top of page

Watershed Analysis


We perform watershed scale hydrologic analysis. Our hydrologic analysis portfolio includes precipitation frequency analysis, numerical model development for GIS-based rainfall-runoff modeling, stormwater modeling and water quality modeling and assessment. 

GIS-based 1D Hydrologic Model 


In the past, the a GIS-based 1-d distributed hydrologic mode (DHM), based on diffusive wave equations was developed. The model was developed for efficient application with limited data requirements (soils, land use, and topography) and was designed to have excellent interface potential with associated water hazard prediction and analysis codes.Testing suggests the model has reached a stage of acceptable simulation time requirement and accuracy for wide-area applications. Figure 1. below shows the process schematic of the DHM.


Using this model, watershed scale assessment of the hydrologic model error incurred by use of land use / land cover datasets to estimate Manning's n was performed. A digital dataset of Manning's n is generated by manual inspection of aerial photos for a 23 sq. km watershed. Manning's n is also estimated using the land use classes in the National Land Cover Dataset (NLCD). Up to 50% difference in the magnitude and variation in spatial distribution of Manning's n values is found in more than 90 % of the study area. The differences did not translate into significantly altered runoff responses (hydrograph magnitude: 9 % to 22 % relative peak discharge difference and shape: 2 % to 18 % relative time to peak difference) from 3 storm events at the watershed outlet for a lumped model (SWMM) and a distributed model. However, these differences are significant (up to 75 % relative peak discharge difference and up to 300 % relative time to peak difference) at the subcatchment levels and showed increasing trend in deviation of the hydrograph peaks with increased Manning's n deviation. The results of this study suggesed that the use of NLCD-defined Manning's n values is acceptable for medium to large watersheds. The paper by Kalyanapu et al., (2009) can be found at this link. 

Figure 1. Schematic of GIS-based 1D DHM (Kalyanapu, 2009)

AnnAGNPS Modeling for Watershed Runoff and Water Quality 

Currently, we are actively working on implementing Annualized Agricultural Non-Point Source (AnnAGNPS) model for the Obed River Watershed in Cumberland Plateau region in the state of Tennessee. Figure 2 shows the Obed River Watershed and its characteristics.

This project will help city planners and regional stakeholders for environmentally sustainable growth in the Obed Watershed region. Funded by Tennessee Healthy Watershed Initiative.

For more information on this, please visit:

Figure 2. Obed River Watershed

Probabilistic Hydrologic Modeling 

Figure 3. Probabilsitic rainfall generatored using GoldSim

In this project, a HEC-HMS model is re-built within a GoldSim modeling framework to enable stochastic sampling of the basin parameters and precipitation inputs. For Swannanoa River watershed near Asheville, NC, the model developed was capable of creating event-driven flood flow hydrographs, generated using a Markov Rainfall Generation model. The Markov model is used to produce more realistic, random rainfall events that are fed into a watershed model to produce probabilistic hydrographs. The inputs to the watershed model can betreated as uncertain inputs, which will further add to the quantification of randomness of the flood hydrographs, and more accurately represent realistic events. The Markov model produces more realistic, random rainfall events that are fed into a watershed model to produce probabilistic hydrographs. Based on the historical precipitation records, probabilistic rainfall hyetographs are generated as shown in Figure 3 below.


These probabilistic hyetographs are input into the watershed model (see Figure 4 below) to generate probabilistic hydrographs (See Figure 5).

Figure 4.HMS Basin

Figure 5.GoldSim model

bottom of page