Water content is one important factor on which velocities, heights, and runout of debris flows and similar phenomena depend. To this purpose, we need two ingredients (i) a mathematical model describing the incorporation of water into the moving soil, which results in a change of water content, and (ii) a rheological model with properties depending on the water content. Modeling of such problems can be done either by using either a: (i) two phases approach, where velocities of solid and water may be different, using two sets of nodes, or (ii) two phases approach where velocities of both are assumed to be the same, using a single set of nodes. In both cases, the models have to implement a mechanism for the water inflow-or outflow-. We will modify both types of two phases models (one or two sets of nodes for solid and water) to include the change of water content due to water inflow. Implementation in the SPH requires extending the algorithm and updating the smoothing length because it is based on the mass of particles and their relative position. Updating the smoothing length when only changes mass is to be avoided. Regarding the rheological model, we will introduce a new model for frictional debris flows implementing a Voellmy coefficient which depends on water content. Alternatively, we will propose a more consistent model based on Bagnold's idea of introducing a 1D concentration parameter (lambda) . Finally, we will illustrate the proposed model capability with two examples, a dam break problem, and a real case in El Salvador where the water content played an important role in the propagation properties of a debris flow.

The advancement of agriculture and a shortage of labor have led to an increased use of agricultural machinery. However, the resulting environmental issues have prompted a shift from internal combustion engines to electric drivetrains. The electric drivetrain includes the installation of batteries, which can lead to decreased energy efficiency and significant loads on the vehicle due to their heavy weight. Consequently, the importance of ensuring the safety of agricultural machinery is being increasingly emphasized. The load on the frame of agricultural machinery is not consistent during off-road driving, and the accumulation of load cycles can lead to the destruction and failure of components. Therefore, it is necessary to ensure a level of safety and to predict the fatigue life. In this study, we estimate the safety factor and predict the fatigue life of weak points in an electrically driven, multi-purpose cultivation tractor based on working conditions (width, soil, and drive). Strain gauges were attached to these weak points to measure the strain, which was then converted to von Mises stress. Fatigue life was predicted using the rainflow counting method and the Palmgren-Miner rule. The results showed that the safety factor measured under various working conditions was greater than 1. The estimated minimum fatigue life was 124,176 years. Considering that the cultivator is used for 29.7 h annually and has a durability lifespan of 5 years, it is expected to be safely usable throughout its service life.

Lateral inflows control the spatial distribution of river discharge, and understanding their patterns is fundamental for accurately modelling instream flows and travel time distributions necessary for evaluating impacts of climate change on aquatic habitat suitability, river energy budgets, and fate of dissolved organic carbon. Yet, little is known about the spatial distribution of lateral inflows in Arctic rivers given the lack of gauging stations. With a network of stream gauging and meteorological stations within the Kuparuk River watershed in northern Alaska, we estimated precipitation and lateral inflows for nine subcatchments from 1 July to 4 August,2013, 2014, and 2015. Total precipitation, lateral inflows, runoff ratios (area-normalized lateral inflow divided by precipitation), percent contribution to total basin discharge, and lateral inflow per river kilometre were estimated for each watershed for relatively dry, moderate, or wet summers. The results show substantial variability between years and subcatchments. Total basin lateral inflow depths ranged 24-fold in response to a threefold change in rainfall between dry and wet years, whereas within-basin lateral inflows varied fivefold from the coastal plain to the foothills. General spatial trends in lateral inflows were consistent with previous studies and mean summer precipitation patterns. However, the spatially distributed nature of these estimates revealed that reaches in the vicinity of a spring-fed surficial ice feature do not follow general spatial trends and that the coastal plain, which is typically considered to produce minimal runoff, showed potential to contribute to total river discharge. These findings are used to provide a spatially distributed understanding of lateral inflows and identify watershed characteristics that influence hydrologic responses.

Understanding the dynamics of heat transfer mechanisms is critical for forecasting the effects of climate change on arctic river temperatures. Climate influences on arctic river temperatures can be particularly important due to corresponding effects on nutrient dynamics and ecological responses. It was hypothesized that the same heat and mass fluxes affect arctic and temperate rivers, but that relative importance and variability over time and space differ. Through data collection and application of a river temperature model that accounts for the primary heat fluxes relevant in temperate climates, heat fluxes were estimated for a large arctic basin over wide ranges of hydrologic conditions. Heat flux influences similar to temperate systems included dominant shortwave radiation, shifts from positive to negative sensible heat flux with distance downstream, and greater influences of lateral inflows in the headwater region. Heat fluxes that differed from many temperate systems included consistently negative net longwave radiation and small average latent heat fluxes. Radiative heat fluxes comprised 88% of total absolute heat flux while all other heat fluxes contributed less than 5% on average. Periodic significance was seen for lateral inflows (up to 26%) and latent heat flux (up to 18%) in the lower and higher stream order portions of the watershed, respectively. Evenly distributed lateral inflows from large scale flow differencing and temperatures from representative tributaries provided a data efficient method for estimating the associated heat loads. Poor model performance under low flows demonstrated need for further testing and data collection to support the inclusion of additional heat fluxes.