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1.An alternative approach to estimate river cross-sections using LIDAR-based digital elevation model
Title An alternative approach to estimate river cross-sections using LIDAR-based digital elevation model Author info Mohd Talha Anees ... [et al.] Author Anees Mohd Talha (15%)
Co-authors Bakar Ahmad Farid Bin Abu (10%)
Khan Mohammad Muqtada Ali (10%)
Syakir Muhammad I. (5%)
Abdullah K. (5%)
Nordin Mohd Nawawi Mohd (5%)
Abdelrahman Kamal (5%)
Eldosouky Ahmed M. (10%)
Andráš Peter 1953- (15%) UMBFP04 - Katedra životného prostredia
Yahaya Nasehir Khan Bin E.M. (5%)
Johar Zubaidi (5%)
Omar Fatehah Mohd (5%)
Kadir Mohd Omar Abdul (5%)
Source document Hydrological sciences journal. Roč. 67, č. 6 (2022), s. 996-1010. - London : Taylor & Francis Group, 2022 Keywords rieky - rivers životné prostredie - environment environmentalistika - environmental science Form. Descr. články - journal articles Language English Country Great Britian Annotation Topographic LIDAR can be used to estimate elevation values for dry areas down to the river water level during the extraction of river cross-sections (XS). However, LIDAR cannot accurately predict the submerged topography, which causes uncertainty in river XS area estimation. This uncertainty affects the channel water level and flood inundation depth estimation in in situ sparse data. Therefore, an alternative approach is presented to estimate unknown submerged topography (UST) using topographic LIDAR. The one dimension/two dimension Hydrologic Engineering Center River Analysis System (1D/2D HEC-RAS) model is used to simulate the estimated river XS with the help of in situ river water level and flow data which is later validated using in situ data. The results show that the proposed approach accurately estimates water level (error >0.5 m), channel flow areas, and floodplain water depths. Notably, the extent of the estimated floodplain overflow by UST models was in 94% agreement with the real XS. URL Link na plný text Public work category ADC No. of Archival Copy 52095 Repercussion category BISWAL, Sabinaya - SAHOO, Bhabagrahi - JHA, Madan K. - BHUYAN, Mahendra K. A hybrid machine learning-based multi-DEM ensemble model of river cross-section extraction : implications on streamflow routing. In Journal of hydrology. ISSN 0022-1694, 2023, vol. 625, art. no. 129951, pp. 1-24.
BISWAL, Sabinaya - SAHOO, Bhabagrahi - JHA, Madan K. - BHUYAN, Mahendra K. A copula model of extracting DEM-based cross-sections for estimating ecological flow regimes in data-limited deltaic-branched river systems. In Journal of environmental management. ISSN 0301-4797, 2023, vol. 342, art. no. 118095, pp. 1-24.
ESSEL-YORKE, K. A. - ANIM, M. - NYARKO, B. K. Sedimentation assessment using hydrological simulation and bathymetry survey : the case of river Amissa drainage basin, Ghana. In Heliyon. ISSN 2405-8440, 2023, vol. 9, no. 3, pp. 1-13.
Catal.org. BB301 - Univerzitná knižnica Univerzity Mateja Bela v Banskej Bystrici Database xpca - PUBLIKAČNÁ ČINNOSŤ References PERIODIKÁ-Súborný záznam periodika 
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