Impact of land uses on water quality in Malaysia: a review

Camara, Moriken; Jamil, Nor Rohaizah; Abdullah, Ahmad Fikri

doi:10.1186/s13717-019-0164-x

Cited by 156 publications

(74 citation statements)

References 36 publications

(17 reference statements)

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“…Additionally, DO concentration decreases because of the discharge of organic matter in urban areas [92]. Urban runoff contains a large number of pollutants accumulating on impervious surfaces, such as parking lots, roads, and housing, thus influencing water quality [94][95][96]. However, in the current study, there were no significant relationships between urban areas and water quality parameters in our OLS models.…”

Section: Land Use Types and Water Qualitycontrasting

confidence: 64%

Spatially Varying and Scale-Dependent Relationships of Land Use Types with Stream Water Quality

Park

Lee

2020

IJERPH

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Understanding the complex relationships between land use and stream water quality is critical for water pollution control and watershed management. This study aimed to investigate the relationship between land use types and water quality indicators at multiple spatial scales, namely, the watershed and riparian scales, using the ordinary least squares (OLS) and geographically weighted regression (GWR) models. GWR extended traditional regression models, such as OLS to address the spatial variations among variables. Our results indicated that the water quality indicators were significantly affected by agricultural and forested areas at both scales. We found that extensive agricultural land use had negative effects on water quality indicators, whereas, forested areas had positive effects on these indicators. The results also indicated that the watershed scale is effective for management and regulation of watershed land use, as the predictive power of the models is much greater at the watershed scale. The maps of estimated local parameters and local R2 in GWR models showcased the spatially varying relationships and indicated that the effects of land use on water quality varied over space. The results of this study reinforced the importance of watershed management in the planning, restoration, and management of stream water quality. It is also suggested that planners and managers may need to adopt different strategies, considering watershed characteristics—such as topographic features and meteorological conditions—and the source of pollutants, in managing stream water quality.

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Section: Land Use Types and Water Qualitycontrasting

confidence: 64%

Spatially Varying and Scale-Dependent Relationships of Land Use Types with Stream Water Quality

Park

Lee

2020

IJERPH

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“…Table 5 shows high temperature in all MPs. One of the causes of the relatively high air temperature was because there was no forest land use in the research are, whereas forest is crucial to decrease physical (pH and air temperature) and chemical parameters concentration [7] [11].…”

Section: River Water Quality Of Cirarab River Segment Curug Districtmentioning

confidence: 99%

Impacts of Land Use and Land Use Change In River Basin to Water Quality of Cirarab River, Indonesia

Indriyani¹,

Hasibuan²,

Gozan³

2020

Proceedings of the Proceedings of the 1st International Conference on Environmental Science and Sustainable Development, ICESSD

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Land use and land cover (LULC) changes are two main factors contribute to the decreasing water quality. This research aims to assess the impacts of LULC changes on the river basin towards water quality of Cirarab River. This research applied GIS analysis with LULC data changes from 2013 to 2018. The potential pollution load originating from residential on the river basin was calculated and compared to the maximum pollutant load. Water samples were collected five times a day in three locations. The result showed residential and industrial areas increased respectively of 110.08ha and 388.37ha; while shrub/vacant land decreased by 407.15ha. Potential pollution load amounted to 2615.78 kgBOD/day and 3713.87 kgCOD/day. This study found almost all monitoring points of COD and BOD parameters exceeded the required quality standard. Water samples collected from river basin with shrubs/vacant land has relatively better water quality compared to those collected from residential and industrial areas.

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“…Four statistical indicators, the Nash-Sutcliffe Efficiency (NSE), relative bias, mean absolute error (MAE), and the relative root mean square error (RRMSE), were calculated We evaluated the predictive performance of our approach to estimate river discharge, SSC, and sediment discharge for the study sites in the Upper Mississippi River with the set of 621 Landsat images from 1984 to 2017. Four statistical indicators, the Nash-Sutcliffe Efficiency (NSE), relative bias, mean absolute error (MAE), and the relative root mean square error (RRMSE), were calculated following Equations (7)- (10):…”

Section: Sediment Discharge Estimation and Performance Evaluationmentioning

confidence: 99%

“…Anthropogenic activities have increasingly altered rivers' physical and chemical properties [3][4][5][6]. These activities include agricultural practices, industrial operations, and land use and land cover changes, which all tend to negatively impact surface water quality through excessive point-or nonpoint-source loadings of pollutants [3,[7][8][9][10][11]. A major driver of this problem is human-induced sedimentation, which affects the hydrologic regime and water quality of a river and its drainage basin [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Estimating River Sediment Discharge in the Upper Mississippi River Using Landsat Imagery

Flores

Stöckle

et al. 2020

Remote Sensing

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With the decline of operational river gauges monitoring sediments, a viable means of quantifying sediment transport is needed. In this study, we address this issue by applying relationships between hydraulic geometry of river channels, water discharge, water-leaving surface reflectance (SR), and suspended sediment concentration (SSC) to quantify sediment discharge with the aid of space-based observations. We examined 5490 Landsat scenes to estimate water discharge, SSC, and sediment discharge for the period from 1984 to 2017 at nine gauging sites along the Upper Mississippi River. We used recent advances in remote sensing of fluvial systems, such as automated river width extraction, Bayesian discharge inference with at-many-stations hydraulic geometry (AMHG), and SSC-SR regression models. With 621 Landsat scenes available from all the gauging sites, the results showed that the water discharge and SSC retrieval from Landsat imagery can yield reasonable sediment discharge estimates along the Upper Mississippi River. An overall relative bias of −25.4, mean absolute error (MAE) of 6.24 × 104 tonne/day, relative root mean square error (RRMSE) of 1.21, and Nash–Sutcliffe Efficiency (NSE) of 0.49 were obtained for the sediment discharge estimation. Based on these statistical metrics, we identified three of the nine gauging sites (St. Louis, MO; Chester, IL; and Thebes, IL), which were in the downstream portion of the river, to be the best locations for estimating water and sediment discharge using Landsat imagery.

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Impact of land uses on water quality in Malaysia: a review

Cited by 156 publications

References 36 publications

Spatially Varying and Scale-Dependent Relationships of Land Use Types with Stream Water Quality

Spatially Varying and Scale-Dependent Relationships of Land Use Types with Stream Water Quality

Impacts of Land Use and Land Use Change In River Basin to Water Quality of Cirarab River, Indonesia

Estimating River Sediment Discharge in the Upper Mississippi River Using Landsat Imagery

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