scholarly journals ASSESSMENT OF THE ARTIFICIAL NEURAL NETWORKS TO ‎GEOMORPHIC MODELLING OF SEDIMENT YIELD FOR ‎UNGAUGED CATCHMENTS, ALGERIA

2015 ◽  
pp. 175-185 ◽  
Author(s):  
Kamel Khanchoul ◽  
Mahmoud Tourki ◽  
Yves Le Bissonnais
Keyword(s):  
Neural Networks ◽  
Suspended Sediment ◽  
Sediment Yield ◽  
Coefficient Of Determination ◽  
Physical Factors ◽  
Ungauged Catchments ◽  
Suspended Sediment Yield ◽  
River Types ◽  
Backpropagation Method ◽  
Hidden Layer

Knowledge of sediment yield and the factors controlling it provides useful ‎information for estimating ‎erosion intensities within river basins. The objective of ‎this study was to build a model from which ‎suspended sediment yield could be ‎estimated from ungauged rivers using computed sediment yield and ‎physical ‎factors. Researchers working on suspended sediment transported by wadis in the ‎Maghreb are ‎usually facing the lack of available data for such river types. Further ‎study of the prediction of sediment ‎transport in these regions and its variability is ‎clearly required. In this work, ANNs were built between ‎sediment yield ‎established from longterm measurement series at gauging stations in Algerian ‎catchments and ‎corresponding basic physiographic parameters such as rainfall, ‎runoff, lithology index, coefficient of ‎torrentiality, and basin area. The proposed ‎Levenberg-Marquardt and Multilayer Perceptron algorithms to ‎train the neural ‎networks of the current research study was based on the feed-forward ‎backpropagation ‎method with combinations of number of neurons in each hidden ‎layer, transfer function, error goal. ‎Additionally, three statistical measurements, ‎namely the ‎root mean square error (RMSE), ‎the coefficient of ‎determination (R²), ‎and the efficiency factor (EF)‎ have been reported for ‎examining the forecasting ‎‎accuracy of the developed model.‎ Single plot displays of network outputs with ‎respect to targets for training ‎have provided good performance results and good ‎fitting . Thus, ANNs were a promising method for ‎predicting suspended sediment ‎yield in ungauged Algerian catchments.‎

scholarly journals The Long-Term Effects of Land Use and Climate Changes on the Hydro-Morphology of the Reno River Catchment (Northern Italy)

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1831 ◽  
Author(s):  
Donatella Pavanelli ◽  
Claudio Cavazza ◽  
Stevo Lavrnić ◽  
Attilio Toscano
Keyword(s):  
Land Use ◽  
Suspended Sediment ◽  
Flow Rate ◽  
Sediment Yield ◽  
River Flow ◽  
Agricultural Land ◽  
Single Channel ◽  
Northern Italy ◽  
Lulc Changes ◽  
Suspended Sediment Yield

Anthropogenic activities, and in particular land use/land cover (LULC) changes, have a considerable effect on rivers’ flow rates and their morphologies. A representative example of those changes and resulting impacts on the fluvial environment is the Reno Mountain Basin (RMB), located in Northern Italy. Characterized by forest exploitation and agricultural production until World War II, today the RMB consists predominantly of meadows, forests and uncultivated land, as a result of agricultural land abandonment. This study focuses on the changes of the Reno river’s morphology since the 1950s, with an objective of analyzing the factors that caused and influenced those changes. The factors considered were LULC changes, the Reno river flow rate and suspended sediment yield, and local climate data (precipitation and temperature). It was concluded that LUCL changes caused some important modifications in the riparian corridor, riverbed size, and river flow rate. A 40–80% reduction in the river bed area was observed, vegetation developed in the riparian buffer strips, and the river channel changed from braided to a single channel. The main causes identified are reductions in the river flow rate and suspended sediment yield (−36% and −38%, respectively), while climate change did not have a significant effect.

scholarly journals Pertinent spatio-temporal scale of observation to understand suspended sediment yield control factors in the Andean region: the case of the Santa River (Peru)

2013 ◽  
Vol 17 (11) ◽  
pp. 4641-4657 ◽  
Author(s):  
S. B. Morera ◽  
T. Condom ◽  
P. Vauchel ◽  
J.-L. Guyot ◽  
C. Galvez ◽  
...  
Keyword(s):  
Suspended Sediment ◽  
Spatial Data ◽  
Sediment Yield ◽  
Water Discharge ◽  
Daily Rainfall ◽  
Sediment Concentration ◽  
Suspended Sediment Yield ◽  
Control Factors ◽  
Daily Water ◽  
Spatio Temporal

Abstract. Hydro-sedimentology development is a great challenge in Peru due to limited data as well as sparse and confidential information. This study aimed to quantify and to understand the suspended sediment yield from the west-central Andes Mountains and to identify the main erosion-control factors and their relevance. The Tablachaca River (3132 km2) and the Santa River (6815 km2), located in two adjacent Andes catchments, showed similar statistical daily rainfall and discharge variability but large differences in specific suspended-sediment yield (SSY). In order to investigate the main erosion factors, daily water discharge and suspended sediment concentration (SSC) datasets of the Santa and Tablachaca rivers were analysed. Mining activity in specific lithologies was identified as the major factor that controls the high SSY of the Tablachaca (2204 t km2 yr−1), which is four times greater than the Santa's SSY. These results show that the analysis of control factors of regional SSY at the Andes scale should be done carefully. Indeed, spatial data at kilometric scale and also daily water discharge and SSC time series are needed to define the main erosion factors along the entire Andean range.

scholarly journals Factors Controlling Contemporary Suspended Sediment Yield in the Caucasus Region

Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3173
Author(s):  
Valentin Golosov ◽  
Anatoly Tsyplenkov
Keyword(s):  
Suspended Sediment ◽  
Sediment Yield ◽  
Strong Relationship ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Ground Acceleration ◽  
The Caucasus ◽  
Suspended Sediment Yield ◽  
Caucasus Region

This paper discusses the joint impact of catchment complexity in topography, tectonics, climate, landuse patterns, and lithology on the suspended sediment yield (SSY, t km−2 year−1) in the Caucasus region using measurements from 244 gauging stations (GS). A Partial Least Square Regression (PLSR) was used to reveal the relationships between SSY and explanatory variables. Despite possible significant uncertainties on the SSY values, analysis of this database indicates clear spatial patterns of SSY in the Caucasus. Most catchments in the Lesser Caucasia and Ciscaucasia are characterized by relatively low SSY values (<100–150 t km−2 year−1), the Greater Caucasus region generally have higher SSY values (more than 150–300 t km−2 year−1). Partial correlation analyses demonstrated that such proxies of topography as height above nearest drainage (HAND) and normalized steepness index (Ksn) tend to be among the most important ones. However, a PLSR analysis suggested that these variables’ influence is likely associated with peak ground acceleration (PGA). We also found a strong relationship between land cover types (e.g., barren areas and cropland) and SSY in different elevation zones. Nonetheless, adding more gauging stations into analyses and more refined characterizations of the catchments may reveal additional trends.

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