Graduation Year

2026

Document Type

Thesis

Degree

M.S.E.V.

Degree Name

MS in Environmental Engr. (M.S.E.V.)

Degree Granting Department

Civil and Environmental Engineering

Major Professor

Mauricio E. Arias, Ph.D.

Committee Member

Qiong Zhang, Ph.D.

Committee Member

Mahmood Nachabe, Ph.D.

Keywords

Biogeochemical, Coastal Watershed, Nutrient Retention, Sensitivity Analysis, Water Quality

Abstract

Urbanization impacts the hydrological and biogeochemical processes that regulate water quality in downstream ecosystems, leading to increased stormwater volume and nitrogen loads in receiving aquatic environments. Although stormwater ponds are designed as simple hydraulic storage basins, they function more like managed ecosystems within urban drainage systems, offering both hydraulic attenuation and passive nutrient treatment. However, nitrogen removal efficiency varies significantly and depends on interactions between hydrological and biogeochemical factors. This thesis details the development, calibration, validation, and sensitivity analysis of a coupled hydrological-nitrogen model framework for Aaran’s Pond, an urban stormwater pond in Hillsborough County, Florida.

A process-based water budget model was developed to simulate hourly pond storage, depth, and hydrological fluxes (inflow, outflow, direct rainfall, runoff, evapotranspiration, and seepage) using site-specific meteorological and observed water-level data. Calibration with 10 parameters yielded R2 = 0.79, RMSE = 0.374 ft, and NSE = 0.618. Validation over a sequential period yielded R2 = 0.604, RMSE = 0.306 ft, and NSE = 0.4. Parameter sensitivity screening identified saturated hydraulic conductivity (Ks) as the dominant control on water-level performance (Spearman's ρ = 0.66), followed by the Inflow 2 event-response baseline coefficient.

The calibrated hydrological parameters were used to drive a monthly nitrogen mass balance model for ammonium (NH4+-N), nitrate (NO3--N), and organic nitrogen, accounting for advective transport, nitrification, denitrification, mineralization, plant uptake, settling, temperature- and dissolved oxygen-dependent rate modifiers. Calibrating the nitrogen model across 13 parameters reproduced adequate Total Kjeldahl Nitrogen (TKN) and organic nitrogen results. These results highlight the model’s ability to replicate magnitudes but struggle to replicate month-to-month variability, reflecting the limited temporal resolution and spatial heterogeneity of the available water-quality observations. Sensitivity screening identified that the settling rate is the most influential to TKN and organic nitrogen (|ρ| = 0.94 and 0.95), while ammonium biological uptake rate influenced NH4+ predictions (|ρ| = 0.84), and nitrate plant uptake rates governed NO3- dynamics (|ρ| = 0.95). A coupled global sensitivity analysis was conducted using the Sobol method across the full 23-parameter space (10 hydrological, 13 nitrogen), calculating 50,000 coupled model evaluations. Results showed that the nitrate uptake coefficient (kuptNO3) was the primary driver of overall coupled model uncertainty, accounting for 76% of the composite score variance (S1 = 0.76 and ST = 0.82), along with kuptNH4 (ST ≈ 0.08), Bk (ST ≈ 0.05), (λ, Sₜ ≈ 0.03), KDOden (ST ≈ 0.05), and Ks (ST ≈ 0.02), collectively explain nearly all of the coupled model uncertainties.

The coupled framework shows that uncertainties in water movement affect nitrogen predictions, and that internal organic nitrogen loading during warmer months is a critical, data-limited process at Aaran’s Pond site. These results support recommendations for focused monitoring, especially of sediment-water nitrogen exchange during summer, and lay a foundation for expanding coupled water-quality models in coastal urban watersheds.

Download

Share

COinS