Most field erosion studies in agricultural areas provide little information on the probable errors involved. Here, for the first time, we compare the accuracy, time and cost of conventional and new methodologies for gully surveying, and provide a model to estimate the effort required to achieve a specified accuracy. Using a terrestrial LiDAR survey of a 7.1-m-long guliy reach as a benchmark data set, the accuracies of different measurement methods (a new 3D photo-reconstruction technique, total station, laser profilemeter, and pole) are assessed for estimating gully erosion at a reach scale. Based on further field measurements performed over nine gullies (>100 m long), a simulation approach is derived to model the expected volume errors when 2D methods are used at the gully scale. All gullies considered were located near Cordoba, Spain. At the reach scale, the field measurements using 3D photo-reconstruction and total station techniques produced cross-sectional area error values smaller than 4%, with other 2D methods exceeding 10%. For volume estimation, photo-reconstruction proved similar to LiDAR data, but 2D methods generated large negative volume error (E^) values (<-13% for laser profilemeter and pole). We show that the proposed error expressions derived from the model are in line with the reach-scale field results. A measurement distance factor (MDF) is defined that represents the ratio between cross-section distance and the gully length, and thus reflects relative survey effort. We calculate the required MDF for specified values of f^, illustrating how MDF decreases with increasing gully length and sinuosity.Abbreviations: A, cross sectional area (m^); D, distance between adjacent cross sections (m); DEM, digital elevation model; E^, relative area measurement error (%); E'-, relative length error (%); E^, relative volume measurement error (m-^); L, Gully length (m); i.g^,, distance between the extremes of the gully (m); i-gj-t-sm' distance between the extremes of a 5 m reach (m); L^, polyline length defined by cross section distance (m); /. ,, length of the polyline that fits coarsely the gully thalweg following knickpoints (m); ¿real-5m' real length of a 5 m reach (m); MDF, measurement distance factor (%); n, number of subreaches; N^^, total number of 5-m reaches within a gully; S^'^¡^^^¡, local sinousity; 5 II , gully sinuosity; SE, sinuosity factor; o^^ standard deviation of the volume error drstribution (%); V, volume of eroded soil within the gully (m^).
Abstract. Three-dimensional photo-reconstruction (PR) techniques have been successfully used to produce high-resolution surface models for different applications and over different spatial scales. However, innovative approaches are required to overcome some limitations that this technique may present for field image acquisition in challenging scene geometries. Here, we evaluate SF3M, a new graphical user interface for implementing a complete PR workflow based on freely available software (including external calls to VisualSFM and CloudCompare), in combination with a low-cost survey design for the reconstruction of a several-hundred-metres-long gully network. SF3M provided a semi-automated workflow for 3-D reconstruction requiring ∼ 49 h (of which only 17 % required operator assistance) for obtaining a final gully network model of > 17 million points over a gully plan area of 4230 m 2 . We show that a walking itinerary along the gully perimeter using two lightweight automatic cameras (1 s time-lapse mode) and a 6 m long pole is an efficient method for 3-D monitoring of gullies, at a low cost (∼ EUR 1000 budget for the field equipment) and the time requirements (∼ 90 min for image collection). A mean error of 6.9 cm at the ground control points was found, mainly due to model deformations derived from the linear geometry of the gully and residual errors in camera calibration. The straightforward image collection and processing approach can be of great benefit for non-expert users working on gully erosion assessment.
Despite the high risk of erosion in olive orchards located in mountainous areas in Spain, little research has been carried out to account for the complexity and interaction of the natural processes of runoff and soil erosion on the catchment scale or small catchment scale. In this study, a microcatchment of 6·7 ha in a mountainous area under no-tillage farming with bare soil was set up to record runoff and sediment. Soil erosion and runoff patterns were monitored over a two-year period. Totally, 22 events were observed. The data were analysed, and then used to calibrate the AnnAGNPS model, which allowed us to complete the data period and describe the hydrological and erosive behaviour on a monthly and annual basis. A high variability in catchment responses was observed, due to differences in the storms and to the effect of the surface soil moisture content. Maximum intensities of 10 and 30 min determined the final runoff values while the total sediment loads were dependent on the rainfall depth. The impact of management on the reduction of porosity can explain the relationship between runoff and intensity in the microcatchment. However, the impact of the spatial scale meant that the transport of sediment required substantial rainfall depths to ensure a continuous flow from the hillslopes. The results of the calibration (E > 0·60 and r > 0·75) on the event and monthly scale confirmed the applicability of AnnAGNPS to predict runoff and erosion in the microcatchment. The predicted average runoff coefficient was 3·3% for the study period and the total average sediment loads, 1·3 Mg/ha/yr. Despite these low values, the model simulation showed that much larger runoff coefficients and soil losses can be expected for periods with several consecutive years in which the annual rainfall depth was over 500 mm. The use of cover is recommended to prevent the high levels of erosion associated with these conditions.
Abstract. There is little information in scientific literature regarding the modifications induced by check dam systems in flow regimes within restored gully reaches, despite it being a crucial issue for the design of gully restoration measures. Here, we develop a conceptual model to classify flow regimes in straight rectangular channels for initial and damfilling conditions as well as a method of estimating efficiency in order to provide design guidelines. The model integrates several previous mathematical approaches for assessing the main processes involved (hydraulic jump, impact flow, gradually varied flows). Ten main classifications of flow regimes were identified, producing similar results when compared with the IBER model. An interval for optimal energy dissipation (ODI) was observed when the steepness factor c was plotted against the design number (DN, ratio between the height and the product of slope and critical depth). The ODI was characterized by maximum energy dissipation and total influence conditions. Our findings support the hypothesis of a maximum flow resistance principle valid for a range of spacing rather than for a unique configuration. A value of c = 1 and DN ∼ 100 was found to economically meet the ODI conditions throughout the different sedimentation stages of the structure. When our model was applied using the same parameters to the range typical of step-pool systems, the predicted results fell within a similar region to that observed in field experiments. The conceptual model helps to explain the spacing frequency distribution as well as the often-cited trend to lower c for increasing slopes in step-pool systems. This reinforces the hypothesis of a close link between stable configurations of step-pool units and man-made interventions through check dams.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.