Non-point source pollution risks in a drinking water protection zone based on remote sensing data embedded within a nutrient budget model

Wang, Guo Qiang; Li, Jiawei; Sun, Wenchao; Xue, Baolin; Yinglan, A; Liu, Tingxi

doi:10.1016/j.watres.2019.03.070

Cited by 155 publications

(32 citation statements)

References 21 publications

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“…On the other hand, groundwater acts as the principal source of nitrogen and phosphorus on account of the agricultural soil leaching and filtration, as well as underground low oxygen environments [22,74]. Therefore, upwelling sites were positively correlated to NH 4 + , NO 3 − , and TN concentrations (Figure 3a).…”

Section: Effect Of Upwelling Dynamics On Macroinvertebrate Communitiesmentioning

confidence: 99%

Effect of Hyporheic Exchange on Macroinvertebrate Community in the Weihe River Basin, China

Lin

Song

Gualtieri

et al. 2020

Water

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The effect of hyporheic exchange on macroinvertebrates is a significant topic in ecohydraulics. A field study was conducted during May and June 2017 to investigate the impacts of magnitude and patterns of hyporheic exchange on the sediment macroinvertebrate community in the Weihe River basin. The results demonstrate that upwelling flows cause resuspension of riverbed sediment, increasing the proportion of swimmer groups (such as Baetidae) in the macroinvertebrate community. However, large resuspension of river bed sediment results in a reduced abundance of macroinvertebrates. By controlling the transport processes of dissolved oxygen (DO), dissolved organic carbon (DOC), nutrients, temperature, and different patterns of hyporheic exchange strongly influence the structure of macroinvertebrate communities. Downwelling is more likely to produce rich invertebrate communities than upwelling. The magnitude for the hyporheic flux of 150-200 mm/d was optimal for the macroinvertebrate community in the Weihe River Basin. Above or below this rate results in a decline in community abundance and diversity. We suggest that research is conducted to better understand the effects of hyporheic exchange across bedforms on macroinvertebrate communities. The study supports any activities to preserve the ecological functions and health of rivers dominated by fine-grained sediments.

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Section: Effect Of Upwelling Dynamics On Macroinvertebrate Communitiesmentioning

confidence: 99%

Effect of Hyporheic Exchange on Macroinvertebrate Community in the Weihe River Basin, China

Lin

Song

Gualtieri

et al. 2020

Water

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“…These findings were consistent with the results of numerous previous studies that showed agricultural and urban land uses make negative contributions to water quality in watersheds [57,58,59], while the proportion of vegetated areas is positively correlated with water quality [60,61,62,63], which suggests the absorption and fixation effects of grassland for water pollutants [64,65]. Regression analysis revealed that increasing urban land percentage was not conductive to the reduction of NH 3 -N and DO pollution, and the increased grassland percentage was beneficial to the control of COD Mn , BOD and COD pollution [66,67]. The relatively small R 2 indicated that the relationship between water quality and land use types at the scale of control units was complicated, and may need to induce the landscape metrics as well as other factors to carry out the further explanation [21].…”

Section: Discussionmentioning

confidence: 99%

Landscape Characteristics Affecting Spatial Patterns of Water Quality Variation in a Highly Disturbed Region

Wang

Zhu

et al. 2019

IJERPH

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Spatial patterns of water quality trends for 45 stations in control units of the Shandong Province, China during 2009–2017 were examined by a non-parametric seasonal Mann-Kendall’s test (SMK) for dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), permanganate index (CODMn), total phosphorus (TP) and ammonia nitrogen (NH3-N). The DO concentration showed significant upward trends at approximately half of the stations, while other parameters showed significant downward trends at more than 40% of stations. The stations with downward trends presented significant spatial autocorrelation, and were mainly concentrated in the northwest and southwest regions. The relationship between the landscape characteristics and water quality was explored using stepwise multiple regression models, which indicated the water quality was better explained using landscape pattern metrics compared to the percentage of land use types. Decreased mean patch area and connectedness of farmland will promote the control of BOD, COD and CODMn, whereas the increased landscape percentage of urban areas were not conducive to the water quality improvement, which suggested the sprawling of farmland and urban land was not beneficial to pollution control. Increasing the grassland area was conducive to the reduction of pollutants, while the effect of grassland fragmentation was reversed.

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“…The researchers developed the remote sensing monitoring of water quality from simple qualitative analysis into quantitative inversion, from an empirical model with spatial and temporal limitations to a widely applicable biological optical model, which continuously broadened the application prospects of remote sensing water quality monitoring [15,16]. In addition, with the emergence of various remote sensing data sources, especially hyperspectral and multispectral remote sensing data, and the deep understanding of the spectra of various water quality parameters, the parameters of remote sensing water quality monitoring continue to increase, and the inversion accuracy also constantly improves [17][18][19]. However, the past remote sensing monitoring was mainly based on satellite remote sensing, and its data source only had a spatial resolution of 10-30 m and a spectral resolution of 10-20 nm, so it isn't suitable for the mapping of inland small and medium inland water, especially the typical aquaculture area in Guangdong Province.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Inversion of Inland Aquaculture Water Quality Based on UAVs-WSN Spectral Analysis

et al. 2020

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The inland aquaculture environment is an artificial ecosystem, where the water quality is a key factor which is closely related to the economic benefits of inland aquaculture and the quality of aquatic products. Compared with marine aquaculture, inland aquaculture is normally smaller and susceptible to pollution, with poor self-purification capacity. Considering its low cost and large-scale monitoring ability, many researches have developed spectrum sensor on-board satellite platforms to allow remote monitoring of inland water surface. However, there remain many problems, such as low image resolution, poor flexible data acquisition, and anti-interference. Apart from that, the conventional forecasting model is of weak generalization ability and low accuracy. In our study, we combine unmanned aerial vehicles system (UAVs) with the wireless sensor network (WSN) to design a new ground water quality parameter and drone spectrum information acquisition approach, and to propose a novel dynamic network surgery-deep neural networks (DNS-DNNs) model based on multi-source feature fusion to forecast the distribution of dissolved oxygen (DO) and turbidity (TUB) in inland aquaculture areas. The result of using fused features, including characteristic spectrum, Gray-level co-occurrence matrix (GLCM) texture feature, and convolutional neural network (CNN) texture feature to build a model is that the characteristic spectrum+ CNN texture fusion features were the best input items for DNS-DNNs when forecasting DO, with the determination coefficient R 2 of the vertical set arriving at 0.8741, while the characteristic spectrum+ GLCM texture+ CNN texture fusion features were the best for TUB, with the R 2 reaching 0.8531. Compared with a variety of conventional models, our model had a better performance in the inversion of DO and TUB, and there was a strong correlation between predicted and real values: R 2 reached 0.8042 and 0.8346, whereas the root mean square error (RMSE) were only 0.1907 and 0.1794, separately. Our study provides a new insight about using remote sensing to rapidly monitor water quality in inland aquaculture regions.

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Non-point source pollution risks in a drinking water protection zone based on remote sensing data embedded within a nutrient budget model

Cited by 155 publications

References 21 publications

Effect of Hyporheic Exchange on Macroinvertebrate Community in the Weihe River Basin, China

Effect of Hyporheic Exchange on Macroinvertebrate Community in the Weihe River Basin, China

Landscape Characteristics Affecting Spatial Patterns of Water Quality Variation in a Highly Disturbed Region

Dynamic Inversion of Inland Aquaculture Water Quality Based on UAVs-WSN Spectral Analysis

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