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Dive into the research topics where Xiaomeng Song is active.

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Featured researches published by Xiaomeng Song.


Journal of Geophysical Research | 2014

Rapid urbanization and changes in spatiotemporal characteristics of precipitation in Beijing metropolitan area

Xiaomeng Song; Jianyun Zhang; Amir AghaKouchak; Shouraseni Sen Roy; Yunqing Xuan; Guoqing Wang; Ruimin He; Xiaojun Wang; Cuishan Liu

This study investigates changes in temporal trends and spatial patterns of precipitation in Beijing over the last six decades. These changes are discussed in the context of rapid urbanization and the growing imbalance between water supply and demand in Beijing. We observed significant decreases in precipitation amounts from 1950 to 2012, with the annual precipitation decreasing by 32% at a decadal rate of 28.5 mm. In particular, precipitation decrease is more pronounced in the summer and warm seasons when water use is at its seasonal peak. We further analyzed hourly precipitation data from 43 rain gauges between 1980 and 2012 to examine the spatiotemporal characteristics of both precipitation amount and intensity across six distinct subregions in Beijing. No significant spatial variations in precipitation changes were identified, but slightly greater amounts of precipitation were noted in the urban areas (plains) than in the surrounding suburbs (mountains), due to the effect of urbanization and topography. Precipitation intensity has increased substantially, especially at the hourly duration, as evidenced by the more frequent occurrence of extreme storms. The observed decreased water availability and the increase in extreme weather events require more integrated water management, particularly given the expectation of a warmer and more variable climate, the continued rapid growth of the Beijing metropolis, and the intensifying conflict between water supply and demand.


Journal of Hydrologic Engineering | 2012

Hybrid Optimization Rainfall-Runoff Simulation Based on Xinanjiang Model and Artificial Neural Network

Xiaomeng Song; Fan-zhe Kong; Chesheng Zhan; Ji-wei Han

AbstractA hybrid rainfall-runoff model that integrates artificial neural networks (ANNs) with Xinanjiang (XAJ) model was proposed in this study. The writers extracted the digital drainage network and subcatchments from digital elevation model (DEM) data considering the spatial distribution of rain-gauge stations. Then the semidistributed XAJ model was established based on DEM. Considering the runoff routing cannot be calculated by the linear superposition of the route runoff from all subcatchments, artificial neural networks as effective tools in nonlinear mapping are employed to explore nonlinear transformations of the runoff generated from the individual subcatchments into the total runoff at the entire watershed outlet. The integrated approach has been demonstrated as feasible and was applied successfully in the Yanduhe watershed, the upper tributary of Yangtze River Basin. The results indicated that the approach of integrating back-propagation ANN with semidistributed XAJ model may achieve the promisi...


Chinese Science Bulletin | 2012

Integration of a statistical emulator approach with the SCE-UA method for parameter optimization of a hydrological model

Xiaomeng Song; Chesheng Zhan; Jun Xia

Parameter optimization of a hydrological model is an indispensable process within model development and application. The lack of knowledge regarding the efficient optimization of model parameters often results in a bottle-neck within the modeling process, resulting in the effective calibration and validation of distributed hydrological models being more difficult to achieve. The classical approaches to global parameter optimization are usually characterized by being time consuming, and having a high computation cost. For this reason, an integrated approach coupling a meta-modeling approach with the SCE-UA method was proposed, and applied within this study to optimize hydrological model parameter estimation. Meta-modeling was used to determine the optimization range for all parameters, following which the SCE-UA method was applied to achieve global parameter optimization. The multivariate regression adaptive splines method was used to construct the response surface as a surrogate model to a complex hydrological model. In this study, the daily distributed time-variant gain model (DTVGM) applied to the Huaihe River Basin, China, was chosen as a case study. The integrated objective function based on the water balance coefficient and the Nash-Sutcliffe coefficient was used to evaluate the model performance. The case study shows that the integrated method can efficiently complete the multi-parameter optimization process, and also demonstrates that the method is a powerful tool for efficient parameter optimization.


Journal of Geographical Sciences | 2012

An efficient global sensitivity analysis approach for distributed hydrological model

Xiaomeng Song; Chesheng Zhan; Jun Xia; Fan-zhe Kong

Sensitivity analysis of hydrological model is the key for model uncertainty quantification. However, how to effectively validate model and identify the dominant parameters for distributed hydrological models is a bottle-neck to achieve parameters optimization. For this reason, a new approach was proposed in this paper, in which the support vector machine was used to construct the response surface at first. Then it integrates the SVM-based response surface with the Sobol’ method, i.e. the RSMSobol’ method, to quantify the parameter sensitivities. In this work, the distributed time-variant gain model (DTVGM) was applied to the Huaihe River Basin, which was used as a case to verify its validity and feasibility. We selected three objective functions (i.e. water balance coefficient WB, Nash-Sutcliffe efficiency coefficient NS, and correlation coefficient RC) to assess the model performance as the output responses for sensitivity analysis. The results show that the parameters g1 and g2 are most important for all the objective functions, and they are almost the same to that of the classical approach. Furthermore, the RSMSobol method can not only achieve the quantification of the sensitivity, and also reduce the computational cost, with good accuracy compared to the classical approach. And this approach will be effective and reliable in the global sensitivity analysis for a complex modelling system.


Frontiers of Environmental Science & Engineering in China | 2015

An enhanced environmental multimedia modeling system based on fuzzy-set approach: II. Model validation and application

Rongrong Zhang; Chesheng Zhan; Xiaomeng Song; Baolin Liu

Part I of this study develops an enhanced environmental multimedia modeling system (EMMS) based on fuzzy-set approach. Once the model development is complete, the composite module and the entire modeling system need to be tested and validated to ensure that the model can simulate natural phenomena with reasonable and reliable accuracy. The developed EMMS is first tested in a complete case study. And then verification results are conducted to compare with extensively researched literature data. In the third step, the data from an experimental landfill site is used for a pilot-scale validation. The comparisons between EMMS outputs and the literature data indicate that the EMMS can perform accurate modeling simulation. The modules of EMMS could support the entire environmental multimedia modeling system. Further field-scale validation is finished. The results are satisfactory. Most of the modeling yields closely match the monitoring data collected from sites. In addition, with the aid of fuzzy-set approach, EMMS can be a reliable and powerful tool to address the complex environmental multimedia pollution problems and provide an extensive support for decision makers in managing the contaminated environmental systems.


Frontiers of Environmental Science & Engineering in China | 2015

An enhanced environmental multimedia modeling system based on fuzzy-set approach: I. theoretical framework and model development

Chesheng Zhan; Rongrong Zhang; Xiaomeng Song; Baolin Liu

Multimedia environmental modeling is extremely complex due to the intricacy of the systems with the consideration of many related factors. Traditional environmental multimedia models (EMMs) are usually based on one-dimensional and first-order assumptions, which may cause numerical errors in the simulation results. In this study, a new user-friendly fuzzy-set enhanced environmental multimedia modeling system (FEEMMS) is developed, and includes four key modules: an air dispersion module, a polluting source module, an unsaturated zone module, and a groundwater module. Many improvements over previous EMMs have been achieved through dynamically quantifying the intermedia mass flux; incorporating fuzzy-set approach into environmental multimedia modeling system (EMMS); and designing a user-friendly graphic user interface (GUI). The developed FEEMMS can be a useful tool in estimating the time-varying and spatial-varying chemical concentrations in air, soil, and groundwater; characterizing the potential risk to human health presented by contaminants released from a contaminated site; and quantifying the uncertainties associated with modeling systems and subsequently providing robustness and flexibility for the remediation-related decision making.


Journal of Hydrology | 2015

Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications

Xiaomeng Song; Jianyun Zhang; Chesheng Zhan; Yunqing Xuan; Ming Ye; Chonggang Xu


Environmental Modelling and Software | 2013

An efficient integrated approach for global sensitivity analysis of hydrological model parameters

Chesheng Zhan; Xiaomeng Song; Jun Xia; Charles Tong


Water Resources Management | 2011

Assessment of Water Resources Carrying Capacity in Tianjin City of China

Xiaomeng Song; Fan-zhe Kong; Chesheng Zhan


Water science and engineering | 2013

Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

Xiaomeng Song; Fan-zhe Kong; Chesheng Zhan; Ji-wei Han; Xin-hua Zhang

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Chesheng Zhan

Chinese Academy of Sciences

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Jianyun Zhang

Ministry of Water Resources

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Fan-zhe Kong

China University of Mining and Technology

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Guoqing Wang

Ministry of Water Resources

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Cuishan Liu

Ministry of Water Resources

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Baolin Liu

China University of Geosciences

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Ji-wei Han

China University of Mining and Technology

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Junliang Jin

Ministry of Water Resources

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