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Fen Qin
Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng 475004, China

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Journal article
Published: 30 June 2021 in Sustainability
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Typhoons are major natural disasters in China. Much typhoon information is contained in a large number of network media resources, such as news reports and volunteered geographic information (VGI) data, and these are the implicit data sources for typhoon research. However, two problems arise when using typhoon information from Chinese news reports. Since the Chinese language lacks natural delimiters, word segmentation error results in trigger mismatches. Additionally, the polysemy of Chinese affects the classification of triggers. Second, there is no authoritative classification system for typhoon events. This paper defines a classification system for typhoon events, and then uses the system in a neural network model, lattice-structured bidirectional long–short-term memory with a conditional random field (BiLSTM-CRF), to detect these events in Chinese online news. A typhoon dataset is created using texts from the China Weather Typhoon Network. Three other datasets are generated from general Chinese web pages. Experiments on these four datasets show that the model can tackle the problems mentioned above and accurately detect typhoon events in Chinese news reports.

ACS Style

Danjie Chen; Fen Qin; Kun Cai; Yatian Shen. Detecting and Classifying Typhoon Information from Chinese News Based on a Neural Network Model. Sustainability 2021, 13, 7332 .

AMA Style

Danjie Chen, Fen Qin, Kun Cai, Yatian Shen. Detecting and Classifying Typhoon Information from Chinese News Based on a Neural Network Model. Sustainability. 2021; 13 (13):7332.

Chicago/Turabian Style

Danjie Chen; Fen Qin; Kun Cai; Yatian Shen. 2021. "Detecting and Classifying Typhoon Information from Chinese News Based on a Neural Network Model." Sustainability 13, no. 13: 7332.

Journal article
Published: 27 June 2021 in Remote Sensing
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Accurate temporal land use mapping provides important and timely information for decision making for large-scale management of land and crop production. At present, temporal land cover and crop classifications within a study area have neglected the differences between subregions. In this paper, we propose a classification rule by integrating the terrain, time series characteristics, priority, and seasonality (TTPSR) with Sentinel-2 satellite imagery. Based on the time series of Normalized Difference Water Index (NDWI) and Vegetation Index (NDVI), a dynamic decision tree for forests, cultivation, urban, and water was created in Google Earth Engine (GEE) for each subregion to extract cultivated land. Then, with or without this cultivated land mask data, the original classification results for each subregion were completed based on composite image acquisition with five vegetation indices using Random Forest. During the post-reclassification process, a 4-bit coding rule based on terrain, type, seasonal rhythm, and priority was generated by analyzing the characteristics of the original results. Finally, statistical results and temporal mapping were processed. The results showed that feature importance was dominated by B2, NDWI, RENDVI, B11, and B12 over winter, and B11, B12, NDBI, B2, and B8A over summer. Meanwhile, the cultivated land mask improved the overall accuracy for multicategories (seven to eight and nine to 13 during winter and summer, respectively) in each subregion, with average ranges in the overall accuracy for winter and summer of 0.857–0.935 and 0.873–0.963, respectively, and kappa coefficients of 0.803–0.902 and 0.835–0.950, respectively. The analysis of the above results and the comparison with resampling plots identified various sources of error for classification accuracy, including spectral differences, degree of field fragmentation, and planting complexity. The results demonstrated the capability of the TTPSR rule in temporal land use mapping, especially with regard to complex crops classification and automated post-processing, thereby providing a viable option for large-scale land use mapping.

ACS Style

Lijun Wang; Jiayao Wang; Fen Qin. Feature Fusion Approach for Temporal Land Use Mapping in Complex Agricultural Areas. Remote Sensing 2021, 13, 2517 .

AMA Style

Lijun Wang, Jiayao Wang, Fen Qin. Feature Fusion Approach for Temporal Land Use Mapping in Complex Agricultural Areas. Remote Sensing. 2021; 13 (13):2517.

Chicago/Turabian Style

Lijun Wang; Jiayao Wang; Fen Qin. 2021. "Feature Fusion Approach for Temporal Land Use Mapping in Complex Agricultural Areas." Remote Sensing 13, no. 13: 2517.

Journal article
Published: 27 May 2021 in Land
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The study of the temporal and spatial evolution of wetland landscapes and its driving factors is an important reference for wetland ecological restoration and protection. This article utilized seven periods of land use data in Henan Province from 1980 to 2015 to extract the spatial distribution characteristics of wetlands and analyze the temporal and spatial changes of wetlands in Henan Province. Transfer matrix, landscape metrics, correlation analysis, and redundancy analysis were applied to calculate and analyze the transformation types and area of wetland resources between all consecutive periods, and then the main driving factors of wetland expansion/contraction were explored. First, the total wetland area in Henan Province increased by 28% from 1980 to 2015, and the increased wetland area was mainly constructed wetlands, including paddy field, reservoir and pond, and canal. Natural wetlands such as marsh, lake, and floodplain decreased by 74%. Marsh area declined the most during 1990–1995, and was mainly transformed into floodplain and “Others” because of agricultural reclamation, low precipitation, and low Yellow River runoff. The floodplain area dropped the most from 2005 to 2010, mainly converted to canals and “Others” because of reclamation, exploitation of groundwater, the construction of the South–to–North Water Transfer Project, and recreational land development. Second, the results of correlation analysis and redundancy analysis indicated that economic factors were positively correlated with the area of some constructed wetlands and negatively correlated with the area of some natural wetlands. Socioeconomic development was the main driving factors for changes in wetland types. The proportion of wetland habitat in Henan Province in 2015 was only 0.3%, which is low compared to the Chinese average of 2.7%. The government should pay more attention to the restoration of natural wetlands in Henan Province.

ACS Style

Heying Li; Jiayao Wang; Jianchen Zhang; Fen Qin; Jiyuan Hu; Zheng Zhou. Analysis of Characteristics and Driving Factors of Wetland Landscape Pattern Change in Henan Province from 1980 to 2015. Land 2021, 10, 564 .

AMA Style

Heying Li, Jiayao Wang, Jianchen Zhang, Fen Qin, Jiyuan Hu, Zheng Zhou. Analysis of Characteristics and Driving Factors of Wetland Landscape Pattern Change in Henan Province from 1980 to 2015. Land. 2021; 10 (6):564.

Chicago/Turabian Style

Heying Li; Jiayao Wang; Jianchen Zhang; Fen Qin; Jiyuan Hu; Zheng Zhou. 2021. "Analysis of Characteristics and Driving Factors of Wetland Landscape Pattern Change in Henan Province from 1980 to 2015." Land 10, no. 6: 564.

Journal article
Published: 16 December 2020 in Remote Sensing
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Accurately identifying and delineating urban boundaries are the premise for and foundation of the control of disorderly urban sprawl, which is helpful for us to accurately grasp the scale and form of cities, optimize the internal spatial structure and pattern of cities, and guide the expansion of urban spaces in the future. At present, the concept and delineation of urban boundaries do not follow a unified method or standard. However, many scholars have made use of multi-source remote sensing images of various scales and social auxiliary data such as point of interest (POI) data to achieve large-scale, high-resolution, and high-precision land cover mapping and impermeable water surface mapping. The accuracy of small- and medium-scale urban boundary mapping has not been improved to an obvious extent. This study uses multi-temporal Sentinel-2 high-resolution images and POI data that can reflect detailed features of human activities to extract multi-dimensional features and use random forests and mathematical morphology to map the urban boundaries of the city of Zhengzhou. The research results show that: (1) the urban construction land extraction model established with multi-dimensional features has a great improvement in accuracy; (2) when the training sample accounts for 65% of the sample data set, the urban construction land extraction model has the highest accuracy, reaching 96.25%, and the Kappa coefficient is 0.93; (3) the optimized boundary of structural elements with a size of 13 × 13 is selected, which is in good agreement in terms of scope and location with the boundary of FROM-GLC10 (Zhengzhou) and visual interpretations. The results from the urban boundary delineation in this paper can be used as an important database for detailed basic land use mapping within cities. Moreover, the method in this paper has some reference value for other cities in terms of delineating urban boundaries.

ACS Style

Zhe Wang; Haiying Wang; Fen Qin; Zhigang Han; Changhong Miao. Mapping an Urban Boundary Based on Multi-Temporal Sentinel-2 and POI Data: A Case Study of Zhengzhou City. Remote Sensing 2020, 12, 4103 .

AMA Style

Zhe Wang, Haiying Wang, Fen Qin, Zhigang Han, Changhong Miao. Mapping an Urban Boundary Based on Multi-Temporal Sentinel-2 and POI Data: A Case Study of Zhengzhou City. Remote Sensing. 2020; 12 (24):4103.

Chicago/Turabian Style

Zhe Wang; Haiying Wang; Fen Qin; Zhigang Han; Changhong Miao. 2020. "Mapping an Urban Boundary Based on Multi-Temporal Sentinel-2 and POI Data: A Case Study of Zhengzhou City." Remote Sensing 12, no. 24: 4103.

Original paper
Published: 26 May 2020 in Arabian Journal of Geosciences
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Protecting the ecological environment is an important goal of the world sustainable development. Rapid and quantitative evaluation of regional ecological environment is the technical support and necessary condition for this goal. The ecological environment index model (RSEI) which used to assess ecological environment is the most popular now. But it changed into two completely opposite models in the application. Most researchers choose which model to use based on the desired results. This article concludes the reason by studying the operating mechanism of the model and finds that it is the eigenvector direction in the principal component analysis causes this to happen. Taking Pingyu County as an example, this article calculates RSEI with Landsat 8 images in different periods in Google Earth Engine using the two existing models respectively and finds that two models show two opposite result trends in spatial distribution. Using any model to calculate the same image, the results are also opposite if changing the input order of the indicators. It is the eigenvector direction determines the spatial distribution by comparing and analyzing the eigenvector of each image and its corresponding RSEI. Then, this paper improves the model by fixing the eigenvector direction based on the actual effects on ecological environment of the four indicators, taking absolute values of the eigenvectors of NDVI and Wet which have a positive effect on the ecological environment and the opposite of absolute values of the eigenvectors of LST and NDSI which have a negative effect on the ecological environment, in order to improve the RSEI model. Using the improved model calculate each image, the results are consistently accurate. Furthermore, this paper also proposed a model for users who calculating the principal components through software where the eigenvector direction cannot be altered artificially. This paper proposes the improved model which is suitable for all users whether using software or conducting programming. The improved model is suitable for all images of any input order of the indicators. It provides the possibility of applying remote sensing big data to the ecological environment. At the same time, the study of the mechanism of the model provides a scientific basis for future scholars to calculate in batches.

ACS Style

Li Ning; Wang Jiayao; Qin Fen. The improvement of ecological environment index model RSEI. Arabian Journal of Geosciences 2020, 13, 1 -14.

AMA Style

Li Ning, Wang Jiayao, Qin Fen. The improvement of ecological environment index model RSEI. Arabian Journal of Geosciences. 2020; 13 (11):1-14.

Chicago/Turabian Style

Li Ning; Wang Jiayao; Qin Fen. 2020. "The improvement of ecological environment index model RSEI." Arabian Journal of Geosciences 13, no. 11: 1-14.

Journal article
Published: 19 March 2020 in Sustainability
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A reasonable layout optimization strategy of rural residential areas can improve the quality of life of rural residents and promote rural revitalization. Evaluating the suitability of rural residential areas is the basis of layout optimization. Based on 1:100,000 land cover data and a digital elevation model (30 m) for the Henan Province, China, we used the minimum cumulative resistance model to evaluate the spatial distribution suitability of rural settlements in the Zhengzhou administrative area (abbreviated: Zhengzhou). Then, we used a weighted Voronoi diagram to determine the scope of influence of central villages and determined the direction of relocation for the “combined migration” rural residential areas. The study results support the following conclusions: (1) the comprehensive resistance value of rural residential areas in the Northeastern part of Zhengzhou is low and the suitability is high. However, the comprehensive resistance value of the Southwestern part is high and the suitability is low. (2) The study area can be divided into highly suitable areas, suitable areas, generally suitable areas, unsuitable areas, and extremely unsuitable areas. Unsuitable areas and extremely unsuitable areas accounted for 33.66% of the total area and included 662 rural residential areas. (3) The rural residential areas were divided into four types of optimization: urbanization, key development, controlled development, and combined migration. Based on an analysis of the characteristics of each type of rural residential area, we proposed corresponding optimization strategies. The results remedy the lack of layout optimization strategies for large-scale rural residential areas and can provide support for the optimization of the layout of rural residential areas in Zhengzhou. Furthermore, the research techniques may apply to other regions.

ACS Style

Pengfei Guo; Fangfang Zhang; Haiying Wang; Fen Qin. Suitability Evaluation and Layout Optimization of the Spatial Distribution of Rural Residential Areas. Sustainability 2020, 12, 2409 .

AMA Style

Pengfei Guo, Fangfang Zhang, Haiying Wang, Fen Qin. Suitability Evaluation and Layout Optimization of the Spatial Distribution of Rural Residential Areas. Sustainability. 2020; 12 (6):2409.

Chicago/Turabian Style

Pengfei Guo; Fangfang Zhang; Haiying Wang; Fen Qin. 2020. "Suitability Evaluation and Layout Optimization of the Spatial Distribution of Rural Residential Areas." Sustainability 12, no. 6: 2409.

Original paper
Published: 22 August 2019 in Theoretical and Applied Climatology
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Plastic film mulch, which effectively maintains soil moisture by suppressing soil evaporation, has been widely used in cropland in Northwest China, where water scarcity severely restricts agricultural development. Plastic mulch affects surface albedo and blocks water vapor exchange between soil and atmosphere. Therefore, the large area of cropland covered by plastic film will have serious impacts on regional climate by modifying the surface-atmosphere partitioning of vapor and energy. In this study, a dynamic irrigation scheme was incorporated into the Weather Research and Forecasting model with Noah land surface scheme; two experiments (with and without plastic mulch) were designed to simulate the impacts of plastic mulch over cropland in Northwest China on regional climate. In irrigated cropland, the irrigation amount decreased substantially during the early stage of crop growth (ESCG; from 22 April to 1 July) with plastic mulch, especially in May, indicating that plastic mulch conserved agricultural water. In nonirrigated cropland, soil moisture in cropland with plastic mulch was clearly greater than that without plastic mulch. The influences of plastic mulch on land surface processes were mainly reflected in the ESCG, such that upward shortwave radiation increased and latent heat flux decreased. In cropland during the ESCG, after plastic mulch, the latent heat flux decreased significantly by 12–30 W m−2, the sensible heat flux increased significantly by 8–16 W m−2, and the surface air temperature increased significantly by 0.2–0.8 °C. The plastic mulch reduced water vapor in the lower atmosphere, which might lead to decrease precipitation in Northwest China.

ACS Style

Liyang Wu; Fen Qin; Jinming Feng; Jinting Huang. Regional climate effects of plastic film mulch over the cropland of arid and semi-arid regions in Northwest China using a regional climate model. Theoretical and Applied Climatology 2019, 139, 335 -349.

AMA Style

Liyang Wu, Fen Qin, Jinming Feng, Jinting Huang. Regional climate effects of plastic film mulch over the cropland of arid and semi-arid regions in Northwest China using a regional climate model. Theoretical and Applied Climatology. 2019; 139 (1-2):335-349.

Chicago/Turabian Style

Liyang Wu; Fen Qin; Jinming Feng; Jinting Huang. 2019. "Regional climate effects of plastic film mulch over the cropland of arid and semi-arid regions in Northwest China using a regional climate model." Theoretical and Applied Climatology 139, no. 1-2: 335-349.

Journal article
Published: 27 February 2019 in ISPRS International Journal of Geo-Information
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A soil erosion model is used to evaluate the conditions of soil erosion and guide agricultural production. Recently, high spatial resolution data have been collected in new ways, such as three-dimensional laser scanning, providing the foundation for refined soil erosion modelling. However, serial computing cannot fully meet the computational requirements of massive data sets. Therefore, it is necessary to perform soil erosion modelling under a parallel computing framework. This paper focuses on a parallel computing framework for soil erosion modelling based on the Hadoop platform. The framework includes three layers: the methodology, algorithm, and application layers. In the methodology layer, two types of parallel strategies for data splitting are defined as row-oriented and sub-basin-oriented methods. The algorithms for six parallel calculation operators for local, focal and zonal computing tasks are designed in detail. These operators can be called to calculate the model factors and perform model calculations. We defined the key-value data structure of GeoCSV format for vector, row-based and cell-based rasters as the inputs for the algorithms. A geoprocessing toolbox is developed and integrated with the geographic information system (GIS) platform in the application layer. The performance of the framework is examined by taking the Gushanchuan basin as an example. The results show that the framework can perform calculations involving large data sets with high computational efficiency and GIS integration. This approach is easy to extend and use and provides essential support for applying high-precision data to refine soil erosion modelling.

ACS Style

Zhigang Han; Fen Qin; Caihui Cui; Yannan Liu; Lingling Wang; Pinde Fu. Mr4Soil: A MapReduce-Based Framework Integrated with GIS for Soil Erosion Modelling. ISPRS International Journal of Geo-Information 2019, 8, 103 .

AMA Style

Zhigang Han, Fen Qin, Caihui Cui, Yannan Liu, Lingling Wang, Pinde Fu. Mr4Soil: A MapReduce-Based Framework Integrated with GIS for Soil Erosion Modelling. ISPRS International Journal of Geo-Information. 2019; 8 (3):103.

Chicago/Turabian Style

Zhigang Han; Fen Qin; Caihui Cui; Yannan Liu; Lingling Wang; Pinde Fu. 2019. "Mr4Soil: A MapReduce-Based Framework Integrated with GIS for Soil Erosion Modelling." ISPRS International Journal of Geo-Information 8, no. 3: 103.

Journal article
Published: 07 November 2018 in Atmosphere
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The Yellow River Basin has been affected by global climate change. Studying the spatial–temporal variability of the hydrothermal climate conditions in the Yellow River Basin is of vital importance for the development of technologies and policies related to ecological, environmental, and agricultural adaptation in this region. This study selected temperature and precipitation data observed from 118 meteorological stations distributed in the Yellow River Basin over the period of 1957–2015, and used the Mann–Kendall, Pettitt, and Hurst indices to investigate the spatial–temporal variability of the hydrothermal climate conditions in this area. The results indicated: (1) the annual maximum, minimum, and average temperatures have increased. The seasonal maximum, minimum, and average temperatures for the spring, summer, autumn, and winter have also increased, and this trend is statistically significant (p < 0.01) between 1957–2015. The rate of increase in the minimum temperature exceeded that of the maximum temperature, and diurnal warming was asymmetric. Annual precipitation and the total spring, summer, and autumn precipitations declined, while the total winter precipitation increased, although the trend was non-significant (p > 0.05). (2) Based on the very restrictive assumption that future changes will be similar to past changes, according to the Hurst index experiment, the future trends of temperature and precipitation in the Yellow River Basin are expected to stay the same as in the past. There will be a long-term correlation between the two trends: the temperature will continue to rise, while the precipitation will continue to decline (except in the winter). However, over the late stage of the study period, the trends slowed down to some extent.

ACS Style

Liqun Ma; Haoming Xia; Jiulin Sun; Hao Wang; Gary Feng; Fen Qin. Spatial–Temporal Variability of Hydrothermal Climate Conditions in the Yellow River Basin from 1957 to 2015. Atmosphere 2018, 9, 433 .

AMA Style

Liqun Ma, Haoming Xia, Jiulin Sun, Hao Wang, Gary Feng, Fen Qin. Spatial–Temporal Variability of Hydrothermal Climate Conditions in the Yellow River Basin from 1957 to 2015. Atmosphere. 2018; 9 (11):433.

Chicago/Turabian Style

Liqun Ma; Haoming Xia; Jiulin Sun; Hao Wang; Gary Feng; Fen Qin. 2018. "Spatial–Temporal Variability of Hydrothermal Climate Conditions in the Yellow River Basin from 1957 to 2015." Atmosphere 9, no. 11: 433.

Article
Published: 12 July 2018 in Chinese Geographical Science
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Implementation of payments for watershed services (PWS) has been regarded as a promising approach to coordinating the interests of upstream and downstream ecosystem services stakeholders. There is growing concern about whether PWS programs have achieved their original environmental goals of improving water quality and quantity, as well as the ancillary objective of increasing the welfare of local people. We start with an overview of PWS schemes and focus on their particularity and implementation mechanisms in China. We proceed to review 62 active PWS cases and examine their environmental performance in detail. The resulting findings show that PWS schemes have been able to reduce water pollution to some extent by establishing collaborative upstream/downstream watershed management policies, thereby improving water quality and quantity, as well as by making government officials more responsible for water resource management. In addition, their continued effectiveness in light of present challenges such as water-quality data availability is discussed. Chinese PWS schemes and their implementation mechanisms also provide information useful in monitoring environmental outcomes and guiding future designs of PWS programs in other regions.

ACS Style

Yan Lu; Jianhua Xu; Fen Qin; Jiayao Wang. Payments for Watershed Services and Practices in China: Achievements and Challenges. Chinese Geographical Science 2018, 28, 873 -893.

AMA Style

Yan Lu, Jianhua Xu, Fen Qin, Jiayao Wang. Payments for Watershed Services and Practices in China: Achievements and Challenges. Chinese Geographical Science. 2018; 28 (5):873-893.

Chicago/Turabian Style

Yan Lu; Jianhua Xu; Fen Qin; Jiayao Wang. 2018. "Payments for Watershed Services and Practices in China: Achievements and Challenges." Chinese Geographical Science 28, no. 5: 873-893.

Journal article
Published: 07 December 2017 in Sustainability
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Ecosystem deterioration has been and is still a serious threat to human survival and regional economic development. Theoretical and methodological challenges exist in assessing ecological risk of watershed ecosystem that is imposed by natural changes or human activities. To fill this research gap, this research proposes an interdisciplinary and quantitative methodology based on some techniques such as the Procedure for Ecological Tiered Assessment of Risk (PETAR), the Entropy, and the Celluar Automata Markov (CA-Markov). We focused on six vulnerable environmental variables, namely land-use change, water quantity, water quality, gross domestic product (GDP), environmental pollutants, and soil erosion in the Huai River watershed in the Henan Province in order to build multi-dimensional quantitative method. Further, the Coupling Coordination Degree Model is constructed, and the “threshold index” is also addressed to reflect the limitation of ecological risk. Our results show that the spatio-temperal distribution of the eco-environmental quality has greatly varied across this study area during different time spans. Natural eco-environmental quality has moderately degraded in 70% of this study area (mainly agricultural region), at a prefectural level from 2000 to 2010, and has slightly improved over the agricultural region (<170 m above sea level) during 2010–2015. However, when considering negative stressors from human social system on the natural ecosystem, the extent and distribution of the ecological risk varied across the whole area during 2000–2015. The results show that there was almost 90.40% of this region under the ecological risk, with varying extents over the study time, e.g., Kaifeng, Shangqiu, Xuchang, and Xinyang, with a moderate deterioration in the eco-environmental quality, and Zhengzhou with a slight deterioration in the eco-environmental quality. This paper provides a valuable perspective for governments at all levels to manage watershed environment resources.

ACS Style

Yan Lu; Fen Qin; Zhongbing Chang; Shuming Bao. Regional Ecological Risk Assessment in the Huai River Watershed during 2010–2015. Sustainability 2017, 9, 2231 .

AMA Style

Yan Lu, Fen Qin, Zhongbing Chang, Shuming Bao. Regional Ecological Risk Assessment in the Huai River Watershed during 2010–2015. Sustainability. 2017; 9 (12):2231.

Chicago/Turabian Style

Yan Lu; Fen Qin; Zhongbing Chang; Shuming Bao. 2017. "Regional Ecological Risk Assessment in the Huai River Watershed during 2010–2015." Sustainability 9, no. 12: 2231.

Journal article
Published: 04 May 2013 in CATENA
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The spatio-temporal variation underlies and complicates studies related to earth surface processes. Subsequent to our previous studies reporting the temporal invariability of sediment concentration, this study further reports the spatial invariability of sediment concentration or the flow–sediment relationship in the hilly part of the Chinese Loess Plateau. The dense channel network dissects this area into numerous sub-watersheds, which are composed of entire slopes (a combination of the hill slope and the valley side slope). Our data mainly involves ten experimental sites of entire slope and sub-watershed and 580 flood events at three locations. Our analysis at the intra-event time scale shows that the instantaneous sediment concentrations in runoff can generally approach the detach-limited maximum sediment concentration since the active massing wasting ensures an abundant sediment supply. Consequently, the event mean sediment concentration does not only remain fairly constant among flow events but also among the experimental sites despite the possible differences in topography, soil management or land cover, water source, soil surface properties, etc. This observation also holds at the annual time scale. Our result implies that a single proportional function is adequate to fit the flow–sediment relationship for any entire slope or sub-watershed, where eroded sediments are primarily sourced, over a considerable areal extent unless soil property has changed or check dams are installed. Moreover, the proportionality coefficient, which is indicative of the maximum detachment capacity, can be approximated through flume experiments rather than necessarily through long-term field observations. Our finding can facilitate the obtainment of spatially distributed information on soil loss in the Chinese Loess Plateau and is also indicative of other locations where sediment supply is sufficiently available.

ACS Style

Mingguo Zheng; Fen Qin; Jishang Yang; Qiangguo Cai. The spatio-temporal invariability of sediment concentration and the flow–sediment relationship for hilly areas of the Chinese Loess Plateau. CATENA 2013, 109, 164 -176.

AMA Style

Mingguo Zheng, Fen Qin, Jishang Yang, Qiangguo Cai. The spatio-temporal invariability of sediment concentration and the flow–sediment relationship for hilly areas of the Chinese Loess Plateau. CATENA. 2013; 109 ():164-176.

Chicago/Turabian Style

Mingguo Zheng; Fen Qin; Jishang Yang; Qiangguo Cai. 2013. "The spatio-temporal invariability of sediment concentration and the flow–sediment relationship for hilly areas of the Chinese Loess Plateau." CATENA 109, no. : 164-176.