An improved method for calculating slope length (λ) and the LS parameters of the Revised Universal Soil Loss Equation for large watersheds

The Universal Soil Loss Equation (USLE) and its revised version (RUSLE) are often used to estimate soil erosion at regional landscape scales. USLE/RUSLE contain parameters for slope length factor (L) and slope steepness factor (S), usually combined as LS. However a major limitation is the difficulty in extracting the LS factor. Methods to estimate LS based on geographic information systems have been developed in the last two decades. L can be calculated for large watersheds using the unit contributing area (UCA) or the slope length (λ) as input parameters. Due to the absence of an estimation of slope length, the UCA method is insufficiently accurate. Improvement of the spatial accuracy of slope length and LS factor is still necessary for estimating soil erosion. The purpose of this study was to develop an improved method to estimate the slope length and LS factor. We combined the algorithm for multiple-flow direction (MFD) used in the UCA method with the LS-TOOL (LS-TOOLSFD) algorithms, taking into account the calculation errors and cutoff conditions for distance, to obtain slope length (λ) and the LS factor. The new method, LS-TOOLMFD, was applied and validated in a catchment with complexly variable slopes. The slope length and LS calculated by LS-TOOLMFD both agreed better with field data than with the calculations using the LS-TOOLSFD and UCA methods, respectively. We then integrated the LS-TOOLMFD algorithm into LS-TOOL developed in Microsoft's.NET environment using C# with a user-friendly interface. The method can automatically calculate slope length, slope steepness, L, S, and LS factor, providing the results as ASCII files that can be easily used in GIS software and erosion models. This study is an important step forward in conducting accurate large-scale erosion evaluation

Quality of terrestrial data derived from UAV photogrammetry : A case study of Hetao irrigation district in northern China

Most crops in northern China are irrigated, but the topography affects the water use, soil erosion, runoff and yields. Technologies for collecting high-resolution topographic data are essential for adequately assessing these effects. Ground surveys and techniques of light detection and ranging have good accuracy, but data acquisition can be time-consuming and expensive for large catchments. Recent rapid technological development has provided new, flexible, high-resolution methods for collecting topographic data, such as photogrammetry using unmanned aerial vehicles (UAVs). The accuracy of UAV photogrammetry for generating high-resolution Digital Elevation Model (DEM) and for determining the width of irrigation channels, however, has not been assessed. A fixed-wing UAV was used for collecting high-resolution (0.15 m) topographic data for the Hetao irrigation district, the third largest irrigation district in China. 112 ground checkpoints (GCPs) were surveyed by using a real-time kinematic global positioning system to evaluate the accuracy of the DEMs and channel widths. A comparison of manually measured channel widths with the widths derived from the DEMs indicated that the DEM-derived widths had vertical and horizontal root mean square errors of 13.0 and 7.9 cm, respectively. UAV photogrammetric data can thus be used for land surveying, digital mapping, calculating channel capacity, monitoring crops, and predicting yields, with the advantages of economy, speed and ease.</p

Pesticides are Substantially Transported in Particulate Phase, Driven by Land use, Rainfall Event and Pesticide Characteristics—A Runoff and Erosion Study in a Small Agricultural Catchment

Agriculture on sloping lands is prone to processes of overland flow and associated soil detachment, transportation, and deposition. The transport of pesticides to off-target areas related to runoff processes and soil erosion poses a threat of pollution to the downstream environment. This study aimed to quantify transport of pesticides both dissolved in water and in the particulate phase in transported sediments. Particulate phase transport of pesticides on short temporal time scales from agricultural fields is scarcely studied. During two growing seasons (2019 and 2020) rainfall—runoff events were monitored in a catchment of 38.5 ha. We selected 30 different pesticides and one metabolite based on interviews with the farmers on the application pattern. Concentrations for these 31 residues were analyzed in runoff water (dissolved phase–DP) and sediment (particulate phase–PP) and in soil samples taken in the agricultural fields. In all runoff events active substances (AS) were detected. There was a clear difference between DP and PP with 0–5 and 8–18 different AS detected in the events, respectively. Concentrations in PP were higher than in DP, with factors ranging from 12 to 3,700 times. DP transport mainly occurs in the first days after application (69% within 10 days), and PP transport occurs over the long term with 90% of transported mass within 100 days after application. Potato cultivation was the main source of runoff, erosion, and pesticide transport. Cereals and apples with grassed inter-rows both have a very low risk of pesticide transport during overland flow. We conclude that for arable farming on sloping lands overland transport of pesticide in the particulate phase is a substantial transport pathway, which can contribute to pollution over longer time periods compared to transport in water. This process needs to be considered in future assessments for pesticide fate and environmental risk

MEMO - multi-experiment mixture model analysis of censored data.

Motivation: The statistical analysis of single-cell data is a challenge in cell biological studies. Tailored statistical models and computational methods are required to resolve the subpopulation structure, i.e. to correctly identify and characterize subpopulations. These approaches also support the unraveling of sources of cell-to-cell variability. Finite mixture models have shown promise, but the available approaches are ill suited to the simultaneous consideration of data from multiple experimental conditions and to censored data. The prevalence and relevance of single-cell data and the lack of suitable computational analytics make automated methods, that are able to deal with the requirements posed by these data, necessary. Results: We present MEMO, a flexible mixture modeling framework that enables the simultaneous, automated analysis of censored and uncensored data acquired under multiple experimental conditions. MEMO is based on maximum-likelihood inference and allows for testing competing hypotheses. MEMO can be applied to a variety of different single-cell data types. We demonstrate the advantages of MEMO by analyzing right and interval censored single-cell microscopy data. Our results show that an examination of censoring and the simultaneous consideration of different experimental conditions are necessary to reveal biologically meaningful subpopulation structures. MEMO allows for a stringent analysis of single-cell data and enables researchers to avoid misinterpretation of censored data. Therefore, MEMO is a valuable asset for all fields that infer the characteristics of populations by looking at single individuals such as cell biology and medicine. Availability: MEMO is implemented in MATLAB and freely available via github (https://github.com/MEMO-toolbox/MEMO)

Transport of silver nanoparticles by runoff and erosion – A flume experiment

Silver nanoparticles (AgNPs) are being used in many products as they have unique antimicrobial-biocidal properties. After disposal of these products AgNPs can reach the soil environment possibly affecting soil organisms and disrupting plants. This work aimed to study the transport of AgNPs by water and sediment during overland flow and soil erosion. This was done in a laboratory setting, using a flume and rainfall simulator. A low concentration of AgNPs (50 μg·kg− 1) was applied to two soil-flumes with slope percentages of 20% and 10%. The rainfall was applied in four events of 15 min each with a total amount of rainfall of 15 mm during each event. After applying the rainfall, samples of the non-transported background soil (BS) and the transported sediment (Sf) were collected from the flume surface. Runoff sediment (RS) and water (RW) were collected from the outlet. AgNPs were detected in all samples collected. However, concentration varied according to sample type (soil or water), time of collection (for runoff water and sediment) and the slope of the soil flume. Higher concentrations of AgNPs in soil were detected in the BS than in the Sf likely due to the BS having more fine particles (silt and clay). The AgNPs concentration in the runoff sediments increased with subsequent applied rain events. In addition, increasing the slope of the flume from 10% to 20% increased the total AgNPs transported with the runoff sediment by a factor 1.5. The study confirms that AgNPs can be transported by both overland flow and sediment due to erosion.</p

Assessing the effect of water harvesting techniques on event-based hydrological responses and sediment yield at a catchment scale in northern Ethiopia using the Limburg Soil Erosion Model (LISEM)

Runoff and sediment yield in semi-arid catchments are highly influenced by infrequent but very heavy rains. These events occur over short temporal scales, so runoff and sediment transport can only be understood using an event-based analysis. We applied a hydrological and soil-erosion model, LISEM, to the Gule catchment (~ 12 km2) in northern Ethiopia. The objectives of the study were: (a) to evaluate the performance of LISEM in describing event-based hydrological processes and sediment yield in a catchment under the influence of different water harvesting techniques (WHTs), and (b) to study the effect of the WHTs on catchment-scale event-based runoff and sediment yield. The model performed satisfactorily (NSE > 0.5) for most of the events when discharge was calibrated at the main outlet (Gule) and at a sub-outlet (Misbar). Runoff coefficients for the Gule catchment and Misbar sub-catchment were expectedly low due to the implementation of WHTs, which can store runoff from the rains and increase infiltration into the soil. Simulated and measured sediment yields were of similar orders of magnitude. LISEM generally overestimated sediment yield compared to the measurements. The poor performance of LISEM in predicting sediment yield could be attributed to the uncertainty of several factors controlling soil erosion and the inadequacy of LISEM in describing soil erosion on steep slopes. Catchment-scale model simulations indicated that runoff and sediment yield could be effectively reduced by implementing WHTs. The model estimated 41 and 61% reductions in runoff and sediment yield at the Gule outlet, respectively. Similarly, runoff and sediment yield at the Misbar sub-outlet were reduced by 45 and 48%, respectively. LISEM can thus be used to simulate the effects of different existing or new WHTs on catchment hydrology and sediment yield. The results of scenario predictions could be useful for land-use planners who intend to implement different measures of catchment management

Determinants of robustness in spindle assembly checkpoint signalling.

The spindle assembly checkpoint is a conserved signalling pathway that protects genome integrity. Given its central importance, this checkpoint should withstand stochastic fluctuations and environmental perturbations, but the extent of and mechanisms underlying its robustness remain unknown. We probed spindle assembly checkpoint signalling by modulating checkpoint protein abundance and nutrient conditions in fission yeast. For core checkpoint proteins, a mere 20% reduction can suffice to impair signalling, revealing a surprising fragility. Quantification of protein abundance in single cells showed little variability (noise) of critical proteins, explaining why the checkpoint normally functions reliably. Checkpoint-mediated stoichiometric inhibition of the anaphase activator Cdc20 (Slp1 in Schizosaccharomyces pombe) can account for the tolerance towards small fluctuations in protein abundance and explains our observation that some perturbations lead to non-genetic variation in the checkpoint response. Our work highlights low gene expression noise as an important determinant of reliable checkpoint signalling

Spatial glyphosate and AMPA redistribution on the soil surface driven by sediment transport processes – A flume experiment

This study investigates the influence of small-scale sediment transport on glyphosate and AMPA redistribution on the soil surface and on their off-site transport during water erosion events. Both a smooth surface (T1) and a surface with “seeding lines on the contour” (T2) were tested in a rainfall simulation experiment using soil flumes (1 × 0.5 m) with a 5% slope. A dose of 178 mg m−2 of a glyphosate-based formulation (CLINIC®) was applied on the upper 0.2 m of the flumes. Four 15-min rainfall events (RE) with 30-min interval in between and a total rainfall intensity of 30 mm h−1 were applied. Runoff samples were collected after each RE in a collector at the flume outlet. At the end of the four REs, soil and sediment samples were collected in the application area and in four 20 cm-segments downslope of the application area. Samples were collected according to the following visually distinguished soil surface groups: light sedimentation (LS), dark sedimentation (DS), background and aggregates. Results showed that runoff, suspended sediment and associated glyphosate and AMPA off-site transport were significantly lower in T2 than in T1. Glyphosate and AMPA off-site deposition was higher for T2 than for T1, and their contents on the soil surface decreased with increasing distance from the application area for all soil surface groups and in both treatments. The LS and DS groups presented the highest glyphosate and AMPA contents, but the background group contributed the most to the downslope off-site deposition. Glyphosate and AMPA off-target particle-bound transport was 9.4% (T1) and 17.8% (T2) of the applied amount, while water-dissolved transport was 2.8% (T1) and 0.5% (T2). Particle size and organic matter influenced the mobility of glyphosate and AMPA to off-target areas. These results indicate that the pollution risk of terrestrial and aquatic environments through runoff and deposition can be considerable. The downslope off-site transport and deposition of glyphosate and AMPA by water erosion onto the soil surface can be considerable, with the consequent pollution risk of off-target terrestrial environments

An integrated method for calculating DEM-based RUSLE LS

The improvement of resolution of digital elevation models (DEMs) and the increasing application of the Revised Universal Soil Loss Equation (RUSLE) over large areas have created problems for the efficiency of calculating the LS factor for large data sets. The pretreatment for flat areas, flow accumulation, and slope-length calculation have traditionally been the most time-consuming steps. However, obtaining these features are generally usually considered as separate steps, and calculations still tend to be time-consuming. We developed an integrated method to improve the efficiency of calculating the LS factor. The calculation model contains algorithms for calculating flow direction, flow accumulation, slope length, and the LS factor. We used the Deterministic 8 method to develop flow-direction octrees (FDOTs), flat matrices (FMs) and first-in-first-out queues (FIFOQs) tracing the flow path. These data structures were much more time-efficient for calculating the slope length inside the flats, the flow accumulation, and the slope length linearly by traversing the FDOTs from their leaves to their roots, which can reduce the search scope and data swapping. We evaluated the accuracy and effectiveness of this integrated algorithm by calculating the LS factor for three areas of the Loess Plateau in China and SRTM DEM of China. The results indicated that this tool could substantially improve the efficiency of LS-factor calculations over large areas without reducing accuracy

An integrated algorithm to evaluate flow direction and flow accumulation in flat regions of hydrologically corrected DEMs

In order to conduct an accurate hydrological analysis of a watershed, certain conditions need to be understood. Flow direction and flow accumulation are important watershed characteristics that need to be determined before an analysis can be made. Other important characteristics which can be gleaned from analysing the digital elevation model (DEM) of a watershed include channel networks, stream lengths and watershed boundaries. Determining flow direction and flow accumulation is usually carried out in separate steps. Flat regions are types of terrain in raster DEMs without local elevation gradients. Evaluating flow direction and flow accumulation in flat regions using DEMs is a well-known problem in watershed analysis because of the occurrence of problematic parallel flow lines. Calculations also tend to be time-consuming. We have developed an efficient and comprehensive integrated approach to assign flow directions and flow accumulation in flat regions. This approach uses values for non-flat flow accumulation and a maze algorithm with a weight value (MW method) to determine several things: a main flow line through the flat area to the local outlet, an octree tree, and first-in first-out queue structures to calculate flow accumulation. The MW method can be applied to hydrologically corrected DEMs and a single flow path can be provided to resolve all flat areas. To investigate the influence on the topological properties of the channel networks, we used this integrated algorithm to extract three sets of flow accumulation areas from existing DEMs. Using this new integrated method was faster than using the two existing methods and produced continuous channel networks without the occurrence of problematic parallel flow lines.</p