Abstract
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.
Highlights
Water yield (WYLD) is of great importance as it supplies water resources to human beings and natural resources [1]
We found that there was a positive correlation between water yield (WYLD) and nutrient yield, which demonstrated that WYLD is relatively more likely to lead to nutrient loss
Our results showed that forestland was the dominant land used in the Hun-Taizi River watershed, which was mainly distributed in the mountain hills, and it was negatively correlated with WYLD and Total nitrogen (TN) and total phosphorus (TP) yields
Summary
Water yield (WYLD) is of great importance as it supplies water resources to human beings and natural resources [1]. Under the background of rapid urbanization and economic development, water shortages and water degradation have become increasingly severe in many watersheds in. Point source (PS) pollution and nonpoint source (NPS) pollution have been identified as key triggers of deteriorating water quality [4]. PS pollution has been fairly controlled, while water quality has not significantly improved, largely due to NPS pollution with a wide range of pollution sources and complex uncertainties [5,6]. Total nitrogen (TN) and total phosphorus (TP) are the major pollutants resulting from agricultural and urban NPS and have become a major contributor to water-related problems, such as river contamination, aquatic ecosystem deterioration, and severe eutrophication [7]. Field monitoring and model prediction are the two main methods used to calculate NPS. Field monitoring is expensive, time-consuming, and regionally characterized, limiting the development of the method. With the development of geographic information systems (GIS), remote sensing (RS), and computer technology, many hydrological models have been developed
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Environmental Research and Public Health
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
