A GIS-based modeling approach for fast assessment of soil erosion by water at regional scale, loess plateau of China

Hu, Liping; Yang, Haijun; Yang, Qinke

doi:10.1007/s11769-010-0416-2

Cited by 10 publications

(1 citation statement)

References 28 publications

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“…Although SWT and lake storage data are available for some lakes, in-situ measurements have been often limited because of the inaccessibility of faraway lakes and inaccuracies in sampling. Naturally, remote sensing has provided great opportunity for monitoring and assessing the climate and environmental change of an area (Wang et al, 2009;Hu et al, 2010;Wang et al, 2012;Shi et al, 2015;Song et al, 2016;Shi et al, 2019). To date, previous studies have been mainly focused on monitoring lake areas, water levels, and lake storage variations (Cretaux et al, 2011), as well as estimating lake SWT (Ke et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Remote Detection of Varying Water Storage in Relation to Surfacial Temperature of Aral Sea

Chen

et al. 2019

Chin. Geogr. Sci.

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Lake monitoring by remote sensing is of significant importance to understanding the lake and ambient ecological and environmental processes. In particular, whether lake water storage variation could predict lake surfacial temperature or vice versa has long fascinated the research community, in that it would greatly benefit the monitoring missions and scientific interpretation of the lake change processes. This study attempted to remotely detect the dynamics of the Aral Sea and pursue the relationships between varying lake water storage attributes and surface water temperature by using MODIS LST (Moderate-resolution Imaging Spectroradiometer Land Surface Temperature) 8-day composite products, satellite altimeter data, and actual meteorological measurements. Their associations with lake Surface Water Temperatures (SWT) were then analyzed. Results showed the lake water surface areas and elevations of the North Aral Sea tended to increasing trend from 2001 (2793.0 km 2 , 13.6 m) to 2015 (6997.8 km 2 , 15.9 m), while those of the South Aral Sea showed a decreasing trend during 2001 (20 434.6 km 2 , 3.9 m) and 2015 (3256.1 km 2 , 0.9 m). In addition, the annual daytime and nighttime lake SWT both decreased in the North Aral Sea, while only the daytime SWT in the South Aral Sea exhibited an increase, indicating a rising deviation of diurnal temperatures in the South Aral Sea during the past 15 yr. Moreover, a lower correlation was found between variations in the daytime SWT and storage capacity in the South Aral Sea (R 2 = 0.33; P < 0.05), no fair correlations were tested between lake water storage and daytime SWT in the North Aral Sea nor between lake water storage and nighttime SWT in either part of the sea. These results implied that climate change, if any at least during the research period, has no significant effects on lake dynamics over the two sectors of the Aral Sea with anthropogenic disturbances. However, climate change and human activities may overlap to explain complex consequences in the lake storage variations. Our results may provide a reference for monitoring the spatiotemporal variations of lakes, increasing understanding of the lake water storage changes in relation to the lake SWT, which may benefit the ecological management of the Aral Sea region, in the effort to face the likely threats from climate change and human activities to the region.

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Section: Introductionmentioning

confidence: 99%

Remote Detection of Varying Water Storage in Relation to Surfacial Temperature of Aral Sea

Chen

et al. 2019

Chin. Geogr. Sci.

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Geoinformation Approach in Soil Erosion Susceptibility Assessment – A Tool for Decision Making: Case Study of the North-Western Bulgaria

Nikolova

Dimitrov

Златева³

2019

IFIP Advances in Information and Communication Technology

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The soil erosion is considered as one of the most serious environmental problem in a global scale. The development of the process could have negative impact on water, vegetation and ecosystem as a hole, as well as to influence on the quality of life. If the process is not mitigated in long term it could change the topographic surface and to trigger geomorphological hazards. The researches on soil erosion require analyses of large volume of information about soil properties, topographic surface, precipitation and land use. In the current research GIS technology is used for building the data base, spatial analyses and visualization of the results. The Universal Soil Loss Equation (USLE) is applied in Map Algebra and spatial distribution of soil loss is presented. The results are considered in relation to land use, particularly arable lands and vineyards. The application of computer technology provide opportunities for easy processing of data and updating the model by adding new data which can be used by territorial planning experts, local authorities and farmers in the planning process, monitoring and mitigating the soil erosion.

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Estimation of soil erosion using RUSLE in Caijiamiao watershed, China

Pan

Wen

2013

Nat Hazards

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A GIS-based modeling approach for fast assessment of soil erosion by water at regional scale, loess plateau of China

Cited by 10 publications

References 28 publications

Remote Detection of Varying Water Storage in Relation to Surfacial Temperature of Aral Sea

Remote Detection of Varying Water Storage in Relation to Surfacial Temperature of Aral Sea

Geoinformation Approach in Soil Erosion Susceptibility Assessment – A Tool for Decision Making: Case Study of the North-Western Bulgaria

Estimation of soil erosion using RUSLE in Caijiamiao watershed, China

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