Toward a framework for runoff and soil loss prediction using GUEST technology

Soil Research ◽  
1997 ◽  
Vol 35 (5) ◽  
pp. 1191 ◽  
Author(s):  
B. Yu ◽  
C. W. Rose ◽  
C. A. A. Ciesiolka ◽  
K. J. Coughlan ◽  
B. Fentie
Keyword(s):  
Soil Loss ◽  
Field Data ◽  
Rainfall Intensity ◽  
Rainfall Amount ◽  
Balance Model ◽  
Erosion Processes ◽  
Total Runoff ◽  
Physically Based ◽  
Loss Prediction ◽  
Runoff Rate

In recent years, a number of physically based models have been developed for soil loss predictions. GUEST is one such model based on fundamental physical principles and the current understanding of water erosion processes. GUEST is mainly used to determine a soil erodibility parameter. To apply the model in a predictive mode, the model is simplified in a physically meaningful manner for flow-driven erosion processes, and 2 essential hydrologic variables are identified, namely total runoff amount and an effective runoff rate. These variables are required to determine soil loss for individual runoff events. A simple water balance model was developed and used to predict runoff amount from rainfall amount. The efficiency of this runoff amount model in prediction was over 90% using field data. A 1-parameter regression model (r2 ~ 0·9) for the effective runoff rate was also established which uses peak rainfall intensity in addition to rainfall and runoff amounts. The prediction of peak rainfall intensity for a given rainfall amount and storm type was also sought. The field data were from Goomboorian, near Gympie, in south-east Queensland and these data were used to test and validate both models. Results overall are satisfactory and the approach adopted is promising. A framework for soil loss prediction is established within which individual parts can be further refined and improved.

scholarly journals Modelling Effects of Rainfall Patterns on Runoff Generation and Soil Erosion Processes on Slopes

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2221
Author(s):  
Qihua Ran ◽  
Feng Wang ◽  
Jihui Gao
Keyword(s):  
Soil Erosion ◽  
Rainfall Intensity ◽  
Temporal Patterns ◽  
Runoff Generation ◽  
Slope Length ◽  
Erosion Processes ◽  
Total Runoff ◽  
Wide Range ◽  
Critical Slope ◽  
Rainfall Patterns

Rainfall patterns and landform characteristics are controlling factors in runoff and soil erosion processes. At a hillslope scale, there is still a lack of understanding of how rainfall temporal patterns affect these processes, especially on slopes with a wide range of gradients and length scales. Using a physically-based distributed hydrological model (InHM), these processes under different rainfall temporal patterns were simulated to illustrate this issue. Five rainfall patterns (constant, increasing, decreasing, rising-falling and falling-rising) were applied to slopes, whose gradients range from 5° to 40° and projective slope lengths range from 25 m to 200 m. The rising-falling rainfall generally had the largest total runoff and soil erosion amount; while the constant rainfall had the lowest ones when the projective slope length was less than 100 m. The critical slope of total runoff was 15°, which was independent of rainfall pattern and slope length. However, the critical slope of soil erosion amount decreased from 35° to 25° with increasing projective slope length. The increasing rainfall had the highest peak discharge and erosion rate just at the end of the peak rainfall intensity. The peak value discharges and erosion rates of decreasing and rising-falling rainfalls were several minutes later than the peak rainfall intensity.

scholarly journals Simulation of Rainfall Intensity and Slope Gradient to Determination the Soil Runoff Coefficient at Microplot Scale

2020 ◽  
Vol 10 (1) ◽  
pp. 12-17
Author(s):  
Dawod Rasooli Keya ◽  
Tariq H. Karim
Keyword(s):  
Soil Loss ◽  
Rainfall Intensity ◽  
Low Cost ◽  
Silty Clay ◽  
Runoff Coefficient ◽  
Slope Gradient ◽  
Erosion Processes ◽  
High Repeatability ◽  
Runoff And Sedimentation ◽  
Rain Simulator

Simulating rainfall is one of the valuable methods of measuring hydrological data and soil erosion processes. Rapid evaluation, high repeatability, and low cost are the reasons of using rain simulators. In this study, a rain simulator was constructed in dimensions of 3.0 × 3.0 × 3.0 m and it was protected on three sides by a plastic cover. An inclined table was used to create slopping surfaces of 5, 10, and 15%. Microplots were used in the dimensions of 0.2 × 0.4 × 1.0 m to collect and measure direct runoff in a bucket outside the device. Nozzles were calibrated to produce two different rainfall intensities 10 and 20 mmh−1 using sprinkler Model 5B at 8 and 12 psi, respectively. Furthermore, three different soil types, namely, clay loam (CL), silty clay (SC) loam, and SC were examined. In general, it was observed that with increasing the rainfall intensity and slope, the rate of runoff and sedimentation increase. SC soil at 15% slop offered the highest performance under the intensity of 20 mmh−1. SC and the CL soils produced the highest and lowest runoff coefficients, respectively. The CL soil produced the highest soil loss (1 kgm2 at 15% and I = 20 mmh−1). Further, it was concluded that a significant change (an average increase of 53%) in soil loss can be achieved as the rainfall intensity increased from 10 to 20 mmh−1.

scholarly journals Experimental Study of Freeze-Thaw/Water Compound Erosion and Hydraulic Conditions as Affected by Thawed Depth on Loessal Slope

2020 ◽  
Vol 8 ◽  
Author(s):  
Wei Wang ◽  
Zhanbin Li ◽  
Rui Yang ◽  
Tian Wang ◽  
Peng Li
Keyword(s):  
Soil Loss ◽  
Loss Rate ◽  
Rainfall Intensity ◽  
Freeze Thaw ◽  
Erosion Processes ◽  
Hydraulic Conditions ◽  
The Mean ◽  
The Relationship ◽  
Thaw Water ◽  
Soil Loss Rate

Freeze-thaw cycles have significant influences on slope erosion processes. In this study, simulated rainfall laboratory experiments were implemented to investigate erosion processes and the relationship between the soil loss rate and hydraulics conditions under different thawed depths and rainfall intensities. The results indicated that linear regression could be used to describe the relationship between the soil loss rate and runoff time. Soil loss rate, as measured by the curve slope k (represented the increase rate in the soil loss rate), generally increased with runoff time over different thawed depths across all rainfall intensities. The k values generally increased with rainfall intensity from 0.6 to 1.2 mm/min, with the exception of the 4 cm thawed slope, for which the k values initially increased before decreasing with rainfall intensity from 0.6 to 1.2 mm/min. The mean soil loss rate and range also increased with thawed depth under the same rainfall intensity. Finally, the interaction of rainfall intensity and thawed depth had the greatest effect on soil loss rate, while stream erosion power was the hydraulic parameter that exhibited the best soil loss rate prediction performance. The results presented herein improve the understanding of the response of freeze-thaw/water compound erosion to hydraulic conditions.

scholarly journals Prediction of soil loss due to erosion using support vector machine model

2020 ◽  
Vol 42 (3) ◽  
Author(s):  
Van Quan Tran ◽  
Indra Prakash
Keyword(s):  
Support Vector Machine ◽  
Soil Erosion ◽  
Vegetation Cover ◽  
Soil Loss ◽  
Rainfall Intensity ◽  
Mean Squared Error ◽  
Support Vector ◽  
Squared Error ◽  
Model Study ◽  
Loss Prediction

Soil erosion refers to the detachment and removal of soil particles from land (topsoil), by the natural physical forces (water, glacier and wind). Soil erosion causes soil loss in the catchment or any land areas severely impacting agriculture activity, sedimentation in the dam reservoirs, and hampering developmental activities. Therefore, it is desirable to accurately measure soil loss due to erosion for the development and management of an area. With this objective, a well-known machine learning algorithm Support Vector Machine (SVM) has been used in the development of the soil loss prediction model. Eight erosion affecting variable inputs: ambient temperature Tair, rainfall, Antecedent Moisture Conditions (AMC), rainfall intensity, slope, vegetation cover, soil temperature Tsoil and moisture of the soil. Data on published literature was used in the model study. The accuracy of the proposed SVM was assessed by using three statistical performance evaluation indicators namely Person correlation coefficient (R), Root Mean Squared Error (RMSE), Mean Squared Error (MAE). Partial Dependence Plots (PDP) was used to investigate the dependence of prediction results of eight input variables used in the model study. Model validation results showed that SVM model performed well for the prediction of soil loss for testing (R = 0.8993) and also for training (R=0.9123). Rainfall intensity and vegetation cover were found to be the two most important affecting input parameters for the soil loss prediction.

scholarly journals Evolutionary Prediction of Soil Loss from Observed Rainstorm Parameters in an Erosion Watershed Using Genetic Programming

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Kennedy C. Onyelowe ◽  
Ahmed M. Ebid ◽  
Light Nwobia
Keyword(s):  
Genetic Programming ◽  
Soil Loss ◽  
Rainfall Intensity ◽  
Coefficient Of Determination ◽  
Learning Abilities ◽  
Maximum Coefficient ◽  
Runoff Rate ◽  
Gully Head ◽  
The Impact ◽  
Gp Model

Various environmental problems such as soil degradation and landform evolutions are initiated by a natural process known as soil erosion. Aggregated soil surfaces are dispersed through the impact of raindrop and its associated parameters, which were considered in this present work as function of soil loss. In an attempt to monitor environmental degradation due to the impact of raindrop and its associated factors, this work has employed the learning abilities of genetic programming (GP) to predict soil loss deploying rainfall amount, kinetic energy, rainfall intensity, gully head advance, soil detachment, factored soil detachment, runoff, and runoff rate database collected over a three-year period as predictors. Three evolutionary trials were executed, and three models were presented considering different permutations of the predictors. The performance evaluation of the three models showed that trial 3 with the highest parametric permutation, i.e., that included the influence of all the studied parameters showed the least error of 0.1 and the maximum coefficient of determination (R2) of 0.97 and as such is the most efficient, robust, and applicable GP model to predict the soil loss value.

Application of a physically based soil erosion model, GUEST, in the absence of data on runoff rates II.

Soil Research ◽  
1999 ◽  
Vol 37 (1) ◽  
pp. 13 ◽  
Author(s):  
B. Yu ◽  
C. W. Rose ◽  
A. Sajjapongse ◽  
D. Yin ◽  
Z. Eusof ◽  
...  
Keyword(s):  
Soil Loss ◽  
Storm Event ◽  
Soil Erodibility ◽  
Storm Events ◽  
Erosion Model ◽  
Physically Based ◽  
Runoff Rate ◽  
Model Efficiency ◽  
Coarse To Fine ◽  
Event Basis

Runoff rates were estimated from rainfall rates and runoff amounts for 4 experimental sites in China, Malaysia, and Thailand before a physically based erosion model GUEST was used to determine the soil erodibility parameter and evaluate the potential to use the erosion model to predict the amount of soil loss on an event basis. We also examined 3 different ways of determining the soil erodibility parameter for the same storm event using: (i) hydrographs estimated from rainfall intensities and runoff amounts; (ii) an effective runoff rate calculated from the hydrograph; (iii) an estimate of the effective runoff rate based on a scaling technique involving the peak rainfall intensity and the gross runoff coefficient. All 3 methods can produce consistent soil erodibility parameters for a given runoff event. The calculated soil erodibility for individual storm events for all sites shows considerable temporal variation and for most sites a decreasing trend over time, as observed elsewhere in the same region. Among the 4 soils examined, the average soil erodibility tends to decrease as the ratio of coarse to fine materials decreases. When the erosion model GUEST is used to predict event soil loss using estimated soil erodibility parameters, an average model efficiency of 0·68 is achieved for the sites tested.

Field rainfall simulator studies on two clay soils of the Darling Downs, Queensland. III. An evaluation of current methods for deriving soil erodbilities (K factors)

Soil Research ◽  
1984 ◽  
Vol 22 (4) ◽  
pp. 401 ◽  
Author(s):  
RJ Loch
Keyword(s):  
Soil Loss ◽  
Single Event ◽  
Erosion Process ◽  
Annual Average ◽  
Slope Length ◽  
Rainfall Simulator ◽  
Erosion Processes ◽  
Runoff Rate ◽  
Simulated Rain ◽  
Soil Losses

Simulated rain has been widely used to derive soil erodibility (K) values for the Universal Soil Loss Equation (USLE). Because of concern that recent work using smaller plots may not give realistic results, this paper considers the effects of plot length and erosion process on values of K derived from rainfall simulator studies. It also highlights problems in the calculation of K from rainfall simulator data, using the factors of the USLE. Rainulator data on slope length/erosion process interactions were used to calculate soil losses and K for plot lengths of 10.7 and 22.5 m tilled up and down the slope, on two soils, both on 4% slope. K showed up to threefold variation with changes in plot length, because different erosion processes contributed to soil loss. The results also showed major differences between single-event and annual average responses of erosion to slope length, leading to the conclusion that the annual average factors of the USLE cannot be used to analyse single-event rainfall simulator data. Instead, rainfall simulator data must be converted to average annual soil losses, which can then be validly analysed, using the factors of the USLE, to derive K. The procedures presently used to calculate annual average soil losses from rainfall simulator data do not take into account erosion process/runoff rate interactions, and are therefore unsatisfactory. Single-event soil loss models may provide a means for producing better estimates of annual average soil losses suitable for the derivation of K.

scholarly journals PRODUÇÃO E DEPOSIÇÃO DE SEDIMENTOS EM UMA SUB-BACIA HIDROGRÁFICA COM SOLOS SUSCETÍVEIS À EROSÃO

Irriga ◽  
2018 ◽  
Vol 21 (2) ◽  
pp. 284 ◽  
Author(s):  
Carla Deisiane De Oliveira Costa ◽  
Marlene Cristina Alves ◽  
Antônio De Pádua Sousa ◽  
Hélio Ricardo Silva ◽  
Antonio Paz González ◽  
...  
Keyword(s):  
Environmental Degradation ◽  
Soil Loss ◽  
Soil Degradation ◽  
Rainfall Intensity ◽  
Soil Samples ◽  
Sediment Deposition ◽  
Mato Grosso ◽  
Erosion Processes ◽  
Water Courses ◽  
Mato Grosso Do Sul

PRODUÇÃO E DEPOSIÇÃO DE SEDIMENTOS EM UMA SUB-BACIA HIDROGRÁFICA COM SOLOS SUSCETÍVEIS À erosão Carla Deisiane de Oliveira Costa1; Marlene Cristina Alves2; Antônio de Pádua Sousa3; HÉLIO RICARDO SILVA2; ANTONIO PAZ GONZÁLEZ4 E JOSÉ MANUEL MIRÁS AVALOS4 1 Universidade Estadual de Mato Grosso do Sul, UEMS/Aquidauana. [email protected] Universidade Estadual Paulista “Júlio de Mesquita Filho”, Faculdade de Engenharia de Ilha Solteira, UNESP/FE/IS. [email protected]; [email protected] Universidade Estadual Paulista “Júlio de Mesquita Filho”, Faculdade de Ciências Agronômicas, UNESP/FCA. [email protected] Universidade da Coruña, UDC, La Coruña, España. [email protected]; [email protected].  1 RESUMO A degradação do solo traz como consequência a sua erosão, causando o assoreamento e a contaminação dos cursos de água. Este trabalho teve por objetivo estimar as perdas de solo e a deposição de sedimentos na sub-bacia Dois Córregos, localizada no munícipio de Selvíria, MS, com o intuito de identificar as áreas com maior suscetibilidade a estes processos, utilizando como ferramenta o modelo LISEM. Os solos da sub-bacia são o Latossolo Vermelho e o Argissolo Vermelho-Amarelo, ambos de textura arenosa. Para as simulações foi utilizado o modelo LISEM, sendo coletados dados de intensidade de precipitação dos anos de 2009 a 2012. Foram selecionados 10 eventos com maiores intensidades de precipitação para o período avaliado. Para obtenção dos parâmetros de entrada necessários, foram coletas amostras de solos. As coletas foram realizadas em dez locais da sub-bacia, sob os diferentes usos e ocupação do solo. O eucalipto propicia proteção aos solos da sub-bacia. Os sedimentos produzidos ficam depositados nos leitos da sub-bacia, ocasionando o assoreamento dos cursos de água. O modelo LISEM se mostrou eficiente para a localização de áreas suscetíveis aos processos erosivos na sub-bacia estudada, porém, quanto à quantificação das perdas de solo, não simula o escoamento subsuperficial, o que pode ter subestimado estes processos. Palavras-chave: degradação ambiental, perdas de solo, assoreamento.  COSTA, C.D.O.; ALVES, M.C.; SOUSA, A.P.; silva, h.r.; gonzález, a.p.; avalos, j.m.m.PRODUCTION AND DEPOSITION SEDIMENT IN A SUB-BASIN RIVER WITH SUSCEPTIBLE SOILS TO erosion  2 abstract Soil degradation brings erosion as consequence , causing siltation and contamination of water courses. This study aimed to estimate soil loss and sediment deposition in the sub-basin ofDois Córregos river, located in Selvíria municipality, MS, Brazil, in order to identify areas with higher susceptibility to these processes, using the LISEM modelas  tool . The sub-basin river soils are Red Oxisol and Red-Yellow Alfisol, both with sandy texture. For the simulations the LISEM model was used, with data collected from rainfall intensity between the years 2009-2012. Ten events were selected with higher rainfall intensities for the study period. To obtain the required input parameters, soil samples were collected. The collections were made at ten sites of the river sub-basin, in the different forms of soil use and occupation. The eucalyptus provides protection to the river sub-basinsoils . The produced sediments are deposited in the beds of the river sub-basin, causing the silting of waterways. The LISEM model is efficient for locating the areas susceptible to erosion processes in the river sub-basin studied, however, in the quantification of soil loss, it does not simulate the runoff subsurface, which may have caused underestimation of these processes. Keywords: environmental degradation, soil loss, siltation.

scholarly journals Soil erosion in sloping vineyards under conventional and organic land use managements (Saar-Mosel Valley, Germany)

2017 ◽  
Vol 43 (1) ◽  
pp. 119 ◽  
Author(s):  
M. Kirchhoff ◽  
J. Rodrigo-Comino ◽  
M. Seeger ◽  
J.B. Ries
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Management Practices ◽  
Conventional Tillage ◽  
Erosion Processes ◽  
Natural Rainfall ◽  
Total Runoff ◽  
Lack Of Information ◽  
Steep Slopes ◽  
Runoff And Soil Loss

German vineyards are one of the land uses most prone to soil erosion. Due to their placement on mainly steep slopes and non-conservative cultivation practices, runoff and soil loss are a serious problem for wine growers. In the Saar-Mosel valley (Rhineland-Palatinate, Germany), there is a tendency towards organic management of vineyards with protective grass cover in the inter-rows. Since there is a lack of information about organic-conventional tillage in German vineyards related to soil erosion processes, this study presents a comparison between these two soil management practices. For this purpose, 22 rainfall simulations were performed as well as a medium-term monitoring by using 4-paired Gerlach troughs in two experimental sites in the Saar-Mosel valley. The mean simulated runoff coefficient and suspended sediment load in conventional vineyards amounted up to 23.3% and 33.75 g m-2, respectively. In the organic site, runoff and soil loss were only recorded in one out of the 11 simulations. Runoff and sediment was collected in the Gerlach troughs for 33 natural rainfall events. In the conventional vineyard, the total measured soil loss was 3314.63 g m-1 and 6503.77 g m-1 and total runoff volumes were 105.52 L m-1 and 172.58 L m-1. In the organic site, total soil losses reached 143.16 g m-1 and 258.89 g m-1 and total runoff was 21.65 L m-1 and 12.69 L m-1. When soil loss was measured without corresponding runoff or precipitation, soil erosion was activated by tillage or trampling. Finally, the conventional vineyard showed a higher variability in soil loss and runoff suggesting less predictable results.

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