Nutrient and Sediment Production, Watershed Characteristics, and Land Use in the Tahoe Basin, California‐Nevada¹

Abstract

In efforts to control the degradation of water quality in Lake Tahoe, public agencies have monitored surface water discharge and concentrations of nitrogen, phosphorus, and suspended sediment in two separate sampling programs. The first program focuses on 20 watersheds varying in size from 162 to 14,000 ha, with continuous stream gaging and periodic sampling; the second focuses on small urbanized catchments, with automated sampling during runoff events. Using data from both programs, we addressed the questions (1) what are the fluxes and concentrations of nitrogen and phosphorus entering the lake from surface runoff; (2) how do the fluxes and concentrations vary in space and time; and (3) how are they related to land use and watershed characteristics? To answer these questions, we calculated discharge‐weighted average concentrations and annual fluxes and used multiple regression to relate those variable to a suite of GIS‐derived explanatory variables. The final selected regression models explain 47‐62% of the variance in constituent concentrations in the stormwater monitoring catchments, and 45‐72% of the variance in mean annual yields in the larger watersheds. The results emphasize the importance of impervious surface and residential density as factors in water quality degradation, and well‐developed soil as a factor in water quality maintenance.

GIS-based spatial regression and prediction of water quality in river networks: A case study in Iowa

“…The watershed characteristics that have been examined include land use and land cover patterns, regional geology, soil characteristics, climate, topography, extent of impervious surface, population density, road density, urbanization pattern, etc. (Ritter, 1986;Battaglin and Goolsby, 1997;McFarland and Hauck, 1999;Arheimer and Liden, 2000;Liu et al, 2000;Ometo et al, 2000;Sliva and Williams, 2001;Smith et al, 2001;Donner, 2003;Meador and Goldstein, 2003;Santos-Roman et al, 2003;Turner and Rabalais, 2003;Carle et al, 2005;Xian et al, 2007;Zampella et al, 2007;Chang, 2008;Coats et al, 2008;Amiri and Nakane, 2009;Atkinson et al, 2009). Understandings of such empirical relationships can help assess conditions of unmonitored water bodies, identify human activities that significantly contribute to pollution as well as critical areas that are at risk, and promote management practices to reduce nonpoint source pollution (McFarland and Hauck, 1999;Gergel et al, 2002;Griffith et al, 2002;Baker, 2003).…”

Temporal and Spatial Trends in Nutrient and Sediment Loading to Lake Tahoe, California‐Nevada, USA

“…Both SRP and TP loads are associated with land development, but PP increases more rapidly than SRP with developed area and total discharge. This is consistent with biogeochemical buffering of SRP concentration (Coats et al ., ).…”

“…In a study of stormwater runoff pollutant concentrations in small developed catchments, Coats et al . () found that the percent of area classed as impervious residential explained 49% of the ln(SRP) discharge‐weighted mean concentration. In the LTIMP dataset, three watersheds have percent developed areas greater than 10%.…”

“…We then screened a suite of LULC explanatory variables using step-wise multiple regression. The LULC variables screened were developed for each of 19 subwatersheds from GIS datasets for the Tahoe Basin (Cartier et al, 1994), and are defined in Coats et al (2008). To reduce collinearity among explanatory variables, the final candidate models were chosen to include only explanatory variables with correlation coefficients (r) < 0.25.…”

Land Use, Microclimate, and Surface Runoff Linkages: Space-Time Modeling From Rokel-Seli River Basin, Sierra Leone

“…Changes in land use and land cover (LULC) can alter biotic diversity, primary productivity, surface runoff, water quality, and a host of other attributes associated with terrestrial and aquatic ecosystems (Coats et al, 2008;Wilson and Weng, 2010). LULC change has a significant spatiotemporal relationship with water supply and quality (Somura et al, 2012;Penha et al, 2016).…”