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The TCRP model can be used to create a runoff pattern, taking into account the effects of tillage-induced roughness. The TCRP model has as main aim to adjust runoff patterns based on topography for tillage induced roughness. The resulting output of TCRP are runoff pattern raster maps, which can be further used as input for hydrological modelling of surface runoff processes. The methodology to create the runoff pattern includes four steps. First, a topographically controlled runoff pattern is created using the standard single-flow, steepest descent algorithm. Next, a tillage-determined runoff pattern is created, i.e. a runoff pattern based on the assumption that water will always flow in the tillage direction. Then, decision rules are applied to determine for each cell whether the water will flow in tillage direction or in topographic direction. Finally, a flow direction map can be generated by combining the topographically determined runoff pattern with the tillage-controlled runoff pattern. This repository is an updated version of the original code, adjusted to run smoothly with the current version of PCRaster (v4.4.0)

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.

This repository contains the code and secondary data used for analysis and calculations on runoff, erosion and pesticide transport in particulate and dissolved phase. The analysis is done on an observational dataset in which rainfall-runoff events where monitored in a small agricultural catchment in Limburg, The Netherlands.

The main data in this dataset are observed rainfall runoff events. During this events runoff, erosion and related pesticide concentrations in the particulate and dissolved phase are measured. For each runoff event timeseries are available of measured discharge (1 minute interval), suspended sediment (5 minute interval) and pesticide concentrations in both phases. In addition, we collected data from field observations and interviews with land managers, data is available on pesticide applications and concentrations of pesticides in soil.

Measuring the characteristics of raindrops is essential for different processes studies. There have been many methods used throughout history to measure raindrops. In recent years, automatic image recognition and processing systems have been used with high-speed cameras to characterize rainfall by obtaining the spectrum of droplet sizes and their speeds and thus being able to use this technology to calibrate rainfall simulators. In this work, two phases were carried out: in the first one, individual drops with terminal speeds of different sizes were measured and processed both in speed and in shape with a high-speed camera; and in the second phase, a calibration procedure was designed but in multidrop images, determining the characteristics of the drops produced by a rain simulator. According to results, the real shape of each drop depending on the size was determined, from round to ovaloid shapes, and the terminal velocity of water drops with different sizes was measured. Based on the rain images used to calibrate a rainfall simulator, it was observed that, with a higher intensity of rain, the drops produced were smaller, which contrasts with real rain, in which just the opposite happens. This calibration evaluates their resemblance to reality, calculates the real kinetic energy of the rain they produce and see if they can be used to model events in nature.

Measuring the characteristics of raindrops is essential for different processes studies. There have been many methods used throughout history to measure raindrops. In recent years, automatic image recognition and processing systems have been used with high-speed cameras to characterize rainfall by obtaining the spectrum of droplet sizes and their speeds and thus being able to use this technology to calibrate rainfall simulators. In this work, two phases were carried out: in the first one, individual drops with terminal speeds of different sizes were measured and processed both in speed and in shape with a high-speed camera; and in the second phase, a calibration procedure was designed but in multidrop images, determining the characteristics of the drops produced by a rain simulator. According to results, the real shape of each drop depending on the size was determined, from round to ovaloid shapes, and the terminal velocity of water drops with different sizes was measured. Based on the rain images used to calibrate a rainfall simulator, it was observed that, with a higher intensity of rain, the drops produced were smaller, which contrasts with real rain, in which just the opposite happens. This calibration evaluates their resemblance to reality, calculates the real kinetic energy of the rain they produce and see if they can be used to model events in nature.