Offshore structures typically experience multiple storms during their service life. The soil around the foundations of offshore structures is subjected to cyclic loading during storm and reconsolidates between storms. Therefore, it is essential to understand the fundamental soil behaviour under episodic cyclic loading and reconsolidation to evaluate the long-term serviceability of offshore foundations. This paper presents experimental results of a comprehensive suite of cyclic DSS tests on a normally consolidated silty clay. The tests explore the soil response under different cyclic loading patterns (e.g., one-way or two-way), different cyclic amplitudes and number of cycles. A theoretical model, which combines the conventional cyclic contour diagram approach and principles of the critical state soil mechanics, is proposed and validated for predicting the cyclic soil response during undrained cyclic loading and hardening after reconsolidation. The model proposed in this paper paves a critical step for developing long-term soil-structure interaction models that are fundamentally linked to soil element level responses.

The direct simple shear (DSS) test serves as a vital method in geotechnics, allowing the measurement of peak and post-liquefaction shear strengths, along with the critical state friction angle of soils. Additionally, the simple shearing mode applied in a DSS test is the predominant failure mode in many geotechnical engineering problems. Although the DSS test is widely used to determine soil strength, a significant challenge with the DSS device is the non-uniformity of stress and strain distributions at the specimen boundaries. This non-uniformity depends on not only the specimen size but also the size of soil particles. The influence of specimen size on boundary effects is typically evaluated using the ratio of specimen diameter (D) to height (H). The median particle diameter (D50), as an indicator of a soil's particle size, could be another influential factor affecting the non-uniformities of stress and strain on specimen boundaries in a DSS test. Through three-dimensional discrete element method (DEM) simulations, this research explores these factors. Specimens were generated with a particle size distribution (PSD) scaled from a coarse sand sample. Laboratory monotonic DSS testing results on the coarse sand were employed to calibrate the DEM model and ascertain the modeling parameters. Boundary displacements were regulated to maintain a constant-volume condition which represents undrained shearing behavior. Various specimen diameters were simulated with identical void ratios to investigate the influence of D/H on stress path, peak and post-peak shear strengths, and critical state behavior. DEM simulations allowed the generation of several particle size distributions through different scaling factors applied to the sand gradation to determine the combined effect D50 and D/H. Limiting D/H and D50/D ratios are subsequently proposed to mitigate specimen boundary effects.

Soil plays a crucial role in hydraulic-forestry and bioengineering works, influencing the design, construction, and implementation of measures aimed at mitigating land degradation and promoting environmental restoration. These systems involve various intensive and extensive interventions designed to address the causes and effects of land instability, particularly in hilly and mountainous torrent basins. A key objective is to create favourable conditions for vegetation re-establishment. Recent advancements have emphasized the use of natural engineering techniques, soil and water bioengineering, and nature-based solutions over traditional masonry structures. These innovative approaches not only restore damaged areas but also focus on preventing future degradation by addressing underlying causes, often related to soil properties and management practices. This review provides an overview of recent developments in Italy, showcasing practical examples of solutions that leverage soil knowledge and mapping, and the use of decision support systems and Geographic Information Systems (GIS). The meta-analysis identifies key soil properties influencing hydrological behavior, which must be considered when assessing hydraulic and geological risk in forested areas and when planning bioengineering or nature-based interventions.

Climate change still adversely affects agriculture in the sub-Saharan Africa. There is need to strengthen early action to bolster livelihoods and food security. Most governments use pre- and post-harvest field surveys to capture statistics for National Food Balance Sheets (NFBS) key in food policy and economic planning. These surveys, though accurate, are costly, time consuming, and may not offer rapid yield estimates to support governments, emergency organizations, and related stakeholders to take advanced strategic decisions in the face of climate change. To help governments in Kenya (KEN), Zambia (ZMB), and Malawi (MWI) adopt digitally advanced maize yield forecasts, we developed a hybrid model based on the Regional Hydrologic Extremes Assessment System (RHEAS) and machine learning. The framework is set-up to use weather data (precipitation, temperature, and wind), simulations from RHEAS model (soil total moisture, soil temperature, solar radiation, surface temperature, net transpiration from vegetation, net evapotranspiration, and root zone soil moisture), simulations from DSSAT (leaf area index and water stress), and MODIS vegetation indices. Random Forest (RF) machine learning model emerged as the best hybrid setup for unit maize yield forecasts per administrative boundary scoring the lowest unbiased Root Mean Square Error (RMSE) of 0.16 MT/ha, 0.18 MT/ha, and 0.20 MT/ha in Malawi's Karonga district, Kenya's Homa Bay county, and Zambia's Senanga district respectively. According to relative RMSE, RF outperformed other hybrid models attaining the lowest score in all countries (ZMB: 25.96%, MWI: 28.97%, and KEN: 27.54%) followed by support vector machines (ZMB: 26.92%, MWI: 31.14%, and KEN: 29.50%), and linear regression (ZMB: 29.44%, MWI: 31.76%, and KEN: 47.00%). Lastly, the integration of VI and RHEAS information using hybrid models improved yield prediction. This information is useful for NFBS bulletins forecasts, design and certification of maize insurance contracts, and estimation of loss and damage in the advent of climate justice.

The soil response under the inherent cyclic loading conditions when dealing with offshore foundations can be considered by using contour plots. These plots are derived from several cyclic laboratory tests and characterize the general cyclic soil behaviour. In the design process with explicit numerical methods, such plots are needed in order to assess the soil behaviour under arbitrary loading conditions and hence estimate the cyclic foundation response. In the paper, excess pore pressure contour plots for a poorly graded medium sand are derived from numerous constant volume (CV) cyclic direct simple shear (DSS) tests and a new approach for parametrization of the plots is presented. Subsequently, the data are assessed regarding scaling for other sand soils, i.e., construction of contour plots with only a small number of test results by using the general trends observed.

The paper details some practical considerations associated with the numerical simulation of liquefaction in Wildlife site in Southern California. Two material constitutive models are implemented in the simulations: a pressure-dependent multi-yield-surface model (PDMY) and PM4Sand, both available in the OpenSees finite elements platform. Both uniaxial as well as biaxial simulations are presented in the paper. The uniaxial simulations only include the predominant horizontal shaking component while the biaxial simulations include both orthogonal horizontal shaking components. Two historical major earthquake events were simulated: the 1987 Superstition Hills and the 2010 El Mayor Cucapah earthquakes. Laboratory experimental data used for calibration of the material models was obtained from historical data published in the 1980's. This data is particularly valuable since they correspond to intact (undisturbed) samples extracted from Wildlife site about two years before occurrence of the 1987 earthquake. In all the simulations, the models were able to capture salient features of the deposit's behavior, such as the magnitude of surface accelerations, and dilative behavior of the soil. However, the excess pore water pressure rises earlier than what the site recordings indicates. This may be attributed to the fact that the constitutive models do not consider the concept of volumetric threshold shear strain below which no excess pore water pressure is generated during cyclic shear loading. It was also found that there was a significant overestimation of the excess pore pressure for the 2010 El Mayor Cucapah earthquake simulations. This may be attributed to the effect of the site shaking history which increased the site resistance to liquefaction. This added resistance was not reflected by the numerical model since it was calibrated with samples extracted about 25 years before the 2010 earthquake.

利用2020年12月至2021年5月的人工观测雪深数据，对青海省平安、达日、曲麻莱3站的DSS1型雪深观测仪雪深数据、HY-WP1A型天气现象智能观测仪雪深数据进行了评估和对比分析。结果表明，2种设备对雪深都有一定的监测能力；DSS1型激光雪深仪雪深数据与人工数据相关系数分别为0.803 7、0.990 6、0.990 7，二者有极显著的线性关系；HY-WP1A型天气现象视频观测仪雪深数据与人工数据相关系数分别为0.023 4、0.421 6、0.923 3，二者存在明显差异；对于青海地区的雪深观测方式，降雪量小、地面积雪偏少时以HY-WP1A型天气现象视频观测仪雪深数据为准，另外的情况以DSS1型激光雪深仪雪深数据为准。

利用2020年12月至2021年5月的人工观测雪深数据，对青海省平安、达日、曲麻莱3站的DSS1型雪深观测仪雪深数据、HY-WP1A型天气现象智能观测仪雪深数据进行了评估和对比分析。结果表明，2种设备对雪深都有一定的监测能力；DSS1型激光雪深仪雪深数据与人工数据相关系数分别为0.803 7、0.990 6、0.990 7，二者有极显著的线性关系；HY-WP1A型天气现象视频观测仪雪深数据与人工数据相关系数分别为0.023 4、0.421 6、0.923 3，二者存在明显差异；对于青海地区的雪深观测方式，降雪量小、地面积雪偏少时以HY-WP1A型天气现象视频观测仪雪深数据为准，另外的情况以DSS1型激光雪深仪雪深数据为准。