scholarly journals Efficient Semi-Distributed Hydrological Modelling Workflow for Simulating Streamflow and Characterizing Hydrologic Processes

2017 ◽  
Vol 1 (3) ◽  
Author(s):  
Matthew Chernos ◽  
Ryan MacDonald ◽  
James Craig
Keyword(s):  
Open Source Software ◽  
Hydrological Modelling ◽  
Western Canada ◽  
Watershed Hydrology ◽  
Hydrologic Processes ◽  
Point Of Interest ◽  
Wide Range ◽  
Distributed Hydrological Modelling ◽  
Data Requirements ◽  
Free Open Source

Streamflow records are required for a wide range of industrial, environmental, and urban applications. However, the sparse coverage of hydrometric stations in western Canada, and their limited spatial and temporal representativeness, necessitate hydrologic regionalization methods to generate streamflow for a point of interest. Here, an efficient semi-distributed hydrological modelling workflow is presented which has modest data requirements, uses publicly available data sources, and applies free open-source software. The method is scalable, relies on few statistical assumptions, and is scientifically rigorous. In addition, the resultant model allows the ability to trace the primary contributors of streamflow in the region, and for the evaluation of future watershed hydrology due to environmental and climatic change.

scholarly journals Ground volume assessment using ’Structure from Motion’ photogrammetry with a smartphone and a compact camera

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Rafał Wróżyński ◽  
Krzysztof Pyszny ◽  
Mariusz Sojka ◽  
Czesław Przybyła ◽  
Sadżide Murat-Błażejewska
Keyword(s):  
Open Source Software ◽  
Structure From Motion ◽  
Point Cloud ◽  
Field Measurements ◽  
Video Frames ◽  
Actual Volume ◽  
Volume Assessment ◽  
Uniform Model ◽  
Free Open Source ◽  
Test Embankment

AbstractThe article describes how the Structure-from-Motion (SfM) method can be used to calculate the volume of anthropogenic microtopography. In the proposed workflow, data is obtained using mass-market devices such as a compact camera (Canon G9) and a smartphone (iPhone5). The volume is computed using free open source software (VisualSFMv0.5.23, CMPMVSv0.6.0., MeshLab) on a PCclass computer. The input data is acquired from video frames. To verify the method laboratory tests on the embankment of a known volume has been carried out. Models of the test embankment were built using two independent measurements made with those two devices. No significant differences were found between the models in a comparative analysis. The volumes of the models differed from the actual volume just by 0.7‰ and 2‰. After a successful laboratory verification, field measurements were carried out in the same way. While building the model from the data acquired with a smartphone, it was observed that a series of frames, approximately 14% of all the frames, was rejected. The missing frames caused the point cloud to be less dense in the place where they had been rejected. This affected the model’s volume differed from the volume acquired with a camera by 7%. In order to improve the homogeneity, the frame extraction frequency was increased in the place where frames have been previously missing. A uniform model was thereby obtained with point cloud density evenly distributed. There was a 1.5% difference between the embankment’s volume and the volume calculated from the camera-recorded video. The presented method permits the number of input frames to be increased and the model’s accuracy to be enhanced without making an additional measurement, which may not be possible in the case of temporary features.

Investigation of multiple flood mitigation strategies for an urban catchment using semi-distributed hydrological modelling

2021 ◽  
Vol 14 (15) ◽  
Author(s):  
Elanchezhiyan Duraisekaran ◽  
Tamilselvi Mohanraj ◽  
Jeciliya Selva Kiruba Samuel ◽  
Sudharsanan Rajagopalan ◽  
Ravikumar Govindasamy
Keyword(s):  
Hydrological Modelling ◽  
Mitigation Strategies ◽  
Flood Mitigation ◽  
Urban Catchment ◽  
Distributed Hydrological Modelling

Alternative climate data sources for distributed hydrological modelling on a daily time step

2010 ◽  
Vol 25 (10) ◽  
pp. 1542-1557 ◽  
Author(s):  
Ashraf El-Sadek ◽  
Max Bleiweiss ◽  
Manoj Shukla ◽  
Steve Guldan ◽  
Alexander Fernald
Keyword(s):  
Hydrological Modelling ◽  
Data Sources ◽  
Climate Data ◽  
Time Step ◽  
Daily Time Step ◽  
Distributed Hydrological Modelling ◽  
Daily Time
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