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Environmental Modelling and Software, Volume 114
Volume 114, April 2019
- Saman Razavi
, Hoshin V. Gupta:
A multi-method Generalized Global Sensitivity Matrix approach to accounting for the dynamical nature of earth and environmental systems models. 1-11 - Annie Gallagher Visser
A coupled modelling framework to assess the hydroecological impact of climate change. 12-28 - Andrea Saltelli
Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices. 29-39 - Christopher Krapu, Mark E. Borsuk
Probabilistic programming: A review for environmental modellers. 40-48 - L. A. Morales-Marín, P. R. Sanyal, H. Kadowaki, Zhaoqin Li
A hydrological and water temperature modelling framework to simulate the timing of river freeze-up and ice-cover breakup in large-scale catchments. 49-63 - Qianjiao Wu
An effective parallelization algorithm for DEM generalization based on CUDA. 64-74 - Baihua Fu
A review of catchment-scale water quality and erosion models and a synthesis of future prospects. 75-97 - Vassilis G. Aschonitis
A ranking system for comparing models' performance combining multiple statistical criteria and scenarios: The case of reference evapotranspiration models. 98-111 - Jamal Zaherpour
Exploring the value of machine learning for weighted multi-model combination of an ensemble of global hydrological models. 112-128 - Xuan Yu
A coupled surface-subsurface hydrologic model to assess groundwater flood risk spatially and temporally. 129-139 - Greg R. Hancock, J. F. Martín Duque, G. R. Willgoose
Geomorphic design and modelling at catchment scale for best mine rehabilitation - The Drayton mine example (New South Wales, Australia). 140-151 - John M. Volk
PRMS-Python: A Python framework for programmatic PRMS modeling and access to its data structures. 152-165 - Kinh Bac Dang
Application of a hybrid neural-fuzzy inference system for mapping crop suitability areas and predicting rice yields. 166-180 - Chun-Sheng Huang
Incorporating satellite-derived data with annual and monthly land use regression models for estimating spatial distribution of air pollution. 181-187 - Dongwei Liu, Jie Peng, Yanyu Wang, Meijin Huang, Qianshan He, Yafei Yan, Bingxin Ma, Caijun Yue, Ying Xie:
Implementation of interactive three-dimensional visualization of air pollutants using WebGL. 188-194 - Holger R. Maier
Introductory overview: Optimization using evolutionary algorithms and other metaheuristics. 195-213
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