Rehabilitaciin de redes de drenaje mediante la combinaciin de tanques de retenciin y sustituciin de conducciones (Rehabilitation of Drainage Networks Through the Combination of Retention Tanks and Replacement of Pipelines)

2017 ◽  
Author(s):  
Ulrich Ngamalieu ◽  
Pedro L. Iglesias-Rey ◽  
F. Javier Marttnez-Solano ◽  
Juan Saldarriaga
Keyword(s):  
Drainage Networks

A storage model for the simulation of the hydraulic behaviour of drainage networks

1997 ◽  
Vol 36 (8-9) ◽  
pp. 57-63 ◽  
Author(s):  
Homayoun Motiee ◽  
Bernard Chocat ◽  
Olivier Blanpain
Keyword(s):  
Wave Model ◽  
Kinematic Wave ◽  
Hydraulic Simulation ◽  
Diffusion Wave ◽  
Storage Model ◽  
Hydraulic Behaviour ◽  
Drainage Networks ◽  
Saint Venant Equations ◽  
Kinematic Wave Model ◽  
And Diffusion

This paper presents a model for the hydraulic simulation of a drainage network using the storage concept. This model is easier to use than the complete Barre de Saint Venant equations and gives better results than the usual conceptual models, i.e. the Muskingum model, or than models obtained by the simplification of the Saint Venant equations (kinematic wave model and diffusion wave model).

EXAMINING THE EFFECTS OF RESOLUTION AND ROADS ON DEM-DERIVED DRAINAGE NETWORKS

2019 ◽  
Author(s):  
J.P. Gannon ◽  
◽  
Diane Styers ◽  
David Kinner ◽  
Mark Lord
Keyword(s):  
Drainage Networks

scholarly journals Inclusion of Hydraulic Controls in Rehabilitation Models of Drainage Networks to Control Floods

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 514
Author(s):  
Leonardo Bayas-Jiménez ◽  
F. Javier Martínez-Solano ◽  
Pedro L. Iglesias-Rey ◽  
Daniel Mora-Melia ◽  
Vicente S. Fuertes-Miquel
Keyword(s):  
Genetic Algorithm ◽  
Drainage System ◽  
Optimal Solution ◽  
Hydraulic Control ◽  
Drainage Systems ◽  
Storm Water Management Model ◽  
Drainage Networks ◽  
Extreme Rain ◽  
Rain Events ◽  
The Cost

A problem for drainage systems managers is the increase in extreme rain events that are increasing in various parts of the world. Their occurrence produces hydraulic overload in the drainage system and consequently floods. Adapting the existing infrastructure to be able to receive extreme rains without generating consequences for cities’ inhabitants has become a necessity. This research shows a new way to improve drainage systems with minimal investment costs, using for this purpose a novel methodology that considers the inclusion of hydraulic control elements in the network, the installation of storm tanks and the replacement of pipes. The presented methodology uses the Storm Water Management Model for the hydraulic analysis of the network and a modified Genetic Algorithm to optimize the network. In this algorithm, called the Pseudo-Genetic Algorithm, the coding of the chromosomes is integral and has been used in previous studies of hydraulic optimization. This work evaluates the cost of the required infrastructure and the damage caused by floods to find the optimal solution. The main conclusion of this study is that the inclusion of hydraulic controls can reduce the cost of network rehabilitation and decrease flood levels.

An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions

2017 ◽  
Vol 45 (4) ◽  
pp. 319-328 ◽  
Author(s):  
Lawrence V. Stanislawski ◽  
Kornelijus Survila ◽  
Jeffrey Wendel ◽  
Yan Liu ◽  
Barbara P. Buttenfield
Keyword(s):  
Surface Water ◽  
Open Source ◽  
High Performance ◽  
Water Drainage ◽  
Drainage Networks

A quick algorithm of counting flow accumulation matrix for deriving drainage networks from a DEM

2011 ◽  
Author(s):  
Yanping Wang ◽  
Yonghe Liu ◽  
Hongbo Xie ◽  
ZhongLin Xiang
Keyword(s):  
Flow Accumulation ◽  
Drainage Networks

scholarly journals Hydraulic transmissivity inferred from ice-sheet relaxation following Greenland supraglacial lake drainages

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ching-Yao Lai ◽  
Laura A. Stevens ◽  
Danielle L. Chase ◽  
Timothy T. Creyts ◽  
Mark D. Behn ◽  
...  
Keyword(s):  
Laboratory Experiments ◽  
Ice Sheet ◽  
Drainage System ◽  
Greenland Ice Sheet ◽  
Field Observations ◽  
Surface Uplift ◽  
Drainage Networks ◽  
Order Of Magnitude ◽  
Lake Drainage ◽  
Magnitude Increase

AbstractSurface meltwater reaching the base of the Greenland Ice Sheet transits through drainage networks, modulating the flow of the ice sheet. Dye and gas-tracing studies conducted in the western margin sector of the ice sheet have directly observed drainage efficiency to evolve seasonally along the drainage pathway. However, the local evolution of drainage systems further inland, where ice thicknesses exceed 1000 m, remains largely unknown. Here, we infer drainage system transmissivity based on surface uplift relaxation following rapid lake drainage events. Combining field observations of five lake drainage events with a mathematical model and laboratory experiments, we show that the surface uplift decreases exponentially with time, as the water in the blister formed beneath the drained lake permeates through the subglacial drainage system. This deflation obeys a universal relaxation law with a timescale that reveals hydraulic transmissivity and indicates a two-order-of-magnitude increase in subglacial transmissivity (from 0.8 ± 0.3 $${\rm{m}}{{\rm{m}}}^{3}$$ m m 3 to 215 ± 90.2 $${\rm{m}}{{\rm{m}}}^{3}$$ m m 3 ) as the melt season progresses, suggesting significant changes in basal hydrology beneath the lakes driven by seasonal meltwater input.

A flooding algorithm for extracting drainage networks from unprocessed digital elevation models

2013 ◽  
Vol 59 ◽  
pp. 116-123 ◽  
Author(s):  
Antonio Rueda ◽  
José M. Noguera ◽  
Carmen Martínez-Cruz
Keyword(s):  
Digital Elevation Models ◽  
Drainage Networks ◽  
Digital Elevation

scholarly journals A novel approach to the classification of terrestrial drainage networks based on deep learning and preliminary results on solar system bodies

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Carlo Donadio ◽  
Massimo Brescia ◽  
Alessia Riccardo ◽  
Giuseppe Angora ◽  
Michele Delli Veneri ◽  
...  
Keyword(s):  
Deep Learning ◽  
Morphological Variations ◽  
Control Factors ◽  
Novel Approach ◽  
Drainage Networks ◽  
Key Characteristics ◽  
Intrinsic Complexity ◽  
Solar System Bodies ◽  
Manual Extraction

AbstractSeveral approaches were proposed to describe the geomorphology of drainage networks and the abiotic/biotic factors determining their morphology. There is an intrinsic complexity of the explicit qualification of the morphological variations in response to various types of control factors and the difficulty of expressing the cause-effect links. Traditional methods of drainage network classification are based on the manual extraction of key characteristics, then applied as pattern recognition schemes. These approaches, however, have low predictive and uniform ability. We present a different approach, based on the data-driven supervised learning by images, extended also to extraterrestrial cases. With deep learning models, the extraction and classification phase is integrated within a more objective, analytical, and automatic framework. Despite the initial difficulties, due to the small number of training images available, and the similarity between the different shapes of the drainage samples, we obtained successful results, concluding that deep learning is a valid way for data exploration in geomorphology and related fields.

Sign in / Sign up

Export Citation Format

Share Document