The influence of land use patterns on water quality at multiple spatial scales in a river system

2013 ◽  
Vol 28 (20) ◽  
pp. 5259-5272 ◽  
Author(s):  
Guoqiang Wang ◽  
Yinglan A ◽  
Zongxue Xu ◽  
Shurong Zhang
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Spatial Scales ◽  
River System ◽  
Land Use Patterns ◽  
Use Patterns ◽  
Multiple Spatial Scales

The Control of Land-Use Patterns for Stormwater Management at Multiple Spatial Scales

2012 ◽  
Vol 51 (3) ◽  
pp. 555-570 ◽  
Author(s):  
Ge Zhang ◽  
Subhro Guhathakurta ◽  
Gang Dai ◽  
Lingying Wu ◽  
Lijiao Yan
Keyword(s):  
Land Use ◽  
Stormwater Management ◽  
Spatial Scales ◽  
Land Use Patterns ◽  
Use Patterns ◽  
Multiple Spatial Scales

A square grid model for assessing the effect of alternative land uses on water quality

1976 ◽  
Vol 3 (2) ◽  
pp. 209-218 ◽  
Author(s):  
Thomas W. Constable ◽  
Nicholas Kouwen ◽  
Shully I. Solomon
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Water Quantity ◽  
Preliminary Design ◽  
Land Use Patterns ◽  
Time Intervals ◽  
Square Grid ◽  
Use Patterns ◽  
Grid Technique ◽  
Artificial Ponds

A mathematical model has been developed which can aid in assessing the effect of the modification of land use patterns on the water quantity and water quality regime of a watershed. The basin under study is divided into a number of elements using a square grid technique. The hydrologic and water quality components are evaluated at each element in the basin at successive time intervals, and flows are routed through the elements by use of a streamflow network system. The model can be used to assist in evaluating the effects of alternative land use configurations in a watershed, such as urbanization, the removal or growth of forests, the construction of dams, etc., on water quantity and water quality. It can also be used in the preliminary design of an urbanized area to estimate the size of storm sewers, artificial ponds, etc.

scholarly journals The Impacts of Land Use Patterns on Water Quality in a Trans-Boundary River Basin in Northeast China Based on Eco-Functional Regionalization

2018 ◽  
Vol 15 (9) ◽  
pp. 1872 ◽  
Author(s):  
Peixuan Cheng ◽  
Fansheng Meng ◽  
Yeyao Wang ◽  
Lingsong Zhang ◽  
Qi Yang ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
River Basin ◽  
Natural Environment ◽  
Flow Region ◽  
High Flow ◽  
Land Use Patterns ◽  
Use Patterns ◽  
The Impact ◽  
Degraded Water Quality

The relationships between land use patterns and water quality in trans-boundary watersheds remain elusive due to the heterogeneous natural environment. We assess the impact of land use patterns on water quality at different eco-functional regions in the Songhua River basin during two hydrological seasons in 2016. The partial least square regression indicated that agricultural activities associated with most water quality pollutants in the region with a relative higher runoff depth and lower altitude. Intensive grazing had negative impacts on water quality in plain areas with low runoff depth. Forest was related negatively with degraded water quality in mountainous high flow region. Patch density and edge density had major impacts on water quality contaminants especially in mountainous high flow region; Contagion was related with non-point source pollutants in mountainous normal flow region; landscape shape index was an effective indicator for anions in some eco-regions in high flow season; Shannon’s diversity index contributed to degraded water quality in each eco-region, indicating the variation of landscape heterogeneity influenced water quality regardless of natural environment. The results provide a regional based approach of identifying the impact of land use patterns on water quality in order to improve water pollution control and land use management.

Preliminary identification of watershed management strategies for the Houjing river in Taiwan

2010 ◽  
Vol 62 (7) ◽  
pp. 1667-1675 ◽  
Author(s):  
C. E. Lin ◽  
C. M. Kao ◽  
C. J. Jou ◽  
Y. C. Lai ◽  
C. Y. Wu ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Point Source ◽  
Watershed Management ◽  
Carrying Capacity ◽  
Pollution Control ◽  
Point Source Pollution ◽  
Land Use Patterns ◽  
River Watershed ◽  
Use Patterns

The Houjing River watershed is one of the three major river watersheds in the Kaohsiung City, Taiwan. Based on the recent water quality analysis, the Houjing River is heavily polluted. Both point and non-point source (NPS) pollutants are the major causes of the poor water quality in the Houjing River. Investigation results demonstrate that the main point pollution sources included municipal, agricultural, and industrial wastewaters. In this study, land use identification in the Houjing River watershed was performed by integrating the skills of geographic information system (GIS) and global positioning system (GPS). Results show that the major land-use patterns in the upper catchment of the Houjing River watershed were farmlands, and land-use patterns in the mid to lower catchment were residential and industrial areas. An integrated watershed management model (IWMM) and Enhanced Stream Water Quality Model (QUAL2K) were applied for the hydrology and water quality modeling, watershed management, and carrying capacity calculation. Modeling results show that the calculated NH3-N carrying capacity of the Houjing River was only 31 kg/day. Thus, more than 10,518 kg/day of NH3-N needs to be reduced to meet the proposed water quality standard (0.3 mg/L). To improve the river water quality, the following remedial strategies have been developed to minimize the impacts of NPS and point source pollution on the river water quality: (1) application of BMPs [e.g. source (fertilizer) reduction, construction of grassy buffer zone, and land use management] for NPS pollution control; (2) application of river management scenarios (e.g. construction of the intercepting and sewer systems) for point source pollution control; (3) institutional control (enforcement of the industrial wastewater discharge standards), and (4) application of on-site wastewater treatment systems for the polishment of treated wastewater for water reuse.

Solution of export coefficients of nitrogen from different land-use patterns based on Bayesian analysis

2013 ◽  
Vol 68 (3) ◽  
pp. 632-640 ◽  
Author(s):  
Mei Liu ◽  
Jun Lu
Keyword(s):  
Land Use ◽  
Probability Distribution ◽  
River System ◽  
Quality Model ◽  
Land Use Patterns ◽  
Dry Land ◽  
K Value ◽  
Barren Land ◽  
Posterior Probability Distribution ◽  
Use Patterns

The export coefficient model has been applied worldwide to the estimation of non-point source (NPS) pollution. Determining the export coefficients (ECs) from each pollution source and different space–time progressions is problematic because of uncertainty in the ECs of nitrogen from different land-use patterns. Bayesian theory uses the prior probability distribution and likelihood data to generate a posterior probability distribution. The total nitrogen (TN) ECs and stream loss rates K (d−1) for five land-use patterns were estimated by combining published results with monthly data for ChangLe River system for 2004–08. After 104 iterations, the results had small Markov chain Monte Carlo errors and convergence was obtained. Average TN ECs for the entire watershed were 26.1 ± 8.8, 70.3 ± 9.4, 41.7 ± 6.9, 8.9 ± 1.6 and 6.2 ± 0.5 kg ha−1 yr−1 for paddy field, dry land, residential land, woodland and barren land with coefficients of variation (CVs) of 16.9, 6.31, 8.91, 13.3 and 27.9% among sub-catchments respectively. The average K value was 0.33 d−1 with a CV of 11.3%. Estimated ECs, K and the coupling water quality model were used to predict the years 2008 and 2009; the results validated the model. This Bayesian model can determine ECs using prior knowledge and monitored data, overcoming the problems of the regression model. The model facilitates explicit consideration of uncertainty in NPS management.

scholarly journals The Variation of Water Quality in Three Land Use Types in U Minh Ha National Park, Ca Mau Province, Vietnam Using Multivariate Statistical Approaches

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1501
Author(s):  
Van Du Le ◽  
Thanh Giao Nguyen ◽  
Hoang Dan Truong
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Rainy Season ◽  
National Park ◽  
Land Use Patterns ◽  
Multivariate Statistical ◽  
Organic Matters ◽  
Use Patterns ◽  
Land Use Types ◽  
Melaleuca Cajuputi

This study was conducted to assess the water quality affected by different land use patterns in U Minh Ha National Park, Ca Mau, Vietnam. This study determined the water quality characteristics in three land use types (Acacia hybrid, planted melaleuca cajuputi, and natural melaleuca cajuputi) at different plant ages on two acid sulfate soil layers in the rainy season (8/2018) and dry season (4/2019) using nine water quality parameters. Multivariate statistical analyses were applied to evaluate the correlation and spatial and temporal variations in the water quality. The study results showed that the water quality in S-ASS was more polluted than that in D-ASS, characterized by low pH; the EC, organic matters (BOD and COD), nutrients (N-NH4+ and N-NO3−), and metal ions (Al3+ and Fe3+) were high; and the EC, BOD, COD, Al3+, and N-NO3− were determined high in D-ASS. The NMC area was noted to have high concentrations of organic matters and nutrients, while the factors specific to acidic soil were found to be higher in the AH and PMC areas. The water quality in the rainy season tended to be more polluted than that in the dry season. The cluster analysis grouped the land use patterns on S-ASS and D-ASS in both seasons into four groups, with a clear similarity between the wet and dry seasons in the areas at various plant ages. The seasonal variations of the water quality of the three land use types were distinguished by the main parameters, including pH, EC, BOD, N-NO3−, and Al3+ (S-ASS) and EC, BOD, N-NO3−, N-NH4+, and Fe3+ (D-ASS). Therefore, there is a need for better water management measures in the rainy season and focus on the key parameters causing water quality variations in each area. The findings in this study provided important information for the future water quality monitoring for both agricultural production and conservation in the national park.

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