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Assessment of the spatial distribution of potential pathways of sediment transport and the degree of linkage between sediment sources and the channel network within a watershed represents a valuable analysis for informing management decisions on sediment yield and transfer. Given the limitations of conventional methods for determining index of sediment connectivity (IC), there is a need to provide a flexible and efficient approach with the ability to apply different factors. In this regard, five decision tree-based machine learning models: M5 prime (M5P), random tree (RT), random forest (RF), alternating model tree (AMT), and reduced error pruning tree (REPT) were tested using geomorphic and climatic factors. Two databases were constructed with 200 and 1600 classes at 50 watersheds in Queensland, Australia. In these models, IC was assessed as an output parameter and six attributes that affect IC were assigned as input parameters (i.e., elevation, slope, area, length of stream channel, normalized difference vegetation index, and rainfall). Statistical validation and comparison of model predictions with calculated IC values based on the approach of Borselli et al. (Catena 75:268–277, 2008) were performed. Based on the statistical criteria, the RF model produced the most robust estimations of IC compared to other models and performed very well for IC modelling, especially in smaller subsections of watersheds. Accordingly, these findings can play an effective role for implementing watershed management and soil and water resources management measures. [ABSTRACT FROM AUTHOR]

Hydrological models have proliferated in the past several decades prompting debates on the virtues and shortcomings of various modelling approaches. Rather than critiquing individual models or modelling approaches, the objective here is to address the critical issues of scaling and hydrological process representation in various types of models with suggestions for improving these attributes in a parsimonious manner that captures and explains their functionality as simply as possible. This discussion focuses mostly on conceptual and physical/process-based models where understanding the internal catchment processes and hydrologic pathways is important. Such hydrological models can be improved by using data from advanced remote sensing (both spatial and temporal) and derivatives, applications of machine learning, flexible structures, and informing models through nested catchment studies in which internal catchment processes are elucidated. Incorporating concepts of hydrological connectivity into flexible model structures is a promising approach for improving flow path representation. Also important is consideration of the scale dependency of hydrological parameters to avoid scale mismatch between measured and modelled parameters. Examples are presented from remote high-elevation regions where water sources and pathways differ from temperate and tropical environments where more attention has been focused. The challenge of incorporating spatially and temporally variable water inputs, hydrologically pathways, climate, and land use into hydrological models requires modellers to collaborate with catchment hydrologists to include important processes at relevant scales—i.e. develop smarter hydrological models. [ABSTRACT FROM AUTHOR]

Background and aims: Agroforestry systems combining trees with crops or pastures have been widely used to reduce water, soil, and nutrient losses and associated water pollution from agricultural lands in both temperate and tropical regions. However, reviews on improvement/efficiency and the scope of such reductions by soil, management, climate, and hydrological processes are limited. Methods: This paper synthesized the available evidence on the reduction in surface runoff, soil erosion, nutrient, and pollutant losses (e.g., herbicides, pesticides, and antibiotics) to quantify the effectiveness of agroforestry systems on water quality improvement based on published studies. Results: On average, agroforestry systems reduced surface runoff, soil, organic carbon, and related nutrient losses by 1–100%, 0–97%, –175–92%, and –265–100%, respectively, with average values of 58%, 65%, 9%, and 50%, respectively. They also lowered herbicide, pesticide, and other pollutant losses by –55–100% (49% on average). Conclusions: Reduction efficiency of agroforestry systems is site-dependent and varies widely depending on different biophysical factors. A comprehensive science-based review is needed to generalize agroforestry design and site adaptability for water and soil conservation where climatic, geographical, ecological, and socio-economic conditions are relatively similar in the world. [ABSTRACT FROM AUTHOR]

Major earthquakes cause widespread environmental and socioeconomic disruptions that persist for decades. Extensive ground disturbances that occurred during the shallow-focus Kumamoto earthquakes will affect future sustainability of ecosystem services west of Aso volcano. Numbers of earthquake-initiated landslides per unit area were higher in grasslands than forests, likely owing to greater root reinforcement of trees, and mostly initiated on ridgelines and/or convex/planar hillslopes. Most landslides traveled short distances and did not initially evolve into debris flows; resultant sediments and wood accumulating in headwater channels can be mobilized into debris flows during future storms. Fissures along ridgelines may promote water ingress and induce future landslides and debris flows that affect residents downstream. Native grasses are at risk because of habitat fragmentation caused by ground disturbances, extensive damage to rural roads, and abandonment of traditional pasture management practices. Sustainable management of affected areas needs to consider future risk of cascading hazards and long-term socioeconomic impacts. [ABSTRACT FROM AUTHOR]

Field measurements conducted 4 years after the construction of a new portion of the Weixi-Shangri-La road in Yunnan, China, reveal that unprecedented rates of mass wasting occurred along the road with much of this sediment directly impacting the headwaters of the Mekong River. Landslide erosion (including dry ravel) exceeded 33,000 t ha year along the most severely eroded sections of the road and averaged more than 9,600 t ha year along the surveyed 23.5 km of road; these values are the highest ever reported for road-related landslides. While surface erosion was only about 7% of the total erosion from the road, it is still more than an order of magnitude higher than typical surface erosion rates from disturbed lands in Southeast Asia. Combined landslide and surface erosion from this road delivered an estimated 19 times more sediment to the river than the remaining 99.6% of the contributing catchment. These sediment inputs are aggrading local channels, promoting downstream sediment transport, degrading aquatic habitat, and creating the possibility for a future debris flood or hyperconcentrated flow. [ABSTRACT FROM AUTHOR]

Slope stability models traditionally use simple indicators of root system structure and strength when vegetation is included as a factor. However, additional root system traits should be considered when managing vegetated slopes to avoid shallow substrate mass movement. Traits including root distribution, length, orientation and diameter are recognized as influencing soil fixation, but do not consider the spatial and temporal dimensions of roots within a system. Thick roots act like soil nails on slopes and the spatial position of these thick roots determines the arrangement of the associated thin roots. Thin roots act in tension during failure on slopes and if they traverse the potential shear zone, provide a major contribution in protecting against landslides. We discuss how root traits change depending on ontogeny and climate, how traits are affected by the local soil environment and the types of plastic responses expressed by the plant. How a landslide engineer can use this information when considering slope stability and management strategies is discussed, along with perspectives for future research. This review encompasses many ideas, data and concepts presented at the Second International Conference ‘Ground Bio- and Eco-engineering: The Use of Vegetation to Improve Slope Stability—ICGBE2’ held at Beijing, China, 14–18 July 2008. Several papers from this conference are published in this edition of Plant and Soil. [ABSTRACT FROM AUTHOR]

This research combines field, laboratory and numerical investigations to estimate the development of a wetting front within a 1.2 m residual soil mantle on a steep forested slope during rainfall events. The field-monitored variations in matric suction due to rain-water infiltration during various events revealed that the maximum infiltration rate was much higher when the wetting front resided in the upper 20 cm of soil compared to the case when the wetting front advanced to depths > 20 cm. Laboratory investigations on soil hydraulic properties (i.e., soil water characteristic curve, and hydraulic conductivity) were useful to establish the parameters of a multilayer finite-element model for one-dimensional vertical infiltration. These parameters were subsequently calibrated by matching the predicted and field measured transient pore water pressure responses during actual rainstorms with irregular rainfall patterns. The calibrated simulation model was used to assess the migration of the wetting front under uniform rainfall with different intensities. Based on the numerical results, a hyperbolic equation was developed to predict the duration of uniform rainfall required for the propagation of wetting front to a certain depth for a given rainfall intensity. The proposed equation was subsequently tested against field-monitored advancements of the wetting front during real rainstorms with variable rainfall intensity. [ABSTRACT FROM AUTHOR]

Resource managers require objective methodologies to optimize decisions related to forest road deactivation and other aspects of road management, especially in steep terrain, where road-related slope failures inflict extensive environmental damage. Decision analysis represents a systematic framework that clearly identifies real options and critical decision points. This framework links current decisions with expected future outcomes and provides advantages such as a common currency to systematically explore the liability consequences of limited budget expenditures to road deactivation and other road-related activities. Furthermore, the decision framework prevents the analysis from becoming hopelessly entangled by the vast number of possibilities generated by the alternative occurrences, magnitudes, and consequences of landslide/debris flow events and provides the information required for the first step of an adaptive management process. Here, a structured analysis of potential environmental risks for a road deactivation project in coastal British Columbia, Canada is presented. The application of decision analysis generates a ranking of the expected benefits of proposed deactivation activities on various road sections. The ranking distinguishes between road sections that offer high expected benefit from those that offer moderate to low expected benefit. Seventeen of 171, 100–m road segments accounted for 18% of the cumulative cost and 98% of the cumulative expected net benefits from road deactivation. Furthermore, the cost of deactivating a section of road is related to the expected benefit from such deactivation, thus providing the basis for more effective resource allocation and budgeting decisions. [ABSTRACT FROM AUTHOR]