Jairo Diaz-Ramirez

Analysis of Hydrological Processes Applying the HSPF Model in Selected Watersheds in Alabama, Mississippi, and Puerto Rico

The goal of this study was to evaluate the Hydrological Simulation Program – FORTRAN (HSPF) to gain more insight in the underlying causes and mechanisms of hydrological processes in an upland basin in Alabama and Mississippi (1,856-km2 Luxapallila Creek), a humid subtropical watershed in coastal Alabama (140-km2 Fish River), and a steep-slope tropical catchment in Puerto Rico (99-km2 Rio Caonillas). For each watershed model, rainfall, potential evapotranspiration, and streamflow time series from January 1999 to December 2000 were used to calibrate model parameters and 2001 time series were applied to verify model results. In each study area, actual evapotranspiration was the main mechanism of water loss followed by river discharge. Annual baseflow values ranged from 58% of total discharge in Luxapallila Creek basin to 84% of total discharge in Fish River watershed. In Luxapallila Creek and Fish River, interflow was the primary mechanism of direct runoff; however, surface runoff was the main process of direct runoff in Rio Caonillas. The HSPF model was successfully adapted to model daily streamflow processes in Luxapallila Creek basin and Rio Caonillas catchment with coefficient of determination and Nash and Sutcliffe coefficient values between 0.61 and 0.71 for the entire period; however, the Fish River watershed model performance was poor. The poor performance is likely due to the lack of rainfall time series available within the watershed boundaries. In general, this study showed the robustness of the HSPF model in extreme environments (small catchments vs. large basins, flat vs. hilly areas, low vs. moderate/high runoff potential, tropical marine vs. humid subtropical climates).

IMPACTS OF LAND USE CHARACTERIZATION IN MODELING HYDROLOGY AND SEDIMENTS FOR THE LUXAPALLILA CREEK WATERSHED, ALABAMA AND MISSISSIPPI

The Hydrological Simulation Program - Fortran (HSPF), interfaced with the Better Assessment Science Integrating Point and Nonpoint (BASINS), was used to evaluate the impact of land use (as characterized by different land use/land cover (LU/LC) datasets) on hydrology and sediment components of the Luxapallila Creek watershed. The 1,770 km2 watershed is located in Alabama and Mississippi. Simulation of the watershed processes were tested at the hillslope and at the watershed outlet for the period between 1985 and 2003. Three LU/LC databases were used: the Geographic Information Retrieval and Analysis System (GIRAS), the Moderate Resolution Imaging Spectroradiometer land cover product (MODIS MOD12Q1), and the National Land Cover Dataset (NLCD). The two main land use categories revealed by the three LU/LC databases were forest and agricultural lands. Whereas forest cover mechanisms were the main source of water loss in hydrology simulation, agricultural land was the main source of sediment export in sediment modeling. Land use datasets of coarser spatial resolution (MODIS and GIRAS) produced larger HSPF estimations for sediment fraction values than land use datasets identifying smaller percentages of those agricultural land cover classes (NLCD). Differences in agricultural land characterization among the land use datasets showed that sediment predictions were more sensitive than streamflow predictions to the scale and resolution of land use datasets. Choosing the right land use dataset will impact the modeling of sediments and, potentially, other water quality constituents that are related with agricultural activities.

A Comparison of Bayesian Methods for Uncertainty Analysis in Hydraulic and Hydrodynamic Modeling

We evaluate and compare the performance of Bayesian Monte Carlo (BMC), Markov chain Monte Carlo (MCMC), and the Generalized Likelihood Uncertainty Estimation (GLUE) for uncertainty analysis in hydraulic and hydrodynamic modeling (HHM) studies. The methods are evaluated in a synthetic 1D wave routing exercise based on the diffusion wave model, and in a multidimensional hydrodynamic study based on the Environmental Fluid Dynamics Code to simulate estuarine circulation processes in Weeks Bay, Alabama. Results show that BMC and MCMC provide similar estimates of uncertainty. The posterior parameter densities computed by both methods are highly consistent, as well as the calibrated parameter estimates and uncertainty bounds. Although some studies suggest that MCMC is more efficient than BMC, our results did not show a clear difference between the performance of the two methods. This seems to be due to the low number of model parameters typically involved in HHM studies, and the use of the same likelihood function. In fact, for these studies, the implementation of BMC results simpler and provides similar results to MCMC. The results of GLUE are, on the other hand, less consistent to the results of BMC and MCMC in both applications. The posterior probability densities tend to be flat and similar to the uniform priors, which can result in calibrated parameter estimates centered in the parametric space.

A Hydrological Model of the Mobile River Watershed, Southeastern USA

A hydrological model of the Mobile Bay watershed located in the northern Gulf of Mexico, (Alabama, USA) is presented. The modeling of hydrological processes is performed using the Hydrological Simulation Program Fortran (HSPF). The project region was divided into two sectors for simplifying the modeling task: an upland watershed (that included streams not draining directly to the Mobile Estuary), and several watersheds of selected streams that drain directly to the Mobile estuary (namely: Fish River, Magnolia River, and Chickasaw Creek). The Better Assessment Science Integrating Point & Nonpoint Sources (BASINS) GIS system was used to perform most of the geospatial operations, although ArcGis and ArcInfo were also used to complement geospatial processing that was not available in BASINS.

Estimation and Propagation of Parameter Uncertainty in Lumped Hydrological Models: A Case Study of HSPF Model Applied to Luxapallila Creek Watershed in Southeast USA

Estimation and Propagation of Parameter Uncertainty in Lumped Hydrological Models: A Case Study of HSPF Model Applied to Luxapallila Creek Watershed in Southeast USA Explicit quantification of the uncertainty associated to the predictions of a hydrologic model is a necessary activity to objectively evaluate and report the limitations of the model caused by different sources of error. The current state of the practice of hydrologic modeling indicates that parametric uncertainty is considered as one of the most important sources of uncertainty. Some of the most relevant problems remaining in the practice include the identification of the principal parameters affecting model predictions and quantification of parameter ranges. This study evaluated stochastically one of the most popular deterministic watershed water quality models for decision making in USA.

Hydrology and Sediment Modeling Using BASINS/HSPF in a Tropical Island Watershed

The Hydrological Simulation Program - FORTRAN (HSPF) in interface with Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) v.3.0 was used to study hydrology, soil erosion, and sediment transport of the Rio Caonillas watershed in Puerto Rico. The HSPF model has been used widely since 1980; however, little is known about the models performance in tropical island watersheds that have extreme environmental conditions, such as rainfall intensity more than 25 mm h-1 and average soil slope of 38%. Three years (1999-2001) of continuous meteorological, flow, and suspended sediments data were used for model evaluation. The study found that the groundwater recession rate coefficient (AGWRC) was the most sensitive model parameter for both streamflow and sediment transport modeling. The calibrated model explained more than 85% of the monthly variability of streamflows and 70% of the monthly variability of suspended sediment concentrations. Agricultural and barren areas yielded the highest soil losses, contributing 55% and 20% of annual soil erosion, respectively. These results demonstrate that HSPF is capable of simulating hydrology and suspended sediment in the river for tropical island watersheds, principally for analysis on a monthly basis.

Latis: A Spatial Decision Support System to Assess Low-Impact Site Development Strategies

Significant advances have been made in the use of spatial and hydrologic models to quantify the impact of Best Management Practices (BMPs) and Low-Impact Development (LID) practices on water quality. Further advances are the goal of this work to add selection of BMP/LID and calculation of implementation costs, all integrated into a spatial decision support system (DSS). The Hydrologic Simulation Program in FORTRAN (HSPF), an unsteady flow model, was combined with links to desktop spatial data analysis tools, a spreadsheet listing BMP/LID and their implementation, operation, and maintenance cost data. Testing of the DSS, named Latis, allowed improvements in direct design of BMP, and a survey of landscape and engineering practitioners provided the impetus for a simplified version, Latis-LIDIA.

Sensitivity of the HSPF Model to Land Use/Land Cover Datasets

Abstract The Hydrological Simulation Program – FORTRAN (HSPF) in interface with the Better Assessment Science Integrating Point and Nonpoint (BASINS) was used to evaluate the impact on hydrology components of the Luxapallila Creek watershed due to different land use/land cover (LU/LC) databases. The 1,770-km2 watershed is located in Alabama and Mississippi. Simulation of the watershed processes were tested at the hillslope and at the watershed outlet for the period between 1985 and 2003. Three LU/LC databases were evaluated: the GIRAS, the Moderate Resolution Imaging Spectroradiometer (MODIS), and the National Land Cover Data (NLCD). The three LU/LC databases showed that more than 70% of the watershed area is covered by forest. Forest areas produced small changes among databases. Forest cover mechanisms were the main source of water losses. The model was more sensitive to daily time steps than annual periods when the MODIS and NLCD datasets were compared to the GIRAS database. In general, the MODIS dataset showed a higher variation on hydrology simulations than the NLCD database when both LU/LC databases were compared to the GIRAS database.

Parameter uncertainty methods in evaluating a lumped hydrological model

Water resources modelers face the challenge of dealing with numerous uncertainties due to the lack of knowledge of the natural systems, numerical approaches used in modeling (equations, parameters, structures, solutions), and field data collected to set up and evaluate models. Propagation of parameter uncertainty into model results is a relevant topic in environmental hydrology. Uncertainty analyses improve assessment of hydrological modeling. There is a need in modern hydrology of developing and testing uncertainty analysis methods that support hydrological model evaluation. In this research the propagation of model parameter uncertainty into streamflow model results is evaluated. The Hydrological Simulation Program – FORTRAN (HSPF) supported by the US Environmental Protection Agency was evaluated using hydroenvironmental data from the Luxapallila Creek watershed located in Mississippi and Alabama, USA. The uncertainty bounds of model outputs were computed using the Monte Carlo simulation and Harr’s point estimation methods. Analysis of parameter uncertainty propagation on streamflow simulations from 12 HSPF parameters was accomplished using 5,000 Monte Carlo random samples and 24 Harr selected points for each selected parameter. The comparison showed that Harr’s method could be an appropriate initial indicator of parameter uncertainty propagation on streamflow simulations, particularly for hydrology models with several parameters.

A Review of HSPF Evaluations on the Southern United States and Puerto Rico

The objective of this study was to evaluate the Hydrological Simulation Program – FORTRAN (HSPF) in three different environments: an upland basin in Alabama and Mississippi, a humid, subtropical watershed in coastal Alabama, and a steep-slope tropical catchment in Puerto Rico. The HSPF model was coded to simulate hydrology, hydraulics, water quality, nutrients, soil erosion, and sediment transport in rural and urban environments. This project used the HSPF version linked to the EPA Better Assessment Science Integrating Point & Non-point Sources (BASINS) model. The HSPF model was applied to the 1,852 km2 Luxapallila Creek basin, 140.1 km2 Fish River watershed, and 98 km2 Rio Caonillas catchment. The HSPF model was successfully adapted to model daily hydrological processes in each study area. When analyzing flow duration curves showed that baseflow was more significant in the Fish River watershed than the other two drainage areas because flow values between 10% and 100% of the time had a low slope. The calibrated models explained more that 71% of the daily variability of streamflows. The models performed better during calibration than the verification period. Coefficient of determination and Nash-Sutcliffe statistics were good on a daily and monthly periods. The three models were evaluated under a large range of streamflows (0.4 m3/s to 897 m3/s). In general, this study showed the robustness of the HSPF model in extreme environments (small catchments vs. large basins, flat vs. hilly areas, tropical vs. subtropical climates).