Remote Sensing-Based Biomass Estimation and Its Spatio-Temporal Variations in Temperate Grassland, Northern China

Monitoring of water quality changes in highly dynamic inland lakes is frequently impeded by insufficient spatial and temporal coverage, for both field surveys and remote sensing methods. To track short-term variations of chlorophyll fluorescence and chlorophyll-a concentrations in Poyang Lake, the largest freshwater lake in China, high-frequency, in-situ, measurements were collected from two fixed stations. The K-mean clustering method was also applied to identify clusters with similar spatio-temporal variations, using remote sensing Chl-a data products from the MERIS satellite, taken from 2003 to 2012. Four lake area classes were obtained with distinct spatio-temporal patterns, two of which were selected for in situ measurement. Distinct daily periodic variations were observed, with peaks at approximately 3:00 PM and troughs at night or early morning. Short-term variations of chlorophyll fluorescence and Chl-a levels were revealed, with a maximum intra-diurnal ratio of 5.1 and inter-diurnal ratio of 7.4, respectively. Using geostatistical analysis, the temporal range of chlorophyll fluorescence and corresponding Chl-a variations was determined to be 9.6 h, which indicates that there is a temporal discrepancy between Chl-a variations and the sampling frequency of current satellite missions. An analysis of the optimal sampling strategies demonstrated that the influence of the sampling time on the mean Chl-a concentrations observed was higher than 25%, and the uncertainty of any single Terra/MODIS or Aqua/MODIS observation was approximately 15%. Therefore, sampling twice a day is essential to resolve Chl-a variations with a bias level of 10% or less. The results highlight short-term variations of critical water quality parameters in freshwater, and they help identify specific design requirements for geostationary earth observation missions, so that they can better address the challenges of monitoring complex coastal and inland environments around the world.

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Are non-loricate ciliates a primary contributor to ecological pattern of planktonic ciliate communities? A case study in Jiaozhou Bay, northern China

Journal of the Marine Biological Association of the United Kingdom ◽

10.1017/s0025315412000276 ◽

2012 ◽

Vol 92 (6) ◽

pp. 1301-1308 ◽

Cited By ~ 21

Author(s):

Yong Jiang ◽

Wei Zhang ◽

Mingzhuang Zhu ◽

Khaled A. S. Al-Rasheid ◽

Henglong Xu

Keyword(s):

Jiaozhou Bay ◽

Northern China ◽

Temporal Variations ◽

Species Number ◽

Protozoan Community ◽

Planktonic Ciliate ◽

Spatio Temporal ◽

Soluble Reactive Phosphorous ◽

Ecological Pattern

The contribution of non-loricate ciliate assemblage to the ecological pattern of a ciliated protozoan community was studied based on a 1-year (June 2007–May 2008) dataset collected from Jiaozhou Bay, northern China. Samples were collected biweekly from five sampling sites. Results showed that: (1) the non-loricate ciliate assemblages were the primary components and significantly correlated with the total ciliate communities in terms of species number, abundance and biomass; (2) the ecological pattern of non-loricate ciliate assemblages was significantly related to that of both total ciliate communities and variations in environmental variables; and (3) spatio-temporal variations in biodiversity (richness, diversity and evenness of species) indices of non-loricate ciliate assemblages were significantly correlated with those of total ciliate communities and the environmental conditions, especially nutrients nitrate nitrogen, nitrite nitrogen and soluble reactive phosphorous. These results suggest that the non-loricate ciliates are a primary contributor to the ecological pattern of total ciliate communities and might be used as a potential bioindicator for bioassessment in marine ecosystems.

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Investigating of River-Aquifer Interactions using Sub-Surface Hydrological Model and Remote Sensing Inputs in an agriculturally Dominated Kosi River Basin, India.

10.5194/egusphere-egu21-14106 ◽

2021 ◽

Author(s):

Naga Venkata Satish Laveti ◽

Suresh A. Kartha ◽

Subashisa Dutta

Keyword(s):

Remote Sensing ◽

Groundwater Recharge ◽

River Basin ◽

Hydrological Model ◽

Temporal Variations ◽

Interaction Process ◽

Groundwater Levels ◽

Physically Based ◽

Spatio Temporal ◽

Exchange Flux

<p>River-Aquifer Interaction is a natural and complex phenomenon for understanding its physical dynamic processes. These interactions highly vary with time and space and are to be investigated at river reach scale. The present study aims to understand and quantify the spatio-temporal variations of river-aquifer interaction process in Kosi river basin, India. This basin is majorly dominated with agricultural lands and irrigation requirement of the crops are mostly met by groundwater. In order to quantify the river-aquifer exchange flux at reach scale, a physically based sub-surface hydrological model has been carried for the study area. For this purpose, high resolution remotely sensed evapotranspiration data and groundwater recharge (estimated using soil water budget method method) along with other aquifer parameters were utilized for simulating the monthly groundwater levels as well as exchange flux between river and aquifer. The model results showed that simulated groundwater levels were well calibrated and validated with measured groundwater levels. Further, this calibrated groundwater flow model has been used to quantify the river-aquifer exchange flux. Based on the obtained exchange flux values, three different interaction zones were identified from upstream (Kosi barrage) to downstream (confluence point with Ganga river) in the study reach. It is observed that the river mostly loses water to the aquifer (as influent) in Zone I (80km from upstream) and the river mostly gains water from the aquifer (as effluent) in Zone III (40 km above downstream to confluence point). Whereas, the river has a combination of both losing and gaining natures in Zone II (between Zone I and III). From this study, it can be concluded that use of satellite remote sensing inputs (groundwater recharge and evapotranspiration) in the sub-surface hydrological model, facilitated to improve the assessment and understanding river-aquifer interaction process in an alluvial River basin.</p>

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Grassland aboveground biomass retrieval from remote sensing data by using artificial neural network in temperate grassland, northern China

2014 The Third International Conference on Agro-Geoinformatics ◽

10.1109/agro-geoinformatics.2014.6910628 ◽

2014 ◽

Author(s):

Y. X. Jin ◽

B. Xu ◽

X. C. Yang ◽

Z. H. Qin ◽

J. Y. Li ◽

...

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Artificial Neural Network ◽

Aboveground Biomass ◽

Remote Sensing Data ◽

Northern China ◽

Temperate Grassland ◽

Sensing Data ◽

Artificial Neural

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Water table fluctuation and its effects on vegetation in a semiarid environment

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-8-3271-2011 ◽

2011 ◽

Vol 8 (2) ◽

pp. 3271-3304 ◽

Cited By ~ 5

Author(s):

L. Duan ◽

T. Liu ◽

X. Wang ◽

Y. Luo ◽

W. Wang ◽

...

Keyword(s):

Water Table ◽

Vegetation Index ◽

Potential Evapotranspiration ◽

Meteorological Data ◽

Depth Map ◽

Northern China ◽

Temporal Variations ◽

Water Table Fluctuation ◽

Semiarid Environment ◽

Spatio Temporal

Abstract. A good understanding of water table fluctuation effects on vegetation is crucial for sustaining fragile hydrology and ecology of semiarid areas such as the Horqin Sandy Land (HSL) in northern China, but such understanding is not well documented in literature. The objectives of this study were to examine spatio-temporal variations of water table and their effects on vegetation in a semiarid environment. A 9.71 km2 area within the HSL was chosen and well-instrumented to continuously measure hydrometeorologic parameters (e.g., water table). The area comprises of meadow lands and sandy dunes as well as transitional zones in between. In addition to those measured data, this study also used Landsat TM and MODIS imageries and meteorological data at a station near the study area. The spatio-temporal variations were examined using visual plots and contour maps, while the effects on vegetation were determined by overlaying a water table depth map with a vegetation index map derived from the MODIS imageries. The results indicated that water table was mainly dependent on local topography, localized geological settings, and human activities (e.g., reclamation). At annual and monthly scales, water table was mainly a function of precipitation and potential evapotranspiration. A region within the study area where depth to water table was smaller tended to have better (i.e., more dense and productive) vegetation cover. Further, the results revealed that water table fluctuation was more sensitive for vegetations in the meadow lands than in the transitional zones, but it was least sensitive for vegetations in the sandy dunes.

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Review of Conceptual Models of Estimating the Spatio-Temporal Variations of Water Depth Using Remote Sensing and GIS for the Management of Dams and Reservoirs

Geospatial Modeling for Environmental Management ◽

10.1201/9781003147107-6 ◽

2022 ◽

pp. 83-109

Author(s):

Abdulkadir Isah Funtua

Keyword(s):

Remote Sensing ◽

Water Depth ◽

Conceptual Models ◽

Temporal Variations ◽

Remote Sensing And Gis ◽

Spatio Temporal

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Hydrologic processes of groundwater in a small monsoon-influenced mountainous watershed

Hydrology Research ◽

10.2166/nh.2018.030 ◽

2018 ◽

Vol 49 (6) ◽

pp. 2016-2029 ◽

Cited By ~ 3

Author(s):

Ruiqiang Yuan ◽

Shiqin Wang ◽

Lihu Yang ◽

Jianrong Liu ◽

Peng Wang ◽

...

Keyword(s):

Water Table ◽

Northern China ◽

Temporal Variations ◽

Hydrologic Processes ◽

Mountain Valley ◽

Mountain Watersheds ◽

Mountainous Watershed ◽

The Mean ◽

Spatio Temporal ◽

In The Beginning

Abstract Mountain block recharge is the least well quantified owing to the lack of a thorough understanding of mountain block hydrological processes. Observations of spatio-temporal variations of groundwater were employed to clarify hydrologic processes in a semi-arid mountainous watershed of northern China. Results showed that the annual feeding rate of precipitation changed between 21% and 40%. However, infiltration of precipitation was mainly drained as interflow on slopes and recharged into the mountain valley as focused recharge. As a result, the mean correlation coefficient between precipitation and groundwater level was only 0.20 and seasonal variations were reduced. Mountain slope is essentially impermeable with no bedrock percolation under arid circumstances. Only a bedrock percolation event occurred after multiple closely-spaced heavy rains during the four-year observation, which induced a local rapid ascending of the water table and an enhanced lateral recharge from upgradient watersheds. The influence of the enhanced lateral recharge lasted three years, suggesting a huge groundwater catchment overcoming local watershed divides in mountain blocks. The average of the gradual recession of the water table was 5.1 mm/d with a maximum of 11.4 mm/d in the beginning stage. Both interflow and bedrock percolation are important. Our results highlight the changeability of hydrologic processes in mountain watersheds.

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Identifying the spatio-temporal variations of Ulva prolifera disasters in all life cycle

Journal of Water and Climate Change ◽

10.2166/wcc.2021.424 ◽

2021 ◽

Author(s):

Baowei Zhang ◽

Jianzhong Guo ◽

Ziwei Li ◽

Yi Cheng ◽

Yao Zhao ◽

...

Keyword(s):

Remote Sensing ◽

Life Cycle ◽

Yellow Sea ◽

Remote Sensing Data ◽

Temporal Variations ◽

Ulva Prolifera ◽

The Yellow Sea ◽

Sensing Data ◽

Spatio Temporal ◽

Sea Area

Abstract Since 2007, Ulva prolifera disasters have occurred every year in the South Yellow Sea of China, the largest green tide disaster in the world. The inter-annual differences make such disasters monitoring and early warning difficult. This study used remote sensing data (2015–2019) to determine its spatio-temporal variations in all life cycle. The results showed a lay effect between the NDVI-mean and the coverage area of U. prolifera. The spatio-temporal distribution of U. prolifera showed stages and regional differences. From late April to early May, U. prolifera first emerged near the Subei Shoal. After development in the middle of the Yellow Sea, U. prolifera outbroke in the eastern sea area of Shandong and Jiangsu, declined in the Shandong sea area, and disappeared near Qingdao. The cycle lasted for approximately 90 days. The sea surface temperature was the necessary condition for the disaster, and the sea wind field was the main driving force for its horizontal drift. This study overcomes the poor timing and continuity of remote sensing data in the monitoring of U. prolifera. It provides a theoretical reference for forecasting the outbreak period of U. prolifera and can aid policy-makers to avert such disasters in advance.

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