scholarly journals Studying rainfall changes and water erosion of soil by using the WEPP model in Lattakia, Syria

2016 ◽  
Vol 61 (4) ◽  
pp. 375-386 ◽  
Author(s):  
Safwan Mohammed ◽  
Issa Kbibo ◽  
Omran Alshihabi ◽  
Elien Mahfoud
Keyword(s):  
Soil Erosion ◽  
Soil Water ◽  
Water Erosion ◽  
Rainfall Amount ◽  
Agricultural System ◽  
Storm Events ◽  
Natural Sources ◽  
Erosion Prediction ◽  
Water Erosion Prediction Project ◽  
General Average

Changes of soil erosion and rainfall have been simulated by using the Water Erosion Prediction Project (WEPP) model between 2016 and 2039 in Lattakia, Syria. This study was conducted in 6 locations that are characterized by two different ecosystems (agricultural, forest). The results show a linear decrease in rainfall amount of about 7.11 mm per year (170 mm for the whole studying period). For the years 2025, 2026 and 2030, three snowy storm events have been predicted, while the year 2030 will record the highest rainfall amount of 1816.1 mm. According to the WEPP model, the average of estimated soil erosion amount in Alhamara has reached 19 t/ha/y for the agricultural system while it is estimated to be 2.03 t/ha/y for the forest system. The general average of soil erosion in the study area (taking into consideration the variety of slope) within the agricultural system has reached 14.086 t/ha/y, which indicates that there will be a dangerous impact of future erosion on the sustainability of natural sources (soil, water) in the study area.

A Process-Based Soil Erosion Model for USDA-Water Erosion Prediction Project Technology

1989 ◽  
Vol 32 (5) ◽  
pp. 1587-1593 ◽  
Author(s):  
M. A. Nearing ◽  
G. R. Foster ◽  
L. J. Lane ◽  
S. C. Finkner
Keyword(s):  
Soil Erosion ◽  
Water Erosion ◽  
Erosion Model ◽  
Erosion Prediction ◽  
Water Erosion Prediction Project

Development and application of modern soil erosion prediction technology - The USDA experience

Soil Research ◽  
1992 ◽  
Vol 30 (6) ◽  
pp. 893 ◽  
Author(s):  
LJ Lane ◽  
KG Renard ◽  
GR Foster ◽  
JM Laflen
Keyword(s):  
Soil Erosion ◽  
Soil Conservation ◽  
Water Erosion ◽  
Systems Model ◽  
Erosion Prediction ◽  
Modern Soil ◽  
Water Erosion Prediction Project ◽  
Applied Technology ◽  
Flow Hydraulics ◽  
Soil Erosion By Water

Erosion prediction efforts are described to provide a synopsis of the USDA's experience in developing and applying soil erosion prediction technology in its research and development activities and its soil conservation programs. For almost five decades, equations to predict soil erosion by water have been useful m developing plans for controlling soil erosion and sedimentation. The Universal Soil Low Equation (USLE) is the most widely known and used of the erosion prediction equations. The USLE presents a simply understood and easily applied technology which has been of incalculable benefit to soil conservation and land management. The Chemicals, Runoff, and Erosion from Agricultural Management Systems Model (CREAMS) contains a sophisticated erosion component based, in part, on the USLE and on flow hydraulics and the processes of sediment detachment, transport, and deposition. In 1985, the USDA in cooperation with BLM and several universities initiated a national project called the Water Erosion Prediction Project (WEPP) to develop a next generation water erosion prediction technology. The Revised Universal Soil Loss Equation (RUSLE) is an update of the USLE to improve erosion prediction in the interim before WEPP is adopted and to provide and adjunct technology thereafter.

Geospatial Application of the Water Erosion Prediction Project (WEPP) Model

2011 ◽  
Author(s):  
Dennis C Flanagan ◽  
James R Frankenberger ◽  
Thomas A Cochrane ◽  
Christian S Renschler ◽  
William J Elliot
Keyword(s):  
Water Erosion ◽  
Erosion Prediction ◽  
Water Erosion Prediction Project

Straw mulch impact on soil properties and initial soil erosion processes in the maize field

2021 ◽  
Author(s):  
Ivan Dugan ◽  
Leon Josip Telak ◽  
Iva Hrelja ◽  
Ivica Kisić ◽  
Igor Bogunović
Keyword(s):  
Soil Erosion ◽  
Soil Water ◽  
Soil Loss ◽  
Bare Soil ◽  
Water Erosion ◽  
Straw Mulch ◽  
Erosion Processes ◽  
Maize Field ◽  
Sediment Loss ◽  
Initial Soil

<p><strong>Straw mulch impact on soil properties and initial soil erosion processes in the maize field</strong></p><p>Ivan Dugan*, Leon Josip Telak, Iva Hrelja, Ivica Kisic, Igor Bogunovic</p><p>University of Zagreb, Faculty of Agriculture, Department of General Agronomy, Zagreb, Croatia</p><p>(*correspondence to Ivan Dugan: [email protected])</p><p>Soil erosion by water is the most important cause of land degradation. Previous studies reveal high soil loss in conventionally managed croplands, with recorded soil losses high as 30 t ha<sup>-1</sup> under wide row cover crop like maize (Kisic et al., 2017; Bogunovic et al., 2018). Therefore, it is necessary to test environmentally-friendly soil conservation practices to mitigate soil erosion. This research aims to define the impacts of mulch and bare soil on soil water erosion in the maize (Zea mays L.) field in Blagorodovac, Croatia (45°33’N; 17°01’E; 132 m a.s.l.). For this research, two treatments on conventionally tilled silty clay loam Stagnosols were established, one was straw mulch (2 t ha<sup>-1</sup>), while other was bare soil. For purpose of research, ten rainfall simulations and ten sampling points were conducted per each treatment. Simulations were carried out with a rainfall simulator, simulating a rainfall at an intensity of 58 mm h<sup>-1</sup>, for 30 min, over 0.785 m<sup>2</sup> plots, to determine runoff and sediment loss. Soil core samples and undisturbed samples were taken in the close vicinity of each plot. The results showed that straw mulch mitigated water runoff (by 192%), sediment loss (by 288%), and sediment concentration (by 560%) in addition to bare treatment. The bare treatment showed a 55% lower infiltration rate. Ponding time was higher (p < 0.05) on mulched plots (102 sec), compared to bare (35 sec), despite the fact that bulk density, water-stable aggregates, water holding capacity, and mean weight diameter did not show any difference (p > 0.05) between treatments. The study results indicate that straw mulch mitigates soil water erosion, because it immediately reduces runoff, and enhances infiltration. On the other side, soil water erosion on bare soil under simulated rainstorms could be high as 5.07 t ha<sup>-1</sup>, when extrapolated, reached as high as 5.07 t ha<sup>-1 </sup>in this study. The conventional tillage, without residue cover, was proven as unsustainable agro-technical practice in the study area.</p><p><strong>Key words: straw mulch, </strong>rainfall simulation, soil water erosion</p><p><strong>Acknowledgment</strong></p><p>This work was supported by Croatian Science Foundation through the project "Soil erosion and degradation in Croatia" (UIP-2017-05-7834) (SEDCRO).</p><p><strong>Literature</strong></p><p>Bogunovic, I., Pereira, P., Kisic, I., Sajko, K., Sraka, M. (2018). Tillage management impacts on soil compaction, erosion and crop yield in Stagnosols (Croatia). Catena, 160, 376-384.</p><p>Kisic, I., Bogunovic, I., Birkás, M., Jurisic, A., Spalevic, V. (2017). The role of tillage and crops on a soil loss of an arable Stagnic Luvisol. Archives of Agronomy and Soil Science, 63(3), 403-413.</p>

Testing a new rill flow resistance approach using the Water Erosion Prediction Project experimental database

2018 ◽  
Vol 33 (4) ◽  
pp. 616-626 ◽  
Author(s):  
Alessio Nicosia ◽  
Costanza Di Stefano ◽  
Vincenzo Pampalone ◽  
Vincenzo Palmeri ◽  
Vito Ferro ◽  
...  
Keyword(s):  
Flow Resistance ◽  
Water Erosion ◽  
Experimental Database ◽  
Erosion Prediction ◽  
Water Erosion Prediction Project ◽  
Resistance Approach ◽  
Rill Flow

scholarly journals Comparação de taxas de erosão em estradas florestais estimadas pelo modelo WEPP (Water Erosion Prediction Project) modificado em relção a medições experimentais

2003 ◽  
Vol 27 (3) ◽  
pp. 295-300 ◽  
Author(s):  
Carlos Cardoso Machado ◽  
Alessandra Reis Garcia ◽  
Elias Silva ◽  
Alessandro Machado Fontes
Keyword(s):  
Water Erosion ◽  
Erosion Prediction ◽  
Water Erosion Prediction Project

O objetivo do trabalho foi testar o modelo WEPP (Water Erosion Prediction Project), através de comparações entre volume de enxurrada e perda de solo observados experimentalmente, provenientes dos segmentos de estradas florestais submetidas à chuva natural com inclinações de 1 e 7% e comprimentos de rampa de 20 e 40 m, e aqueles preditos pelo aplicativo, visando o desenvolvimento de um modelo brasileiro de predição de erosão em estradas florestais. Na determinação da quantidade do material erodido foram instalados tambores coletores, com capacidade de 209,25 litros, localizados na parte inferior das estradas, onde foram inseridas tubulações de PVC de 2 polegadas para coleta dos sedimentos provenientes da estrada propriamente dita. Nos tambores coletores foram feitos orifícios nivelados e perfeitamente iguais, posicionados a 0,65 m do fundo do primeiro e a 0,60 m do fundo do segundo, que funcionaram como um divisor Geib. Nas parcelas de 20 e 40 m de comprimento foram feitos cinco e sete orifícios, respectivamente, no primeiro e segundo tambores. O terceiro tambor foi utilizado para coletar o excedente da enxurrada proveniente do segundo tambor. Os tambores foram ligados em série, através de cano PVC de 2 polegadas. Os dados de volume e intensidade de precipitação diária foram obtidos com a instalação de pluviômetro e pluviógrafo no local. O período de coleta de dados foi de um ano, concentrando-se na época das chuvas. Posteriormente, os arquivos de clima, precipitação, solo, inclinação e comprimento do segmento foram introduzidos e adaptados ao modelo de predição de erosão WEPP com o propósito de testá-lo, visando a confecção de um modelo apropriado às condições brasileiras.

GeoWEPP - The Geo-spatial interface for the Water Erosion Prediction Project

2002 ◽  
Author(s):  
Chris S. Renschler ◽  
Dennis C. Flanagan ◽  
Bernard A. Engel ◽  
James R. Frankenberger
Keyword(s):  
Water Erosion ◽  
Erosion Prediction ◽  
Water Erosion Prediction Project
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