТЯЖЕНИИ

The main regularities of deformation processes are consideredand degradation of the initial strength properties of structural materials (metals and their alloys) by the mechanism of long-term strength. To describe the processes of high-temperature creep and long-term strength of polycrystalline structural alloys, an approach based on the concept of “hidden” or “internal” parameters is used, which can give a qualitative and quantitative description of experimental data. This approach has two important advantages: it allows you to cover a wide range of behavior of structural materials and at the same time it is very convenient for analyzing the stress-strain state. The mathematical model of the mechanics of a damaged medium used in this work, describing the processes of inelastic deformation and damage accumulation during creep, consists of three interrelated components: evolutionary relations that determine the inelastic behavior of the material, considering the dependence on the destruction process; kinetic equations describing the process of damage accumulation; criteria for the strength of the damaged material. The variant of the determining relations of viscoplastic deformationof polycrystalline structural alloys is based on the idea of the existence of a family of equipotential creep surfaces in the stress space and the principle of gradiency of the creep strain rate vector to the corresponding surface at the loading point.This version of the equations of state reflects the main regularitiesthe process of viscoplastic deformation of the material under proportional and disproportionate modes of combined thermomechanical loading. The variant of the kinetic equations of damage accumulation is based on theintroduction of a scalar damage parameter, is based on energy principles, and considers the main effects of the formation, growth and fusion of microdefects for arbitrary complex modes of thermomechanical loading. As a criterion of the strength of the damaged material, the condition for reaching the critical value of the damage value is used. The results of experimental studies of short-term high-temperature creep of several structural alloys (copper, stainless steel X18H10T) at constant temperature values and various levels of forces set in the samples are presented. To assess the degree of reliability and determine the limits of applicabilitymodels of the mechanics of the damaged medium numerical studies of the process of high-temperature creep and long-term strength of these structural alloys are carried out and the numerical results obtained are compared with the data of field experiments. The results of comparing the calculated and experimental data allow us to conclude that the proposed determining relationships are reliable when the initial strength properties of structural materials are degraded by the mechanism of long-termstrength. It is shown that the model used qualitatively and with the accuracy necessary for practical calculations quantitatively describes the main effects of the process of viscoplastic deformation and damage accumulation in polycrystalline structural alloys under high-temperature thermomechanical loading.

Inflation of water to the soil in the fields of drop irrigation

The article presents theoretical and field experimental data on determining the rates of infiltration and filtration of irrigation water in the soil - grounds of the calculated layer in the cotton fields of the Dzharkurgan massif in the Surkhandarya region. Based on the established values of the rates of infiltration of irrigation water, the drip irrigation regime for cotton of the new Sultan variety has been determined, the parameters of the innovative drip irrigation technology have been determined.

A simple and robust model for prediction of liquid-loading onset in gas wells

Accurate prediction of liquid loading is of great importance for production optimisation in gas wells. In this paper, the authors present a simple and accurate empirical model based on attached-film reversal for predicting liquid-loading onset in vertical and horizontal gas wells. Unlike established and complicated analytical models based on force balance, this model is developed from the empirical flooding equation by matching the experimental data from previous studies. Further, this model adopts the Belfroid angle-correction term for horizontal gas wells. Compared with the traditional entrained-droplet models, this model considers the effect of pipe diameter and liquid velocity. This study investigated the effect of pressure on the predicted critical gas velocity and scaled up low pressure by comparing some other analytical models. This model was also validated against the experimental data and field data. Results show that the presented model is capable of accurately predicting liquid-loading onset in gas wells. [Received: December 4, 2018; Accepted: December 13, 2019]

Simulation of Soil Salinity using DRAINMOD-S Model under Subsurface Drainage System in Arid and Semi-arid Regions of Punjab, India

Water management simulation model DRAINMOD-S was calibrated (1995-96) and validated (1997) using 3-year experimental field data (1995-1997) from the installed subsurface drainage system at 1.8 m drain depth with 40, 60, and 80 m drain spacing at Golewala watershed, Faridkot, Punjab, India. Sensitivity analysis of the model parameters revealed that lateral saturated hydraulic conductivity, drain depth, and drain spacing are the most effective parameters in changing the model output. The root mean square error, efficiency, and coefficient of determination between observed and simulated soil salinity ranged from 0.01to 0.06 dS.m-1, 0.647 to 0.834 dS.m-1 and 0.957 to 0.999 dS.m-1 for three drain spacings (40, 60 and 80 m), respectively, during calibration and validation period. The calibrated and validated model was used to predict the soil salinity (EC) for five consecutive years (1998-2003). The average soil salinity of root zone (300-600 mm), (600-900 mm) and (900-1200 mm) decreased from January, 1998 to December, 2003. The predicted values of soil salinity were found to decrease from 2.23, 2.34, and 1.92 dS.m-1 to 1.68 dS.m-1, 1.70 and 1.42 dS.m-1 for 40 m drain spacing at root zone depth of 300-600 mm, 600-900 mm, and 900-1200 mm, respectively. Similarly, the salinity values for the same period and root zone depth were found to decrease from 2.20, 2.31, and 1.90 dS.m-1 to 1.75,1.78, and 1.74 dS.m-1 for 60 m drain spacing; and 2.21, 2.31, and 1.93 dS.m-1 to 1.80,1.82, and 1.48 dS.m-1 for 80 m drain spacing, respectively, at the end of five years. DRAINMOD-S model was reliably applicable for predicting soil salinity under sub-surface drainage system in arid and semi-arid region of Punjab, India.

Modeling the Effects of Crop Rotation and Tillage on Sugarbeet Yield and Soil Nitrate Using RZWQM2

HighlightsFour crop growth modules in RZWQM2 were calibrated for four sugarbeet rotation sequences.Sugarbeet following wheat had a slightly higher yield (3% to 6.5%).Moldboard plow increased sugarbeet yield by 1% to 2%.The difference in N losses under different crop rotations and tillage operations was negligible.Abstract. Sugarbeet (Beta vulgaris) is considered to be one of the most viable alternatives to corn for biofuel production as it may be qualified as the feedstock for advanced biofuels (reducing greenhouse gas emission by 50%) under the Energy Independence and Security Act (EISA) of 2007. Because sugarbeet production is affected by crop rotation and tillage through optimal use of soil water and nutrients, simulation of these effects will help in making proper management decisions. In this study, the CSM-CERES-Beet, CSM-CERES-Maize, CROPSIM-Wheat, and CROPGRO-Soybean models included in the RZWQM2 were calibrated against experimental field data of crop yield, soil water, and soil nitrate from the North Dakota State University Carrington Research Extension Center from 2014 to 2016. The models performed reasonably well in simulating crop yield, soil water, and nitrate (rRMSE = 0.055 to 2.773, d = 0.541 to 0.997). Simulation results identified a non-significant effect of crop rotation on sugarbeet yield, although sugarbeets following wheat resulted in 3% to 6.5% higher yields compared to other crops. Net mineralization and N uptake rates were slightly higher when sugarbeets followed wheat compared to the other crops. Seasonal N and water mass balances also showed lower N and water stresses when sugarbeets followed wheat. The effects of tillage operations on sugarbeet yield were also non-significant. The difference in the N losses to runoff and drainage from the sugarbeet fields under different crop rotations and tillage operations was negligible. As sugarbeet production may be expanded into nontraditional planting areas in the Red River Valley due to potential demand for biofuel production, our findings will help to assess the associated environmental impacts and identify suitable crop rotations and management scenarios in the region. Keywords: Biofuel, Crop rotation, RZWQM2, Sugarbeet, Tillage.

Spatial kernel models capturing field heterogeneity for accurate estimation of genetic potential.

According to Fisher’s principles, an experimental field is typically divided into multiple blocks for local control. Although homogeneity is supposed within a block, this assumption may not be practical for large blocks, such as those including hundreds of plots. In line evaluation trials, which are essential in plant breeding, field heterogeneity must be carefully treated, because it can cause bias in the estimation of genetic potential. To more accurately estimate genotypic values in a large field trial, we developed spatial kernel models incorporating genome-wide markers, which consider continuous heterogeneity within a block and over the field. In the simulation study, the spatial kernel models were robust under various conditions. Although heritability, spatial autocorrelation range, replication number, and missing plots directly affected the estimation accuracy of genotypic values, the spatial kernel models always showed superior performance over the classical block model. We also employed these spatial kernel models for quantitative trait locus mapping. Finally, using field experimental data of bioenergy sorghum lines, we validated the performance of the spatial kernel models. The results suggested that a spatial kernel model is effective for evaluating the genetic potential of lines in a heterogeneous field.

QUANTIFYING THE INFLUENCE OF TRANSITIONS ON GRASS COVER EROSION BY OVERTOPPING WAVES

Transitions in vegetated dike covers, such as geometry changes or roughness differences, are identified as weak spots in dikes for grass cover erosion by wave overtopping. Although several erosion models exist to model grass cover erosion on dikes, it is unclear how the effect of transitions on grass cover erosion must be included in these models. Therefore, we have developed a model approach to analyze the effects of transitions on grass cover erosion using field experimental data and to derive representative influence factors for one transition type. The model approach has been applied to the transition at the landward toe where the slope changes to a horizontal plane. The model approach is general applicable and can be transferred easily to other transitions. The derived factors can be used to improve predictions of dike cover erosion near transitions.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/YVH6PN4-Er0

Multi-Gene Genetic Programming Regression Model for Prediction of Transient Storage Model Parameters in Natural Rivers

A Transient Storage Model (TSM), which considers the storage exchange process that induces an abnormal mixing phenomenon, has been widely used to analyze solute transport in natural rivers. The primary step in applying TSM is a calibration of four key parameters: flow zone dispersion coefficient (Kf), main flow zone area (Af), storage zone area (As), and storage exchange rate (α); by fitting the measured Breakthrough Curves (BTCs). In this study, to overcome the costly tracer tests necessary for parameter calibration, two dimensionless empirical models were derived to estimate TSM parameters, using multi-gene genetic programming (MGGP) and principal components regression (PCR). A total of 128 datasets with complete variables from 14 published papers were chosen from an extensive meta-analysis and were applied to derivations. The performance comparison revealed that the MGGP-based equations yielded superior prediction results. According to TSM analysis of field experiment data from Cheongmi Creek, South Korea, although all assessed empirical equations produced acceptable BTCs, the MGGP model was superior to the other models in parameter values. The predicted BTCs obtained by the empirical models in some highly complicated reaches were biased due to misprediction of Af. Sensitivity analyses of MGGP models showed that the sinuosity is the most influential factor in Kf, while Af, As, and α, are more sensitive to U/U*. This study proves that the MGGP-based model can be used for economic TSM analysis, thus providing an alternative option to direct calibration and the inverse modeling initial parameters.

Global negative effects of nutrient enrichment on arbuscular mycorrhizal fungi, plant diversity and ecosystem multifunctionality.

Despite widespread anthropogenic nutrient enrichment, it remains unclear how nutrient enrichment influences plant-arbuscular mycorrhizal fungi (AMF) symbiosis and ecosystem multifunctionality at the global scale. Here, we conducted a meta-analysis to examine the worldwide effects of nutrient enrichment on AMF and plant diversity and ecosystem multifunctionality using data of field experiments from 136 papers. Our analyses showed that nutrient addition simultaneously decreased AMF diversity and abundance belowground and plant diversity aboveground at the global scale. The decreases in AMF diversity and abundance associated with nutrient addition were more pronounced with increasing experimental duration, mean annual temperature (MAT) and mean annual precipitation (MAP). Nutrient addition-induced changes in soil pH and available phosphorus (P) predominantly regulated the responses of AMF diversity and abundance. Furthermore, AMF diversity correlated with ecosystem multifunctionality under nutrient addition worldwide. Our findings identify the negative effects of nutrient enrichment on AMF and plant diversity and suggest that AMF diversity is closely linked with ecosystem function. This study offers an important advancement in our understanding of plant-AMF interactions and their likely responses to ongoing global change.