effluents affect water quality immensely, particularly where the population density is
substantial.
Conversely, the strong correlation of water variables with agricultural lands in the
wet season cannot be overlooked. Runoff resulting from rainfall carries fertilizer
ingredients and eroded soil into waterways, which worsen the water quality in the
river. Still, the impact of residential areas, which are also strongly correlated with
most water parameters, should be counted since the input or effluent from residential
areas is relatively consistent regardless of the season albeit with different quantities
(Namugize Jean et al. 2018). Moreover, residential areas tend to increase inorganic
nitrogen concentrations in river water, which would also explain the high correlation
with nutrients especially NH 3 -N (Foley et al. 2005). Although Oliveira et al. (2016)
mentioned that in areas with distinctive rainy seasons (like Malaysia), non-point
pollution sources typically have a reduced impact on water characteristics due to the
drop in runoff rate in the dry and normal seasons. Thus, attentions to hydrological
and temporal data are necessary to illustrate precisely the effects of land uses on
water quality.
Moreover, Yu et al. (2013)) stated that converting natural lands and forests into
residential areas alters the soil surface conditions, and elevates the imperviousness
levels in the area and ultimately runoff with rainstorms (White and Greer 2006).
Thus, pollution and changes in water characteristics tend to increase in these areas.
Other researchers also observed that water quality deterioration is directly linked
with increasing residential areas, along with agricultural and cultivated lands (Zhao
et al. 2015; Wan et al. 2014; Du Plessis et al. 2014). Similarly, transforming forest
areas into cultivated lands might change and raise water and sediment connectivity,
consequently affecting water quality (Masselink et al. 2017). From the correlation
results, it is evident that most water quality variables are significantly related more to
agricultural lands than to forests. Thus, land use types had a significant influence not
merely on the correlation coefficients with water parameters but also on the extent of
effect that land use itself had on every water quality parameter (Yu et al. 2016). Still,
using Pearson correlation analysis to support the presumption that land uses are in
fact the main driver of water quality changes must be taken cautiously (Ferreira et al.
2017).
2.6 Landscape Metrics Relationship with Water Quality
Landscape configuration signifies the physical distribution or spatial makeup of
patches within a class or landscape (Mcgarigal et al. 2002). Landscape metrics
have been established to measure and quantify land use patterns and to better
comprehend the landscape configuration and spatial diverseness (Griffith 2002).
Understanding the influence of landscapes and human interference with land composition on water quality is required, in order to implement protection and rehabilitation practices on water bodies (Tudesque et al. 2014). It has been found that
landscape metrics might be important parameters in predicting water quality at
2 Landscape Perspective to River Pollution: A Case Study of Bentong River,. . .
31
substantial.
Conversely, the strong correlation of water variables with agricultural lands in the
wet season cannot be overlooked. Runoff resulting from rainfall carries fertilizer
ingredients and eroded soil into waterways, which worsen the water quality in the
river. Still, the impact of residential areas, which are also strongly correlated with
most water parameters, should be counted since the input or effluent from residential
areas is relatively consistent regardless of the season albeit with different quantities
(Namugize Jean et al. 2018). Moreover, residential areas tend to increase inorganic
nitrogen concentrations in river water, which would also explain the high correlation
with nutrients especially NH 3 -N (Foley et al. 2005). Although Oliveira et al. (2016)
mentioned that in areas with distinctive rainy seasons (like Malaysia), non-point
pollution sources typically have a reduced impact on water characteristics due to the
drop in runoff rate in the dry and normal seasons. Thus, attentions to hydrological
and temporal data are necessary to illustrate precisely the effects of land uses on
water quality.
Moreover, Yu et al. (2013)) stated that converting natural lands and forests into
residential areas alters the soil surface conditions, and elevates the imperviousness
levels in the area and ultimately runoff with rainstorms (White and Greer 2006).
Thus, pollution and changes in water characteristics tend to increase in these areas.
Other researchers also observed that water quality deterioration is directly linked
with increasing residential areas, along with agricultural and cultivated lands (Zhao
et al. 2015; Wan et al. 2014; Du Plessis et al. 2014). Similarly, transforming forest
areas into cultivated lands might change and raise water and sediment connectivity,
consequently affecting water quality (Masselink et al. 2017). From the correlation
results, it is evident that most water quality variables are significantly related more to
agricultural lands than to forests. Thus, land use types had a significant influence not
merely on the correlation coefficients with water parameters but also on the extent of
effect that land use itself had on every water quality parameter (Yu et al. 2016). Still,
using Pearson correlation analysis to support the presumption that land uses are in
fact the main driver of water quality changes must be taken cautiously (Ferreira et al.
2017).
2.6 Landscape Metrics Relationship with Water Quality
Landscape configuration signifies the physical distribution or spatial makeup of
patches within a class or landscape (Mcgarigal et al. 2002). Landscape metrics
have been established to measure and quantify land use patterns and to better
comprehend the landscape configuration and spatial diverseness (Griffith 2002).
Understanding the influence of landscapes and human interference with land composition on water quality is required, in order to implement protection and rehabilitation practices on water bodies (Tudesque et al. 2014). It has been found that
landscape metrics might be important parameters in predicting water quality at
2 Landscape Perspective to River Pollution: A Case Study of Bentong River,. . .
31