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Jie Niu
Jie Niu
Guizhou University, Guiyang, China
Verified email at gzu.edu.cn
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Cited by
Cited by
Year
Surface‐subsurface model intercomparison: A first set of benchmark results to diagnose integrated hydrology and feedbacks
RM Maxwell, M Putti, S Meyerhoff, JO Delfs, IM Ferguson, V Ivanov, J Kim, ...
Water resources research 50 (2), 1531-1549, 2014
2962014
Evaluating controls on coupled hydrologic and vegetation dynamics in a humid continental climate watershed using a subsurface‐land surface processes model
C Shen, J Niu, MS Phanikumar
Water Resources Research 49 (5), 2552-2572, 2013
1172013
Estimating longitudinal dispersion in rivers using Acoustic Doppler Current Profilers
C Shen, J Niu, EJ Anderson, MS Phanikumar
Advances in Water Resources 33 (6), 615-623, 2010
812010
Quantifying Storage Changes in Regional Great Lakes Watersheds Using a Coupled Subsurface - Land Surface Process Model and GRACE, MODIS products
J Niu, C Shen, SG Li, SM Phanikumar
Water Resources Research 50, 2014
602014
Real-time nowcasting of microbiological water quality at recreational beaches: a wavelet and artificial neural network-based hybrid modeling approach
J Zhang, H Qiu, X Li, J Niu, MB Nevers, X Hu, MS Phanikumar
Environmental science & technology 52 (15), 8446-8455, 2018
552018
Prediction of groundwater level in seashore reclaimed land using wavelet and artificial neural network-based hybrid model
J Zhang, X Zhang, J Niu, BX Hu, MR Soltanian, H Qiu, L Yang
Journal of Hydrology 577, 123948, 2019
532019
Incorporating root hydraulic redistribution in CLM 4.5: Effects on predicted site and global evapotranspiration, soil moisture, and water storage
J Tang, WJ Riley, J Niu
Journal of Advances in Modeling Earth Systems 7 (4), 1828-1848, 2015
492015
Modeling watershed-scale solute transport using an integrated, process-based hydrologic model with applications to bacterial fate and transport
J Niu, MS Phanikumar
Journal of Hydrology 529, 35-48, 2015
492015
A comparative analysis of artificial neural networks and wavelet hybrid approaches to long-term toxic heavy metal prediction
P Li, P Hua, D Gui, J Niu, P Pei, J Zhang, P Krebs
Scientific reports 10 (1), 13439, 2020
452020
Simulation of regional groundwater levels in arid regions using interpretable machine learning models
Q Liu, D Gui, L Zhang, J Niu, H Dai, G Wei, BX Hu
Science of the Total Environment 831, 154902, 2022
432022
Quantifying the effects of data integration algorithms on the outcomes of a subsurface–land surface processes model
C Shen, J Niu, K Fang
Environmental modelling & software 59, 146-161, 2014
342014
Improving Budyko curve‐based estimates of long‐term water partitioning using hydrologic signatures from GRACE
K Fang, C Shen, JB Fisher, J Niu
Water Resources Research 52 (7), 5537-5554, 2016
312016
Quantifying wetland–aquifer interactions in a humid subtropical climate region: An integrated approach
I Mendoza-Sanchez, MS Phanikumar, J Niu, JR Masoner, IM Cozzarelli, ...
Journal of Hydrology 498, 237-253, 2013
272013
A review of applications of fractional advection–dispersion equations for anomalous solute transport in surface and subsurface water
L Sun, H Qiu, C Wu, J Niu, BX Hu
Wiley Interdisciplinary Reviews: Water 7 (4), e1448, 2020
262020
Comparative analysis of meteorological and hydrological drought over the Pearl River basin in southern China
K Xu, G Qin, J Niu, C Wu, BX Hu, G Huang, P Wang
Hydrology Research 50 (1), 301-318, 2019
262019
Interannual variation in hydrologic budgets in an Amazonian watershed with a coupled subsurface–land surface process model
J Niu, C Shen, JQ Chambers, JM Melack, WJ Riley
Journal of Hydrometeorology 18 (9), 2597-2617, 2017
222017
Modeling green roof potential to mitigate urban flooding in a Chinese city
L Liu, L Sun, J Niu, WJ Riley
Water 12 (8), 2082, 2020
212020
Assessing the spatiotemporal uncertainties in future meteorological droughts from CMIP5 models, emission scenarios, and bias corrections
C Wu, PJF Yeh, J Ju, YY Chen, K Xu, H Dai, J Niu, BX Hu, G Huang
Journal of Climate 34 (5), 1903-1922, 2021
192021
Interannual and seasonal variations of permafrost thaw depth on the Qinghai-Tibetan plateau: A comparative study using long short-term memory, convolutional neural networks …
Q Liu, J Niu, P Lu, F Dong, F Zhou, X Meng, W Xu, S Li, BX Hu
Science of The Total Environment 838, 155886, 2022
132022
Quantifying the space–time variability of water balance components in an agricultural basin using a process-based hydrologic model and the Budyko framework
H Qiu, J Niu, MS Phanikumar
Science of the total environment 676, 176-189, 2019
112019
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