Publications by authors named "Gaohuan Liu"

Article Synopsis
  • Nonpoint source pollution (NPSP) is the main environmental threat to regional waters, and a new assessment model called SL-NPSRI was created to evaluate its risks based on soil loss and phosphorus levels.
  • The model, tested in the Yellow River Delta, effectively measures pollutant loss during heavy rainfall, highlighting that higher NPSP risks are found in areas with low vegetation and high soil erodibility.
  • To manage NPSP, the research suggests implementing specific land use strategies and improving vegetation coverage tailored to different regions and rainfall patterns.
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Taking the Yellow River Delta as a typical research area, we constructed a coastal agricultural TN and TP non-point source pollution estimating model by analyzing the relationship between the surface soil pollutant loss risks and the monitored pollutant flux into the sea. On this basis, TN and TP non-point source export coefficients of paddy fields, irrigated land, and dry land were calculated, and the verification showed that the estimated export coefficients were acceptable. In the study area, the TN and TP export coefficients into the sea of arable land were 18.

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The 2019 novel coronavirus pandemic (COVID-19) negatively affected global public health and socioeconomic development. Lockdowns and travel restrictions to contain COVID-19 resulted in reduced human activity and decreased anthropogenic emissions. However, the secondary effects of these restrictions on the biophysical environment are uncertain.

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Soil erosion contributes greatly to nonpoint source pollution (NSP). We built a coastal NSP risk calculation method (CNSPRI) based on the Revised Universal Soil Loss Equation (RUSLE) and geospatial methods. In studies on the formation and transport of coastal NSP, we analysed the pollution impacts on the sea by dividing subbasins into the sea and monitoring the pollutant flux.

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The response of floodplain wetlands to changes in river hydrology caused by different dam operation strategies in arid regions has attracted worldwide attention in recent decades. However, less is known about quantifying the effects of dam operations on wetlands in different lateral zones located in low-gradient floodplains in arid regions using remote sensing and hydrological time series. In this study, hydrological time series from 1975 to 1985 and 2008-2014 were used to quantify 67 flow metrics during different dam operation periods.

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Human activities can affect soil nutrients, thereby influencing river water quality. The spatial pattern of precipitation also impacts distributions of water quality. In this paper, we employed a method that combines point survey, soil, and water quality data to analyze the spatial relationships between precipitation, soil nutrient and water quality in the basin on the basis of field surveys and laboratory analysis.

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Based on soil sampling data from the dry season and the rainy season, the spatial heterogeneity and spatial pattern of soil nutrients in the Mun River Basin, Thailand, were studied and the seasonal variation in soil nutrients was analyzed using classical statistical methods and geostatistical methods. The soil nutrient content in the Mun Basin showed moderate and strong variations, and the descending order of soil variability was as follows: available phosphorous (AP) > electric conductivity (EC) > soil organic matter (SOM) > total nitrogen (TN) > pH value in the dry season, with AP showing strong variation, and EC > AP > SOM > TN > pH in the rainy season, with EC showing strong variation. Different soil nutrients and different soil properties had different spatial variation characteristics, and their corresponding best-fitting models were also different.

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Vegetation in arid and semi-arid regions frequently exists in patches, which can be effectively mapped by remote sensing. However, not all satellite images are suitable to detect the decametric-scale vegetation patches because of low spatial resolution. This study compared the capability of the first Gaofen Satellite (GF-1), the second Gaofen Satellite (GF-2), and China-Brazil Earth Resource Satellite 4 (CBERS-04) panchromatic images for mapping quasi-circular vegetation patches (QVPs) with K-Means (KM) and object-based example-based feature extraction with support vector machine classification (OEFE) in the Yellow River Delta, China.

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The Yellow River Delta (YRD), located in Yellow River estuary, is characterized by rich ecological system types, and provides habitats or migration stations for wild birds, all of which makes the delta an ecological barrier or ecotone for inland areas. Nevertheless, the abundant natural resources of YRD have brought huge challenges to the area, and frequent human activities and natural disasters have damaged the ecological systems seriously, and certain ecological functions have been threatened. Therefore, it is necessary to determine the status of the ecological environment based on scientific methods, which can provide scientifically robust data for the managers or stakeholders to adopt timely ecological protection measures.

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Leaf area index (LAI) is one of the key biophysical parameters in crop structure. The accurate quantitative estimation of crop LAI is essential to verify crop growth and health. The PROSAIL radiative transfer model (RTM) is one of the most established methods for estimating crop LAI.

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By using the 2001-2008 MOMS land cover products (MCDl2Ql) and based on the modified classification scheme embodied the characteristics of land cover in northern Tibetan Plateau, the annual land cover type maps of the Plateau were drawn, with the dynamic changes of each land cover type analyzed by classification statistics, dynamic transfer matrix, and landscape pattern indices. In 2001-2008, due to the acceleration of global climate warming, the areas of glacier and snow-covered land in the Plateau decreased rapidly, and the melted snow water gathered into low-lying valley or basin, making the lake level raised and the lake area enlarged. Some permanent wetlands were formed because of partially submersed grassland.

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The Yellow River Delta, one of China's three major river deltas, is becoming a major region for the development of agriculture and fisheries. Protecting the delicate ecology of newly formed aquatic systems as well as the evolution of soils, natural vegetation, and fauna on older upland environments in the delta is a priority in planning for the wise use of the delta's resources for future agricultural development. In this article, we use a Geographic Information System (GIS) to analyze relationships between land-use/ land-cover characteristics in the Dongying municipality, one of the most intensely developed areas of the delta, and spatial variations in soil salinity and landforms.

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