Evaluation of runoff, peak flow and sediment yield for events simulated by the AnnAGNPS model in a belgian agricultural watershed

Abstract

The AnnAGNPS model, widely utilized as a practical tool for addressing erosion problems and land use planning, was implemented in a small agricultural watershed located in central Belgium, to assess its prediction capacity of runoff, peak flow and sediment yield in humid temperate conditions. Model performance was evaluated at the event scale by using a database reporting hydrological, geomorphologic and land use data collected during a 2-year period. Seventeen events were modelled and compared with the corresponding observations at the watershed outlet.The model performed well in predicting the largest runoff volumes, as shown by the high values achieved for the coefficients of efficiency (E ¼ 0Á89) and determination (r 2 ¼ 0Á92). However, some events resulted in zero runoff simulation. The prediction capability for peak flow and sediment yield was poor (E ¼ 0Á35 and 0Á16, respectively). This inaccuracy can have several causes: the internal model deficiencies may be due to the incomplete representation of watershed complex processes, while external problems may be related to the conditions within the modelled watershed and the quality of recorded data.On the whole the AnnAGNPS model may be considered as being suitable to simulate the significant runoff events in the experimental watershed. However, the model may be seen as better suited for comparative assessments of alternative management and policy scenarios and for gross estimation of nutrient loads rather than the precise prediction of a single event, consequently helping in the prediction of land degradation problems in the experimented conditions.

Runoff and sediment yield modeling in a medium-size mediterranean watershed

“…High efficiency is shown by the coefficient of determination R 2 value (R 2 =0.81), while other statistical indexes (NSE and RMSE) show a satisfactory prediction (Table 6). Other authors (Zema et al, 2010;Shrestha et al, 2006;Licciardello et al, 2007) Horizons in agricultural, forestry and biosystems engineering, Viterbo, Italy, September 8-12, 2013 . For forest and rangeland, MN values respectively equal to 0.8 and 0.13 were set , while for urban areas, cropland and pasture the initial value of 0.15 was considered.…”

“…Continuous distributed simulation models (as AnnAGNPS, WEPP, SWAT) provide great advantages as they allow watersheds response to be studied over a longer time period and can help to select the most practical and effective tools in reducing erosion problems (Zema et al, 2010).…”

“…Assessments of model performance, frequently coupled with calibration/validation trials in monitored watersheds ranging from 32 ha to 2500 km 2 , have recently been published (Licciardello et al, 2007;Yuan et al, 2008;Parajuli et al, 2009;Zema et al, 2010) Few studies have been conducted using AnnAGNPS at the watershed scale in semi-arid environments. Here the quantification of sediment transport is quite difficult due to the high variability of rainfalls and water flows.…”

Hydrological Effects of Different Soil Management Practices in Mediterranean Areas

“…As well known, prediction models are useful tools for monitoring and controlling the impacts of soil erosion (e.g. Engel et al, 1993;Licciardello et al, 2007;Zema et al, 2011). While the potential of process based models is greater in comparison to empirical ones, their complexity means larger data requirements, potentially greater problems of error propagation and increased difficulty in understanding the way the model simulates the erosion processes (Favis-Mortlock et al, 2001).…”

Sustaining reservoir use through sediment trapping in NW Ethiopia

“…As increasing pressure mounts on agricultural lands to feed an ever growing global population, land exploitation and unabated soil erosion will occur, especially in developing parts of the world (Lal, 2001), and in other regions were the intensification of agriculture is taking place (Cerda et al, 2009;Zema et al, 2012) or where natural or human-driven disturbances take place: forest fires (Lasanta & Cerdà, 2005), landslides (Douglas et al, 2013), heavy rainfall events (Ziadat & Taimeh, 2013), land abandonment (Cerdà, 1997b). The exploitation of land resources results from a number of factors including extensive deforestation for fuel wood, expansion of cultivation into steep erosion-prone areas and over grazing pressures (Zeleke, 2000;Bewket, 2002;Ritsema, 2003;Amsalu & de Graaff, 2007).…”