Gully Erosion Model Research Articles

Prioritising interventions for the reduction of erosion in classical gullies: a modelling study

Context Gully erosion is a significant socioeconomic and environmental issue that affects agricultural productivity, infrastructure, and water quality of receiving waters. Despite a variety of interventions to prevent gully formation and rehabilitate existing gullies, cost-effective interventions are specific to individual gullies. Aims The aim of this study was to assess the performance of a suite of gully management interventions across three different classical gullies. Methods A one-dimensional process-based model, MERGE (modelling erosion resistance for gully erosion), was used to quantify the sediment yield exiting the gullies, in response to various management interventions. Key results The net decrease in sediment yield was 2.5–57.4% for each of four interventions applied in isolation and 51.2–78.7% in combination. Reductions in sediment yield for each intervention varied markedly among sites, by a factor of 2.6–78.3 in absolute terms. This resulted in a unique ranking of the interventions by their effectiveness for a given site. Overall, interventions applied in combination were most effective, outperforming those applied in isolation by a factor of 1.24–1.37, but the effect of applying interventions in combination was not additive. Conclusions This study demonstrates the ability of the gully erosion model MERGE to be a useful tool to identify and tailor effective intervention strategies for individual gullies, and be a useful guide for decision making for erosion management. Implications Analysis of expected benefits of gully remediation using tools such as MERGE is important for assessing options at gully sites due to their widely varying response.

Entropy-based Model for Gully Erosion - A combination of probabilistic and deterministic components.

Gullies are a major threat to ecosystems, potentially leading to land degradation, groundwater depletion, crop loss, debris flow, and desertification. Gullies are also characterized by having a fast development and turning into primary sediment sources. Despite their impact, we have but scarce understanding of how gully erosion evolves and how to model it. In this paper, we propose a new gully erosion model that is based on the classical premise of net shear stress, i.e., hydraulic shear stress minus critical (resistant) shear stress, to calculate detachment rates. In order to calculate hydraulic shear stress, we developed a new equation derived from the principle of minimum cross-entropy; it was validated with laboratory measures from the literature with a Nash-Sutcliffe Efficiency of 0.95. Soil samples were analysed in the laboratory to assess critical shear stress and other soil properties. The novel gully erosion model was implemented in three gully impacted locations with catchment areas ranging from 10-2 to 10+1 ha. To assess channel geometry and eroded volumes, we used Unmanned Aerial Vehicle and Structure-from-Motion technique. The model successfully estimated long-term erosion rates, its efficiency was 0.77, and it is recommended for catchments up to 8 ha. Therefore, the new model provides planners and stakeholders with a tool to assess gully erosion, sediment yield and geometry in most areas.

The Theoretical Approach to the Modelling of Gully Erosion in Cohesive Soil

The stochastic gully erosion model (STOGEM) is based on a combination of deterministic mechanics and a stochastic description of the erosion control factors. The main proposition in the model is that the depth of the active surface layer of eroded cohesive soil is equal to one particle diameter, and the deposition of eroded particles is negligible. The erosion rate at the gully bed is calculated directly from the equation of the balance between driving and resistance forces acting on soil particles in flowing water using the probability density functions of stochastic variables: flow velocity, soil aggregate size and cohesion. Probability density functions of cohesion in the model vary through time and space during the erosion event due to the changes in soil composition—armoring and loosening. This theory is still far from achieving practical application, but opens up a new way for better understanding the experimental results of gully erosion and shows the direction for future investigations.

Models of Gully Erosion by Water

The type of modelling of gully erosion for the projects of land management depend on the targets and degree of details of these projects, as well as on the availability of input data. The set of four models cover a broad range of possible applications. The most detailed information about predicted gullies, change of their depth, width, and volume throughout the gully lifetime is obtained with the gully erosion and thermoerosion dynamic model. The calculation requires the time series of surface runoff, catchment relief, and lithology and the complex of coefficients and parameters, some of which can be estimated only by model calibration on the measurements. The difficulty in obtaining some of these coefficients makes it necessary to use less complicated models. The stable gully model predicts final gully depths and widths and is useful for projects where only stable gully geometry is used. The modified area–slope approach is used in the two simplest models, where the position on the slopes of possible gullies is calculated without details of the gully geometry. One of these models calculates total erosion potential, taking into account all water runoff transforming a gully. The second calculates gully erosion risk, using the information about slope inclination, contributing area and maximum surface runoff.

Novel ensembles of COPRAS multi-criteria decision-making with logistic regression, boosted regression tree, and random forest for spatial prediction of gully erosion susceptibility

Gully erosion is considered as a severe environmental problem in many areas of the world which causes huge damages to agricultural lands and infrastructures (i.e. roads, buildings, and bridges); however, gully erosion modeling and prediction with high accuracy are still difficult due to the complex interactions of various factors. The objective of this research was to develop and introduce three new ensemble models, which were based on Complex Proportional Assessment of Alternatives (COPRAS), Logistic Regression (LR), Boosted Regression Tree (BRT), Random Forest (RF), and Frequency Ratio (FR) for spatial prediction of gully erosion with a case study at the Najafabad watershed (Iran). For this purpose, a total of 290 head-cut of gullies and 17 conditioning factors were collected and used to establish a geospatial database. Subsequently, FR was used to determine the spatial relationship between the conditioning factors and the head-cut of gullies, whereas RF, BRT, and LR were used to quantify the relative importance of these factors. In the next step, three ensemble gully erosion models, named COPRAS-FR-RF, COPRAS-FR-BRT, and COPRAS-FR-LR were developed and verified. The Success Rate Curve (SRC), and the Prediction Rate Curve (PRC) and their areas under the curves (AUC) were used to check the performance of the three proposed models. The result showed that Soil group, geomorphology, and drainage density factors played the key role on the occurrence of the gully erosion. All the three models have very high degree-of-fit and the prediction performance, the COPRAS-FR-RF model (AUC-SRC = 0.974 and AUC-PRC = 0.929), the COPRAS-FR-BRT model (AUC-SRC = 0.973 and AUC-PRC = 0.928), and the COPRAS-FR-LR model (AUC-SRC = 0.972 and AUC-PRC = 0.926); therefore, it is concluded that they are efficient and new powerful tools which could be used for predicting gully erosion in prone-areas.

The role of vegetation on gully erosion stabilization at a severely degraded landscape: A case study from Calhoun Experimental Critical Zone Observatory

Gully erosion was evidence of land degradation in the southern Piedmont, site of the Calhoun Critical Zone Observatory (CCZO), during the cotton farming era. Understanding of the underlying gully erosion processes is essential to develop gully erosion models that could be useful in assessing the effectiveness of remedial and soil erosion control measures such as gully backfilling, revegetation, and terracing.Development and validation of process-based gully erosion models is difficult because observations of the formation and progression of gullies are limited. In this study, analytic formulations of the two dominant gullying processes, namely, plunge pool erosion and slab failure, are utilized to simulate the gullying processes in the 4-km2 Holcombe's Branch watershed. In order to calibrate parameters of the gully erosion model, gully features (e.g., depth and area) extracted from a high-resolution LiDAR map are used. After the calibration, the gully model is able to delineate the spatial extent of gullies whose statistics are in close agreement with the gullies extracted from the LiDAR DEM. Several simulations with the calibrated model are explored to evaluate the effectiveness of various gully remedial measures, such as backfilling and revegetation. The results show that in the short-term, the reshaping of the topographical surface by backfilling and compacting gullies is effective in slowing down the growth of gullies (e.g., backfilling decreased the spatial extent of gullies by 21–46% and decreased the average depth of gullies by up to 9%). Revegetation, however, is a more effective approach to stabilizing gullies that would otherwise expand if no gully remedial measures are implemented. Analyses of our simulations show that the gully stabilization effect of revegetation varies over a wide range, i.e., leading to 23–69% reduction of the spatial extent of gullies and up to 45% reduction in the depth of gullies, depending on the selection of plant species and management practices.

Assessment of land use impact on hydraulic threshold conditions for gully head cut initiation

Abstract. A gully as an accelerated erosion process is responsible for land degradation under various environmental conditions and has been known as a threshold phenomenon. Although the effects of gullying processes have been well documented, few soil erosion models have taken into account the threshold condition necessary for gully development. This research was devoted to determining the effects of land use change on hydraulic threshold condition and stream power of water flow through an in situ experimental flume (15 m × 0.4 m). Results indicated that head cut initiation and detachment rates showed a better correlation to stream power indices than shear stress (τcr). The threshold unit stream power value (ωu) for head cut initiation in rangeland, abandoned land, and dry farming land was 0.0276, 0.0149, and 4.5 × 10−5 m s−1, respectively. Moreover, the micro-relief condition of soil surface and surface vegetation affected the flow regime of discharge and velocity. It is seen that the composite hydraulic criteria of Froude number (Fr) and discharge (Q) can clearly discriminate the land uses' threshold. In fact, the remarkable decrease of τcr in dry farming was related to the effect of tillage practice on soil susceptibility and aggregate strength. The findings indicated that using the unit steam power index instead of critical shear stress could increase the models' precision for prediction of head cut development. Compared to the Ephemeral Gully Erosion Model (EGEM) equation for critical shear stress, it is important to point out that for modelling of gully erosion, using single soil attributes can lead to an inaccurate estimation for τcr. In addition, based on the findings of this research, the use of threshold values of τcr = 35 dyne cm−2 and ωu = 0.4 cm s−1 in physically based soil erosion models is susceptible to high uncertainty when assessing gully erosion.

Evaluating sediment transport capacity relationships for use in ephemeral gully erosion models

Abstract. On cropland, ephemeral gully erosion in the USA may contribute up to 40% of the sediment delivered to the edge of the field. Well-tested, physically- and process-based tools for field and watershed scale prediction of gully erosion are lacking due to the fact that the complex nature of migrating headcuts is poorly understood. Understanding sediment transport capacity downstream of migrating headcuts is essential, as sediment deposition often leads to temporary storage that controls downstream water elevation, which in turn affects the rate of headcut migration. Current process-based gully erosion prediction technology used by the Agricultural Research Service (ARS) is based on characterizing the headcut migration rate, which requires the deposition depth as input to the model. Alternatively, the deposition depth can be calculated if downstream sediment transport capacity can be predicted. Data collected at the ARS-National Sedimentation Laboratory were used to test existing sediment transport relationships for the five sediment size classes (clay, silt, sand, small aggregates, large aggregates) typically used in ARS soil erosion models. The results show that the transport rate can be satisfactorily predicted for sand and large aggregate size fractions using common transport relationships based on unit stream power theory. The fractional content of the sand and large aggregate size classes can be computed using standard relationships, which are based on soil texture, previously developed by ARS. The transport of clays, silts and small aggregates is detachment limited and must therefore be computed using improved soil detachment relationships for ephemeral gullies.

Efficiency test of adapted EGEM model in predicting ephemeral gully erosion around Mubi, Northeast Nigeria

A field adaptation test of the Ephemeral Gully Erosion Model (EGEM) to predict ephemeral gully (EG) erosion was carried out in the 2008 and 2009 farming seasons in the Mubi area, NE Nigeria. Land use, conservation practices, and EG channel features were measured and/or noted at each site. Soil loss varied among the sites and seasons. The measured area, volume, and mass of soil loss were used to test the standard EGEMstd, and the adapted models׳ (EGEMAd and EGEMAl) prediction efficiencies. The result showed that EGEMstd could not predict the area of soil loss adequately. Both EGEMAd and EGEMAl were efficient and better adapted to predicting area, volume, and mass loss from EG erosion. The adapted models are therefore strongly recommended for implementation in the study area.

Incorporating uncertainty in gully erosion calculations using the random forests modelling approach

AbstractGully erosion represents one of the greatest threats to agricultural watersheds around the world and this is exacerbated with continual changes to land practices and changing climatic condition at a temporal scale. Catchment based models which include gully erosion have received increased attention in recent years due to the impact of gully erosion on downstream water quality. These types of models take gully erosion calculated via a deterministic model at a particular spatial location, along with other measures of erosion to provide an end‐of‐catchment load. Although seen as a major contributor to erosion in this type of modelling framework, the error surrounding the gully erosion calculation is ignored in the sediment model. We propose a methodology that investigates the error in the gully erosion model. The methodology uses Random Forests to predict gully density and its associated prediction error across a catchment using environmental variables, which are then incorporated into the gully erosion model. We demonstrate the approach using the Burdekin catchment in Queensland, Australia, where only a very small proportion of gullies (∼0.88%) have been mapped. Our results cast doubt in the predictive ability of models of sediment transportation that use gully erosion where the error is estimated high. Copyright © 2009 John Wiley & Sons, Ltd.

Stages in gully evolution and self‐organized criticality

AbstractThe process of gully erosion at the active stage is far from equilibrium; rather, the gully shows the characteristics of a self‐organizing system that is close to crisis. This qualitative description is similar to the understanding of open dynamic systems at a state of selforganized criticality (SOC). We tried to find the quantitative attributes of SOC in numerical simulations of gully evolution with a dynamic gully erosion model. Three scenarios were used: (1) gully evolution is controlled by initial topography and texture, when the discharge and base level are constant; (2) discharge is constant and the base level lowers over time; (3) the base level is constant and the discharge changes naturally. The results of numerical simulations of gully evolution are consistent with the expectations of the SOC theory. Under the first scenario, when the gully was at the initial active stage of evolution, the system showed all the SOC attributes: a fractal long profile; a ‘red‐noise’ spectrum; and the power‐law frequency–magnitude relationship (FMR). With gully stabilization, the system had lost SOC behaviour and became non‐fractal, with a ‘blue‐noise’ spectrum and exponential FMR. For this scenario SOC criteria can be used to find the boundary between active and stable states of gully evolution. Simulations under the second scenario showed that the riverbed incision made the active stage of the gully evolution with all SOC attributes much longer than with a stable base level. Simulation under the third scenario, with variable discharge (with the elements of SOC), showed that the SOC attributes of the hydrological system could be induced on the landform system. While the gully had evidently reached the stable stage, the process of gully volume change still indicated active‐stage SOC attributes. Therefore some landform systems can really be in the SOC stage, which can diagnose their activity; others only show SOC attributes induced by climatic or hydrologic systems. Copyright © 2006 John Wiley & Sons, Ltd.

Application of the EGEM model to predict ephemeral gully erosion in Sicily, Italy

Recent research has shown the importance of ephemeral gully (EG) erosion in the context of global erosion and, at the same time, the lack of adequate models to estimate it. At present, the ephemeral gully erosion model (EGEM) is the only conceptual model specifically developed for ephemeral gully erosion estimation. The main aim of the paper is to evaluate the performance of EGEM model adapted to local conditions compared with that of simple empirical equations. A data set of 92 ephemeral gullies formed between 1995 and 2000 in a wheat-cultivated study area in Sicily, Italy, was used for the purpose. In order to improve EGEM performance, two important adaptations were made. Both the rain distribution type and the causative rainfall of the hydrological component of EGEM were modified to reproduce local conditions. The EGEM assumption of a constant depth for the entire length of the ephemeral gully was also modified. EGEM performance was tested with two different rain distribution types, three different causative rainfalls and two different EG depths. The adaptation of the EGEM hydrological component improves the volume prediction with respect to the standard version of EGEM; the improvement is mainly due to the rain distribution type, whereas causative rainfall seems to be less important. The use of adjusted EG depths is, however, essential to minimise the errors between measured and predicted volumes. The capability of EGEM to predict the ephemeral gully cross-section is weak and non-significant relationships were found between measured and estimated width. A regression analysis between ephemeral gully-eroded volume and different morphological, topographical and hydrological parameters confirms the great importance of EG length to explain eroded volume ( R 2=0.64 for the simple correlation between volume and length). Considering that the adaptation of the hydrological component and the measurement of EG depths are necessary for the EG volumes estimated by EGEM to be reliable, it seems more simple, as suggested by other authors, to use empirical relations between eroded volume and length performed in different environments, until more precise physically based models are developed.

Integrating geographical information systems, remote sensing, ground truthing and modelling approaches for regional erosion classification of semi‐arid catchments in South Africa

AbstractWater resources management is an important issue in southern African countries. With respect to water quality problems, the understanding of the dynamics of integrated soil erosion processes in river basins is of crucial importance. This study is on the delineation of response units (RUs) in the Mkomazi River catchment (KwaZulu/Natal; South Africa). It was carried out within the framework of an interdisciplinary EU‐funded project aimed at developing an integrated water resources management system for water resources analyses and prognostic scenario planning in semi‐arid catchments of southern Africa. Within this more general framework, particular attention was focused on the identification of sediment source areas. For this purpose, the RUs concept was applied to delineate erosion RUs (ERUs). The ERUs were subsequently used to identify heterogeneously distributed areas within a river catchment characterized by specific hydrological and erosion dynamics and features. Therefore, they can be applied as modelling entities in physically based hydrological and erosion models. Spatially distributed input data from the catchment were derived by remote sensing techniques and geographical information systems analyses. Taking into account the high amount of sediments produced by gully erosion, not considered in USLE‐type models, special attention was focused on gully erosion using a dynamic gully erosion model. The example from southern Africa shows that the methods applied are able to identify areas affected by gully erosion. Furthermore, it was possible to estimate the entire amount of soil loss, including gully erosion. Copyright © 2003 John Wiley & Sons, Ltd.

The value of a physically based model versus an empirical approach in the prediction of ephemeral gully erosion for loess-derived soils

A data set on soil losses and controlling factors for 58 ephemeral gullies has been collected in the Belgian loess belt from March 1997 to March 1999. Of the observed ephemeral gullies, 32 developed at the end of winter or in early spring (winter gullies) and 26 ephemeral gullies developed during summer (summer gullies). The assessed data have been used to test the physically based Ephemeral Gully Erosion Model (EGEM) and to compare its performance with the value of simple topographical and morphological indices in the prediction of ephemeral gully erosion. Analysis shows that EGEM is not capable of predicting ephemeral gully cross-sections well. Although conditions for input parameter assessment were ideal, some parameters such as channel erodibility, critical flow shear stress and local rainfall depth showed great uncertainty. Rather than revealing EGEM's inability of predicting ephemeral gully erosion, this analysis stresses the problematic nature of physically based models, since they often require input parameters that are not available or can hardly be obtained. With respect to the value of simple topographical and morphological indices in predicting ephemeral gully erosion, this study shows that for winter gullies and summer gullies, respectively, over 80% and about 75% of the variation in ephemeral gully volume can be explained when ephemeral gully length is known. Moreover, when previously collected data for ephemeral gullies in two Mediterranean study areas and the data for summer gullies formed in the Belgian loess belt are pooled, it appears that one single length ( L)–volume ( V) relation exists ( V=0.048 L 1.29; R 2=0.91). These findings imply that predicting ephemeral gully length is a valuable alternative for the prediction of ephemeral gully volume. A simple procedure to predict ephemeral gully length based on topographical thresholds is presented here. Secondly, the empirical length–volume relation can also be used to convert ephemeral gully length data extracted from aerial photos into ephemeral gully volumes.

Testing the Ephemeral Gully Erosion Model (EGEM) for two Mediterranean environments

Testing the Ephemeral Gully Erosion Model (EGEM) for two Mediterranean environments

Testing the Ephemeral Gully Erosion Model (EGEM) for two Mediterranean environments

Few models can predict ephemeral gully erosion rates (e.g. CREAMS, EGEM). The Ephemeral Gully Erosion Model (EGEM) was specifically developed to predict soil loss by ephemeral gully erosion. Although EGEM claims to have a great potential in predicting soil losses by ephemeral gully erosion, it has never been thoroughly tested. The objective of this study was to evaluate the suitability of EGEM for predicting ephemeral gully erosion rates in Mediterranean environments. An EGEM-input data set for 86 ephemeral gullies was collected: detailed measurements of 46 ephemeral gullies were made in intensively cultivated land in southeast Spain (Guadalentin study area) and another 40 ephemeral gullies were measured in both intensively cultivated land and abandoned land in southeast Portugal (Alentejo study area). Together with the assessment of all EGEM-input parameters, the actual eroded volume for each ephemeral gully was also determined in the field. A very good relationship between predicted and measured ephemeral gully volumes was found (R2 = 0·88). But as ephemeral gully length is an EGEM input parameter, both predicted and measured ephemeral gully volumes have to be divided by this ephemeral gully length in order to test the predictive capability of EGEM. The resulting relationship between predicted and measured ephemeral gully cross-sections is rather weak (R2 = 0·27). Therefore it can be concluded that EGEM is not capable of predicting ephemeral gully erosion for the given Mediterranean areas. A second conclusion is that ephemeral gully length is a key parameter in determining the ephemeral gully volume. Regression analysis shows that a very significant relation between ephemeral gully length and ephemeral gully volume exists (R2 = 0·91). Accurate prediction of ephemeral gully length is therefore crucial for assessing ephemeral gully erosion rates. Copyright © 2001 John Wiley & Sons, Ltd.

Method to predict cropland ephemeral gully erosion

Erosion of farmland due to concentrated flow is very severe on many unprotected fields across the United States. Small channels can turn into large gullies if not controlled. These small channels are routinely obliterated by tillage of the field and other routine farm operations only to be reformed again. Opposing slopes adjacent to an ephemeral gully allow runoff to reestablish a channel in approximately the same location. Since the 1960s, the Universal Soil Loss Equation (USLE) has been used to estimate rill and sheet erosion. This paper describes the Ephemeral Gully Erosion Model (EGEM). EGEM is a modification of the Agricultural Research Service Ephemeral Gully Erosion Estimate (EGEE) computer model to meet the Natural Resources Conservation Service (NRCS) needs. Limited field data obtained by NRCS were used to validate the single event component of EGEM. This paper presents a summary of these studies. There were no data available at the time of the model development to validate the average annual concept of the model. ARS conducted validation studies for the EGEE model.

Soil and gully erosion models for effective control programmes

Many parts of the world have been ravaged by soil and gully erosion, resulting in major environmental problems and causing extensive badland topography, devastated economies, untold human suffering, loss of agricultural land, ancestral homes and economic trees. The underlying causes are rarely fully-understood. Control measures based on incorrect information, incomplete data or wrong concepts have failed. Soil properties, rainfall and runoff intensity, wind action, geological, hydrogeochemical and geotechnical characteristics, and anthropogenic activities are factors generating soil and gully erosion processes. Three different soil and gully erosion models, the SEM, TOM and SOM ( STS), are proposed. The Sediment Off-loading Model ( SOM), and the Tectonic Origin Model ( TOM) distinguish two types of gully erosion in terms of their origin, growth and methods of control. The Soil Erosion Model ( SEM) distinguishes soil erosion from the gully erosion models. Improved understanding and application of these models based on their origin, characteristics and control modes may provide solutions to problems posed by widespread soil and gully erosion. A brief case study of the Agulu-Nanka gully system of Nigeria exemplifies the potential uses of the models and control programmes.