Impervious Surfaces Mapping Using High Resolution Satellite Imagery

In recent years, impervious surfaces have emerged not only as an indicator of the degree of urbanization, but also as an indicator of environmental quality. As impervious surface area increases, storm water runoff increases in velocity, quantity, temperature and pollution load. Any of these attributes can contribute to the degradation of natural hydrology and water quality. Various image processing techniques have been used to identify the impervious surfaces, however, most of the existing impervious surface mapping tools used moderate resolution imagery. In this project, the potential of standard image processing techniques to generate impervious surface data for change detection analysis using high-resolution satellite imagery was evaluated. The city of Oxford, MS was selected as the study site for this project. Standard image processing techniques, including Normalized Difference Vegetation Index (NDVI), Principal Component Analysis (PCA), a combination of NDVI and PCA, and image classification algorithms, were used to generate impervious surfaces from multispectral IKONOS and QuickBird imagery acquired in both leaf-on and leaf-off conditions. Accuracy assessments were performed, using truth data generated by manual classification, with Kappa statistics and Zonal statistics to select the most appropriate image processing techniques for impervious surface mapping. The performance of selected image processing techniques was enhanced by incorporating Soil Brightness Index (SBI) and Greenness Index (GI) derived from Tasseled Cap Transformed (TCT) IKONOS and QuickBird imagery. A time series of impervious surfaces for the time frame between 2001 and 2007 was made using the refined image processing techniques to analyze the changes in IS in Oxford. It was found that NDVI and the combined NDVI–PCA methods are the most suitable image processing techniques for mapping impervious surfaces in leaf-off and leaf-on conditions respectively, using high resolution multispectral imagery. It was also found that IS data generated by these techniques can be refined by removing the conflicting dry soil patches using SBI and GI obtained from TCT of the same imagery used for IS data generation. The change detection analysis of the IS time series shows that Oxford experienced the major changes in IS from the year 2001 to 2004 and 2006 to 2007

Rain Induced Runoff Simulation Using A 2D Numerical Model

Runoff plays an important role in the agricultural and urbanized environments. Surface runoff is determined primarily by the amount of precipitation and by infiltration characteristics related to soil type, soil moisture, antecedent rainfall, land cover type, impervious surfaces, and surface retention. In this study, CCHE2D, a numerical model for free surface flow hydrodynamics, is applied to study the rain induced runoff and channel flow mixed problems. The main goal of this study is to incorporate rainfall as an input into the existing free surface flow model, CCHE2D; to verify and validate the CCHE2D model’s runoff simulation capability using analytical solutions and experimental data so that the model is proven to be accurate and capable of simulating rainfall induced flow and runoff; and to simulate runoff process in complex watershed using high resolution data such as LiDAR topography to validate that the model can be applicable to problems with a variety of spatial scales and complexity. Infiltration and subsurface flow is not considered throughout the study. The model’s capability of simulating the rainfall generated runoff processes is tested using analytical solutions, experimental data and field data. Comparison of numerical solutions with both analytic solutions and observed overland flows resulting from unsteady rainfalls is satisfactory. To validate the applicability of the shallow water model CCHE2D, research has been conducted using very high resolution LiDAR data in a small real world agricultural watershed in northwestern Mississippi, USA, in the Mississippi River Alluvial Plain known as the Mississippi Delta. The fine resolution of the numerical simulations resolved detailed runoff patterns in watersheds. This capability can be used for soil erosion and agro-pollutant transport and flood impact studies

Simulation of Rainfall-runoff Process in Watersheds Using CCHE2D

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

Simulation of Surface Runoff and Channel Flows Using a 2D Numerical Model

Numerical simulation of surface runoff is used to understand and predict watershed sediment transport and water quality and improve management of agricultural watersheds. However, models currently available are either simplified or parameterized for efficiency. In this chapter, CCHE2D, a physically based hydrodynamic model for general free surface flow hydrodynamics, was applied to study watershed surface runoff and channel flows. Multiple analytical solutions and experimental data were used to verify and validate this finite element model systematically with good results. A numerical scheme for correcting the bilinear interpolation of the water surface elevation solutions from the cell centers to the computational nodes was developed to improve the model. The correction was found necessary and effective for the sheet runoff simulations over the irregular bed topography. The modified numerical model was then used to simulate storms in a low-relief agricultural watershed in the Mississippi River alluvial plain. This physically based model identified the channel networks, watershed boundary automatically, and helped to develop rating curves at the gage station of this complex watershed. The numerical simulations resolved detailed runoff and turbulent channel flows, which can be used for soil erosion and gully development analyses