Attribution of river water-quality trends to agricultural land use and climate variability in New Zealand

Abstract. Relationships between land use and water quality are complex with interdependencies, feedbacks, and legacy effects. Most river water quality studies have assessed catchment land use as areal coverage, but here, we hypothesize and test whether land use intensity – the inputs (fertilizer, livestock) and activities (vegetation removal) of land use – is a better predictor of environmental impact. We use New Zealand (NZ) as a case study because it has had one of the highest rates of agricultural land intensification globally over recent decades. We interpreted water quality state and trends for the 26 years from 1989 to 2014 in the National Rivers Water Quality Network (NRWQN) – consisting of 77 sites on 35 mostly large river systems. To characterize land use intensity, we analyzed spatial and temporal changes in livestock density and land disturbance (i.e., bare soil resulting from vegetation loss by either grazing or forest harvesting) at the catchment scale, as well as fertilizer inputs at the national scale. Using simple multivariate statistical analyses across the 77 catchments, we found that median visual water clarity was best predicted inversely by areal coverage of intensively managed pastures. The primary predictor for all four nutrient variables (TN, NOx, TP, DRP), however, was cattle density, with plantation forest coverage as the secondary predictor variable. While land disturbance was not itself a strong predictor of water quality, it did help explain outliers of land use–water quality relationships. From 1990 to 2014, visual clarity significantly improved in 35 out of 77 (34∕77) catchments, which we attribute mainly to increased dairy cattle exclusion from rivers (despite dairy expansion) and the considerable decrease in sheep numbers across the NZ landscape, from 58 million sheep in 1990 to 31 million in 2012. Nutrient concentrations increased in many of NZ's rivers with dissolved oxidized nitrogen significantly increasing in 27∕77 catchments, which we largely attribute to increased cattle density and legacy nutrients that have built up on intensively managed grasslands and plantation forests since the 1950s and are slowly leaking to the rivers. Despite recent improvements in water quality for some NZ rivers, these legacy nutrients and continued agricultural intensification are expected to pose broad-scale environmental problems for decades to come.

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Supplementary material to "River water quality changes in New Zealand over 26 years (1989–2014): Response to land use and land disturbance"

10.5194/hess-2016-323-supplement ◽

2016 ◽

Author(s):

Jason P. Julian ◽

Kirsten M. de Beurs ◽

Braden Owsley ◽

Robert J. Davies-Colley ◽

Anne-Gaelle E. Ausseil

Keyword(s):

Water Quality ◽

Land Use ◽

New Zealand ◽

River Water ◽

River Water Quality ◽

Quality Changes ◽

Land Disturbance ◽

Supplementary Material

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Agricultural land use management responses to a cap and trade regime for water quality in Lake Taupo catchment, New Zealand

Land Use Policy ◽

10.1016/j.landusepol.2020.105200 ◽

2021 ◽

Vol 102 ◽

pp. 105200

Author(s):

E. Anne Spicer ◽

Simon Swaffield ◽

Kevin Moore

Keyword(s):

Water Quality ◽

Land Use ◽

New Zealand ◽

Agricultural Land ◽

Agricultural Land Use ◽

Land Use Management ◽

Cap And Trade ◽

Trade Regime

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River water quality changes in New Zealand over 26 years (1989–2014): Response to land use and land disturbance

10.5194/hess-2016-323 ◽

2016 ◽

Cited By ~ 1

Author(s):

Jason P. Julian ◽

Kirsten M. de Beurs ◽

Braden Owsley ◽

Robert J. Davies-Colley ◽

Anne-Gaelle E. Ausseil

Keyword(s):

Water Quality ◽

Land Use ◽

New Zealand ◽

River Water ◽

River Water Quality ◽

Point Sources ◽

Diffuse Pollution ◽

Sediment Runoff ◽

Nutrient Mobilization ◽

Land Disturbance

Abstract. River water quality reflects land use in the catchment (mobilizing diffuse pollution) as well as point source discharges. In New Zealand (NZ) diffuse pollution vastly outweighs point sources which have largely cleaned up over many decades. Because NZ has good geospatial data on physiographic variables, land cover and agricultural statistics, and time series on water quality at the national scale over several decades, the country is a natural laboratory for investigating water quality response to land use/disturbance and associated diffuse pollution "pressures". We interpreted water quality state and trends for the 26 years from 1989 and 2014 in the National Rivers Water Quality Network (NRWQN), consisting of 77 sites on 35 mostly large river systems with an aggregate catchment amounting to half of NZ's land area. To characterize water quality pressures, we used multiple land use datasets spanning 1990–2012, plus recently-developed 8-day land-disturbance datasets using MODIS imagery. Current state and directions of change in visual clarity and nitrate-nitrite-nitrogen provide a particularly valuable summary of impact, respectively from mobilization of fine particulate matter and soluble nutrients. We show that the greatest impact on river water quality in NZ over the 1989–2014 period is high-producing pastures with their high nutrient inputs to support high densities of livestock. While land disturbance was not itself a strong predictor of water quality, it did help explain outliers of land use-water quality relationships, especially those with large areas of plantation forest. Plantation forestry was strongly associated with water quality impacts, particularly on visual clarity and particulate nutrients when land disturbed for harvesting generated sediment runoff and nutrient mobilization. In all, our study demonstrates how interdisciplinary combinations of expertise including geospatial analysis, land management, remote-sensing, and water quality can advance understanding of broad-scale and long-term impacts of land use change on river water quality.

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Relationship between land use and water quality in a small watershed in South Korea

Water Science & Technology ◽

10.2166/wst.2010.498 ◽

2010 ◽

Vol 62 (11) ◽

pp. 2607-2615 ◽

Cited By ~ 10

Author(s):

J. Y. Lee ◽

J. S. Yang ◽

D. K. Kim ◽

M. Y. Han

Keyword(s):

Water Quality ◽

Land Use ◽

River Water ◽

Agricultural Land ◽

Principal Component ◽

Quality Parameters ◽

River Water Quality ◽

Water Quality Parameters ◽

Metallic Ions ◽

Residential Areas

Recent research and monitoring undertaken by various institutions have emphasized measurements of river-water quality. Based on the results, government agencies have set guidelines to improve river-water quality management. However, the relationship between water quality and land use/land cover (LULC) has not been examined closely in South Korea to date. This study investigated this relationship in the Imgok River watershed. For this study, the relationship between water quality parameters, e.g. metallic ions, biological oxygen demand and chemical oxygen demand (BOD and COD), NH3, NO3 and PO4 levels and land-use types (abandoned mine land, forest/grassland, agricultural, livestock and residential areas) was examined by correlation analysis with significant level (p < 0.05) and principal component analysis (PCA). Applying PCA to water quality parameters according to land-use coverage, the principal component impacting river water quality were found to be the pH, metallic ions, BOD, PO4, COD and total suspended solids (TSS) for abandoned mine land (AML) coverage; BOD, NO3 and PO4 for forest/grassland areas; TSS, NO3, and PO4 for agricultural land; BOD, COD, NH3 and NO3 for livestock coverage; and BOD, COD, NH3 and PO4 for residential areas. For the AML, the pH exhibited a significant negative correlation with other water quality parameters at the significant level (p < 0.05). Grassland showed significant positive correlations of BOD with values of 0.837 NO3 and 0.514 PO4. In agricultural land, TSS had a significant negative correlation with value of −0.772 PO4. For livestock coverage, BOD had significant positive correlations with values of 0.865 COD, 0.629 NH3, 0.709 NO3 and 0.472 TSS. In residential areas, COD was significantly positively correlated with values of 0.988 BOD and 0.856 PO4, and TSS was highly positively correlated with value of 0.810 NO3 but highly negatively correlated with value of −0.702 PO4. Based on the above, LULC is a significant factor to influence on river water quality and this relationship should be based on the management plan for river water quality control. Future work will be conducted to take more samples in the entire river and season, to run water quality model and to choose a new method for better analysis and more accurate relationship between land-use and water quality.

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