[1] Over the last century, land use and land cover (LULC) in the United States Corn Belt region shifted from mixed perennial and annual cropping systems to primarily annual crops. Historical LULC change impacted the annual water balance in many Midwestern basins by decreasing annual evapotranspiration (ET) and increasing streamflow and base flow. Recent expansion of the biofuel industry may lead to future LULC changes from increasing corn acreage and potential conversion of the industry to cellulosic bioenergy crops of warm or cool season grasses. In this paper, the Soil and Water Assessment Tool (SWAT) model was used to evaluate potential impacts from future LULC change on the annual and seasonal water balance of the Raccoon River watershed in west-central Iowa. Three primary scenarios for LULC change and three scenario variants were evaluated, including an expansion of corn acreage in the watershed and two scenarios involving expansion of land using warm season and cool season grasses for ethanol biofuel. Modeling results were consistent with historical observations. Increased corn production will decrease annual ET and increase water yield and losses of nitrate, phosphorus, and sediment, whereas increasing perennialization will increase ET and decrease water yield and loss of nonpoint source pollutants. However, widespread tile drainage that exists today may limit the extent to which a mixed perennial-annual land cover would ever resemble pre-1940s hydrologic conditions. Study results indicate that future LULC change will affect the water balance of the watershed, with consequences largely dependent on the future LULC trajectory.

DONGXIAO ZHANG. Academic Press, San Diego, CA. 2002. Hardcover, 350 pp. $89.95. ISBN: 0-12-779621-5. Hydrogeological variables of a groundwater system, for example, the hydraulic head and contaminant concentration, vary with space and time. The variability is due to spatial heterogeneities of geological materials and temporal variations of the internal and external input to and output from the groundwater system, such as groundwater recharge, evapotranspiration, and base flow to streams. These spatial heterogeneities and temporal variations are difficult if not impossible to characterize. As a result, modeling of fluid flow and solute transport in the subsurface environment is prone to errors and uncertainties. Yet, modeling of fluid flow and solute transport in soils and aquifers has traditionally been carried out almost exclusively with deterministic approaches.A large volume of research has been published, and various theories of subsurface flow and solute transport have been developed based on stochastic (as opposed to deterministic) methods since the publication of a seminal paper by Freeze (1975). As a result, our knowledge and understanding of fluid flow and solute transport in complex heterogeneous soils and aquifers have been significantly enhanced and improved. However, applications of stochastic theories and approaches in real world problems have been limited, and they have not become a routine tool in hydrological modeling (Dagan, 2002). In a forum organized for the journal Stochastic Environmental Research and Risk Assessment (Zhang and Zhang, 2004), a series of short articles written by some of the most prominent researchers in this area of research tackle the question: Why aren't stochastic hydrogeological approaches more widely used in real-world applications? Several participants in the forum pointed out that lack of background and training and tools is one of the main reasons. I think that the book, Stochastic Methods for Flow in Porous Media: Coping with Uncertainties, written by Dongxiao Zhang, provides an excellent training tool for teaching necessary skills needed in filling the gap between the theory and application.Dongxiao's book covers a broad spectrum of stochastic methods for both stationary and nonstationary flow problems in saturated aquifers and unsaturated soils with numerous tutorial examples and useful exercises. Chapter 1 of the book introduces some of the basic concepts in stochastic subsurface hydrology and presents the moment differential and integral equations, direct moment and PDF method, and solutions for the cases of one-dimensional flow with random forcing terms, boundary conditions, and parameters. The closure difficulties and the way to close the system at low orders were introduced in this chapter. Chapter 2 reviews the basics of stochastic variables and processes, which I found very useful for teaching the stochastic subsurface hydrology course to those who are unfamiliar with this topic. Chapter 3 deals with more general steady-state flow problems in three-dim...

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[1] Spectral analyses were conducted for hourly hydraulic head (h) data observed over a 4-year period at seven monitoring wells in the Walnut Creek watershed, Iowa. The log power spectral density of the hydraulic head fluctuations versus log frequency ( f ) at all seven wells is shown to have a distinct slope or fractal dimension (D), indicating temporal scaling in the time series of water level fluctuations. The fractal dimension of the time series varies from well to well, and the spectrum for the average h over all seven wells has a fractal dimension of 1.46 and Hurst coefficient of 0.54. The log power spectral density of estimated base flow in the Walnut Creek and four other watersheds versus log f is shown to have two distinct slopes with a break in scaling at about 30 days. It is shown that the groundwater recharge process in a basin can be estimated from a head spectrum based on existing theoretical results. Hydraulic head in an aquifer may fluctuate as a fractal in time in response to either a white noise or fractal recharge process, depending on physical parameters (i.e., transmissivity and specific yield) of the aquifer. The recharge process at the Walnut Creek watershed is shown to have a white noise spectrum based on the observed head spectrum.

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[1] Temporal scaling of the hydraulic head time series, h(t), was found in a previous analysis of hourly measured head data. This issue is further investigated in this paper with nonstationary spectral analyses and numerical simulations. The results show that temporal scaling may indeed exist in h(t), which fluctuates like a fractional Brownian motion in most aquifers. On the basis of a linear reservoir model with a white noise recharge input, we show that the variance and covariance of h(t) are functions of time: The head variance increases with time and approaches a constant limit as time progresses, while the covariance decreases with the separation time interval for a fixed time and approaches the typical exponential covariance as time increases. The spectra of the simulated h(t) using a one-dimensional transient groundwater flow model with a white noise recharge in both homogeneous and heterogeneous aquifers are shown to be proportional to f Àb , where f is frequency and b % 1.84 (or H = 0.42). Heterogeneity in the hydraulic conductivity may affect the fractal dimension of h(t) in highly permeable aquifers but not in the low permeable aquifer simulated in this study.

Multi-scale entropy (MSE) analysis was applied to the long-term (131 years) daily flow rates (Q) of the Mississippi River (MR) to investigate possible change in the complexity of the MR system due to human activities since 1940s. Unlike traditional entropy-based method that calculates entropy at only one single scale, the MSE analysis provided entropies over multiple time scales and thus accounts for multi-scale structures embedded in time series. It is found that the sample entropy (S E ) for Q of the MR and its two components, overland flow (OF) and base flow (BF), generally increase as time scale increases. More importantly, it is found that there have been entropy decreases in Q, OF, and BF over large time scales. In other words, the MR may have been losing its complexity since 1940s. We explain that the possible loss in the complexity of the MR system may be due to the major changes in land use and land cover and soil conservation practices in the MR basin since 1940s.