Mohamed M. Hantush

Models for leaching of pesticides in soils and groundwater.

Models are developed which describe leaching of pesticides in the root zone and the intermediate vadose zone, and flushing of residual solute mass in the aquifer. Pollutants’ loss pathways in the soil, such as volatilization, crop uptake, and biochemical decay, are emphasized, and the effect of local dispersion and nonequilibrium transport in mobile–immobile phases is analyzed. It is shown that the effect of diffusive transfer on the leached mass fractions is dependent on the volume fraction of the immobile phase, adsorption, the apparent mass-transfer rate coefficient, the first-order decay rate in the immobile zone. Error analysis indicates that complete-mixing models can be used to simulate leaching fractions of the pollutant when the Peclet number, Pr, is greater than one. However, ignoring the effect of dispersion may underestimate leaching significantly when Pr<1, such as for volatile compounds. Potential application of the models to the design of groundwater protection zones is investigated, analysis and application results demonstrate the dependence of the size of protective buffer on potential loss pathways in the soil environment, the size of the source area, and aquifer geometric, hydraulic and biochemical properties. Potential use of the models for the management of pesticides is also investigated with implication on hazardous waste land treatment.

Screening model for volatile pollutants in dual porosity soils

This paper develops mass fraction models for transport and fate of agricultural pollutants in structured two-region soils. Mass fraction index models, based on a semi-infinite domain solution, are derived that describe leaching at depth, vapor losses through soil surface, absorption, and degradation in the dynamic- and stagnant-water soil regions. The models predict that leaching is the result of the combined effect of the upward vapor-phase transport relative to downward advection, residence time relative to half-life, dispersion, and lateral diffusive mass transfer. Simulations show that leached fraction of volatile compounds does not always decrease monotonically with increased residence time relative to the pollutant half-life, as a result of complex interactions among the different physical and biochemical processes. The results show that leaching, volatilization, and degradation losses can be affected significantly by lateral diffusive mass transfer into immobile-water regions and advection relative to dispersion (i.e. Peclet number) in the mobile-water regions. It is shown that solute diffusion into the immobile phase and subsequent biochemical decay reduces leaching and vapor losses through soil surface. Potential use of the modified leaching index for the screening of selected pesticides is illustrated for different soil textures and infiltration rates. The analysis may be useful to the management of pesticides and the design of landfills.

Uncertainty and sensitivity analysis of runoff and sediment yield in a small agricultural watershed with KINEROS2 / Analyse d'incertitude et de sensibilité des simulations d'écoulement et de transport solide de KINEROS2 dans un petit bassin versant agricole

Abstract Using the Monte Carlo (MC) method, this paper derives arithmetic and geometric means and associated variances of the net capillary drive parameter, G, that appears in the Parlange infiltration model, as a function of soil texture and antecedent soil moisture content. Approximate expressions for the arithmetic and geometric statistics of G are also obtained, which compare favourably with MC generated ones. This paper also applies the MC method to evaluate parameter sensitivity and predictive uncertainty of the distributed runoff and erosion model KINEROS2 in a small experimental watershed. The MC simulations of flow and sediment related variables show that those parameters which impart the greatest uncertainty to KINEROS2 model outputs are not necessarily the most sensitive ones. Soil hydraulic conductivity and wetting front net capillary drive, followed by initial effective relative saturation, dominated uncertainties of flow and sediment discharge model outputs at the watershed outlet. Model predictive uncertainty measured by the coefficient of variation decreased with rainfall intensity, thus implying improved model reliability for larger rainfall events. The antecedent relative saturation was the most sensitive parameter in all but the peak arrival times, followed by the overland plane roughness coefficient. Among the sediment related parameters, the median particle size and hydraulic erosion parameters dominated sediment model output uncertainty and sensitivity. Effect of rain splash erosion coefficient was negligible. Comparison of medians from MC simulations and simulations by direct substitution of average parameters with observed flow rates and sediment discharges indicates that KINEROS2 can be applied to ungauged watersheds and still produce runoff and sediment yield predictions within order of magnitude of accuracy.

Watershed reliability, resilience and vulnerability analysis under uncertainty using water quality data

A method for assessment of watershed health is developed by employing measures of reliability, resilience and vulnerability (R-R-V) using stream water quality data. Observed water quality data are usually sparse, so that a water quality time-series is often reconstructed using surrogate variables (streamflow). A Bayesian algorithm based on relevance vector machine (RVM) was employed to quantify the error in the reconstructed series, and a probabilistic assessment of watershed status was conducted based on established thresholds for various constituents. As an application example, observed water quality data for several constituents at different monitoring points within the Cedar Creek watershed in north-east Indiana (USA) were utilized. Considering uncertainty in the data for the period 2002-2007, the R-R-V analysis revealed that the Cedar Creek watershed tends to be in compliance with respect to selected pesticides, ammonia and total phosphorus. However, the watershed was found to be prone to violations of sediment standards. Ignoring uncertainty in the water quality time-series led to misleading results especially in the case of sediments. Results indicate that the methods presented in this study may be used for assessing the effects of different stressors over a watershed. The method shows promise as a management tool for assessing watershed health.

How Do Land-Use and Climate Change Affect Watershed Health? A Scenario-Based Analysis

With the growing emphasis on biofuel crops and potential impacts of climate variability and change, there is a need to quantify their effects on hydrological processes for developing watershed management plans. Environmental consequences are currently estimated by utilizing computer models such as Soil and Water Assessment Tool (SWAT) to simulate watershed hydrology under projected climate and land-use scenarios to assess the effect on water quantity and/or quality. Such studies have largely been deterministic in nature, with the focus being on whether hydrologic variables such as runoff, sediment and/or nutrient loads increase or decrease from the baseline case under projected scenarios. However, studying how these changes would affect watershed health in a risk-based framework has not been attempted. In this study, impacts of several projected land-use and climate change scenarios on the health of the Wildcat Creek watershed in Indiana have been assessed through three risk indicators, namely reliability–resilience–vulnerability (R–R–V). Results indicate that cultivation of biofuel crops such as Miscanthus and switchgrass has the potential to improve risk indicator values with respect to sediment, total N and total P. Climate change scenarios that involved rising precipitation levels were found to negatively impact watershed health indicators. Trends of water quality constituents under risk-based watershed health assessment revealed nuances not readily apparent from deterministic assessments alone. For example, while biofuel crop cultivation reduced total N loads under all hypothetical land-use scenarios examined in this study, watershed vulnerability in terms of total N also rose in some of those scenarios. Risk-based analyses coupled with deterministic methods are needed for a more comprehensive assessment of the health of a watershed under projected scenarios.

An auxiliary method to reduce potential adverse impacts of projected land developments: subwatershed prioritization.

AbstractAn index based method is developed that ranks the subwatersheds of a watershed based on their relative impacts on watershed response to anticipated land developments, and then applied to an urbanizing watershed in Eastern Pennsylvania. Simulations with a semi-distributed hydrologic model show that computed low- and high-flow frequencies at the main outlet increase significantly with the projected landscape changes in the watershed. The developed index is utilized to prioritize areas in the urbanizing watershed based on their contributions to alterations in the magnitude of selected flow characteristics at two spatial resolutions. The low-flow measure, 7Q10, rankings are shown to mimic the spatial trend of groundwater recharge rates, whereas average annual maximum daily flow,

Theoretical development and analytical solutions for transport of volatile organic compounds in dual-porosity soils

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Aggregate Measures of Watershed Health from Reconstructed Water Quality Data with Uncertainty.

, and average monthly median of daily flows,