Integration of GIS and Geomorphic Data to Assess the Impact of Landscape Features on River Water Quality DOI Open Access
Damanjeet Aulakh, Shashikant Patil,

M Santhosh Kumar

и другие.

Natural and Engineering Sciences, Год журнала: 2025, Номер 10(1), С. 290 - 300

Опубликована: Апрель 1, 2025

Assessing the impact of landscape features on river water quality is essential for effective organization. Geographic Information Systems (GIS) serve as valuable tools integrating spatial data, while geomorphic characteristics offer critical insights into hydrological processes that quality. Traditional research has typically lacked a full grasp direct certain land cover in rivers, sometimes overlooking complicated connections between geomorphological elements and characteristics. As result, this intends to combine GIS data assess Water samples were obtained from numerous locations, with characteristics, such pH, dissolved oxygen (DO), turbidity, temperature, perform thorough assessment Geomorphic factors slope, elevation, pattern also included spatially examine their connection indicators. The used comparison indicators Low Relief Areas (LGRA) High (HGRA) investigate changing correlations across areas. findings show varies significantly LGRA HGRA, elevation pattern, having considerable influence This technique illustrates efficiency combining managing protecting ecosystems.

Язык: Английский

Mechanisms and thresholds of land use affecting surface water quality in Hangzhou City’s residential areas DOI Creative Commons

Qianhu Chen,

Jing Huang

Ecological Indicators, Год журнала: 2025, Номер 170, С. 113097 - 113097

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

1
Multiscale impacts of landscape metrics on water quality based on fine-grained land use maps DOI Creative Commons

Yanan Zhou,

Jing He, Feng Li

и другие.

Frontiers in Environmental Science, Год журнала: 2025, Номер 13

Опубликована: Фев. 20, 2025

Quantifying the impact of landscape metrics on water quality can offer scientific supports for conservation and land use planning. However, previous studies mainly relied coarse maps, were lack understanding effects from physiographic metrics. Here, based in-situ monitoring data in Fujiang river basin, we used redundancy analysis, variation partitioning Shapley Additive exPlanations methods to assess quality. We these analyses dry wet season, circular buffer zone, riparian at sub-basin scale, are able analyze understand complex interactions between features quality, as well spatial temporal scale effects. The results indicated that be ranked following order: composition (15.8%–32.2%) > configuration (1.2%–19.5%)> (−2.0%-0.6%). Forests grasslands improved whereas farmland impervious surfaces degraded At a finer types, closed broadleaf evergreen forests while rainfed cropland had opposite effect. 1500 m was key with highest rate interpretation. relationship marginally stronger during season than season. Water by large relief amplitude slope standard deviation. is not significantly affected network density, length river, or basin area. These conclusions could provide science-informed information support study

Язык: Английский

Процитировано

0
Water Pollution in the Haihe River Basin, China: Spatial and Temporal Variations, Sources Apportionment and Sustainable Control Strategies DOI
Lian Feng, LI Jin-zhong, Jianling Li

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Integration of GIS and Geomorphic Data to Assess the Impact of Landscape Features on River Water Quality DOI Open Access
Damanjeet Aulakh, Shashikant Patil,

M Santhosh Kumar

и другие.

Natural and Engineering Sciences, Год журнала: 2025, Номер 10(1), С. 290 - 300

Опубликована: Апрель 1, 2025

Assessing the impact of landscape features on river water quality is essential for effective organization. Geographic Information Systems (GIS) serve as valuable tools integrating spatial data, while geomorphic characteristics offer critical insights into hydrological processes that quality. Traditional research has typically lacked a full grasp direct certain land cover in rivers, sometimes overlooking complicated connections between geomorphological elements and characteristics. As result, this intends to combine GIS data assess Water samples were obtained from numerous locations, with characteristics, such pH, dissolved oxygen (DO), turbidity, temperature, perform thorough assessment Geomorphic factors slope, elevation, pattern also included spatially examine their connection indicators. The used comparison indicators Low Relief Areas (LGRA) High (HGRA) investigate changing correlations across areas. findings show varies significantly LGRA HGRA, elevation pattern, having considerable influence This technique illustrates efficiency combining managing protecting ecosystems.

Язык: Английский

Процитировано

0