Interpretable machine learning on large samples for supporting runoff estimation in ungauged basins

Y Xu, K Lin, C Hu, S Wang, Q Wu, J Zhang, M Xiao… - Journal of …, 2024 - Elsevier
The distribution of flowmeter data and basin characteristic information exhibits substantial
disparities, with most flow observations being recorded at a limited number of well …

Learning distributed parameters of land surface hydrologic models using a Generative Adversarial Network

R Sun, B Pan, Q Duan - Water Resources Research, 2024 - Wiley Online Library
Land surface hydrologic models adeptly capture crucial terrestrial processes with a high
level of spatial detail. Typically, these models incorporate numerous uncertain, spatially …

Parameter regionalization with donor catchment clustering improves urban flood modeling in ungauged urban catchments

C Hu, J Xia, D She, Z Jing, S Hong… - Water Resources …, 2024 - Wiley Online Library
The lack of discharge observations and reliable drainage information is a pervasive problem
in urban catchments, resulting in difficulties in parameterizing urban hydrological models …

A mass‐conserving‐perceptron for machine‐learning‐based modeling of geoscientific systems

YH Wang, HV Gupta - Water Resources Research, 2024 - Wiley Online Library
Although decades of effort have been devoted to building Physical‐Conceptual (PC) models
for predicting the time‐series evolution of geoscientific systems, recent work shows that …

The impact of future climate and land use changes on runoff in the Min-Tuo River Basin

N Jiang, F Ni, Y Deng, M Wu, Z Yue, M Zhu… - Journal of Water and …, 2024 - iwaponline.com
In the face of escalating global warming and intensified human activities, it is crucial to
quantitatively assess the combined impacts of future climate change (CC) and land use …

Changes in the water retention of mountainous landscapes since the 1820s in the Austrian Alps

G Stecher, S Hohensinner… - Frontiers in Environmental …, 2023 - frontiersin.org
Interactions of humans with the environment are strongly related to land use and land cover
changes (LULCCs). In the last decades, these changes have led to a degradation of …

Using Machine Learning to Identify and Optimize Sensitive Parameters in Urban Flood Model Considering Subsurface Characteristics

H Jin, Y Zhao, P Lu, S Zhang, Y Chen, S Zheng… - International Journal of …, 2024 - Springer
This study presents a novel method for optimizing parameters in urban flood models, aiming
to address the tedious and complex issues associated with parameter optimization. First, a …

Toward understanding parametric controls on runoff sensitivity to climate in the community land model: A case study over the Colorado River headwaters

A Elkouk, Y Pokhrel, B Livneh, E Payton… - Water Resources …, 2024 - Wiley Online Library
Crucial to the assessment of future water security is how the land model component of Earth
System Models partition precipitation into evapotranspiration and runoff, and the sensitivity …

[HTML][HTML] Regionalization in global hydrological models and its impact on runoff simulations: a case study using WaterGAP3 (v 1.0. 0)

J Kupzig, N Kupzig, M Flörke - Geoscientific Model …, 2024 - gmd.copernicus.org
Valid simulation results from global hydrological models (GHMs), such as WaterGAP3, are
essential for detecting hotspots or studying patterns in climate change impacts. However, the …

Time-varying parameters of the hydrological simulation model under a changing environment

R Liu, Y Luo, Q Wang, Y Wang, Y Liu, X Xia, E Jiang - Journal of Hydrology, 2024 - Elsevier
Time-varying parameters of hydrological models play a crucial role in capturing the dynamic
nature of hydrological processes and nonpoint source pollution under changing …