The Augmented Kalman Filter (AKF) has been applied previously for input-state estimation of offshore wind turbines (OWT). However, the accuracy of the estimated results depend on the chosen model, for which various complexities exist, making this a challenging task. Two of which are the lack of information required to model the Rotor-Nacelle Assembly (RNA), and the high uncertainty associated with the soil-structure-interaction (SSI). Therefore, the primary focus of this work is to avoid these limitations by considering a suitable substructure which eliminates the need to model the RNA and the SSI, thus significantly reducing uncertainties. The substructure is obtained by 'cutting' the OWT at the top of the tower and at the ground level. To define the model, the resulting substructure then only requires geometries and material properties for the monopile and tower; information which is often known with greater certainty. A numerical case study is presented to investigate the accuracy of the proposed approach for input-state estimation of a 15 MW OWT. A series of commonly used setups involving accelerometers and inclinometers are used and the effects on the predicted fatigue life of the structure are discussed. Additionally, a simple approximation of the wave loading is considered to estimate and account for its contribution to the dynamics of the substructure. The proposed approach is shown to be an effective solution for input-state estimation of OWTs when the RNA or SSI are unknown or associated with significant uncertainty.

Seismic fragility denotes the probabilities of a system exceeding some prescribed damage levels under a range of seismic intensities. Classical seismic fragility studies in slope engineering usually construct fragility functions by making some assumptions for fragility curve shape, and always neglect spatial variability of soil materials. In this study, an assumption-free method on the basis of probability density evolution theory (PDET) is proposed for seismic fragility assessment of slopes. The random input earthquakes and spatially-variable soil parameters in slope are simultaneously quantified. By the proposed method, assumption-free fragility curves of a slope are established without limiting the fragility curve shape. The obtained fragility results are also compared with those from two classic parametric fragility methods (linear regression and maximum likelihood estimation) and Monte Carlo simulation. The results demonstrate that the proposed assumption-free method has potential to gives more rigorous and accurate fragility results than classical parametric fragility analysis methods. With the proposed method, more reliable fragility results can be obtained for slope seismic risk assessment.

Mato Grosso is the largest consumer of pesticides in Brazil, and although their role in phytosanitary control is evident, environmental contamination is a concern due to their intensive use. Therefore, identifying the behavior of pesticides in the environment can assist in risk management, and the Environmental Risk Index (ERI) is an indirect way of knowing the potential of these compounds. This study was aimed at evaluating the ERI of the most sold insecticides in Mato Grosso used for the control of lepidopteran pests. The parameters evaluated were persistence in the soil, leaching, volatility, toxicological profile and recommended dose. Our findings reported on 24 insecticides, which totaled an annual amount of 23,046,348 kg of active ingredients, with acephate at the top of the ranking with 8,974,413 kg sold in 2020. This insecticide, despite being widely used, had the lowest ERI due to low persistence, leaching and volatility, and its critical factor was animal toxicity. Malathion, methoxyphenozide, chlorantraniliprole, flubendiamide, and beta-cyfluthrin had the highest ERI, with toxicological profile and persistence in the environment as critical factors. In general, all compounds exhibited medium to very high levels of toxicity, indicating the need to manage risks associated with insecticide use and select those with lower impact, to minimize damage to agroecosystems.

The constitutive model is essential for predicting the deformation and stability of rock-soil mass. The estimation of constitutive model parameters is a necessary and important task for the reliable characterization of mechanical behaviors. However, constitutive model parameters cannot be evaluated accurately with a limited amount of test data, resulting in uncertainty in the prediction of stress-strain curves. This paper proposes a Bayesian analysis framework to address this issue. It combines the Bayesian updating with the structural reliability and adaptive conditional sampling methods to assess the equation parameter of constitutive models. Based on the triaxial and ring shear tests on shear zone soils from the Huangtupo landslide, a statistical damage constitutive model and a critical state hypoplastic constitutive model were used to demonstrate the effectiveness of the proposed framework. Moreover, the parameter uncertainty effects of the damage constitutive model on landslide stability were investigated. Results show that reasonable assessments of the constitutive model parameter can be well realized. The variability of stress-strain curves is strongly related to the model prediction performance. The estimation uncertainty of constitutive model parameters should not be ignored for the landslide stability calculation. Our study provides a reference for uncertainty analysis and parameter assessment of the constitutive model.

This paper presents a data-driven model updating framework to estimate the operational parameters of a laterally-impacted pile. The goal is to facilitate the estimation of soil-pile interaction parameters such as the mobilized mass and stiffness, as well as geometrical data such as embedded pile length, using output-only information. Accurate knowledge of mass, stiffness, and pile embedded length is essential for understanding foundation behavior when developing digital-twin models of structures for the purpose of damage detection. The method first employs subspace identification to determine modal parameters and quantifies their uncertainties using output-only data. The covariance matrix adaptation evolution strategy (CMA-ES), a stochastic evolutionary algorithm, is subsequently used to update the model. The effectiveness of the approach is demonstrated through its application to numerical models in this paper, to quantify errors, and subsequently to data from a documented full-scale field test of a pile subjected to an impact load. The work underscores the potential of statistical updating in advancing the accuracy and reliability of soil-structure interaction parameter estimation for systems where only output data might exist.

Soil salinization in arid and coastal areas poses a significant threat to crop production, which is further aggravated by climate change and the over-exploitation of aquifers. Cultivation of salt and drought-tolerant crops such as quinoa represents a promising adaptation pathway for agriculture in saline soils. Quinoa (Chenopodium quinoa Willd.) is a salt-loving plant, known for its tolerance to drought and salinity using complex stress responses. However, available models of quinoa growth are limited, particularly under salinity stress. The objective of this study was to calibrate the crop growth, and salinity and drought stress parameters of the SWAP - WOFOST model and evaluate whether this model can represent quinoa's stress tolerance mechanisms. Field experimental data were used from two quinoa varieties: ICBA-Q5 grown under saline conditions in Laayoune, Morocco, in 2021, and Bastille grown under rainfed, non-saline conditions in Merelbeke, Belgium, from 2018 to 2023. Calibration and parameter uncertainty was performed using the DiffeRential Evolution Adaptive Metropolis (DREAMzs) algorithm on key parameters identified via sensitivity analysis using the Morris method. The resulting crop parameters provide insights into the stress tolerance mechanisms of quinoa, including reduction of transpiration and uptake of solutes. The salinity stress function of SWAP effectively represents these tolerance mechanisms and accurately predicts the impact on yield, under arid conditions. Under Northwestern European climate, the model replicates the impact of drought stress on yield. The calibrated model offers perspectives for evaluating practices to reduce soil salinization in arid conditions and for modeling crop performance under water-limited conditions or future salinization in temperate regions.

Storage of nematode-infected soil, roots and nematode suspensions is important in nematological research. The available storage methods are based on potato cyst nematodes, where cysts with viable eggs can be stored for long periods at 4 degrees C. When dealing with other nematode species, understanding the effect of storage temperature is crucial. This study was designed to investigate the decline rate and survival of four root-knot and a lesion nematode of both temperate and tropical origin, when stored at 4 degrees C in three substrates: water, soil and roots. The starting density (P-i ) for each substrate was determined at t = 0 and survival of all nematode species was estimated at 10-day intervals for 100 days. During storage, population densities of all species declined in all substrates exponentially. A slower decline rate (r(d) = 0.988-0.999) was observed for juveniles of Meloidogyne fallax in water, soil and roots compared to juveniles of M. hapla and Pratylenchus penetrans. Meloidogyne incognita was seriously affected by cold storage with the highest decline rate (r(d) = 0.919-0.977) observed in all substrates. Only data on the root substrate were obtained for M. javanica with a decline rate of (r(d) = 0.977) predicting zero survival at t > 100 days. Notable is the higher fraction of surviving P. penetrans (P-i = 0.238-0.545) in all substrates during the storage period, compared with all other species. Based on the results, it is recommended to process nematode samples in the three substrates as quickly as possible, as underestimation of the actual population densities is likely. Consequences of cold storage in handling and processing of samples from different substrates are discussed.

Elemental carbon (EC), also known as black carbon, plays an important role in climate change. Accurately assessing EC concentration in aerosols remains challenging due to the overestimations caused by carbonates and organic carbon (OC) during thermal-optical measurement in the Tibetan Plateau (TP). This study evaluates the extent of EC overestimated by carbonates and OC at four remote sites (Nyalamu, Lulang, Everest and Ngari) in southern and western of the TP using different treatments. The average overestimation of EC concentration due to acid treatment was consistent across all sites (25.5 f 2.4 %). After correction, the proportion of EC overestimated by carbonates were approximately 8.5 f 7.3 %, 12.3 f 6.9 %, 18.1 f 11.8 % and 22.7 f 13.3 %, respectively, revealing an increasing trend from humid to arid regions. Methanol-soluble OC (MSOC) concentrations were significantly correlated with the reduction of EC concentrations, indicating that the methanol extraction effectively mitigates EC overestimation. Seasonal variation of carbonaceous aerosol concentrations was significantly affected by sources from South Asia. Despite the variations in climate and aerosol sources, the average overestimations of measured EC concentration by carbonates and OC were similar at Nyalamu (49.4 f 14.0 %), Lulang (47.8 f 8.4 %), Everest (48.7 f 15.9 %) and Ngari (49.3 f 13.7 %) sites. Therefore, the actual EC concentrations were only about 51.2 f 13.1 % of the original values. This estimation will significantly enhance the contribution of brown carbon (BrC) to radiative forcing relative to EC, highlighting a critical area for future research. Investigating the actual concentrations of EC in the TP provides critical data to support model simulation and validate model accuracy, further enhancing our understanding of EC's impacts on climate warming and glacier melting.

A vertical tube surface drip irrigation system was designed to address the damage caused by soil drought and high surface temperature to sand-fixing seedlings in a plant sand-fixation area. Numerical simulation and experimental verification were used to study soil water movement with vertical tube infiltration and surface drip irrigation for four aeolian sandy soils with different hydraulic conductivity (Ks), drip discharge (Q), vertical tube diameter (D), and vertical tube buried depth (B). The results show that a power function relationship exists between the soil-stable infiltration rate (if) and Ks, D, and B given the condition of vertical tube water accumulated infiltration, and its coefficient is 0.17. The power function indices of Ks, D, and B are 0.87, 1.89, and -0.37, respectively. The if can be used to determine the maximum drip discharge (Qmax) of the dripper in the vertical tube to ensure that the sand-fixing plants are not submerged during drip irrigation through the vertical tube (Qmax=if). The wetting front transport distance in the three directions increased with increasing Ks and Q but decreased with increasing D and B. After determining the time required for water to reach the bottom of the vertical tube, an estimation model of soil wetting body transport for vertical tube surface drip irrigation, including Ks, Q, D, and B, was constructed. Compared with the experimental data, the root mean square error (RMSE) is between 0.17 and 0.42 cm, and the Nash-Sutcliffe efficiency (NSE) is at least 0.88. Therefore, the model is appropriate and can provide valuable practical tools for the design of vertical tube surface drip irrigation in different plant sand fixation areas. A surface drip irrigation system and pipe protection technology were combined to form a vertical tube surface drip irrigation system to address the damage caused by soil drought and high surface temperature to sand-fixing seedlings. However, this irrigation technology has the problem that it is difficult to quantify the matching of drip discharge and pipe parameters (vertical tube diameter and burial depth), wetted soil volume, and plant roots due to the single soil sample used in the laboratory experiments. This paper considers the influence of soil differences in diverse plant sand-fixing areas and establishes a stable infiltration rate model to determine the maximum drip discharge. Additionally, a soil wetted volume prediction model was developed by combining HYDRUS-2D simulations and experimental verification. The model is simple and has high prediction accuracy, which is convenient for designers to determine the appropriate vertical tube parameters for different plant sand-fixation areas.

The Canadian prairies are renowned for their substantial agricultural contributions to the global food market. Harrow tines are indispensable in farming equipment, especially for soil preparation and weed control before planting crops. During operation, these tines are exposed to repetitive cyclic loading, which eventually causes fatigue failure. Commercially available three different harrow tines named 0.562HT, 0.625HT, and 0.500HT undergo an experimental fatigue evaluation and are validated through Finite Element Analysis (FEA). Fatigue life estimation for different deflections under various real-field deflections was carried out where 0.562HT showed groundbreaking life compared with others. The study results showed that the fatigue life is highly dependent on geometry, number of coils, pitch angle, leg length, and coil diameter. The 0.354HT model, developed to investigate the effect of wire diameter, closely resembles the 0.500HT model. The harrowing ability of the four different harrow tine models against identical deflections has been analyzed. Experimental fractured surfaces went through morphological investigation. This research has an impeccable impact on prairies' agricultural acceleration by saving time and mitigating unpredictable fatigue failure often faced by farmers. Even the observed failure phenomena can serve as motivation to develop more reliable and durable harrow tines, which could increase agricultural efficiency. Higher coil diameter and lower pitch results in higher spring stiffness and load-carrying capability.Harrow tines have shorter lifespans with smaller diameters within a range and with larger or smaller diameters beyond thresholds.Higher tapered angles reduce cyclic load capacity due to increased stress concentration from the smaller surface area of each coil.