Journal of Hydrologic Engineering

Unsaturated flow transforms streams from constant head boundaries to constant flux boundaries, impacting the quantity of stream recharge to groundwater. The objective of this research was to analyze the impact of unsaturated flow on stream/aquifer exchange by incorporating a three-regime, saturated/unsaturated flow, stream recharge model into MODFLOW, the most commonly used numerical flow model in ground water hydrology. This three-regime model extends prior research by accounting for a transition regime between fully saturated and gravity-driven unsaturated flow. Accounting for unsaturated flow between a stream and aquifer is necessary to adequately simulate stream depletion. Sensitivity analyses of steady stream recharge versus drawdown demonstrated that the transition regime became more important for cases with small stream stages, smaller streambed thicknesses, and larger entry pressure heads. Based on coarse sand and fine sand hypothetical scenarios, the transition regime in the proposed three-regime model could generally be neglected with minor error for most stream/aquifer scenarios. However, the transition regime became important when: (1) the drawdown stabilized near the range of drawdowns that represented the transition regime; and (2) there must be a significant difference (i.e., $0.2\mathrm{m}$ ) in the entry and ultimate capillary pressure heads, which occurred with larger entry pressure heads (i.e., equal to or greater than $1.0\mathrm{m}$ ) and a smaller pore size distribution index (i.e., approximately 1.0).

An approximate solution for flow to a well in an aquifer overlain by both an aquitard and a second aquifer containing a free surface is obtained from numerical inversions of exact analytical solutions for Laplace transforms. This study extends previous work on this topic in three ways: (1) it improves an eigenvalue decomposition solution method used earlier by Hemker and Maas in 1987 for unsteady flow in multiaquifer systems; (2) it obtains an approximate solution that is simpler to evaluate than previously known solutions; and (3) it utilizes a much more general solution from a MODFLOW finite-difference model to explore both limitations of the approximate solution and the physical behavior of the two-aquifer system. In addition, criteria are obtained that show when the two-aquifer solution can be replaced with the simpler Boulton solution when analyzing pumping test field data.

A $43\text{-}\text{year}$ database of reconstructed atmospheric data at $3\text{-}\mathrm{km}$ spatial resolution and hourly temporal resolution was created using a nonhydrostatic regional atmospheric model and archived global, coarse-resolution atmospheric data. The archived atmospheric data at approximately $200\text{-}\mathrm{km}$ spatial resolution and $6\text{-}\mathrm{h}$ temporal resolution were used as initial and boundary conditions in the regional model to generate the reconstructed data. Data for seven variables were extracted from model results for the database: precipitation, atmospheric temperature, relative humidity, wind speed, incoming solar radiation, downward longwave radiation, and latent heat flux. In addition, dew point temperature was computed from simulation results and stored in the database. Model results for temperature and precipitation were compared to observed data collected at three sites in the basin over a $6\text{-}\text{year}$ period. Model-generated results match the seasonal, annual, and interannual fluctuations in the observed data quite well. Results indicate that the method for reconstructing atmospheric data for use in distributed parameter hydrologic and environmental models provides spatial detail unmatched by existing observed data networks and is a viable alternative to statistical manipulation of limited observed data.

The results of distributed watershed models could be sensitive to spatial and temporal scales at which inputs and model parameters are aggregated. This paper reports findings of a detailed sensitivity analysis conducted on the U.S. Department of Agriculture’s distributed watershed simulation model, known as the Soil and Water Assessment Tool (SWAT). The Big Creek Watershed, located in southern Illinois, is used for the study. The model is calibrated to improve accuracy of its streamflow and sediment concentration predictions using observed data at two locations in the study watershed. Streamflow and sediment concentrations that are simulated by the calibrated model at various spatial scales of discritization are extracted and compared, and inputs and model parameters responsible for sensitivity of model responses are identified. Several indices that could be used as indicators of model behavior are also derived. In addition, feasibility analysis of SWAT is conducted to see if the watershed simulation model could be used as a component in future decision support models developed to assist in identifying integrative watershed management practices that control agricultural nonpoint source pollutions from watersheds. The major findings of the study are: (1) accuracy of the raw model output (streamflow and sediment yield) is very poor for all delineations indicating the need for careful model calibration; (2) streamflow is relatively insensitive to spatial scale; and (3) sediment generated and sediment that leaves the watershed decreases as spatial scale gets coarser. Unlike the findings of previous studies, sediment yield significantly varies, even when properties of the outlet channel remain practically the same. (4) SWAT’s estimate of sediment yield is sensitive to human activities conducted in subbasins of the watershed, thus indicating the capability of SWAT to evaluate consequences of alternative watershed management practices.

Recent interest in tracking environmental benefits of conservation practices on agricultural watersheds throughout the United States has led to the development of the U.S. Department of Agriculture’s (USDA) Conservation Effects Assessment Project (CEAP). The purpose of CEAP is to assess environmental benefits derived from implementing various USDA conservation programs for cultivated, range, and irrigated lands. Watershed scale, hydrologic simulation models such as the Soil and Water Assessment Tool (SWAT) will be used to relate principal source areas of contaminants to transport paths and processes under a range in climatic, soils, topographic, and land use conditions on agricultural watersheds. To better understand SWAT’s strengths and weaknesses in simulating streamflow for anticipated applications related to CEAP, we conducted a study to evaluate the model’s performance under a range of climatic, topographic, soils, and land use conditions. Hydrologic responses were simulated on five USDA Agricultural Research Service watersheds that included Mahantango Creek Experimental Watershed in Pennsylvania and Reynolds Creek Experimental Watershed in Idaho in the northern part of the United States, and Little River Experimental Watershed in Georgia, Little Washita River Experimental Watershed in Oklahoma, and Walnut Gulch Experimental Watershed in Arizona in the south. Model simulations were performed on a total of 30 calibration and validation data sets that were obtained from a long record of multigauge climatic and streamflow data on each of the watersheds. A newly developed autocalibration tool for the SWAT model was employed to calibrate eleven parameters that govern surface and subsurface response for the three southern watersheds, and an additional five parameters that govern the accumulation of snow and snowmelt runoff processes for the two northern watersheds. Based on a comparison of measured versus simulated average annual streamflow, SWAT exhibits an element of robustness in estimating hydrologic responses across a range in topographic, soils, and land use conditions. Differences in model performance, however, are noticeable on a climatic basis in that SWAT will generally perform better on watersheds in more humid climates than in desert or semidesert climates. The model may therefore be better suited for CEAP investigations in wetter regions of the eastern part of the United States that are predominantly cultivated than the dryer regions of the West that are more characteristically rangeland.

In 2003, Reilly and Kroll examined the baseflow correlation method at river sites throughout the United States. The current study reexamines Reilly and Kroll’s baseflow correlation experiment by investigating the use of different performance metrics, experimental parameters, and model assumptions that were not investigated by Reilly and Kroll. The goal of this study is to provide additional guidance on how to implement the baseflow correlation method in practice. The results confirm that baseflow measurements should be obtained during low flow seasons and as far as possible from runoff events. When one has only five baseflow measurements at the low-flow partial-record site, the correlation coefficient between baseflows at gauged and low-flow partial-record sites should be at least 0.9; when the number of baseflow measurements is 10 or more, the method performs adequately if the correlation coefficient is greater than 0.6. The performance of the baseflow correlation method improves as the number of baseflow measurements increases, but levels off dramatically when one has more than 10 measurements.

Green building design principles advocate the use of rainwater storage units to collect roof runoff during nonwinter seasons for landscaping, hardscape cleaning, and/or maintenance purposes, either in the form of rain barrels for smaller scale applications or cisterns for larger scale applications. This not only saves water which would otherwise be supplied from municipal water distribution systems but also reduces storm-water runoff which would otherwise be handled through urban storm-water management systems. The size of the storage units needs to be commensurate with the area of the roof and the desired water use rate. The local climate has an influence on the required size and achievable use rate as well. In this paper, analytical formulas are derived to estimate the required rainwater storage volume as a function of desired water use rate, reliability and local climate. In deriving these formulas, local climate characteristics are represented by probabilistic models and incorporated into the stochastic description of storage unit operating procedures and requirements. The resulting formulas may be used by engineers, architects, municipal governments, and storage unit manufactures for the estimation or recommendation of suitable rainwater storage unit sizes.

A conventional simulation-optimization model with constraint on drawdown at an area of interest is used to optimize additional groundwater withdrawal at multiple demand locations in a coastal aquifer. After obtaining the optimal solution, a decision-making analysis is conducted using fuzzy logic concepts. The goal is to evaluate multiple objectives and select the best management strategy. This methodology is applied to a hypothetical case consisting of six groundwater demand locations in Savannah, Ga. The objective function of the optimization model includes a penalty term which can be adjusted by the user to control the degree of “fairness” with respect to the distribution of limited groundwater resources in the region. The decision-making framework incorporates hydrologically, politically, and economically motivated multiple conflicting objectives into the evaluation process. Results of the coupled simulation-optimization model are used to determine individual satisfaction degrees of each management strategy with respect to multiple objectives. Based on this outcome, an overall performance value is calculated by using the ordered weighted averaging (OWA) operator and the management strategy with the highest overall performance is identified as the best strategy. The OWA operator is an averaging operator that avoids ruling out some alternatives in favor of others which is observed in the logical operators such as “and” and “or.” When combined with expert knowledge to identify the appropriate membership functions for the fuzzy objectives, the procedure developed in this study may yield transparent and robust groundwater management solutions in coastal aquifers.

The normal and lognormal distributions are frequently used in hydrology. As these distributions are in the form of integrals, they cannot be used for generation of normal and lognormal random numbers using inverse transforms. In this study, functions closely approximating the normal and lognormal distributions have been obtained and their use in hydrological studies is indicated.

The use of the gamma distribution as instantaneous unit hydrograph (IUH) for modeling runoff is simple and reasonably accurate. A simplified procedure was proposed for modeling runoff using the gamma IUH, in which the incomplete gamma function was computed indirectly, but the gamma function was computed. A further simplified procedure for runoff modeling using a gamma IUH or Nash model’s IUH is proposed. This procedure does not require computation of either the gamma function or incomplete gamma function.

Hydrodynamic modeling of flood detention reservoirs is an effective tool to evaluate reservoir performance, to plan modifications, and to design new reservoirs. The one-dimensional (1D) Saint Venant equations (SVE) are suitable to simulate the standing waves and other degenerations that occur in the reservoirs. The accuracy of these simulations depends on the Courant numbers used in the simulations. Consequently, the use of an appropriate time step for a specific grid size is crucial for the accuracy of the solution. A series of numerical experiments were performed and compared to observed data to develop time step criteria for solving the 1D SVE using the Abbott-Ionescu scheme. The time step was normalized by the wave celerity to make it problem dependent. The new time step criteria were evaluated on a different reservoir and proved to be adequate for selecting a time step for reservoir modeling. The criteria could readily be integrated in existing models to be used in an adaptive time stepping scheme.

Runoff simulation and prediction in watersheds is an important and essential step in water management systems, safety yield computations, environmental disposal, design of flood control structures, and so on. In this study, the runoff records of Linshan Watershed, Sichuan Province, PRC, during 1984–1993 are presented and used as samples for predictions. The time-delay neural network (TDNN) model combined with a genetic algorithm is proposed and used to predict the nonlinear relationship and to analyze the characteristics of runoff time series in the Linshan Watershed area. Based on analyzing the whole runoff process—for example, the average, maximum, and standard deviation—during said period, the equal length for training and testing is defined. The optimum TDNN structure of August 20, 2001 has been obtained by gradually increasing the time delay to avoid the limitations of the TDNN model. Comparisons between training and testing show that the forecasting model of the runoff level using TDNN combined with genetic algorithms is generally satisfactory and effective, with slight underpredictions at some points.