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1. Dynamic runoff simulation in a changing environment: A data stream approach

Author:
Yang, Qinli; Zhang, Heng; Wang, Guoqing; Luo, Shasha; Chen, Dongzi; Peng, Wanshan; Shao, Junming
Source:
Environmental modelling & software 2019 v.112 pp. 157-165
ISSN:
1364-8152
Subject:
runoff,   etc   ; hydrologic models; rain; temperature;     Show all 4 Subjects
Abstract:
... In this study, we introduce a data stream method for dynamic runoff simulation, which allows capturing the evolving relationship between runoff and its impact factors (e.g., temperature, rainfall). The basic idea is to view continuously arriving data of runoff and its impact factors as a data stream, and dynamically learn its relationship. To validate the effectiveness of the proposed method, we c ...
DOI:
10.1016/j.envsoft.2018.11.007

2. Mapping water and sediment connectivity

Author:
Cavalli, Marco; Vericat, Damià; Pereira, Paulo
Source:
The Science of the total environment 2019 v.673 pp. 763-767
ISSN:
0048-9697
Subject:
runoff,   etc   ; landforms; models; quantitative analysis; sediments; watersheds;     Show all 6 Subjects
Abstract:
... Connectivity has become a key issue in the study of processes acting in hydro-geomorphic systems and has strong implications on the understanding of their behaviour. Given the high complexity of hydro-geomorphic systems and the large variety of the processes controlling the efficiency of water and sediment transfer through a catchment, mapping hydrological and sediment connectivity is fundamental ...
DOI:
10.1016/j.scitotenv.2019.04.071

3. Flood mitigation performance of low impact development technologies under different storms for retrofitting an urbanized area

Author:
Hu, Maochuan; Zhang, Xingqi; Li, Yu; Yang, Hong; Tanaka, Kenji
Source:
Journal of cleaner production 2019 v.222 pp. 373-380
ISSN:
0959-6526
Subject:
runoff,   etc   ; hydrologic models; rain; rainfall duration; storms;     Show all 5 Subjects
Abstract:
... Low impact development technologies (LIDs) have been reported as alternatives to mitigate urban water-related hazards, particularly for urban flooding. However, the effectiveness of LIDs on flood mitigation is still not well understood. This study assessed the mitigation extent of urban flooding by LIDs for retrofitting an urbanized area at a feasible level using a hydrological model. A range of s ...
DOI:
10.1016/j.jclepro.2019.03.044

4. Tire and road wear particles in road environment – Quantification and assessment of particle dynamics by Zn determination after density separation

Author:
Klöckner, Philipp; Reemtsma, Thorsten; Eisentraut, Paul; Braun, Ulrike; Ruhl, Aki Sebastian; Wagner, Stephan
Source:
Chemosphere 2019 v.222 pp. 714-721
ISSN:
0045-6535
Subject:
runoff,   etc   ; particulates; sediments; tires; traffic; zinc;     Show all 6 Subjects
Abstract:
... In this study, a method for the determination of tire and road wear particle (TRWP) contents in particulate samples from road environment was developed. Zn was identified as the most suitable elemental marker for TRWP, due to its high concentration in tire tread and the possibility of separation from other Zn sources. The mean concentration of 21 tire samples was 8.7 ± 2.0 mg Zn/g. Before quantifi ...
DOI:
10.1016/j.chemosphere.2019.01.176

5. Exploring the value of machine learning for weighted multi-model combination of an ensemble of global hydrological models

Author:
Zaherpour, Jamal; Mount, Nick; Gosling, Simon N.; Dankers, Rutger; Eisner, Stephanie; Gerten, Dieter; Liu, Xingcai; Masaki, Yoshimitsu; Müller Schmied, Hannes; Tang, Qiuhong; Wada, Yoshihide
Source:
Environmental modelling & software 2019 v.114 pp. 112-128
ISSN:
1364-8152
Subject:
runoff,   etc   ; artificial intelligence; hydrologic models; watersheds;     Show all 4 Subjects
Abstract:
... This study presents a novel application of machine learning to deliver optimised, multi-model combinations (MMCs) of Global Hydrological Model (GHM) simulations. We exemplify the approach using runoff simulations from five GHMs across 40 large global catchments. The benchmarked, median performance gain of the MMC solutions is 45% compared to the best performing GHM and exceeds 100% when compared t ...
DOI:
10.1016/j.envsoft.2019.01.003

6. Misinterpretation of the Kenessey method for the determination of the runoff coefficient: a review

Author:
D’Alberto, Lucio; Lucianetti, Giorgia
Source:
Hydrological sciences journal 2019 v.64 no.3 pp. 288-296
ISSN:
2150-3435
Subject:
runoff,   etc   ; climatic zones; water budget; water management;     Show all 4 Subjects
Abstract:
... The calculation of runoff and infiltration parameters is a fundamental task for water budget estimation and water resources management. The “Kenessey method” allows these values to be calculated and its use is widespread among water scientists and practitioners. Due to language barriers and inefficient translation in past decades, the method has undergone some misinterpretations and is now far fro ...
DOI:
10.1080/02626667.2019.1578965

7. Input Selection of Wavelet-Coupled Neural Network Models for Rainfall-Runoff Modelling

Author:
Shoaib, Muhammad; Shamseldin, Asaad Y.; Khan, Sher; Sultan, Muhammad; Ahmad, Fiaz; Sultan, Tahir; Dahri, Zakir Hussain; Ali, Irfan
Source:
Water resources management 2019 v.33 no.3 pp. 955-973
ISSN:
0920-4741
Subject:
runoff,   etc   ; hydrologic models; neural networks; wavelet;     Show all 4 Subjects
Abstract:
... The use of wavelet-coupled data-driven models is increasing in the field of hydrological modelling. However, wavelet-coupled artificial neural network (ANN) models inherit the disadvantages of containing more complex structure and enhanced simulation time as a result of use of increased multiple input sub-series obtained by the wavelet transformation (WT). So, the identification of dominant wavele ...
DOI:
10.1007/s11269-018-2151-x

8. On the Effect of Intermittent Nonstationarity of Long-Term Changes in the River Runoff

Author:
Solomonova, I. V.; Yushkov, V. P.; Dobrovolski, S. G.
Source:
Water resources 2018 v.45 no.Supplement 2 pp. 99-109
ISSN:
0097-8078
Subject:
runoff,   etc   ; effluents; rivers;     Show all 3 Subjects
Abstract:
... Based on the analysis of 162 longest (more than 100 years each) series of annual, maximal, and minimal runoff in rivers of different genetic types, the regularities of changes in the degree of stationarity/nonstationarity of the runoff changes are studied. It is shown that changes in the average annual and maximum runoff in the rivers of the “main” type—non-effluent, unregulated, as well as in the ...
DOI:
10.1134/S0097807818060295

9. Correction to: Effects of the morphology of sediment-transporting channels on the erosion and deposition of debris flows

Author:
He, Songtang; Wang, Daojie; Chang, Shiqiu; Fang, Yingchao; Lan, Huijuan
Source:
Environmental earth sciences 2018 v.77 no.17 pp. 599
ISSN:
1866-6280
Subject:
runoff,   etc   ; basins; mass movement;     Show all 3 Subjects
Abstract:
... In the original publication, the reference “Gregoretti C, Fontana GD (2008) The triggering of debris flow due to channel-bed failure in some alpine headwater basins of the Dolomites: analyses of critical runoff. Hydrol Process 22(13):2248–2263” is published wrong. ...
DOI:
10.1007/s12665-018-7763-1

10. PRMS-Python: A Python framework for programmatic PRMS modeling and access to its data structures

Author:
Volk, John M.; Turner, Matthew A.
Source:
Environmental modelling & software 2019 v.114 pp. 152-165
ISSN:
1364-8152
Subject:
runoff,   etc   ; case studies; hydrologic models; metadata; provenance; solar radiation;     Show all 6 Subjects
Abstract:
... A persistent problem in numerical hydrologic modeling, is tracking provenance or how particular data came to be. With multiple modules available for individual flux parameterizations and over 100 parameters, the Precipitation-Runoff Modeling System (PRMS) is a perfect example of why it is such a challenge to track the history of input and output of complex models. We present a lightweight, object- ...
DOI:
10.1016/j.envsoft.2019.01.006

11. Rainfall-runoff simulation in Karst dominated areas based on a coupled conceptual hydrological model

Author:
Zhou, Qing; Chen, Lu; Singh, Vijay P.; Zhou, Jianzhong; Chen, Xiaohong; Xiong, Lihua
Source:
Journal of hydrology 2019
ISSN:
0022-1694
Subject:
runoff,   etc   ; groundwater; hydrologic models; karsts; limestone; soil; subsurface flow; watersheds;     Show all 8 Subjects
Abstract:
... Rainfall-runoff processes in the karst dominated regions are of great importance. However, not all areas in a karst-dominated river basin are covered by typical limestone and both limestone and soil cover may exist. This study proposes a coupled conceptual hydrological model for simulating the rainfall-runoff processes in karst-dominated areas. The model, named as K-XAJ, couples the traditional Xi ...
DOI:
10.1016/j.jhydrol.2019.03.099

12. Micropaleontological assessment of sediments from Buor-Khaya Bay (Laptev Sea)

Author:
Obrezkova, M.S.; Tsoy, I.B.; Semiletov, I.P.; Vagina, N.K.; Karnaukh, V.N.; Dudarev, O.V.
Source:
Quaternary international 2019 v.508 pp. 60-69
ISSN:
1040-6182
Subject:
runoff,   etc   ; Bacillariophyceae; coasts; drilling; geophysics; permafrost; rivers; silt; tundra;     Show all 9 Subjects
Abstract:
... The paper presents the first set of micropaleontological data from the Buor-Khaya Bay sediments in the southeastern part of the Laptev Sea, obtained from the bottom sediments through permafrost drilling. The study of diatoms and spore-pollen assemblages in Hole 1D-11 and Hole 4D-12, high-resolution seismic profiling, and lithological composition of the sediments have facilitated the identification ...
DOI:
10.1016/j.quaint.2018.10.033

13. Daily Runoff Forecasting Using a Hybrid Model Based on Variational Mode Decomposition and Deep Neural Networks

Author:
He, Xinxin; Luo, Jungang; Zuo, Ganggang; Xie, Jiancang
Source:
Water resources management 2019 v.33 no.4 pp. 1571-1590
ISSN:
0920-4741
Subject:
runoff,   etc   ; learning; neural networks; prediction; rivers; water management; China;     Show all 7 Subjects
Abstract:
... Accurate and reliable runoff forecasting plays an increasingly important role in the optimal management of water resources. To improve the prediction accuracy, a hybrid model based on variational mode decomposition (VMD) and deep neural networks (DNN), referred to as VMD-DNN, is proposed to perform daily runoff forecasting. First, VMD is applied to decompose the original runoff series into multipl ...
DOI:
10.1007/s11269-019-2183-x

14. FluBiDi – a model to estimate flood based on runoff: validation using extreme and natural basin conditions

Author:
De Luna-Cruz, Faustino; Ramos-Hernández, J.G.; Fuentes-Mariles, O.A.; Gracia-Sánchez, J.
Source:
Hydrological sciences journal 2019 v.64 no.3 pp. 297-317
ISSN:
2150-3435
Subject:
runoff,   etc   ; basins; digital elevation models; floods; hydrograph; laboratory experimentation;     Show all 6 Subjects
Abstract:
... FluBiDi is a two-dimensional model created to simulate real events that can take days and months, as well as short events (minutes or hours) and inclusive laboratory tests. To verify the robustness of FluBiDi, it was tested using a previous study with both designed and real digital elevation models. The results highlight good agreement between the models (i.e. Mike Flood, SOBEK, ISIS 2D, and other ...
DOI:
10.1080/02626667.2019.1578464

15. Considering the effect of groundwater on bioretention using the Storm Water Management Model

Author:
Kim, Hwansuk; Mallari, Kristine Joy B.; Baek, Jongrak; Pak, Gijung; Choi, Hyun Il; Yoon, Jaeyoung
Source:
Journal of environmental management 2019 v.231 pp. 1270-1276
ISSN:
0301-4797
Subject:
runoff,   etc   ; bioretention areas; groundwater; hydrologic models; pollutants; prediction; watersheds;     Show all 7 Subjects
Abstract:
... The Storm Water Management Model (SWMM), with its recently released low impact development (LID) module, is among several models used for the performance evaluation of LID facilities in reducing runoff and pollutants. Modeling is often difficult because of the variety of factors affecting the LID system. Among these factors, the effect of groundwater can be important in the LID modeling results du ...
DOI:
10.1016/j.jenvman.2018.03.032

16. Data-based bivariate uncertainty assessment of extreme rainfall-runoff using copulas: comparison between annual maximum series (AMS) and peaks over threshold (POT)

Author:
Dodangeh, Esmaeel; Shahedi, Kaka; Solaimani, Karim; Shiau, Jenq-Tzong; Abraham, John
Source:
Environmental monitoring and assessment 2019 v.191 no.2 pp. 67
ISSN:
0167-6369
Subject:
runoff,   etc   ; bivariate analysis; planning; probabilistic models; rain; uncertainty; watersheds; Iran;     Show all 8 Subjects
Abstract:
... Bivariate frequency analysis of extreme rainfall and runoff is crucial for water resource planning and management in a river basin. This study is aimed at accounting for uncertainties in bivariate analysis of extreme rainfall-runoff frequency in the Taleghan watershed, one of the major watersheds in northern Iran, using copulas. Two types of paired rainfall and runoff data, including annual maximu ...
DOI:
10.1007/s10661-019-7202-0

17. Evaluating Different Machine Learning Models for Runoff and Suspended Sediment Simulation

Author:
Kumar, Ashish; Kumar, Pravendra; Singh, Vijay Kumar
Source:
Water resources management 2019 v.33 no.3 pp. 1217-1231
ISSN:
0920-4741
Subject:
runoff,   etc   ; basins; fuzzy logic; neural networks; prediction; sediments; suspended sediment;     Show all 7 Subjects
Abstract:
... In the present study, prediction of runoff and sediment at Polavaram and Pathagudem sites of the Godavari basin was carried out using machine learning models such as artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). Different combinations of antecedent stage, current day stage and antecedent runoff for current day runoff prediction and antecedent runoff, current da ...
DOI:
10.1007/s11269-018-2178-z

18. Impact of reservoir operation on runoff and sediment load at multi-time scales based on entropy theory

Author:
Zhang, Jinping; Xiao, Honglin; Zhang, Xin; Li, Fawen
Source:
Journal of hydrology 2019 v.569 pp. 809-815
ISSN:
0022-1694
Subject:
runoff,   etc   ; entropy; monitoring; pollution load; sediment yield; Yellow River;     Show all 6 Subjects
Abstract:
... Based on the runoff and sediment load data series obtained at the Guide hydrological station (GHS) in the upper reaches of the Yellow River from 1960 to 2013, the varying quasi-periodic fluctuations of runoff and sediment load existing in different decomposed time scales are revealed by using the complementary ensemble empirical mode decomposition (CEEMD) method pre- and post-reservoir operation. ...
DOI:
10.1016/j.jhydrol.2019.01.005

19. Modelling the combined effects of runoff reduction and increase in evapotranspiration for green roofs with a storage layer

Author:
Li, Shu-xiao; Qin, Hua-peng; Peng, Yue-nuan; Khu, Soon Thiam
Source:
Ecological engineering 2019 v.127 pp. 302-311
ISSN:
0925-8574
Subject:
runoff,   etc   ; evapotranspiration; green roofs; hydrologic models; rain; temperature; China;     Show all 7 Subjects
Abstract:
... Reduction in runoff and increase in actual evapotranspiration (AET) are two well-known benefits of green roofs. However, few studies have been carried out to investigate how green roofs affect runoff and AET when there is interaction between them. Such interaction is most prominent when green roofs have an additional storage layer. In this study, a modified hydrological model for green roofs is pr ...
DOI:
10.1016/j.ecoleng.2018.12.003

20. Reverification of antecedent moisture condition dependent runoff curve number formulae using experimental data of Indian watersheds

Author:
Lal, Mohan; Mishra, S.K.; Kumar, Mukesh
Source:
Catena 2019 v.173 pp. 48-58
ISSN:
0341-8162
Subject:
runoff,   etc   ; agricultural land; antecedent moisture; data collection; rain; watersheds; India;     Show all 7 Subjects
Abstract:
... The present study evaluates the performance of five existing and three proposed antecedent moisture condition (AMC)-based runoff curve number (CN) conversion formulae utilizing the data of a large number of naturally observed rainfall (P)–runoff (Q) for an agricultural field located at Roorkee, Uttarakhand, India and available published data around the globe. For developing the proposed formulae, ...
DOI:
10.1016/j.catena.2018.09.002