scholarly journals Effects of Landscape Pattern Change on Water Yield and Nonpoint Source Pollution in the Hun-Taizi River Watershed, China

2020 ◽  
Vol 17 (9) ◽  
pp. 3060 ◽  
Author(s):  
Min Zong ◽  
Yuanman Hu ◽  
Miao Liu ◽  
Chunlin Li ◽  
Cong Wang ◽  
...  
Keyword(s):  
Water Quality ◽  
Landscape Pattern ◽  
Water Area ◽  
Nonpoint Source ◽  
Landscape Patterns ◽  
Water Yield ◽  
River Watershed ◽  
Nps Pollution ◽  
Nutrient Yield ◽  
Taizi River

Understanding the influence of landscape pattern changes on water yield (WYLD) and nutrient yield is a key topic for water resource management and nonpoint source (NPS) pollution reduction. The annual WYLD and NPS pollution were estimated in 2004 and 2015 with the calibrated and validated Soil and Water Assessment Tool (SWAT) in the Hun-Taizi River watershed. The impact of land use and landscape pattern changes on the annual WYLD and NPS loading changes were analyzed with a boosted regression tree (BRT) and redundancy analysis (RDA). The results showed that WYLD had a positive correlation with dry farmland and built-up area; however, a negative correlation with paddy field and water area, with the relative contribution of 42.03%, 23.79%, 17.06%, and 13.55%, respectively. The change in nutrient yield was positively correlated with changes in dry farmland, built-up area, and water area but negatively with forestland, according to the BRT model. Landscape patterns had an important influence on WYLD and NPS pollution. A large unfragmented forestland may improve water quality, while a large concentrated dry farmland results in water quality deterioration due to NPS pollution. Water quality is more likely degraded when land uses are complex and scattered with many small patches in a forestland dominated watershed.

scholarly journals Review of Watershed-Scale Water Quality and Nonpoint Source Pollution Models

Geosciences ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 25 ◽  
Author(s):  
Lifeng Yuan ◽  
Tadesse Sinshaw ◽  
Kenneth J. Forshay
Keyword(s):  
Water Quality ◽  
Model Selection ◽  
Nonpoint Source Pollution ◽  
Assessment Tool ◽  
Nonpoint Source ◽  
Screening Tools ◽  
Simulation Program ◽  
Management Model ◽  
Watershed Scale ◽  
Nps Pollution

Watershed-scale nonpoint source (NPS) pollution models have become important tools to understand, evaluate, and predict the negative impacts of NPS pollution on water quality. Today, there are many NPS models available for users. However, different types of models possess different form and structure as well as complexity of computation. It is difficult for users to select an appropriate model for a specific application without a clear understanding of the limitations or strengths for each model or tool. This review evaluates 14 more commonly used watershed-scale NPS pollution models to explain how and when the application of these different models are appropriate for a given effort. The models that are assessed have a wide range of capacities that include simple models used as rapid screening tools (e.g., Long-Term Hydrologic Impact Assessment (L-THIA) and Nonpoint Source Pollution and Erosion Comparison Tool (N-SPECT/OpenNSPECT)), medium-complexity models that require detail data input and limited calibration (e.g., Generalized Watershed Loading Function (GWLF), Loading Simulation Program C (LSPC), Source Loading and Management Model (SLAMM), and Watershed Analysis Risk Management Frame (WARMF)), complex models that provide sophisticated simulation for NPS pollution processes with intensive data and rigorous calibration (e.g., Agricultural Nonpoint Source pollution model (AGNPS/AnnAGNPS), Soil and Water Assessment Tool (SWAT), Stormwater Management Model (SWMM), and Hydrologic Simulation Program Fortran (HSPF)), and modeling systems that integrate various sub-models and tools, and contain the highest complexity to solve all phases of hydrologic, hydraulic, and chemical dynamic processes (e.g., Automated Geospatial Watershed Assessment Tool (AGWA), Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) and Watershed Modeling System (WMS)). This assessment includes model intended use, components or capabilities, suitable land-use type, input parameter type, spatial and temporal scale, simulated pollutants, strengths and limitations, and software availability. Understanding the strengths and weaknesses of each watershed-scale NPS model will lead to better model selection for suitability and help to avoid misinterpretation or misapplication in practice. The article further explains the crucial criteria for model selection, including spatial and temporal considerations, calibration and validation, uncertainty analysis, and future research direction of NPS pollution models. The goal of this work is to provide accurate and concise insight for watershed managers and planners to select the best-suited model to reduce the harm of NPS pollution to watershed ecosystems.

scholarly journals Landscape Pattern Change of Impervious Surfaces and Its Driving Forces in Shanghai during 1965–2010

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1956
Author(s):  
Yang Yao ◽  
Sen Zhang ◽  
Yuqing Shi ◽  
Mengqi Xu ◽  
Jiaquan Zhang ◽  
...  
Keyword(s):  
Water Quality ◽  
Landscape Pattern ◽  
Driving Forces ◽  
Surface Water Quality ◽  
Water Area ◽  
Impervious Surfaces ◽  
Rapid Urbanization ◽  
The Past ◽  
Pattern Change ◽  
Quality Variation

Rapid urbanization influences the landscape pattern of impervious surfaces, and potentially affects surface water quality. Using ArcGIS and Fragstats, this study analyzed the temporal change of the landscape pattern of impervious surfaces in Shanghai over the past 45 years, and its driving forces and impact on water quality were also analyzed. The results show that both low and high impervious surfaces showed different degrees of expansion, and as a result, the pervious surfaces and water area reduced by 40.1% and 13.8%, respectively. It proves that the fragmentation and diversity of impervious surfaces in Shanghai notably increased in the past decades, and especially the low and high impervious surfaces show substantial changes. The primary driving forces of the landscape pattern change are population density, unit area Gross Domestic Product (GDP), and the percentage of primary industry. The result of Redundancy analysis (RDA) is that the explanatory ability of landscape pattern to water quality variations decreased from 68.7% to 46.4% in the period 2000–2010. It should be stressed that the contribution of the configuration of impervious surfaces to water quality variation is less than that of the percentage of impervious surfaces.

scholarly journals Present and potential future critical source areas of nonpoint source pollution: a case of the Nakdong River watershed, South Korea

2021 ◽  
Author(s):  
Mijin Seo ◽  
Joonghyeok Heo ◽  
Yongseok Kim
Keyword(s):  
Climate Change ◽  
Nonpoint Source ◽  
Nakdong River ◽  
Related Factors ◽  
Critical Source Areas ◽  
River Watershed ◽  
Source Areas ◽  
Nps Pollution ◽  
The Future ◽  
The Nakdong River

AbstractIdentifying critical source areas (CSAs) is the first step to effectively managing nonpoint source (NPS) pollution. Increasing variability in climate can affect identification of CSAs. In this study, we identified present and future CSAs of NPS pollution in the Nakdong River watershed and examined how climate change will influence the identification of CSAs. Nine NPS pollution-related factors affecting the watershed environment and water quality were considered. These factors were rescaled through a min-max normalization to propose an index system that ranks basins based on the sensitivity of basins to climate change on identifying CSAs. For analyses, past rainfall was replaced with future rainfall under two RCP scenarios, RCP 2.6 and RCP 8.5. Results showed insignificant differences in the spatial distribution of CSAs between the present and the future and between the future scenarios. Basins that are on or adjacent to the Nakdong River mainstream were mainly identified as CSAs, in addition to many basins of the Geumho and Nam rivers. Highly ranked CSAs including the level 1 CSAs, were mainly distributed in the mid- and downstream areas of the Nakdong River, indicating high need of NPS pollution management. This study can provide a foundation for the effective management of NPS pollution in the present and the future.

Policy tools for agricultural nonpoint source water pollution control in the U.S. and E.U.

2016 ◽  
Vol 27 (2) ◽  
pp. 106-123 ◽  
Author(s):  
Ann Drevno
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Pollution Control ◽  
Nonpoint Source ◽  
Content Type ◽  
Policy Tool ◽  
Nps Pollution ◽  
The Usa ◽  
Management Approaches ◽  
Agricultural Nonpoint Source

Purpose – In the USA and Europe, agricultural nonpoint source (NPS) pollution continues to be among the chief impediments to achieving water quality standards. While the implementation of technology-based water pollution control tools has resulted in evident point source pollution abatement, NPSs continue to threaten surface water and groundwater. The purpose of this paper is to draw from environmental policy literature to identify regulatory tools and management approaches that specifically target agricultural NPS pollution and the factors that drive or impede their implementation and enforcement. This paper utilizes the policy tool framework to help characterize the widespread policy problem, distinguishing its unique set of hurdles from other environmental problems. Design/methodology/approach – Discussion of agricultural NPS pollution management approaches is based on a thorough review of relevant environmental policy and environmental economic literature as well as case studies from the USA and Europe. Analysis is based on the policy tool framework. Findings – This study finds that controlling numerous diffuse sources of agricultural pollution requires an integrated approach that utilizes river basin management and a mix of policy instruments. Additionally, findings suggest that transitioning from voluntary mechanisms to more effective instruments based on measurable water quality performance relies predominantly on three factors: first, more robust quality monitoring data and models; second, local participation; and third, political will. Originality/value – This research provides important information for regional and national policymakers in areas where there is increasing pollution and regulatory mandates. Identifying conditions of effective water quality policy is applicable and will be of direct use to agencies charged with pollution control.

scholarly journals Monitoring the Landscape Pattern and Characteristics of Non-Point Source Pollution in a Mountainous River Basin

2021 ◽  
Vol 18 (21) ◽  
pp. 11032
Author(s):  
Yuepeng Liu ◽  
Chuanfeng Yang ◽  
Xinyang Yu ◽  
Mengwen Wang ◽  
Wei Qi
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Point Source ◽  
Pollution Index ◽  
Landscape Patterns ◽  
Nutrient Loads ◽  
Buffer Zones ◽  
Water Pollution Index ◽  
Nps Pollution ◽  
Elevation Model

This study aimed to assess the relationship between the landscape patterns and non-point source (NPS) pollution distribution in Qixia County, China. The sub-basin classification was conducted based on a digital elevation model and Landsat8 satellite images. Water samples were collected from each sub-basin, andtheir water quality during the wet and dry seasons was estimated. The correlation between the landscape indices and water pollution indicators was determined by Pearson analysis. The location-weighted landscape contrast index (LWLCI) was calculated based on the “source-sink” theory. Qixia was further divided into five sections based on the LWLCI score to illustrate the potential risk of NPS pollution. The results showed that the water quality in Qixia County was generally good. Cultivated land, orchards, construction areas, and unused land were positively correlated with the water pollution index and weredesignated as the “source” landscape categories, while forests, grasslands, and water bodies, which were negatively correlated with water pollution, were the “sink” landscapes; the LWCI was high in 36.94% of the study area. In these areas, measures such as increasing vegetation buffer zones are necessary to decrease the sediment and nutrient loads carried by precipitation.

scholarly journals Correlation between Spatial-Temporal Variation in Landscape Patterns and Surface Water Quality: A Case Study in the Yi River Watershed, China

2019 ◽  
Vol 9 (6) ◽  
pp. 1053
Author(s):  
Ziqi Bian ◽  
Lyuyi Liu ◽  
Shengyan Ding
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Sampling Site ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Ammonia Nitrogen ◽  
Landscape Composition ◽  
Landscape Patterns ◽  
Buffer Zones ◽  
River Watershed

The evidence for a correlation between landscape patterns and surface water quality is still weak. We chose the Yi River watershed in China as a study area. We selected and determined the chemical oxygen demand, ammonia nitrogen, total phosphorus, dissolved oxygen, and electric conductivity to represent the surface water quality. We analyzed the spatial distribution of the surface water quality. Buffer zones with five different radii were built around each sampling site to analyze landscape patterns on different scales. A correlation analysis was completed to examine the influencing rules and the response mechanisms between landscape patterns and surface water quality indicators. The results show that: (1) Different landscape composition types impact the surface water quality differently and increasing the area of forest land can effectively reduce non-point source pollution, (2) an increase in urban area may threaten the surface water quality, and (3) landscape compositional change has a greater influence on surface water quality compared to landscape configurational change. This study provides a scientific foundation for the spatial development of watersheds and outlines a strategy for improving the sustainability of surface water quality and the surrounding environment.

Sign in / Sign up

Export Citation Format

Share Document