Soil-rock mixtures are composed of a complex heterogeneous medium, and its mechanical properties and mechanism of failure are intermediate between those of soil and rock, which are difficult to determine. To consider the influence of different particle groups on soil-rock mixture's shear strengths, based on the mesomotion properties of the particles of different particle groups when the soil-rock mixture is deformed, it is classified into two-phase composites, matrix and rock mass. In this paper, based on the representative volume element model of soil-rock mixtures and the Eshelby-Mori-Tanaka equivalent contained mean stress principle, a model of shear constitutive of the accumulation considering the mesoscopic characteristics of the rock is established, the influence of different factors on the shear strength of the accumulation is investigated, and the mesoscopic strengthening mechanism of the rock on the shear strength of the accumulation is discussed. The results show that there is a positive correlation between the rock content, the surface roughness of the rock, the stress concentration coefficient, coefficient of average shear displacement, and the accumulation's shear strength. When the accumulation is deformed, it stores or releases additional energy than the pure soil material, so it shows an increase in deformation resistance and shear strength on a macroscopic scale.

The mechanical properties and failure characteristics of soil-rock mixtures (SRMs) directly affect the stability of tunnels constructed in SRMs. A new SRM modelling method based on the combined finite-discrete element method (FDEM) was proposed. Using this new SRM modelling method based on the FDEM, the mechanical characteristics and failure behaviour of SRM samples under uniaxial compression, as well as the failure mechanism of SRMs around a tunnel, were further investigated. The study results support the following findings: (1) The modelling of SRM samples can be achieved using a heterogeneous rock modelling method based on the Weibull distribution. By adjusting the relevant parameters, such as the soil-rock boundaries, element sizes and modelling control points, SRM models with different rock contents and morphologies can be obtained. (2) The simulation results of uniaxial compression tests of SRM samples with different element sizes and morphologies validate the reliability and robustness of the new modelling method. In addition, with increasing rock content, VBP (volumetric block proportion), the uniaxial compressive strength and Young's modulus increase exponentially, but the samples all undergo single shear failure within the soil or along the soil-rock interfaces, and the shear failure angles are all close to the theoretical values. (3) Tunnels in SRMs with different rock contents all exhibit X-shaped conjugate shear failure, but the fracture network propagation depth, the maximum displacement around the tunnel, and the failure degree of the tunnel in the SRM roughly decreases via a power function as the rock content increases. In addition, as the rock content increases, such as when VBP = 40%, large rocks have a significant blocking effect on fracture propagation, resulting in an asymmetric fracture network around the tunnel. (4) The comparisons of uniaxial compression and tunnel excavation simulation results with previous theoretical results, laboratory test results, and numerical simulation results verify the correctness of the new modelling method proposed in this paper.

Red stratum is widely distributed in Southwest China, and a large number of deep soil-red stratum soft rock mixed backfill areas were formed when the site was leveled by high excavation and low filling during the construction of mountain city in this area. Tunnels under construction inevitably go through backfill, which makes tunnel excavation under deep soil-rock mixture backfill become a common condition. Meanwhile, rainfall is frequent and concentrated in Southwest China, and the resulting wet disintegration of red stratum soft rock has a significant impact on the deformation and bearing characteristics of soil-rock mixture. As a result, it was decided in the present study to conduct a shear-unloading test on the soil-red stratum soft rock mixture, augmented by discrete element numerical simulations, to reveal the influence of wetting. This all-encompassing strategy seeks to examine the laws governing the deformation and progression of damage of the mixture, offering valuable insights into its response when subjected to unloading conditions. The findings indicate that the soil-red stratum soft rock mixture prior to and after wetting shows obvious strain hardening characteristics during the shear process. The residual strength after unloading has a linear correlation with unloading amplitude. The soilred stratum soft rock mixture prior to wetting is loaded by the rock block bearing skeleton, and the rock block breakage is primarily caused by shear, while jointly loaded by soil and rock block in saturated sample, with the rock block breakage caused by wetting. After the unloading process, the dry sample's bearing capacity no longer increases and eventually overall failure occurs. Conversely, the saturated sample's bearing capacity can continue to increase and ultimately layered failure from the top to the bottom occurs. The unloading rate mainly affects the growth rate of load-bearing capacity after unloading of saturated samples.

积雪融水是西北干旱区水资源的重要组成部分，准确模拟融雪径流过程对西北干旱区水资源管理和规划具有重要意义。本研究以新疆开都河流域上游为研究区，通过设置径流判定阈值与径流放大函数对SRM模型进行改进，以补充考虑地下水对径流过程的影响。在此基础上，拟定不同正积温、径流系数以及退水系数组合下的模型参数方案，使用2000—2009年实测径流数据进行参数率定与模型验证。结果表明：改进的SRM模型对研究区冬季径流过程模拟精度明显提高，而基于最高气温分段函数的正积温估算方案以及基于降水量分段函数的径流系数确定方案均可明显提高模型模拟精度。研究成果可为西北干旱区的水文预报以及水资源管理提供参考。

积雪融水是西北干旱区水资源的重要组成部分，准确模拟融雪径流过程对西北干旱区水资源管理和规划具有重要意义。本研究以新疆开都河流域上游为研究区，通过设置径流判定阈值与径流放大函数对SRM模型进行改进，以补充考虑地下水对径流过程的影响。在此基础上，拟定不同正积温、径流系数以及退水系数组合下的模型参数方案，使用2000—2009年实测径流数据进行参数率定与模型验证。结果表明：改进的SRM模型对研究区冬季径流过程模拟精度明显提高，而基于最高气温分段函数的正积温估算方案以及基于降水量分段函数的径流系数确定方案均可明显提高模型模拟精度。研究成果可为西北干旱区的水文预报以及水资源管理提供参考。

积雪融水是西北干旱区水资源的重要组成部分，准确模拟融雪径流过程对西北干旱区水资源管理和规划具有重要意义。本研究以新疆开都河流域上游为研究区，通过设置径流判定阈值与径流放大函数对SRM模型进行改进，以补充考虑地下水对径流过程的影响。在此基础上，拟定不同正积温、径流系数以及退水系数组合下的模型参数方案，使用2000—2009年实测径流数据进行参数率定与模型验证。结果表明：改进的SRM模型对研究区冬季径流过程模拟精度明显提高，而基于最高气温分段函数的正积温估算方案以及基于降水量分段函数的径流系数确定方案均可明显提高模型模拟精度。研究成果可为西北干旱区的水文预报以及水资源管理提供参考。

Purpose - The purpose of this paper is to propose a new combined finite-discrete element method (FDEM) to analyze the mechanical properties, failure behavior and slope stability of soil rock mixtures (SRM), in which the rocks within the SRM model have shape randomness, size randomness and spatial distribution randomness. Design/methodology/approach - Based on the modeling method of heterogeneous rocks, the SRM numerical model can be built and by adjusting the boundary between soil and rock, an SRM numerical model with any rock content can be obtained. The reliability and robustness of the new modeling method can be verified by uniaxial compression simulation. In addition, this paper investigates the effects of rock topology, rock content, slope height and slope inclination on the stability of SRM slopes. Findings - Investigations of the influences of rock content, slope height and slope inclination of SRM slopes showed that the slope height had little effect on the failure mode. The influences of rock content and slope inclination on the slope failure mode were significant. With increasing rock content and slope dip angle, SRM slopes gradually transitioned from a single shear failure mode to a multi-shear fracture failure mode, and shear fractures showed irregular and bifurcated characteristics in which the cut-off values of rock content and slope inclination were 20% and 80 degrees, respectively. Originality/value - This paper proposed a new modeling method for SRMs based on FDEM, with rocks having random shapes, sizes and spatial distributions.

额尔齐斯河流域受地理条件的影响，流域内水文气象站点较少，基础资料匮乏，而融雪洪水在该流域的汛期及水资源管理上有着较大影响。本研究通过应用降水和气温的再分析产品及AVHRR积雪数据，利用K-means聚类法进行不同径流时期特点的划分，并在不同时期构建相应SRM+LSTM模型，并使用2009年数据及2023年实地观测的径流数据进行验证。结果表明：再分析产品CMFD能够较好地应用于额尔齐斯河流域，并能根据降水、温度、积雪及径流间的关系得到不同径流划分时期，即12月11日—次年4月10日为积雪退水期、4月11日—8月10日为融雪降水产流期、8月11日为降水产流期。SRM模型模拟效果较差，大部分径流纳什效率系数（NSE）<0；而SRM+LSTM模型能够较好地模拟该流域的不同时期的径流，决定系数R2均能达到0.5以上，纳什效率系数也能达到0.5以上，证明SRM+LSTM模型能够较好地应用于该地区，精度较高。

额尔齐斯河流域受地理条件的影响，流域内水文气象站点较少，基础资料匮乏，而融雪洪水在该流域的汛期及水资源管理上有着较大影响。本研究通过应用降水和气温的再分析产品及AVHRR积雪数据，利用K-means聚类法进行不同径流时期特点的划分，并在不同时期构建相应SRM+LSTM模型，并使用2009年数据及2023年实地观测的径流数据进行验证。结果表明：再分析产品CMFD能够较好地应用于额尔齐斯河流域，并能根据降水、温度、积雪及径流间的关系得到不同径流划分时期，即12月11日—次年4月10日为积雪退水期、4月11日—8月10日为融雪降水产流期、8月11日为降水产流期。SRM模型模拟效果较差，大部分径流纳什效率系数（NSE）<0；而SRM+LSTM模型能够较好地模拟该流域的不同时期的径流，决定系数R2均能达到0.5以上，纳什效率系数也能达到0.5以上，证明SRM+LSTM模型能够较好地应用于该地区，精度较高。

额尔齐斯河流域受地理条件的影响，流域内水文气象站点较少，基础资料匮乏，而融雪洪水在该流域的汛期及水资源管理上有着较大影响。本研究通过应用降水和气温的再分析产品及AVHRR积雪数据，利用K-means聚类法进行不同径流时期特点的划分，并在不同时期构建相应SRM+LSTM模型，并使用2009年数据及2023年实地观测的径流数据进行验证。结果表明：再分析产品CMFD能够较好地应用于额尔齐斯河流域，并能根据降水、温度、积雪及径流间的关系得到不同径流划分时期，即12月11日—次年4月10日为积雪退水期、4月11日—8月10日为融雪降水产流期、8月11日为降水产流期。SRM模型模拟效果较差，大部分径流纳什效率系数（NSE）<0；而SRM+LSTM模型能够较好地模拟该流域的不同时期的径流，决定系数R2均能达到0.5以上，纳什效率系数也能达到0.5以上，证明SRM+LSTM模型能够较好地应用于该地区，精度较高。