The effect of projected 21st Century climate change on hydrological variables in Old Woman Creek estuary was evaluated using 20 Coupled Model Intercomparison Project Phase 5 (CMIP5) precipitation and temperature projections as input to the Soil and Water Assessment Tool (SWAT). Model calibration and validation was done using the Multi-Objective Evolutionary Algorithm and Pareto Optimization. PRISM climate data for the period 1985 -2014 compared with the average of the 20 CMIP5 models show good agreement in both precipitation and temperature with CMIP5 exhibiting low variability across models. Flow, sediment, and organic nitrogen analyzed from simulations run with PRISM show good correlation with the average of 20 CMIP5 simulations. The performance of each of the 20 CMIP5 inputs to the SWAT model was tested using Euclidean distance relative to their average. The three best CMIP5 models (GFDL-ESM2M, MPI-ESM-MR, EC-EARTH) were used for seasonal analysis. The analysis was done in one past and three future climate windows (1985 -2014, 2018 -2045, 2046 -2075 and 2076 -2100). For the historical period, the result shows an over-estimation of flow, sediment and organic nitrogen from January to March in the SWAT model runs with CMIP5 inputs, relative to runs with the PRISM input. Peak flow, sediment and organic nitrogen were observed changing from winter to spring across the time periods. The expected seasonal and annual changes in each variable over the 21st century have implications for algae growth and general health of the Old Woman Creek estuary.
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Landuse/Landcover (LULC) change modeling of Old Woman Creek (OWC)Watershed using Remote Sensing and GIS03/21/2019
This study employs Markov chain model and Cellular Automation analysis to analyze the land use/land cover change of Old Woman Creek watershed in Ohio from 1992 to 2018 and to predict same for 2022 and 2026. Supervised classification was carried out on preprocessed 1992, 2003, 2013 and 2018 Landsat images to produce four main LULC categories namely; Agriculture, Urban, Forest/wetland and Water. Different GIS layers needed as input for Markov chain were produced with the same scale and spatial resolution. Data analysis showed that road is a major driver of urbanization in OWC watershed with farthest distances from road being about 1470m. Change detection analysis was conducted between 2 different time period namely 1992-2003 and 2003- 2013 to study the rate and pattern of urban growth. Urban growth rate was found to be less than 1% of the watershed per annum in both time period. Transition probability matrix was generated to show the rate of conversion of one LULC class to another after a period. Initial simulation was validated with 2103 and 2018 LULC map with the accuracy ranging from 95% to 99% for all the LULC classes. LULC will be simulated for 2022 and 2026 and the projected area and percentage change in each of the LULC classes will be discussed with emphasis to loss and growth. This study provides a good strategy for LULC monitoring for management practices and assesses the efficacy of the modeling method.