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One of the most effective systems for managing water is subsurface trickle irrigation. Finding empirical formulas and studying the effect of soil texture are the main purposes of this paper. In order to reach an ideal irrigation system as a modern technique to save water, especially in arid regions, soil textures of loam, silt, and silt loam were studied on a subsurface trickle irrigation system by utilizing HYDRUS/2D. The trickle system is usually operated at low pressure, in this paper the used pressure is 30 cm with an emitter buried at 10, 15, and 20 cm at different diameters. Patterns of wetting fronts in both directions at various times depending on soil texture are gathered to find out empirical formulas that are a function of operative time, emitter diameter, depth of buried, and finally, saturated hydraulic conductivity. The statistical parameters make it evident that the formulas provide reasonable prediction accuracy in both dimensions wetted width & depth. The percentage of mean relative error is less than 3%, and the coefficient of determination of both dimensions is more than 0.990. Moreover, the simulation results of this paper are compared with field experiments and based on relative error to find a precise distribution of water around a trickle.

The quantitative characterization of tactile perception, which is crucial in the design of tactile devices, requires the tested samples to have individually and precisely controlled properties associated with the senses. In this work, we microfabricated such tactile samples and then quantitatively characterized tactile perception with a focus on roughness and dryness. In the roughness perception experiments, the tactile samples had a stripe pattern with ridge and groove widths that were individually controlled. The experimental results revealed that the feeling of roughness was more dominated by the width of the groove than that of the ridge and that conventionally used roughness parameters such as Sa and Sq were not sufficient for predicting roughness perception. In the dryness perception experiments, the tactile samples had a micropattern formed by dry etching and an array of squares. The experimental results revealed that dry perception had different properties when the feature sizes were below and above 30 µm, which may have been due to the effect of adhesion on friction. The proposed tactile samples were suitable for the quantitative and precise characterization of tactile perception.

Red-bed argillaceous siltstone is a common soft rock in the drawdown area of water diversion project extending from the Yangtze to Huaihe Rivers, with the characteristics of water softening and disintegration, which directly threatens the stability and safety of the diversion project. To better understand the effect of cyclic drying–wetting on the disintegration characteristics and mechanism, disintegration experiments were conducted on the red-bed argillaceous siltstone from the Tongcheng area of the water diversion project extending from the Yangtze to Huaihe Rivers. Experimental results indicated that, with an increasing number of drying–wetting cycles, the red-bed argillaceous siltstone was gradually crushed, large particles gradually transformed into small particles. A microstructural analysis showed that a continuous drying–wetting process resulted in the sample surface becoming disordered and complicated, and new micro-fractures and pores were generated. Notable changes in the concentrations of ions in the soaking solutions indicated continuous dissolution of the minerals, and a large amount of mineral loss under the action of cyclic drying–wetting. Furthermore, the evolution of disintegration parameter further indicated that the disintegration of red-bed argillaceous siltstone was gradually intensified by the increasing number of drying–wetting cycles. The fractal dimension D and the incremental surface energy gradually increased with an increase in the number of drying–wetting cycles. Thus, the proposed energy dissipation model effectively describes the disintegration characteristics of red-bed argillaceous siltstone under the cyclic drying–wetting, and thus, it can be used to guide engineering practices.

Dimensions of tree root systems in savannas are poorly understood, despite being essential in resource acquisition and post-disturbance recovery. We studied tree rooting patterns in Southern African savannas to ask: how tree rooting strategies affected species responses to severe drought; and how potential rooting depths varied across gradients in soil texture and rainfall. First, detailed excavations of eight species in Kruger National Park suggest that the ratio of deep to shallow taproot diameters provides a reasonable proxy for potential rooting depth, facilitating extensive interspecific comparison. Detailed excavations also suggest that allocation to deep roots traded off with shallow lateral root investment, and that drought-sensitive species rooted more shallowly than drought-resistant ones. More broadly across 57 species in Southern Africa, potential rooting depths were phylogenetically constrained, with investment to deep roots evident among miombo Detarioids, consistent with results suggesting they green up before onset of seasonal rains. Soil substrate explained variation, with deeper roots on sandy, nutrient-poor soils relative to clayey, nutrient-rich ones. Although potential rooting depth decreased with increasing wet season length, mean annual rainfall had no systematic effect on rooting depth. Overall, our results suggest that rooting depth systematically structures the ecology of savanna trees. Further work examining other anatomical and physiological root traits should be a priority for understanding savanna responses to changing climate and disturbances.

The influence of water–rock interaction in the process of coal mine construction cannot be ignored, especially when the groundwater quality is complex and contains acidic substances. In this paper, considering the influence of mining, blasting, and earthquake, the dynamic mechanical properties and fractal characteristics of sandstone under acid dry–wet cycle were studied. A comprehensive method combining X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive spectrometer mapping (EDS Mapping) technology for chemical damage analysis was established, and the damage mechanism of sandstone was summarized. The test results show that the acid dry–wet cycle has a great influence on the dynamic peak stress of sandstone (σd) and elastic modulus (Ed) is higher than neutral. And with the decrease of pH value of acidic solution, σd and Ed decrease and the peak strain increases, indicating that the acid solution has corrosion and softening effect on sandstone. With the increase of acid dry–wet cycles, the fractal dimension increases linearly. Sandstone fragments show more broken blocks and smaller particle sizes. Microscopic comprehensive analysis shows that acid solution (H2SO4) will preferentially react with metal oxides and salt cements to open rock pores, and gypsum (CaSO4) and other products will be formed in the process. In the process of the acid dry–wet cycle, the sandstone is corroded by acid solution, which leads to pore growth. Meanwhile, the dry–wet cycle causes repeated expansion and contraction of rock particles. Both of them accelerate rock failure.HighlightsAcid solution weakens the dynamic mechanical parameters of rock, softens the specimen and increases the post-peak strain. With the increase of cycles, the fractal dimension of sandstone increases linearly, and the lower the pH, the more fragmentation and the smaller the particle size.The damage caused by the acid dry-wet cycle to the rock consists of two parts: physical and chemical.

The Great Barrier Reef (GBR) is the largest coral reef system on earth, with ecological and scientific importance for the world and economic and iconic value for Australia. However, the characterisation of its offshore wave climate remains challenging because of its remoteness and large dimensions. Here, we present a detailed analysis of the offshore wave climate of the GBR, unveiling the details of both modal conditions and extreme events. We used a calibrated satellite radar altimeter dataset (spanning from 1985 to 2018) to quantify wave climate, assess the influence of climate drivers, and analyse the wave conditions generated by tropical cyclones at three main regions of the GBR (northern, central, and southern). Our results indicate average significant wave heights of 1.6 m, 1.5 m, and 1.7 m for the northern, central, and southern GBR, respectively. The modal wave climate exhibits substantial seasonality, particularly in the northern region with dry season wave heights up to twofold larger than during wet season. The northern and central wave climates show decreasing wave height and wave energy trends over the last 33 yrs, whilst the southern region remains stable. Consistent with prior studies, we found that the wave climate in the southern region is modulated by the El Niño-Southern Oscillation and the southern annular mode, with influence additionally extending to the central region. Analysis of the extreme waves generated by tropical cyclones revealed they generate large, long period waves, frequently above 7 m, resulting in wave power up to 32-fold higher than median conditions.

To thoroughly investigate the patterns of crack development and the mechanisms of degradation damage in shallow, highly weathered mudstone subjected to repeated dry-wet cycles, a series of laboratory tests were conducted. Initially, the progression of surface cracks on the specimens was documented through fixed-point photography. Image processing techniques using ImageJ software were employed, with crack ratio and fractal dimension as evaluation indices, to quantitatively analyze the relationship between fracture development and the dry-wet effect at both macro and mesoscales. Secondly, stress-strain characteristics of mudstone under different numbers of dry-wet cycles were obtained through direct shear tests. Mesoscopic parameters, crack ratio and fractal dimension, were introduced to establish a damage constitutive model for mudstone under the coupled action of dry-wet cycles and loading. The results indicate that both cohesion and internal friction angle exhibit a stepwise degradation pattern with increasing dry-wet cycles. After 9 cycles, the loss rate of cohesion is significantly higher than that of the internal friction angle. Both crack ratio and fractal dimension increase with the number of dry-wet cycles but decrease with increasing compaction degree. After 3 dry-wet cycles, the basic skeletal structure of the cracks has been preliminarily formed, gradually developing into a reticulated crack network. The stress-strain characteristics can be roughly divided into elastic deformation, elastoplastic deformation, and plastic deformation stages. Furthermore, the stress state of mudstone gradually transitions from strain hardening to strain softening with increasing dry-wet cycles. The established meso-damage constitutive model demonstrates a strong correlation with experimental data, effectively capturing the deformation and failure processes of shallow, highly weathered mudstone subjected to dry-wet cycles. Notably, the model exhibits the highest fitting accuracy under low-stress conditions, underscoring its robust applicability in characterizing the deformation and failure characteristics of shallow weathered mudstone in such environments.The research findings provide theoretical references for the optimal design of reinforcement for shallow weathered mudstone cut slopes in practical engineering.

This paper develops a deep reinforcement learning (DRL) framework for intelligence operation of cascaded hydropower reservoirs considering inflow forecasts, in which two key problems of large discrete action spaces and uncertainty of inflow forecasts are addressed. In this study, a DRL framework is first developed based on a newly defined knowledge sample form and a deep Q-network (DQN). Then, an aggregation-disaggregation model is used to reduce the multi-dimension spaces of state and action for cascaded reservoirs. Following, three DRL models are developed respectively to evaluate the performance of the newly defined decision value functions and modified decision action selection approach. In this paper, the DRL methodologies are tested on China’s Hun River cascade hydropower reservoirs system. The results show that the aggregation-disaggregation model can effectively reduce the dimensions of state and action, which also makes the model structure simpler and has higher learning efficiency. The Bayesian theory in the decision action selection approach is useful to address the uncertainty of inflow forecasts, which can improve the performance to reduce spillages during the wet season. The proposed DRL models outperform the comparison models (i.e., stochastic dynamic programming) in terms of annual hydropower generation and system reliability. This study suggests that the DRL has the potential to be implemented in practice to derive optimal operation strategies.

Internal erosion is capable of leading to substantial soil losses and piping erosion in prolonged rainfall scenarios and the research about it poses a significant challenge. The current landscape lacks comprehensive insights into evaluating internal erosion at both macro- and micro-scales. To address this gap and quantitatively assess soil erosion, we define the erosion factor as the rates of change of various parameters, encompassing microstructure, soil resistivity, and slope erosion morphology characteristics. An indoor rainfall erosion experiment was meticulously crafted, integrating computed tomography (CT) and electrical measurements. Results unveil the nonlinear dynamics of internal particle losses and fracture generations concerning rainfall intensity. Erosion factors, defined by micro-parameters like fractal dimension and probability entropy, exhibit an exponential correlation with resistivity change rates. Furthermore, a three-dimensional (3D) model test was conducted, employing 3D scanning and electrical measurement. Digital elevation models (DEMs) illustrate the formation of splash pits across the slope and the expansion of erosion rills, particularly in low-lying areas. Two resistivity profiles exhibit similar increasing trends attributed to internal erosion. Classifying erosion states based on erosion factors of macro-deformation parameters and soil resistivity underscores spatiotemporal characteristics, notably downward evolution, maintaining consistency between surface and internal erosion. Subsequently, electrical measurement validated internal erosion induced by infiltration channels in in-situ slopes before and after the rainy season. In conclusion, this study unveils intricate relationships among resistivity, macro- and micro-parameters, highlighting the promising potential of electrical measurements in nuanced internal erosion evaluation.

Every year, droughts and floods cause significant damage to the economy and water resources of the UK. Numerous studies have been explored droughts and floods from various points of view, however few have pointed the variations in the patterns induced by climate change. The precipitation data of Central England in the UK was gathered from 1931 to 2020. The analysis was performed by application of fractal dimension, noise variance, Lyapunov exponent, approximate entropy, extreme climate indices, and Standard Precipitation Index. The cross-correlation results indicated the study area warming owing to CO 2 emissions on a global and local scale, implicating the climate change in the study area. Moreover, the mean maximum and minimum temperatures were affected by CO 2 emissions on global and local scales, respectively. The nonlinear dynamic analysis indicated that the duration and intensity of the dry and wet spells were increased due to climate change. In other words, the droughts’ intensity and duration were augmented. However, the number of annual droughts and wetness’s have remained unaffected by climate change. The results signified a weakening in the flash floods possibility and an increment in the flash floods severity owing to climate change. Moreover, climate change brought about an intensification in the rivers’ inundation (fluvial floods) probability. The findings of the present study contribute to the understanding of the mechanism of climate change impacts on droughts and floods (flash, pluvial, and fluvial) patterns and furnished references for nonlinear dynamic studies of droughts and floods patterns.