scholarly journals A Pragmatic Framework for Urban River System Plan in Plain River Network Area of China

2012 ◽  
Vol 28 ◽  
pp. 494-500 ◽  
Author(s):  
Hui Xu ◽  
Duozhi Lv ◽  
Yinghua Fan
Keyword(s):  
River System ◽  
River Network ◽  
Urban River ◽  
Network Area

Risk prediction of microcystins based on water quality surrogates: A case study in a eutrophicated urban river network

2021 ◽  
Vol 275 ◽  
pp. 116651
Author(s):  
Xinchen He ◽  
Hua Wang ◽  
Wei Zhuang ◽  
Dongfang Liang ◽  
Yanhui Ao
Keyword(s):  
Water Quality ◽  
Risk Prediction ◽  
River Network ◽  
Urban River

scholarly journals A new vector-based global river network dataset accounting for variable drainage density

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peirong Lin ◽  
Ming Pan ◽  
Eric F. Wood ◽  
Dai Yamazaki ◽  
George H. Allen
Keyword(s):  
Spatial Variability ◽  
Flow Direction ◽  
River System ◽  
Drainage Density ◽  
River Network ◽  
River Networks ◽  
Digital Elevation ◽  
Machine Learning Approach ◽  
Elevation Model ◽  
National Hydrography Dataset

AbstractSpatial variability of river network drainage density (Dd) is a key feature of river systems, yet few existing global hydrography datasets have properly accounted for it. Here, we present a new vector-based global hydrography that reasonably estimates the spatial variability of Dd worldwide. It is built by delineating channels from the latest 90-m Multi-Error-Removed Improved Terrain (MERIT) digital elevation model and flow direction/accumulation. A machine learning approach is developed to estimate Dd based on the global watershed-level climatic, topographic, hydrologic, and geologic conditions, where relationships between hydroclimate factors and Dd are trained using the high-quality National Hydrography Dataset Plus (NHDPlusV2) data. By benchmarking our dataset against HydroSHEDS and several regional hydrography datasets, we show the new river flowlines are in much better agreement with Landsat-derived centerlines, and improved Dd patterns of river networks (totaling ~75 million kilometers in length) are obtained. Basins and estimates of intermittent stream fraction are also delineated to support water resources management. This new dataset (MERIT Hydro–Vector) should enable full global modeling of river system processes at fine spatial resolutions.

scholarly journals ĐẶC ĐIỂM HỆ THỐNG SÔNG CỔ VÀ TÁC ĐỘNG NHÂN SINH DỰA TRÊN KẾT QUẢ MÔ HÌNH TIẾN HÓA TỈ LỆ LỚN KHU VỰC CHÂU THỔ SÔNG HỒNG

2020 ◽  
Vol 19 (4) ◽  
pp. 463-478
Author(s):  
Mai Duc Dong ◽  
Phung Van Phach ◽  
Nguyen Trung Thanh ◽  
Duong Quoc Hung ◽  
Pham Quoc Hiep ◽  
...  
Keyword(s):  
Late Pleistocene ◽  
River System ◽  
River Network ◽  
River Delta ◽  
Red River ◽  
River Systems ◽  
Red River Delta ◽  
The World ◽  
History Of

The Simclast model has been verified and applied effectively in simulating the delta development for some major deltas in the world. In this study, we applied the model Simclast for simulating the history of the Red river delta development in late Pleistocene-Holocene. Results of the model reveal that the mainland of study area had reduced rapidly during transgression period (10,000-8,000 BP). The morphology changed significantly in the paleo-Red and Day river systems, but slightly in the paleo Thai Binh river system. The paleo-river network had been active in upper part before 11,000 BP and then shifted seaward until 2,000 BP. The river-sea interaction causes erosion and accumulation; as a result the morphology changed remarkably. The paleo-Thai Binh river had been inactive until 5,500 BP and then it was active but the morphology had not varied remarkably. The recent coastline generated from Simclast is relatively in accordance with the present coastline.

scholarly journals Effects of land use and water quality on greenhouse gas emissions from an urban river system

2020 ◽  
Author(s):  
Long Ho ◽  
Ruben Jerves-Cobo ◽  
Matti Barthel ◽  
Johan Six ◽  
Samuel Bode ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Urban Areas ◽  
Anthropogenic Activities ◽  
Ghg Emissions ◽  
Flow Characteristics ◽  
River System ◽  
Urban River ◽  
Polluted Water ◽  
Land Use Types

Abstract. Rivers act as a natural source of greenhouse gases (GHGs) that can be released from the metabolisms of aquatic organisms. Anthropogenic activities can largely alter the chemical composition and microbial communities of rivers, consequently affecting their GHG emissions. To investigate these impacts, we assessed the emissions of CO2, CH4, and N2O from Cuenca urban river system (Ecuador). High variation of the emissions was found among river tributaries that mainly depended on water quality and neighboring landscapes. By using Prati and Oregon Indexes, a clear pattern was observed between water quality and GHG emissions in which the more polluted the sites were, the higher were their emissions. When river water quality deteriorated from acceptable to very heavily polluted, their global warming potential (GWP) increased by ten times. Compared to the average estimated emissions from global streams, rivers with polluted water released almost double the estimated GWP while the proportion increased to ten times for very heavily polluted rivers. Conversely, the GWP of good-water-quality rivers was half of the estimated GWP. Furthermore, surrounding land-use types, i.e. urban, roads, and agriculture, significantly affected the river emissions. The GWP of the sites close to urban areas was four time higher than the GWP of the nature sites while this proportion for the sites close to roads or agricultural areas was triple and double, respectively. Lastly, by applying random forests, we identified dissolved oxygen, ammonium, and flow characteristics as the main important factors to the emissions. Conversely, low impact of organic matter and nitrate concentration suggested a higher role of nitrification than denitrification in producing N2O. These results highlighted the impacts of land-use types on the river emissions via water contamination by sewage discharges and surface runoff. Hence, to estimate of the emissions from global streams, both their quantity and water quality should be included.

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