Description: The excessive exploitation of groundwater aquifers is emerging as a worldwide problem, but it is nowhere as dramatic and consequential as it is in India, the world's largest consumer, where hundreds of millions of people depend on it. Usually the problem is framed in terms of a long-term decline in water tables and its consequence for extraction costs, resource depletion, and the sustainability of irrigated agriculture. Here a comparative analysis is provided of coupled groundwater, energy, and irrigation dynamics in two groundwater intensive regions in India that differ in their underlying hydrogeology—the Indian Punjab with its deep alluvial aquifers and the Telangana region in south-central India with its shallow hard rock aquifers. Using a simple modeling framework and piezometric and agricultural time series, we show that in shallow aquifers the sense in which extraction is excessive is different, and is related to the short-term reliability of water supply rather than long-term sustainability. This has important repercussions for irrigated agricultural economies.

Description: The self-purifying capacity of aquifers strongly depends on the attenuation of waterborne contaminants, i.e., irreversible loss of contaminant mass on a given scale as a result of coupled transport and transformation processes. A general formulation of tracer attenuation in groundwater is presented. Basic sensitivities of attenuation to macrodispersion and retention are illustrated for a few typical retention mechanisms. Tracer recovery is suggested as an experimental proxy for attenuation. Unique experimental data of tracer recovery in crystalline rock compare favorably with the theoretical model that is based on diffusion-controlled retention. Non-Fickian hydrodynamic transport has potentially a large impact on field-scale attenuation of dissolved contaminants.

Description: We propose closed-form approximate solutions for the moments of a nonreactive tracer that can be used in applications, such as risk analysis. This is in line with the tenet that analytical solutions provide useful information, with minimum cost, during initial site characterization efforts and can serve as a preliminary screening tool when used with prior knowledge. We show that with the help of a few assumptions, the first-order solutions of the concentration moments proposed by Fiori and Dagan (2000) can be further simplified to assume a form similar to well-known deterministic solutions, therefore facilitating their use in applications. A highly anisotropic formation is assumed, and we neglect the transverse components of the two-particle correlation trajectory. The proposed solution compares well with the work of Fiori and Dagan while presenting the same simplicity of use of existing solutions for homogeneous porous media.

Description: Methods to select parsimonious and hydrologically consistent model structures are useful for evaluating dominance of hydrologic processes and representativeness of data. While information criteria (appropriately constrained to obey underlying statistical assumptions) can provide a basis for evaluating appropriate model complexity, it is not sufficient to rely upon the principle of maximum likelihood (ML) alone. We suggest that one must also call upon a “principle of hydrologic consistency,” meaning that selected ML structures and parameter estimates must be constrained (as well as possible) to reproduce desired hydrological characteristics of the processes under investigation. This argument is demonstrated in the context of evaluating the suitability of candidate model structures for lumped water balance modeling across the continental United States, using data from 307 snow-free catchments. The models are constrained to satisfy several tests of hydrologic consistency, a flow space transformation is used to ensure better consistency with underlying statistical assumptions, and information criteria are used to evaluate model complexity relative to the data. The results clearly demonstrate that the principle of consistency provides a sensible basis for guiding selection of model structures and indicate strong spatial persistence of certain model structures across the continental United States. Further work to untangle reasons for model structure predominance can help to relate conceptual model structures to physical characteristics of the catchments, facilitating the task of prediction in ungaged basins.

Description: Plantation forestry is an increasingly important land use in Australia. While plantations can present significant environmental benefits such as salinity and erosion controls, their impact on streamflow needs to be recognized. This study evaluated the impacts of plantation and climate variability on streamflow from catchments in Australia. In total 15 catchments were selected based on the availability of streamflow, meteorological, and plantation information. The catchment areas range from 0.6 to 1136 km2 and represent different climatic conditions and management practices. The Mann–Kendall test was used to estimate trends in the annual streamflow, rainfall, potential evaporation, and runoff ratio. The plantation effect on streamflow was determined with the time-trend analysis method, while the effect of climate variability was calculated using the sensitivity-based approach. All the selected catchments showed reductions in annual streamflow and runoff ratio over the period of the records. The results indicate that plantation expansions accounted for 28% to 106% of the observed total streamflow reductions, while climate variability was responsible for 5% to 80% of the total streamflow reductions. It is evident that both plantation expansions and climate variability contributed to the observed streamflow reductions. In most of the catchments, the effect of plantation expansion on streamflow was more important than that of climate variability and is likely to have exacerbated the effect of climate variability on streamflow. Plantation expansions can reduce streamflow from both small and large catchments as this study demonstrated and the relative streamflow reduction can be linearly related to percentage plantation area in a catchment.

Description: We investigate the upscaling of dispersion from a pore-scale analysis of Lagrangian velocities. A key challenge in the upscaling procedure is to relate the temporal evolution of spreading to the pore-scale velocity field properties. We test the hypothesis that one can represent Lagrangian velocities at the pore scale as a Markov process in space. The resulting effective transport model is a continuous time random walk (CTRW) characterized by a correlated random time increment, here denoted as correlated CTRW. We consider a simplified sinusoidal wavy channel model as well as a more complex heterogeneous pore space. For both systems, the predictions of the correlated CTRW model, with parameters defined from the velocity field properties (both distribution and correlation), are found to be in good agreement with results from direct pore-scale simulations over preasymptotic and asymptotic times. In this framework, the nontrivial dependence of dispersion on the pore boundary fluctuations is shown to be related to the competition between distribution and correlation effects. In particular, explicit inclusion of spatial velocity correlation in the effective CTRW model is found to be important to represent incomplete mixing in the pore throats.

Description: Many flood events involving water and sediments have been characterized using classic hydraulics principles, assuming the existence of critical flow and many other simplifications. In this paper, hyperconcentrated flow discharge was evaluated by using paleoflood reconstructions (based on paleostage indicators [PSI]) combined with a detailed hydraulic analysis of the critical flow assumption. The exact location where this condition occurred was established by iteratively determining the corresponding cross section, so that specific energy is at a minimum. In addition, all of the factors and parameters involved in the process were assessed, especially those related to the momentum equation, existing shear stresses in the wetted perimeter, and nonhydrostatic and hydrostatic pressure distributions. The superelevation of the hyperconcentrated flow, due to the flow elevation curvature, was also estimated and calibrated with the PSI. The estimated peak discharge was established once the iterative process was unable to improve the fit between the simulated depth and the depth observed from the PSI. The methodological approach proposed here can be applied to other higher-gradient mountainous torrents with a similar geomorphic configuration to the one studied in this paper. Likewise, results have been derived with fewer uncertainties than those obtained from standard hydraulic approaches, whose simplifying assumptions have not been considered.

Description: Modern environmental management and decision-making is based on the use of increasingly complex numerical models. Such models have the advantage of allowing representation of complex processes and heterogeneous system property distributions inasmuch as these are understood at any particular study site. The latter are often represented stochastically, this reflecting knowledge of the character of system heterogeneity at the same time as it reflects a lack of knowledge of its spatial details. Unfortunately, however, complex models are often difficult to calibrate because of their long run times and sometimes questionable numerical stability. Analysis of predictive uncertainty is also a difficult undertaking when using models such as these. Such analysis must reflect a lack of knowledge of spatial hydraulic property details. At the same time, it must be subject to constraints on the spatial variability of these details born of the necessity for model outputs to replicate observations of historical system behavior. In contrast, the rapid run times and general numerical reliability of simple models often promulgates good calibration and ready implementation of sophisticated methods of calibration-constrained uncertainty analysis. Unfortunately, however, many system and process details on which uncertainty may depend are, by design, omitted from simple models. This can lead to underestimation of the uncertainty associated with many predictions of management interest. The present paper proposes a methodology that attempts to overcome the problems associated with complex models on the one hand and simple models on the other hand, while allowing access to the benefits each of them offers. It provides a theoretical analysis of the simplification process from a subspace point of view, this yielding insights into the costs of model simplification, and into how some of these costs may be reduced. It then describes a methodology for paired model usage through which predictive bias of a simplified model can be detected and corrected, and postcalibration predictive uncertainty can be quantified. The methodology is demonstrated using a synthetic example based on groundwater modeling environments commonly encountered in northern Europe and North America.

Description: Quantile-quantile plots (QQ plots) are often applied to investigate tail behavior in extreme value analysis. When used for flood frequency analysis, based on river flow data, dependence in these data affects the extreme value distribution's tail behavior in the QQ plot. This problem is investigated on the basis of both synthetic and observed river flow series. The synthetic series are generated on the basis of a stochastic simulation procedure, which allows the real statistical flow properties to be known. Through simulation study, we demonstrate that serial dependence causes bending behavior in the QQ plot in the region of higher quantiles. This leads to the estimating error when the slope of the QQ plot is used as an estimator in the extreme value analysis. A correction method is proposed by modifying the plotting position using the extremal index.

Description: Understanding the mobilization processes of phosphorus (P) in the plow layer are essential to quantify potential P losses and suggest management strategies to reduce P losses. This study is aimed at examining nonequilibrium exchange dynamics on the mobilization of slurry-amended Br−, and dissolved and particulate P in slurry-injected soils. We compared leaching from intact soil columns (20 cm diam., 20 cm high) under unsaturated flow (suction at the lower boundary of 5 hPa) subjected to continuous irrigation at 2 mm hr−1, and intermittent irrigation at 2 mm hr−1 and 10 mm hr−1 to with interruptions of 10 h duration simulate periodic precipitation events. Suction was increased to 20 hPa during interruptions to allow drainage of the largest pores. Irrigation interruptions induced fluctuations in leaching of nonreactive tracers, particles, and particulate P indicating nonequilibrium transport. A nonreactive tracer, 3H2O, applied with irrigation water, diffused from mobile to less mobile pore regions during interruptions, leading to a lower mass recovery during low-intermittent (76.4%) compared with continuous irrigation (86.6%). In contrast, mass recovery of slurry-injected Br− increased as Br− diffused from less mobile to mobile pore regions during low-intermittent (53%–64%) compared with continuous irrigation (42%–47%). Despite high fluctuations during the leaching of particles and particulate P during low-intermittent irrigation, accumulated values did not differ from continuous irrigation. Increased preferential flow during high-intermittent irrigation lowered the mass exchange between pore regions of nonreactive tracers, particles, and particulate P compared with low-intermittent irrigation. The leaching of dissolved inorganic and organic P was low during all of the experiments and scarcely affected by the irrigation regime. These results highlight that nonequilibrium exchange dynamics are important when evaluating processes affecting mobilization and transport in structured soils. Leaching experiments, including cycles of irrigation interruptions and gravitational drainage, thus, adds significantly to the understanding and interpretation of processes affecting mobilization and transport under natural conditions.