Prescribed fire impacts on soil properties, overland flow and sediment transport in a Mediterranean forest: A 5 year study

2018 ◽  
Vol 636 ◽  
pp. 1480-1489 ◽  
Author(s):  
Paloma Hueso-González ◽  
Juan F. Martínez-Murillo ◽  
José D. Ruiz-Sinoga
Agronomie ◽  
2002 ◽  
Vol 22 (5) ◽  
pp. 489-501 ◽  
Author(s):  
Yves Le Bissonnais ◽  
Sylvie Cros-Cayot ◽  
Chantal Gascuel-Odoux

Water ◽  
2015 ◽  
Vol 7 (10) ◽  
pp. 5239-5257 ◽  
Author(s):  
Shervin Faghihirad ◽  
Binliang Lin ◽  
Roger Falconer

1978 ◽  
Vol 1 (16) ◽  
pp. 76
Author(s):  
William N. Seelig ◽  
Robert M. Sorensen

A spatially integrated one-dimensional numerical model of inlet bay hydraulics has been combined with a simple sediment transport model to investigate selected tidal inlet-bay system characteristics. A parametric study has been performed using the models to determine the effect of various factors on the net direction and order of magnitude of inlet channel flow and sediment transport. Factors considered include astronomical tide type, storm surge height and duration, variation in bay surface area, time-dependent channel friction factor, and the addition of a second inlet connecting the bay and sea.


Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3132
Author(s):  
Ahmed Mohsen ◽  
Ferenc Kovács ◽  
Gábor Mezősi ◽  
Tímea Kiss

Downstream of the confluence of rivers, complex hydrological and morphological processes control the flow and sediment transport. This study aimed to analyze the spatio-temporal dynamics of suspended sediment in the confluence area of the Tisza and its main tributary Maros River using Sentinel-2 images and to reveal the correlation between the hydrological parameters and the mixing process through a relatively long period (2015–2021). The surficial suspended sediment dynamism was analyzed by applying K-means unsupervised classification algorithm on 143 images. The percentages of the Tisza (TW) and Maros (MW) waters and their mixture (MIX) were calculated and compared with the hydrological parameters in both rivers. The main results revealed that the areal, lateral, and longitudinal extensions of TW and MIX have a better correlation with the hydrological parameters than the MW. The Pearson correlation matrix revealed that the discharge ratio between the rivers controls the mixing process significantly. Altogether, 11 mixing patterns were identified in the confluence area throughout the studied period. The TW usually dominates the confluence in November and January, MW in June and July, and MIX in August and September. Predictive equations for the areal distribution of the three classes were derived to support future water sampling in the confluence area.


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