Amir P. Nejadhashemi

Uncertainty Analysis of Hydrologic and Water Quality Predictions for a Small Watershed Using SWAT2000

Hydrologic and water quality (H/WQ) models are being used with increasing frequency to devise alternative pollution control strategies. It has been recognized that such models may have a large degree of uncertainty associated with their predictions, and that this uncertainty can significantly impact the utility of the model. In this study, ARRAMIS (Advanced Risk & Reliability Assessment Model) software package was used to analyze the uncertainty of the SWAT2000 (Soil and Water Assessment Tool) outputs concerning nutrients and sediment losses from agricultural lands. ARRAMIS applies Monte Carlo simulation technique connected with Latin hypercube sampling (LHS) scheme. This technique is applied to the Warner Creek watershed located in the Piedmont physiographic region of Maryland, and it provides an interval estimate of a range of values with an associated probability instead of a point estimate of a particular pollutant constituent. Uncertainty of model outputs was investigated using LHS scheme with restricted pairing for the model input sampling. Probability distribution functions (pdfs) for each of the 50 model simulations were constructed from these results. Model output distributions of interest in this analysis were stream flow, sediment, organic nitrogen (organic-N), organic phosphorus (organic-P), nitrate, ammonium, and mineral phosphorus (mineral-P) transported with water. Developed probability distribution functions for the model provided information with desirable probability. Results indicate that consideration of input parameter uncertainty produces 64% less mean stream flow along with approximately 8.2% larger sediment loading than obtained using mean input parameters. On the contrary, mean of outputs regarding nutrients such as nitrate, ammonia, organic-N, and organic-P (but not mineral-P) were almost the same as the one using mean input parameters. The uncertainty in predicted stream flow and sediment loading is large, but that for nutrient loadings is the same as that of the corresponding input parameters. This study concluded that using a best possible distribution for the input parameters to reflect the impact of soils and land use diversity in a small watershed on SWAT2000 model outputs may be more accurate than using average values for each input parameter.

Evaluation of Streamflow Partitioning Methods

Evaluating the relative amounts of stored or moving water via the different components of the hydrological cycle is highly depended on prudent management and planning. Proper characterization of hydrological cycle components is even more critical since both water quality and water quantity are considered in the water management scheme. One of the most challenging parts of this process is the separation and quantification of baseflow from the streamflow hydrograph. Streamflow partitioning has long been a topic of interest in the science of hydrology. Baseflow recession curve itself contains valuable information about ground water flow and it is widely used in hydrological models such as HEC-1 and other water resource applications. During the last few decades, an important number of case studies have been made with the aim of identifying the streamflow partitioning and physical factors, which control it. As a result of the limitation of available data, most of them were developed and tested on specific physiographic regions. The large number of existing techniques and high level of subjectivity in separating baseflow from streamflow indicates that the problem is not fully understood. The purpose of this paper is to review and evaluate the previously developed streamflow partitioning methods and highlight their advantages and disadvantages. This is important for appropriate use and to avoid any misuse. Successful application of hydrological models depends on their calibration and validation; therefore, the main part of this study focuses on the principles governing streamflow separation and its elements.

Evaluation of Analytical Methods for Streamflow Partitioning

Like many problems in hydrology, numbers of methods have been proposed for streamflow partitioning. Numerous hydrograph-partitioning techniques, including three-component, analytical, empirical, graphical, geochemical, and automated methods were reviewed. Five methods were identified as being the most relevant and less input intensive. This paper presents the testing of these five methods against separately measured surface and subsurface flow from the Coastal Plain physiographic region of the southeastern United States.

Comparison of Four Water Quality Models (STEPL, PLOAD, L-THIA, and AVSWAT-X) in Simulating Sediment and Nutrient Dynamics in a Watershed

Watershed water-quality models are essential for evaluating the natural processes that lead to waterbody impairments. Selection of the most suitable model for a given watershed and target pollutant is critical to modeling success, but few studies provide the comparisons needed to allow this evaluation. This study will compare utility and results of four watershed models that include water-quality constituents: Spreadsheet Tool for Estimating Pollutant Load (STEPL), GIS Pollutant Load (PLOAD), Long-Term Hydrologic Impact Assessment (L-THIA), and ArcView Soil and Water Assessment Tool (AVSWAT-X). Flow rates and sediment, nitrogen and phosphorus yields were measured over 16 years in the Pomona Lake watershed in North-east Kansas. Each model was setup using the methods recommended by each model. The modeling efforts showed that effective stakeholder involvement provides the reality check for scientific efforts. The results of this study also showed that in the quest to efficiently allocate resources, states should recognize that simpler analyses can often support informed decision-making and that complex modeling studies should be pursued only if warranted by the complexity of the analytical problem.

Analysis of Watershed Physical and Hydrological Effects on Baseflow Separation

There is a great interest in understanding groundwater-surface water interactions among hydrologists and water resources planners. One of the most challenging parts of this concept is the separation and quantification of baseflow from the streamflow hydrograph. However, in the science of hydrology, no conceptual or physical based techniques may operate effectively without considering physical and hydrological characteristics of watersheds. Hydrograph separation methods are not exceptions. Therefore, this study is widely devoted to define and test these dominant forces within a watershed and incorporate their impact on streamflow components. The study area is located in the Coastal Plain of the Southeastern United States where separately measured surface and subsurface flow data are available for a field scale watershed for nine years (1970-1978). Sensitivity analysis was conducted with respect to the impact of different watershed characteristics on streamflow components and parameters of interest were identified. Improvement in the streamflow partitioning accuracy was accomplished by incorporating the most sensitive parameters in the streamflow partitioning approach using a regression equation built based on watershed physical (e.g., land use, soils) and hydrologic characteristics (e.g. rainfall, soil moisture). Using new technique improved the streamflow partitioning method’s performance significantly. It is anticipated that these improvements will contribute to the accuracy of streamflow separation estimation for large-scale watersheds with diverse soils and cover conditions.

Prediction of NO3-N Losses in Surface Runoff from a Field with Seepage Zones Using GLEAMS and RZWQM

Seepage zones have been shown to be of critical importance in controlling contaminant export from agricultural watersheds. However, their impacts on water quality have not been effectively modeled. The Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) model and the Root Zone Water Quality Model (RZWQM) were used to predict daily and monthly nitrate-nitrogen (NO3-N) concentration and loss in surface runoff from an agricultural field with seepage zones. The results of the study show that calibrated GLEAMS and RZWQM predicted daily NO3-N concentration [index of agreement (D) > 0.57] in surface runoff from the field with seepage zones. Based on the different model evaluation techniques used in this study, both GLEAMS and RZWQM performed fairly well in assessing the effects of seepage zones on daily NO3-N losses in surface runoff. However, GLEAMS (D = 0.93) performed relatively better than RZWQM (D = 0.45) in predicting NO3-N loss in surface runoff on a monthly basis, while both GLEAMS and RZWQM performed equally well in predicting NO3-N loss in surface runoff on a daily basis. Both models performed poorly in predicting NO3-N concentration in surface runoff on a monthly basis (D < 0.44). Additionally, since neither model adequately simulated monthly NO3-N concentration in surface runoff from the field with seepage zones, their ability in water quality modeling for such fields will be compromised, and further model evaluation and development is justified.

Improvement in Hydrograph Separation Estimation by Incorporating Hydrologic Characteristics of Watersheds

Evaluating the relative amounts of stored or moving water through the different components of the hydrological cycle is required for precise management and planning of water resources. An important aspect of this evaluation is the partitioning of streamflow into surface and baseflow components. A prior study evaluated forty different approaches for hydrograph-partitioning on a field scale watershed in the Coastal Plain of the Southeastern United States and concluded that the Boughton method produced the most consistent and accurate results. However, its accuracy depends upon the proper estimation of: 1) the inflection point on the recession limb of the hydrograph, and 2) the fraction factor (a) that is function of many physical and hydrologic characteristics of a watershed. Proper identification of the inflection point was accomplished by using a 2nd derivative approach, which was automated by writing a computer program in Visual BASIC. Applying this approach to twelve years of streamflow data proved to be accurate for 87% of the time. Estimation of the a value was accomplished in this study using two steps; first, alpha was fitted to individual hydrographs, and, second, a regression equation that determines these alpha values based on watersheds hydrologic characteristics (e.g. rainfall, evaporation) was developed. Using these strategies for identifying a values and inflection points improved the streamflow partitioning method’s performance significantly. It is anticipated that these improvements will contribute to the accuracy of this method on streamflow partitioning for large-scale watersheds with diverse soils and cover conditions.

Nonlinear Analysis of Phosphorus Transport in Soils

The effects of sorption dynamics and hysteresis on phosphorus transport through saturated soils are investigated using an advective-dispersive transport model coupled with three sorption models: 1) Equilibrium Langmuir; 2) Dynamic Langmuir, and; 3) Hysteretic Dynamic Langmuir. Three transport scenarios are investigated: 1) a slug in a phosphorus free soil; 2) a slug in a phosphorus-laden soil, and; 3) a phosphorus-free slug in a phosphorus-laden soil. Results indicate that phosphorus does not move in phosphorus-free soils but can move significantly in phosphorusladen soils. Sorption dynamics have a significant effect on leaching but hysteresis has only a mild influence on transport. It is concluded that nonlinear sorption dynamics are important in subsurface transport of phosphorus and should be investigated further.

Evaluation of a Decision Support System for Phosphorus Management at the Watershed Scale

A Decision Support System (DSS) is applied to the development of a phosphorus export control Best Management Practice (BMP) allocation plan for a watershed on the Eastern Shore of Maryland. The system efficiently identifies critical source areas, probable causes for excessive export and applicable BMPs. The predicted reduction in phosphorus loading of watershed streams, with BMPs in-place, is 79% and exceeds the 50% reduction goal of the analysis. It is concluded that the present DSS is an effective tool for developing BMP allocation plans.