Mapping and analyzing change of impervious surface for two decades using multi-temporal Landsat imagery in Missouri

et al. 2017

Hydrol. Process.

Self Cite

Climatic changes have altered surface water regimes worldwide, and climate projections suggest that such alterations will continue. To inform management decisions, climate projections must be paired with hydrologic models to develop quantitative estimates of watershed scale water regime changes. Such modeling approaches often involve downscaling climate model outputs, which are generally presented at coarse spatial scales. In this study, Coupled Model Intercomparison Project Phase 5 climate model projections were analyzed to determine models representing severe and conservative climate scenarios for the study watershed. Based on temperature and precipitation projections, output from GFDL‐ESM2G (representative concentration pathway 2.6) and MIROC‐ESM (representative concentration pathway 8.5) were selected to represent conservative (ΔC) and severe (ΔS) change scenarios, respectively. Climate data were used as forcing for the soil and water assessment tool to analyze the potential effects of climate change on hydrologic processes in a mixed‐use watershed in central Missouri, USA. Results showed annual streamflow decreases ranging from −5.9% to −26.8% and evapotranspiration (ET) increases ranging from +7.2% to +19.4%. During the mid‐21st century, sizeable decreases to summer streamflow were observed under both scenarios, along with large increases of fall, spring, and summer ET under ΔS. During the late 21st century period, large decreases of summer streamflow under both scenarios, and large increases to spring (ΔS), fall (ΔS) and summer (ΔC) ET were observed. This study demonstrated the sensitivity of a Midwestern watershed to future climatic changes utilizing projections from Coupled Model Intercomparison Project Phase 5 models and presented an approach that used multiple climate model outputs to characterize potential watershed scale climate impacts.

Section: Methodsmentioning

confidence: 99%

Integrating downscaled CMIP5 data with a physically based hydrologic model to estimate potential climate change impacts on streamflow processes in a mixed-use watershed

Sunde

et al. 2017

Hydrol. Process.

Self Cite

“…These distinctions are important for understanding of the effects of land use on T w . Approximately 60% of the City of Columbia containing 27.74 km 2 of impervious surface (Zhou et al ) drains to Hinkson Creek. The population of Columbia, Missouri, was estimated to be 113 225 as per 2012 census results (USCB, ).…”

Section: Site Descriptionmentioning

confidence: 99%

Quantifying and modelling urban stream temperature: a central US watershed study

Zeiger

Anderson

et al. 2015

Hydrological Processes

Abstract:Hydrologic models that rely on site specific linear and non-linear regression water temperature (T w ) subroutines forced solely with observed air temperature (T a ) may not accurately estimate T w in mixed-use urbanizing watersheds where hydrogeological and land use complexity may confound common T w regime assumptions. A nested-scale experimental watershed study design was used to test T w model predictions in a representative mixed-use urbanizing watershed of the central USA. The linear regression T w model used in the Soil and Water Assessment Tool (SWAT), a non-linear regression T w model, and a processbased T w model that accounts for watershed hydrology were evaluated. The non-linear regression T w model tested at a daily time step performed significantly (P < 0.01) better than the linear T w model currently used in SWAT. Both regression T w models overestimated T w in lower temperature ranges (T w < 10.0°C) with percent bias (PBIAS) values ranging from À28.2% (non-linear T w model) to À66.1% (linear regression T w model) and underestimated T w in the higher temperature range (T w > 25.0°C) by 3.2%, and 7.2%, respectively. Conversely, the process-based T w model closely estimated T w in lower temperature ranges (PBIAS = 4.5%) and only slightly underestimated T w in the higher temperature range (PBIAS = 1.7%). Findings illustrate the benefit of integrating process-based T w models with hydrologic models to improve model transferability and T w predictive confidence in urban mixed-land use watersheds. The findings in this work are distinct geographically and in terms of mixed-land use complexity and are therefore of immediate value to land-use managers in similarly urbanizing watersheds globally.

“…Approximately 28 km 2 of impervious surfaces in HCW (e.g., roads, parking areas, sidewalks, etc.) [29] were located within the municipal boundary of the city of Columbia (population 116,000) [30] at the time of the study. HCW contains a drainage network of 1st to 3rd order streams.…”

Section: Study Site Descriptionmentioning

confidence: 99%

Advancing Understanding of the Surface Water Quality Regime of Contemporary Mixed-Land-Use Watersheds: An Application of the Experimental Watershed Method

Kellner

2017

Hydrology

A representative watershed was instrumented with five gauging sites (n = 5), partitioning the catchment into five nested-scale sub-watersheds. Four physiochemical variables were monitored: water temperature, pH, total dissolved solids (TDS), and dissolved oxygen (DO). Data were collected four days per week from October 2010-May 2014 at each gauging site. Statistical analyses indicated significant differences (p < 0.05) between nearly every monitoring site pairing for each physiochemical variable. The water temperature regime displayed a threshold/step-change condition, with an upshifted and more variable regime attributable to the impacts of urban land uses. TDS, pH, and DO displayed similar spatiotemporal trends, with increasing median concentrations from site #1 (agriculture) to #3 (mixed-use urban) and decreasing median concentrations from site #3 to #5 (suburban). Decreasing concentrations and increasing streamflow volume with stream distance, suggest the contribution of dilution processes to the physiochemical regime of the creek below urban site #3. DO concentrations exceeded water quality standards on an average of 31% of observation days. Results showed seasonal trends for each physiochemical parameter, with higher TDS, pH, and DO during the cold season (November-April) relative to the warm season (May-October). Multivariate modeling results emphasize the importance of the pH/DO relationship in these systems, and demonstrate the potential utility of a simple two factor model (water temperature and pH) in accurately predicting DO. Collectively, results highlight the interacting influences of natural (autotrophic photosynthesis, organic detritus loading) and anthropogenic (road salt application) factors on the physiochemical regime of mixed-land-use watersheds.