Results 271 to 280 of about 583,271 (336)

Effects of grass vegetation coverage and position on runoff and sediment yields on the slope of Loess Plateau, China

Agricultural Water Management, 2022
Soil erosion poses serious challenge to the sustainable utilization of soil and water resources worldwide. Vegetation restoration can sufficiently improve the environment and reduce soil erosion.
P. Shi, Peng Li, Zhan-bin Li, Jingmei Sun, D. Wang, Zhiqiang Min   +5 more
semanticscholar   +1 more source

Microplastics in urban runoff: Global occurrence and fate.

Water Research, 2022
Public concerns on microplastic (MP) pollution and its prevalence in urban runoff have grown exponentially. Huge amounts of MPs are transported from urban environments via surface runoff to different environment compartments, including rivers, lakes ...
Chengqian Wang, David O’Connor, Liuwei Wang, Wei-Min Wu, Jian Luo, Deyi Hou   +5 more
semanticscholar   +1 more source

A Rainfall‐Runoff Model With LSTM‐Based Sequence‐to‐Sequence Learning

Water Resources Research, 2020
Rainfall‐runoff modeling is a complex nonlinear time series problem. While there is still room for improvement, researchers have been developing physical and machine learning models for decades to predict runoff using rainfall data sets.
Z. Xiang, June Yan, I. Demir
semanticscholar   +1 more source

Occurrence of microplastics and phthalate esters in urban runoff: A focus on the Persian Gulf coastline.

Science of the Total Environment, 2021
Urban runoff seems an obvious pathway for the transfer of microplastics (MPs) and phthalate acid esters (PAEs) from land-based sources to the marine environment; an issue that still lacks attention.
Shamim Hajiouni, A. Mohammadi, B. Ramavandi, H. Arfaeinia, G. De-la-Torre, Agnes Tekle-Röttering, S. Dobaradaran   +6 more
semanticscholar   +1 more source

Short-term runoff prediction with GRU and LSTM networks without requiring time step optimization during sample generation

, 2020
Runoff forecasting is an important approach for flood mitigation. Many machine learning models have been proposed for runoff forecasting in recent years.
Shuai Gao, Yuefei Huang, Shuo Zhang, Jingcheng Han, Guangqian Wang, Meixin Zhang, Qingsheng Lin   +6 more
semanticscholar   +1 more source

Groundwater-runoff relationships

CATENA, 1980
Summary Stable environmental isotope ( 2 HH, 8 O)O) techniques were applied to an Alpine watershed of 18.7 km 2 and 670–1801 m a.s.l. From this example some insights into the runoff generation in a natural hydrologic system are developed. Isotopic hydrograph separations into direct and indirect runoff fractions, based on these techniques, show ...
Herrmann, A., Stichler, W.
openaire   +2 more sources

Monthly runoff time series prediction by variational mode decomposition and support vector machine based on quantum-behaved particle swarm optimization

, 2020
Accurate monthly runoff prediction plays an important role in the planning and management of water resources. However, owing to climate changes and human activities, natural runoff often contains a variety of frequency components, and existing monthly ...
Zhong-kai Feng, Wen-jing Niu, Zheng-yang Tang, Zhi-qiang Jiang, Yang Xu, Yi Liu, Hairong Zhang   +6 more
semanticscholar   +1 more source

Effect of shrub-grass vegetation coverage and slope gradient on runoff and sediment yield under simulated rainfall

, 2021
Evaluating the benefits of sediment and runoff reduction in different vegetation types is essential for studying the mechanisms of soil and water conservation on the Loess Plateau.
D. Han, Jingcheng Deng, Chaojun Gu, Xingmin Mu, P. Gao, Jianjian Gao   +5 more
semanticscholar   +1 more source

A hybrid runoff generation modelling framework based on spatial combination of three runoff generation schemes for semi-humid and semi-arid watersheds

, 2020
It is challenging to accurately differentiate and simulate different runoff components yielded under the saturation-excess and infiltration-excess mechanisms in semi-arid and semi-humid watersheds.
Yuhuan Liu, Ke Zhang, Zhijia Li, Zhiyu Liu, Zhiyu Liu, Jingfeng Wang, Jingfeng Wang, Pengnian Huang   +7 more
semanticscholar   +1 more source