scholarly journals Analysis and Estimation of Geographical and Topographic Influencing Factors for Precipitation Distribution over Complex Terrains: A Case of the Northeast Slope of the Qinghai–Tibet Plateau

Atmosphere ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 349 ◽  
Author(s):  
Weicheng Liu ◽  
Qiang Zhang ◽  
Zhao Fu ◽  
Xiaoyan Chen ◽  
Hong Li

Due to the complex terrain, sparse precipitation observation sites, and uneven distribution of precipitation in the northeastern slope of the Qinghai–Tibet Plateau, it is necessary to establish a precipitation estimation method with strong applicability. In this study, the precipitation observation data from meteorological stations in the northeast slope of the Qinghai–Tibet Plateau and 11 geographical and topographic factors related to precipitation distribution were used to analyze the main factors affecting precipitation distribution. Based on the above, a multivariate linear regression precipitation estimation model was established. The results revealed that precipitation is negatively related to latitude and elevation, but positively related to longitude and slope for stations with an elevation below 1700 m. Meanwhile, precipitation shows positive correlations with both latitude and longitude, and negative correlations with elevation for stations with elevations above 1700 m. The established multivariate regression precipitation estimating model performs better at estimating the mean annual precipitation in autumn, summer, and spring, and is less accurate in winter. In contrast, the multivariate regression mode combined with the residual error correction method can effectively improve the precipitation forecast ability. The model is applicable to the unique natural geographical features of the northeast slope of the Qinghai–Tibet Plateau. The research results are of great significance for analyzing the temporal and spatial distribution pattern of precipitation in complex terrain areas.

2020 ◽  
Author(s):  
Hongwei Liu ◽  
Jiufu Liu ◽  
Jin Lin ◽  
Wenzhong Wang ◽  
Xing Min ◽  
...  

<p>The glacier recession and the runoff variation on the Qinghai-Tibet plateau conducted by the global warming is changing the regional hydrological and ecological processes. Although there is great need for the knowledge of the runoff evolution and biogenic substances migration and transformation for developing strategies for adaptive utilization of runoff, progress in study on these hydrological questions lags behind because of lack of observation dataset under harsh plateau cold conditions.</p><p>In order to understand the critical zone ecohydrological dynamics and evaluate the runoff components in the Qinghai-Tibet Plateau, a series of observation and research were carried out in the Niyang River watershed, a tributary of the Yarlung Zangbo River. Four basins embed in a larger basin (1500 km<sup>2</sup>) were monitored and sampled at altitudes between 3667 to 6140 m. More than 500 samples from rain, snow, river water, spring water, glacier ice, vegetation stem, and soil were collected, with which theδ<sup>2</sup>H, δ<sup>18</sup>O, K, Ca, Na, Mg, Sr, Si, F, Cl, N, and S in the water are examined. 5 automatic hydrometric stations were established, and the water level data was sent back by Beidou satellite. The 3D laser scanning and RTK technologies were used to obtain detailed geomorphological information near the 5 current measurement section, based on which a hydrodynamic model is able to be calibrated for the discharge estimation.</p><p>The δ<sup>2</sup>H and δ<sup>18</sup>O of the precipitation proposed a local meteoric water isotope line, which is parallel to the WMWL but higher in the δD~δ<sup>18</sup>O graph. The river water isotopes suggest its source is the precipitation, which are similar to the spring ground water (but the geochemical elements are quite different between the surface and ground water). The vegetation stems water and soil water (by cryogenic vacuum extraction) isotope values suggest the attribute of the river/precipitation sources, but a few observation data appear different implying using water formed by the multiple precipitation events or supplied by the higher place under a significant evaporation influence.</p><p>The time series of the runoff and the snow cover and glacier variation results show that the base flow is varied obviously relate to the temperature which influence the melting processes of the glacier and frozen earth from March to August, and the rain runoff events control the flood peek. It suggests that the concentration time should be less than 10 days in the interested watershed.</p><p>The tempo-spatial variation characteristics of the geochemical elements are analyzed and mapped in the interested area, which suggested relative steady water components signals contributing to the runoff. Based on which, a set of overdetermined equations are established to evaluate the quantities of different runoff components.</p><p>This study could help to evaluate runoff components quantitively in Tibet where lack of data. Monitoring and studing is still going on, which is included in the 2<sup>nd</sup> comprehensive scientific investigation into Qinghai-Tibet Plateau since 2019.</p><p>Funded by the NSFC project 91647111 and 91647203 included in the Runoff Change and its Adaptive Management in the Major Rivers in Southwestern China Major Research Plan.</p>


2022 ◽  
Vol 9 ◽  
Author(s):  
Hongshan Gao ◽  
Fenliang Liu ◽  
Tianqi Yan ◽  
Lin Qin ◽  
Zongmeng Li

The drainage density (Dd) is an important index to show fluvial geomorphology. The study on Dd is helpful to understand the evolution of the whole hydrological and geomorphic process. Based on the Shuttle Radar Topography Mission 90-m digital elevation model, the drainage network of basins along the eastern margin of the Qinghai–Tibet Plateau is extracted using a terrain morphology-based method in ArcGIS 10.3, and Dd is calculated. The spatial characteristics of Dd are analyzed, and the relationship between Dd and its influencing factors, e.g., the topography, precipitation, and vegetation coverage, is explored. Our results show that terrains with a plan curvature ≥3 can represent the channels in the study area. Dd ranges from 2.5 to 0.1 km/km2, increases first, and then decreases from north to south on the eastern margin of the Qinghai–Tibet Plateau. Dd decreases with increasing average slope and average local relief. On the low-relief planation surfaces, Dd increases with increasing altitude, while on the rugged mountainous above planation surfaces, Dd decreases rapidly with increasing altitude. Dd first increased and then decreased with increasing mean annual precipitation (MAP) and normalized difference vegetation index (NDVI), and Dd reaches a maximum in the West Qinling Mountains with a semi-arid environment, indicating that Dd in different climatic regions of the eastern margin of the Qinghai–Tibet Plateau was mainly controlled by precipitation and vegetation.


Water ◽  
2018 ◽  
Vol 10 (4) ◽  
pp. 513 ◽  
Author(s):  
Jun Liu ◽  
Donghui Shanguan ◽  
Shiyin Liu ◽  
Yongjian Ding

Multisource reanalysis datasets provide an effective way to help us understand hydrological processes in inland alpine regions with sparsely distributed weather stations. The accuracy and quality of two widely used datasets, the China Meteorological Assimilation Driving Datasets to force the SWAT model (CMADS), and the Climate Forecast System Reanalysis (CFSR) in the Qinghai-Tibet Plateau (TP), were evaluated in this paper. The accuracy of daily precipitation, max/min temperature, relative humidity and wind speed from CMADS and CFSR are firstly evaluated by comparing them with results obtained from 131 meteorological stations in the TP. Statistical results show that most elements of CMADS are superior to those of CFSR. The average correlation coefficient (R) between the maximum temperature and the minimum temperature of CMADS and CFSR ranged from 0.93 to 0.97. The root mean square error (RMSE) for CMADS and CFSR ranged from 3.16 to 3.18 °C, and ranged from 5.19 °C to 8.14 °C respectively. The average R of precipitation, relative humidity, and wind speed for CMADS are 0.46; 0.88 and 0.64 respectively, while they are 0.43, 0.52, and 0.37 for CFSR. Gridded observation data is obtained using the professional interpolation software, ANUSPLIN. Meteorological elements from three gridded data have a similar overall distribution but have a different partial distribution. The Soil and Water Assessment Tool (SWAT) is used to simulate hydrological processes in the Yellow River Source Basin of the TP. The Nash Sutcliffe coefficients (NSE) of CMADS+SWAT in calibration and validation period are 0.78 and 0.68 for the monthly scale respectively, which are better than those of CFSR+SWAT and OBS+SWAT in the Yellow River Source Basin. The relationship between snowmelt and other variables is measured by GeoDetector. Air temperature, soil moisture, and soil temperature at 1.038 m has a greater influence on snowmelt than others.


2015 ◽  
Vol 12 (1) ◽  
pp. 481-513 ◽  
Author(s):  
S. Ding ◽  
Y. Xu ◽  
Y. Wang ◽  
Y. He ◽  
J. Hou ◽  
...  

Abstract. The methylation index of branched tetraethers (MBT) and cyclization ratio of branched tetraethers (CBT) based on the distribution of bacteria-derived branched glycerol dialkyl glycerol tetraethers (bGDGTs) are useful proxies for the reconstruction of continental paleotemperature and soil pH. Several calibrations of the MBT-CBT index have been proposed based on global and regional soils and lake sediments. However, little is known about the distribution and applicability of GDGTs proxies in the Qinghai–Tibet Plateau (QTP), a critical region of the global climate system. Here, we investigated 33 surface soils covering a large area of the QTP. Redundancy analysis showed that soil pH was the most important factor affecting GDGT distributions, followed by mean annual precipitation (MAP) and mean annual air temperature (MAT). The branched-isoprenoid tetraether (BIT) index, an indicator for estimation of soil organic matter in aquatic environments, varied from 0.48 to 1 and negatively correlated with soil pH (r2 = 0.38), suggesting that the BIT index should be used with caution in the QTP. A transfer function of the CBT index-soil pH was established to estimate paleo-soil pH in the QTP: pH = 8.33–1.43 × CBT (r2 = 0.80, RMSE = 0.27 pH unit). The local calibration of MBT-CBT index presented a weak, still significant correlation with MAT (r2 = 0.36) mainly owing to the additional influence of MAP (r2 = 0.50). Combining our data with previously reported GDGTs for Chinese soils resulted in a new calibration of MBT/CBT-MAT: MAT = 2.68+26.14 × MBT–3.37 × CBT (r2 = 0.73; RMSE = 4.2 °C, n = 164). The correlation coefficient and residual error of this new transfer function is comparable with global calibrations, suggesting that MBT-CBT paleotemperature proxy is still valid in the QTP.


PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0252149
Author(s):  
Jinke Sun ◽  
Ying Yue ◽  
Haipeng Niu

Estimating net primary productivity (NPP) is significant in global climate change research and carbon cycle. However, there are many uncertainties in different NPP modeling results and the process of NPP is challenging to model on the absence of data. In this study, we used meteorological data as input to simulate vegetation NPP through climate-based model, synthetic model and CASA model. Then, the results from three models were compared with MODIS NPP and observed data over China from 2000 to 2015. The statistics evaluation metrics (Relative Bias (RB), Pearson linear Correlation Coefficient (CC), Root Mean Square Error (RMSE), and Nash-Sutcliffe efficiency coefficient (NSE)) between simulated NPP and MODIS NPP were calculated. The results implied that the CASA-model performed better than the other two models in terms of RB, RMSE, NSE and CC whether on the national or the regional scale. It has a higher CC with 0.51 and a smaller RMSE with 111.96 g C·m-2·yr-1 in the whole country. The synthetic model and CASA-model has the same advantages at some regions, and there are lower RMSE in Southern China (86.35 g C·m-2·yr-1), Xinjiang (85.53 g C·m-2·yr-1) and Qinghai-Tibet Plateau (93.22 g C·m-2·yr-1). The climate-based model has widespread overestimation and large systematic errors, along with worse performances (NSEmax = 0.45) and other metric indexes unsatisfactory, especially Qinghai-Tibet Plateau with relatively lower accuracy because of the unavailable observation data. Overall, the CASA-model is much more ideal for estimating NPP all over China in the absence of data. This study provides a comprehensive intercomparison of different NPP-simulated models and can provide powerful help for researchers to select the appropriate NPP evaluation model.


2015 ◽  
Vol 78 (3) ◽  
pp. 1843-1857 ◽  
Author(s):  
Bing Guo ◽  
Yi Zhou ◽  
Jinfeng Zhu ◽  
Wenliang Liu ◽  
Futao Wang ◽  
...  

2020 ◽  
Vol 206 ◽  
pp. 01010
Author(s):  
Guolin Yang ◽  
Chuanyin Zhang ◽  
Xuexian Sun ◽  
Tao Liu ◽  
Xuwei An

Periodic crustal movement are mainly caused by ocean tides and changes of atmospheric pressure. In this project, the researcher has used the spherical harmonic coefficient of the ocean tide and actual observation data to study the impact on vertical crustal deformation due to changes of oceanic tide loading from 2012 to 2017 at the northeastern margin of the Qinghai-Tibet Plateau, based on the theory of crustal load deformation. The result shows that changes in oceanic tide loading have little impact on vertical crustal deformation compared with the impact of atmospheric loading at the northeastern margin of the Qinghai. The impact range of oceanic tide loading in this region is within ±3mm. In contrast, impact of atmospheric loading can reach ±12mm.


2020 ◽  
Vol 12 (4) ◽  
pp. 683 ◽  
Author(s):  
Lei Bai ◽  
Yuanqiao Wen ◽  
Chunxiang Shi ◽  
Yanfen Yang ◽  
Fan Zhang ◽  
...  

Precipitation serves as a crucial factor in the study of hydrometeorology, ecology, and the atmosphere. Gridded precipitation data are available from a multitude of sources including precipitation retrieved by satellites, radar, the output of numerical weather prediction models, and extrapolation by ground rain gauge data. Evaluating different types of products in ungauged regions with complex terrain will not only help researchers in applying scientific data, but also provide useful information that can be used to improve gridded precipitation products. The present study aims to evaluate comprehensively 12 precipitation datasets made by raw retrieved products, blended with rain gauge data, and blended multiple source datasets in multi-temporal scales in order to develop a suitable method for creating gridded precipitation data in regions with snow-dominated regions with complex terrain. The results show that the Multi-Source Weighted-Ensemble Precipitation (MSWEP), Global Satellite Mapping of Precipitation with Gauge Adjusted (GSMaP_GAUGE), Tropical Rainfall Measuring Mission (TRMM_3B42), Climate Prediction Center Morphing Technique blended with Chinese observations (CMORPH_SUN), and Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) can represent the spatial pattern of precipitation in arid/semi-arid and humid/semi-humid areas of the Qinghai-Tibet Plateau on a climatological spatial pattern. On interannual, seasonal, and monthly scales, the TRMM_3B42, GSMaP_GAUGE, CMORPH_SUN, and MSWEP outperformed the other products. In general, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN_CCS) has poor performance in basins of the Qinghai-Tibet Plateau. Most products overestimated the extreme indices of the 99th percentile of precipitation (R99), the maximal of daily precipitation in a year (Rmax), and the maximal of pentad accumulation of precipitation in a year (R5dmax). They were underestimated by the extreme index of the total number of days with daily precipitation less than 1 mm (dry day, DD). Compared to products blended with rain gauge data only, MSWEP blended with more data sources, and outperformed the other products. Therefore, multi-sources of blended precipitation should be the hotspot of regional and global precipitation research in the future.


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