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Featured researches published by Xianyong Meng.


Scientific Reports | 2017

Investigating spatiotemporal changes of the land-surface processes in Xinjiang using high-resolution CLM3.5 and CLDAS: Soil temperature.

Xianyong Meng; Hao Wang; Yiping Wu; Aihua Long; Jianhua Wang; Chun-xiang Shi; Xiaonan Ji

Soil temperature plays a key role in the land surface processes because this parameter affects a series of physical, chemical, and biological processes in the soil, such as water and heat fluxes. However, observation of soil temperature is quite limited, especially at the regional scale. Therefore, this study is to investigate the spatiotemporal features of soil temperature in Xinjiang, China, using the Community Land model 3.5 (CLM3.5) with the atmospheric near-surface forcing data of the China Meteorological Administration Land Data Assimilation System (CLDAS). We use the observed soil temperature data collected from 105 national automatic stations during 2009 through 2012 in the study area to verify the simulation capability. The comparison results indicate that the CLM3.5 with the CLDAS driving field could well simulate the spatiotemporal patterns of the soil temperature at hourly, daily, and monthly time scales and at three depths (5 cm, 20 cm, and 80 cm). We also produce a soil temperature database of the region that is continuous both in time and space with high resolution (about 6.25 km). Overall, this study could help understand the regional and vertical characteristics of the soil temperature and provide an important scientific basis for other land-surface processes.


Journal of Mountain Science | 2015

Energy Balance-Based SWAT Model to Simulate the Mountain Snowmelt and Runoff – Taking the Application in Juntanghu Watershed (China) as an Example

Xianyong Meng; Dan-Lin Yu; Zhihui Liu

In order to predict long-term flooding under extreme weather conditions in central Asia, an energy balance-based distributed snowmelt runoff model was developed and coupled with the Soil and Water Assessment Tool (SWAT) model. The model was tested at the Juntanghu watershed on the northern slope of the TianShan Mountains, Xinjiang, China. We compared the performances of temperature-index method and energy balanced method in SWAT model by taking Juntanghu river basin as an application example (as the simulation experiment was conducted in Juntanghu River, we call the energy balanced method as SWAT-JTH). The results suggest that the SWAT snowmelt model had overall Nash-Sutcliffe efficiency (NSE) coefficients ranging from 0.61 to 0.85 while the physical based approach had NSE coefficients ranging from 0.58 to 0.69. Overall, on monthly scale, the SWAT model provides better results than that from the SWAT-JTH model. However, results generated from both methods seem to be fairly close at a daily scale. The structure of the temperature-index method is simple and produces reasonable simulation results if the parameters are well within empirical ranges. Although the data requirement for the energy balance method in current observation is difficult to meet and the existence of uncertainty is associated with the experimental approaches of physical processes, the SWAT-JTH model still produced a reasonably high NSE. We conclude that using temperature-index methods to simulate the snowmelt process is sufficient, but the energy balance-based model is still a good choice to simulate extreme weather conditions especially when the required data input for the model is acquired.


Water Resources | 2014

Responses of runoff to climate change and human activities in the Ebinur Lake Catchment, western China

Junqiang Yao; Zhihui Liu; Qing Yang; Xianyong Meng; Chengzhi Li

Based on hydrological and climatic data covering the period from 1961 to 2008, this paper studies the hydrological responses to climate change and to human activities in the Ebinur Lake Catchment. The results show that the annual runoff of three rivers in Ebinur Lake Catchment exhibited different change trends. Specifically, in Jinghe River and Kuytun River exhibited a slightly increasing trend, but an adverse trend in Bortala River, and the variation trend has been the most dramatic since the mid-1990s. The observed variation in the runoff was resulted from the elevated alpine precipitation, rather than rising temperature, and that precipitation is a major factor for runoff generation. The runoff CAR model proposed by this paper can be used to predict the annual runoff in three rivers, and demonstrated annual runoff in Bortala River and Jinghe River will display an increased trend, while a less decreasing trend in Kuytun River under the climate change scenarios of warm-humid variation. In addition, the exploitation of the area of cultivated land led to more water resources consumption, primarily for agriculture irrigation, is the cause of the persistently ecoenvironment degradation, which have reached in a critical state thus, a more pressing concern is the development a scientifically reasonable and administratively practical water resource management scheme.


Scientific Reports | 2018

Simulation and spatiotemporal pattern of air temperature and precipitation in Eastern Central Asia using RegCM

Xianyong Meng; Aihua Long; Yiping Wu; Gang Yin; Hao Wang; Xiaonan Ji

Central Asia is a region that has a large land mass, yet meteorological stations in this area are relatively scarce. To address this data issues, in this study, we selected two reanalysis datasets (the ERA40 and NCEP/NCAR) and downscaled them to 40 × 40 km using RegCM. Then three gridded datasets (the CRU, APHRO, and WM) that were extrapolated from the observations of Central Asian meteorological stations to evaluate the performance of RegCM and analyze the spatiotemporal distribution of precipitation and air temperature. We found that since the 1960s, the air temperature in Xinjiang shows an increasing trend and the distribution of precipitation in the Tianshan area is quite complex. The precipitation is increasing in the south of the Tianshan Mountains (Southern Xinjiang, SX) and decreasing in the mountainous areas. The CRU and WM data indicate that precipitation in the north of the Tianshan Mountains (Northern Xinjiang, NX) is increasing, while the APHRO data show an opposite trend. The downscaled results from RegCM are generally consistent with the extrapolated gridded datasets in terms of the spatiotemporal patterns. We believe that our results can provide useful information in developing a regional climate model in Central Asia where meteorological stations are scarce.


Scientific Reports | 2017

Study on the characteristics of future precipitation in response to external changes over arid and humid basins

Lianqing Xue; Boli Zhu; Changbing Yang; Guanghui Wei; Xianyong Meng; Aihua Long; Guang Yang

The simulation abilities of the Coupled Model Inter-comparison Project Phase 5 (CMIP5) models to the arid basin (the Tarim River Basin, TRB) and humid basin (the Yangtze River Basin, YRB) were evaluated, determining the response of precipitation to external changes over typical basins. Our study shows that the future temporal and spatial variation characteristics of precipitation are different in different regions with the CMIP5. The annual and seasonal changes in precipitation were analyzed for the RCP2.6, RCP4.5 and RCP8.5 during 2021~2100 compared to those during 1961~2005. Precipitation shows an increasing trend in the TRB, but which decreases and then increases in the YRB, with a turning point in the middle of twenty-first Century. The ranges in annual precipitation increase with the increase in the scenario emissions in the future. Note that the Tarim River Basin is more vulnerable to the impact of emissions, especially for annual or spring and winter precipitation. Based on the uncertainty of CMIP5 data, the links between future precipitation changes and the elevation and relief amplitude were evaluated. The change of precipitation decreases with elevation, relief amplitude in the TRB, while it increases with elevation but decreases with relief amplitude in the YRB.


Tehnicki Vjesnik-technical Gazette | 2018

Spring Flood Forecasting Based on the WRF-TSRM Mode

Xianyong Meng; Zhiqun Sun; Honggang Zhao; Xiaonan Ji; Hao Wang; Lianqing Xue; Hongjing Wu; Yongnan Zhu

The snowmelt process is becoming more complex in the context of global warming, and the current existing studies are not effective in using the short-term prediction model to drive the distributed hydrological model to predict snowmelt floods. In this study, we selected the Juntanghu Watershed in Hutubi County of China on the north slope of the Tianshan Mountains as the study area with which to verify the snowmelt flood prediction accuracy of the coupling model. The weather research and forecasting (WRF) model was used to drive a double-layer distributed snowmelt runoff model called the Tianshan Snowmelt Runoff Model (TSRM), which is based on multi-year field snowmelt observations. Moreover, the data from NASA’s moderate resolution imaging spectroradiometer (MODIS) was employed to validate the snow water equivalent during the snow-melting period. Results show that, based on the analysis of the flow lines in 2009 and 2010, the WRF-driven TSRM has an overall 80% of qualification ratios (QRs), with determination coefficients of 0.85 and 0.82 for the two years, respectively, which demonstrates the high accuracy of the model. However, due to the influence of the ablation of frozen soils, the forecasted flood peak is overestimated. This problem can be solved by an improvement to the modeled frozen soil layers. The conclusion reached in this study suggests that the WRF-driven TSRM can be used to forecast short-term snowmelt floods on the north slope of the Tianshan Mountains, which can effectively improve the local capacity for the forecasting and early warning of snowmelt floods.


Hydrology and Earth System Sciences Discussions | 2017

Spatiotemporal response of the water cycle to land use conversions in a typical hilly-gully basin on the Loess Plateau, China

Linjing Qiu; Yiping Wu; Lijing Wang; Xiaohui Lei; Weihong Liao; Ying Hui; Xianyong Meng

The hydrological effects of the “Grain for Green” project (GFGP) on the Loess Plateau have been extensively debated due to the complexity of the water system and its multiple driving factors. The aim of this study was to investigate the response of the hydrological cycle to the GFGP measures based in a case study of the Yanhe Basin, a typical hilly–gully area on the Loess Plateau of China. First, we analyzed the land use and land cover (LULC) changes from 1990 to 2010. Then, we evaluated the effects of LULC changes and sloping land conversion on the main hydrological components in the basin using the Soil and Water Assessment Tool (SWAT). The results indicated that cropland exhibited a decreasing trend, declining from 40.2 % of the basin area in 1990 to 17.6 % in 2010, and that the woodland and grassland areas correspondingly increased. With the land use changes from 1990 to 2010, the water yield showed a decreasing trend which was mainly due to decrease in surface runoff. In contrast, evapotranspiration (ET) showed an increasing trend over the same period, resulting in a persistent decrease in soil water. The conversion of sloping cropland to grassland or woodland exerted negative effects on water yield and soil water. Compared with the land use condition in 2010, the negative effects were most evident where cropland with a slope ≥ 15 was converted to woodland, with decreases in surface runoff and soil water of 17.1 and 6.4 %, respectively. These results suggest that the expansive reforestation on sloping land in the loess hilly–gully region decreased water yield and increased ET, resulting in reduced soil water. The results of this study can be used to support sustainable land use planning and water resource management on the Loess Plateau in China.


Multimedia Tools and Applications | 2017

Towards a partial differential equation remote sensing image method based on adaptive degradation diffusion parameter

Xianyong Meng; Lei Che; Zhihui Liu; Ning Che; Xiaonan Ji

For the anisotropy diffusion feature, Partial Differential Equation (PDE) methods keep edge detail characters well in case of denoising, thus being widely applied in remote sense image denoising, smoothing, filtering and reconstruction. A PDE remote sensing image denoising method based on Adaptive Degradation Diffusion Parameter (ADDP) was proposed in the paper to deal with fuzzy detail problem caused by increasing iteration number. The PDE denoising method with ADDP enlarged diffusion size in the plat region of remote sensing image without affecting the remote sensing image edge, thus avoiding loss of remote sensing image detail and intersections caused by Gaussian convolution smoothing in the PDE filtering model based on curvature-based movement (CM) and image denoising model based on total variation (TV). In the region where gradation value changes little, the method executed isotropic diffusion to remove isolated noise. The upwind scheme was applied for model numerical realization. Experimental in remote sensing image denoising results proved its feasibility and effectiveness.


Water | 2017

Significance of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) of East Asia

Xianyong Meng; Hao Wang


Tehnicki Vjesnik-technical Gazette | 2017

Hidrološko modeliranje u porječju rijeke Manas primjenom alata za procjenu tla i vode pomoću CMADS-a

Xianyong Meng; Hao Wang; Xiaohui Lei; Siyu Cai; Hongjing Wu; Xiaonan Ji; Jianhua Wang

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Hao Wang

Ministry of Water Resources

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Xiaonan Ji

Chinese Academy of Sciences

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Hongjing Wu

Memorial University of Newfoundland

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Chun-xiang Shi

China Meteorological Administration

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Gang Yin

Chinese Academy of Sciences

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Yiping Wu

Xi'an Jiaotong University

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