Coupling Land Use Change Modeling with Climate Projections to Estimate Seasonal Variability in Runoff from an Urbanizing Catchment Near Cincinnati, Ohio

Abstract

This research examines the impact of climate and land use change on watershed hydrology. Seasonal variability in mean streamflow discharge, 100-year flood, and 7Q10 low-flow of the East Fork Little Miami River watershed, Ohio was analyzed using simulated land cover change and climate projections for 2030. Future urban growth in the Greater Cincinnati area, Ohio, by the year 2030 was projected using cellular automata. Projected land cover was incorporated into a calibrated BASINS-HSPF model. Downscaled climate projections of seven GCMs based on the assumptions of two IPCC greenhouse gas emissions scenarios were integrated through the BASINS Climate Assessment Tool (CAT). The discrete CAT output was used to specify a seed for a Monte Carlo simulation and derive probability density functions of anticipated seasonal hydrologic responses to account for uncertainty. Sensitivity analysis was conducted for a small catchment in the watershed using the Storm Water Management Model (SWMM) developed U.S. Environmental Protection Agency. The results indicated higher probability of exceeding the 100-year flood over the fall and winter months, and a likelihood of decreasing summer low flows.

WOF-SWAT: A Web-Based Open-Source Framework for Investigating the Hydrological Impacts of Climate Change and Human Activities Through Online Simulation and Visualization of SWAT Models

“…Climate change, together with human activities such as deforestation, urban development, and unregulated sewage discharge, are further complicating the prediction of watershed-scale processes by placing additional uncertainty on future water resource conditions. In an attempt to answer the numerous important questions posed by the hydrological community, a large number hydrological models have been devised to simulate the hydrological cycle, investigate cause-effect relationships at various spatial and temporal scales, and help in decision-making to find solutions for better watershed protection and management [1][2][3][4]. However, it is considered that these models have not yet been applied to their full potential in terms of watershed management and policy-making [5,6].…”

Estimating the Effect of Urban Growth on Annual Runoff Volume Using GIS in the Erbil Sub-Basin of the Kurdistan Region of Iraq

“…Built-up areas lead to an increase in impervious surfaces which in turn reduces the runoff concentration time. Accordingly, higher peak discharge rates occur sooner after rainfall in the catchment area [12]. In addition-n, the runoff volume and potential flood risk greatly increases [8,13,14].…”

A Local Land Use Competition Cellular Automata Model and Its Application

“…Currently, there are many valuable land use change simulation and prediction models and related research work, which typically include the system dynamics model (SD) [6], Markov model [7], conversion of land use and its effects at small regional extent (CLUE-S) model, multi-agent systems (MAS) model [8,9], cellular automata (CA) model [10][11][12][13], and the integration of these models [14]. Many studies emphasize in particular a macro perspective of the driving factors to simulate land use changes.…”