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Yan-Fen Yang
State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A&F University, Yangling, Shaanxi 712100, PR China

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Journal article
Published: 12 September 2020 in Science of The Total Environment
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Plant root systems can greatly reduce soil loss, and their effects on soil erosion differ across species due to their varied root traits. The purpose of this study was to determine the effects of root morphology traits of herbaceous plants on the soil detachment process. Ten herbaceous plants (dominant species) in the Loess Plateau were selected, and 300 undisturbed soil samples (including living roots from the selected herbages) were scoured with flowing water to measure their soil detachment capacities under six levels of shear stress (4.98 to 16.37 Pa). Then, the root traits of each soil sample were measured, and the rill erodibility and critical shear stress were estimated based on the Water Erosion Prediction Project (WEPP) model. The results showed that root morphology traits varied greatly among the ten selected herbages. Accordingly, resulting variations in soil detachment capacity (0.030 to 3.297 kg m−2 s−1), rill erodibility (0.004 to 0.447 s m−1), and critical shear stress (4.73 to 1.13 Pa) were also observed. Plants with fibrous roots were more effective than those with tap roots in reducing soil detachment. Their mean soil detachment capacity and rill erodibility were 93.2% and 93.4% lower, respectively, and their mean critical shear stress was 1.15 times greater than that of the herbaceous plants with tap root systems. Of all the root traits, root surface area density (RSAD) was the primary root trait affecting the soil detachment, and it estimated the soil detachment capacity well (R2 = 0.91, normalized squared error (NSE) = 0.82). Additionally, an equation with few factors (soil aggregate and RSAD) was suggested to simulate the soil detachment capacity when the plant root parameters and soil properties were limited.

ACS Style

Bing Wang; Pan-Pan Li; Chi-Hua Huang; Guo-Bin Liu; Yan-Fen Yang. Effects of root morphological traits on soil detachment for ten herbaceous species in the Loess Plateau. Science of The Total Environment 2020, 754, 142304 .

AMA Style

Bing Wang, Pan-Pan Li, Chi-Hua Huang, Guo-Bin Liu, Yan-Fen Yang. Effects of root morphological traits on soil detachment for ten herbaceous species in the Loess Plateau. Science of The Total Environment. 2020; 754 ():142304.

Chicago/Turabian Style

Bing Wang; Pan-Pan Li; Chi-Hua Huang; Guo-Bin Liu; Yan-Fen Yang. 2020. "Effects of root morphological traits on soil detachment for ten herbaceous species in the Loess Plateau." Science of The Total Environment 754, no. : 142304.

Journal article
Published: 19 February 2020 in Remote Sensing
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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.

ACS Style

Lei Bai; Yuanqiao Wen; Chunxiang Shi; Yanfen Yang; Fan Zhang; Jing Wu; Junxia Gu; Yang Pan; Shuai Sun; Junyao Meng. Which Precipitation Product Works Best in the Qinghai-Tibet Plateau, Multi-Source Blended Data, Global/Regional Reanalysis Data, or Satellite Retrieved Precipitation Data? Remote Sensing 2020, 12, 683 .

AMA Style

Lei Bai, Yuanqiao Wen, Chunxiang Shi, Yanfen Yang, Fan Zhang, Jing Wu, Junxia Gu, Yang Pan, Shuai Sun, Junyao Meng. Which Precipitation Product Works Best in the Qinghai-Tibet Plateau, Multi-Source Blended Data, Global/Regional Reanalysis Data, or Satellite Retrieved Precipitation Data? Remote Sensing. 2020; 12 (4):683.

Chicago/Turabian Style

Lei Bai; Yuanqiao Wen; Chunxiang Shi; Yanfen Yang; Fan Zhang; Jing Wu; Junxia Gu; Yang Pan; Shuai Sun; Junyao Meng. 2020. "Which Precipitation Product Works Best in the Qinghai-Tibet Plateau, Multi-Source Blended Data, Global/Regional Reanalysis Data, or Satellite Retrieved Precipitation Data?" Remote Sensing 12, no. 4: 683.

Journal article
Published: 23 January 2020 in Remote Sensing
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Gridded precipitation products are the potential alternatives in hydrological studies, and the evaluation of their accuracy and potential use is very important for reliable simulations. The objective of this study was to investigate the applicability of gridded precipitation products in the Yellow River Basin of China. Five gridded precipitation products, i.e., Multi-Source Weighted-Ensemble Precipitation (MSWEP), CPC Morphing Technique (CMORPH), Global Satellite Mapping of Precipitation (GSMaP), Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis 3B42, and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), were evaluated against observations made during 2001−2014 at daily, monthly, and annual scales. The results showed that MSWEP had a higher correlation and lower percent bias and root mean square error, while CMORPH and GSMaP made overestimations compared to the observations. All the datasets underestimated the frequency of dry days, and overestimated the frequency and the intensity of wet days (0–5 mm/day). MSWEP and TRMM showed consistent interannual variations and spatial patterns while CMORPH and GSMaP had larger discrepancies with the observations. At the sub-basin scale, all the datasets performed poorly in the Beiluo River and Qingjian River, whereas they were applicable in other sub-basins. Based on its superior performance, MSWEP was identified as more suitable for hydrological applications.

ACS Style

Yanfen Yang; Jing Wu; Lei Bai; Bing Wang. Reliability of Gridded Precipitation Products in the Yellow River Basin, China. Remote Sensing 2020, 12, 374 .

AMA Style

Yanfen Yang, Jing Wu, Lei Bai, Bing Wang. Reliability of Gridded Precipitation Products in the Yellow River Basin, China. Remote Sensing. 2020; 12 (3):374.

Chicago/Turabian Style

Yanfen Yang; Jing Wu; Lei Bai; Bing Wang. 2020. "Reliability of Gridded Precipitation Products in the Yellow River Basin, China." Remote Sensing 12, no. 3: 374.

Journal article
Published: 05 November 2019 in Agriculture, Ecosystems & Environment
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Soil and water conservation measures such as vegetation cover and terraces effectively reduce runoff and sediment yield. However, there is little information available on how vegetation cover and terraces affect peak flow under extreme rainstorm conditions. The purpose of this study was to investigate the effect of vegetation cover and terraces on peak flow rate in small catchments under “7.26” extreme rainstorm conditions on the Chinese Loess Plateau. Thirty-two small watersheds located in Chabagou Watershed, Zizhou County, Shaanxi Province, were selected. The watershed areas ranged from 0.03 to 1.55 km2. An aerial image with a resolution of 0.2 m was used to determine the land use and engineering practice by means of visual interpretation. The cross-section at the watershed outlets were investigated. At each cross-section, the flow depth, cross-sectional area of flow, wetted perimeter, and slope gradient of the channel were measured. Then, flow velocity was calculated using Manning’s equation. Peak flow rate was calculated based on flow velocity and cross-sectional area of flow. The results showed that peak flow rates varied from 0.35 to 79.89 m3/s. Unit flood peak ranged from 4.3 to 153.0 m3/(km2·s). Peak flow rate was significantly correlated with watershed area, main channel length of the watershed, mean slope gradient of the watershed, and area percentage of the grassland at p < 0.01. The unit flood peak in the grassland and woodland decreased by 36% and 64%, respectively, compared with that in the watershed with the largest cropland component. Terraces reduced the unit flood peaks in the farmland and grassland by 48% and 39%, respectively. Thus, vegetation cover and terraces effectively reduced peak flow rate, and the susceptibility of the sampled watersheds to flood generation was evaluated as “average’’ under extreme storm conditions. Our findings indicate that vegetation cover and terraces play an important role in soil conservation onsite and flood safety offsite under extreme rainstorm conditions.

ACS Style

Suhua Fu; Yanfen Yang; BaoYuan Liu; Hanqi Liu; Jiaxin Liu; Liang Liu; Panpan Li. Peak flow rate response to vegetation and terraces under extreme rainstorms. Agriculture, Ecosystems & Environment 2019, 288, 106714 .

AMA Style

Suhua Fu, Yanfen Yang, BaoYuan Liu, Hanqi Liu, Jiaxin Liu, Liang Liu, Panpan Li. Peak flow rate response to vegetation and terraces under extreme rainstorms. Agriculture, Ecosystems & Environment. 2019; 288 ():106714.

Chicago/Turabian Style

Suhua Fu; Yanfen Yang; BaoYuan Liu; Hanqi Liu; Jiaxin Liu; Liang Liu; Panpan Li. 2019. "Peak flow rate response to vegetation and terraces under extreme rainstorms." Agriculture, Ecosystems & Environment 288, no. : 106714.

Journal article
Published: 13 February 2019 in Science of The Total Environment
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General circulation models (GCMs) are useful tools for investigating mechanisms of climate change and projecting future climate change scenarios, but have large uncertainties and biases. Accurate models are of significant importance for agriculture, water resources management, hydrological simulation, and species distribution. In this study, we examined the precipitation and temperature reproducibility of 34 GCMs during the period from 1961 to 1999 over arid and semiarid regions of China. The study area was divided into eight sub-regions; each represented a specific topography. The evaluation was conducted for the whole study area and the sub-regions. Spatial and temporal indices and weighting methodology were used to comprehensively illustrate the models' reproducibility. The results showed that the simulation ability during winter outperformed than that during summer (the weight was 0.192 higher for precipitation and 0.044 higher for temperature during winter than that during summer over the whole study area). Precipitation was more accurately simulated during spring than during autumn as opposed to temperature (the weight was 0.124 higher during spring than during autumn for precipitation and 0.1 higher during autumn than during spring for temperature for the whole region). For precipitation, the simulation ability in the basins was the best, followed by plateaus and mountains; the weights were 0.462, 0.308, and 0.231, respectively. For temperature, the mountains and plateaus had the best and poorest reproducibility, at weights of 0.446 and 0.198, respectively. The top models for precipitation and temperature at different spatial scales (whole study area, three topography types, eight sub-regions) were recommended. The results served as a reference for model selection in future studies regarding impacts of climate change on eco-hydrology.

ACS Style

Yanfen Yang; Lei Bai; Bing Wang; Jing Wu; Suhua Fu. Reliability of the global climate models during 1961–1999 in arid and semiarid regions of China. Science of The Total Environment 2019, 667, 271 -286.

AMA Style

Yanfen Yang, Lei Bai, Bing Wang, Jing Wu, Suhua Fu. Reliability of the global climate models during 1961–1999 in arid and semiarid regions of China. Science of The Total Environment. 2019; 667 ():271-286.

Chicago/Turabian Style

Yanfen Yang; Lei Bai; Bing Wang; Jing Wu; Suhua Fu. 2019. "Reliability of the global climate models during 1961–1999 in arid and semiarid regions of China." Science of The Total Environment 667, no. : 271-286.

Journal article
Published: 26 February 2018 in Remote Sensing
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Precipitation is the main component of global water cycle. At present, satellite quantitative precipitation estimates (QPEs) are widely applied in the scientific community. However, the evaluations of satellite QPEs have some limitations in terms of the deficiency in observation, evaluation methodology, the selection of time windows for evaluation and short periods for evaluation. The objective of this work is to make some improvements by evaluating the spatio-temporal pattern of the long-terms Climate Hazard Group InfraRed Precipitation Satellite’s (CHIRPS’s) QPEs over mainland China. In this study, we compared the daily precipitation estimates from CHIRPS with 2480 rain gauges across China and gridded observation using several statistical metrics in the long-term period of 1981–2014. The results show that there is significant difference between point evaluation and grid evaluation for CHIRPS. CHIRPS has better performance for a large amount of precipitation than it does for arid and semi-arid land. The change in good performance zones has strong relationship with monsoon’s movement. Therefore, CHIRPS performs better in river basins of southern China and exhibits poor performance in river basins in northwestern and northern China. Moreover, CHIRPS exhibits better in warm season than in Winter, owing to its limited ability to detect snowfall. Nevertheless, CHIRPS is moderately sensitive to the precipitation from typhoon weather systems. The limitations for CHIRPS result from the Tropical Rainfall Measuring Mission (TRMM) 3B42 estimates’ accuracy and valid spatial coverage.

ACS Style

Lei Bai; Chunxiang Shi; Lanhai Li; Yanfen Yang; Jing Wu. Accuracy of CHIRPS Satellite-Rainfall Products over Mainland China. Remote Sensing 2018, 10, 362 .

AMA Style

Lei Bai, Chunxiang Shi, Lanhai Li, Yanfen Yang, Jing Wu. Accuracy of CHIRPS Satellite-Rainfall Products over Mainland China. Remote Sensing. 2018; 10 (3):362.

Chicago/Turabian Style

Lei Bai; Chunxiang Shi; Lanhai Li; Yanfen Yang; Jing Wu. 2018. "Accuracy of CHIRPS Satellite-Rainfall Products over Mainland China." Remote Sensing 10, no. 3: 362.