APPLICATION OF THE RHESSys MODEL TO A CALIFORNIA SEMIARID SHRUBLAND WATERSHED1

ABSTRACT: Distributed hydrologic models which link seasonal streamflow and soil moisture patterns with spatial patterns of vegetation are important tools for understanding the sensitivity of Mediterranean type ecosystems to future climate and land use change. RHESSys (Regional Hydro‐Ecologic Simulation System) is a coupled spatially distributed hydroecological model that is designed to be able to represent these feedbacks between hydrologic and vegetation carbon and nutrient cycling processes. However, RHESSys has not previously been applied to semiarid shrubland watersheds. In this study, the hydrologic submodel of RHESSys is evaluated by comparing model predictions of monthly and annual streamflow to stream gage data and by comparing RHESSys behavior to that of another hydrologic model of similar complexity, MIKESHE, for a 34 km² watershed near Santa Barbara, California. In model intercomparison, the differences in predictions of temporal patterns in streamflow, sensitivity of model predictions to calibration parameters and landscape representation, and differences in model estimates of soil moisture patterns are explored. Results from this study show that both models adequately predict seasonal patterns of streamflow response relative to observed data, but differ significantly in terms of estimates of soil moisture patterns and sensitivity of those patterns to the scale of landscape tessellation used to derive spatially distributed elements. This sensitivity has implications for implementing RHESSys as a tool to investigate interactions between hydrology and ecosystem processes.     

SOIL MOISTURE PREDICTION USING SUPPORT VECTOR MACHINES1

ABSTRACT: Herein, a recently developed methodology, Support Vector Machines (SVMs), is presented and applied to the challenge of soil moisture prediction. Support Vector Machines are derived from statistical learning theory and can be used to predict a quantity forward in time based on training that uses past data, hence providing a statistically sound approach to solving inverse problems. The principal strength of SVMs lies in the fact that they employ Structural Risk Minimization (SRM) instead of Empirical Risk Minimization (ERM). The SVMs formulate a quadratic optimization problem that ensures a global optimum, which makes them superior to traditional learning algorithms such as Artificial Neural Networks (ANNs). The resulting model is sparse and not characterized by the “curse of dimensionality.” Soil moisture distribution and variation is helpful in predicting and understanding various hydrologic processes, including weather changes, energy and moisture fluxes, drought, irrigation scheduling, and rainfall/runoff generation. Soil moisture and meteorological data are used to generate SVM predictions for four and seven days ahead. Predictions show good agreement with actual soil moisture measurements. Results from the SVM modeling are compared with predictions obtained from ANN models and show that SVM models performed better for soil moisture forecasting than ANN models.     

渗滤液回灌在实际应用中应注意的问题

本文介绍了垃圾填埋场渗滤液回灌的机理、优缺点,“干填埋”与“湿填埋”之间的区别。渗滤液回灌可增加填埋废物的含水率,加快垃圾的降解速率,减少渗滤液的处理时间,提高填埋气中甲烷的含量,加速填埋场稳定化进程。鉴于以上这些优点,渗滤液回灌作为一种渗滤液处理方式将会有极大的应用前景。但在实际应用中回灌的渗滤液容易泄漏而导致地下水污染,这是影响渗滤液回灌广泛应用的主要原因。为了避免使地下水受污染,本文总结和分析了渗滤液回灌在实际应用中应注意的问题。     

Curve Number Derivation for Watersheds Draining Two Headwater Streams in Lower Coastal Plain South Carolina,USA

The objective of this study was to assess curve number (CN) values derived for two forested headwater catchments in the Lower Coastal Plain (LCP) of South Carolina using a three‐year period of storm event rainfall and runoff data in comparison with results obtained from CN method calculations. Derived CNs from rainfall/runoff pairs ranged from 46 to 90 for the Upper Debidue Creek (UDC) watershed and from 42 to 89 for the Watershed 80 (WS80). However, runoff generation from storm events was strongly related to water table elevation, where seasonally variable evapotranspirative wet and dry moisture conditions persist. Seasonal water table fluctuation is independent of, but can be compounded by, wet conditions that occur as a result of prior storm events, further complicating flow prediction. Runoff predictions for LCP first‐order watersheds do not compare closely to measured flow under the average moisture condition normally associated with the CN method. In this study, however, results show improvement in flow predictions using CNs adjusted for antecedent runoff conditions and based on water table position. These results indicate that adaptations of CN model parameters are required for reliable flow predictions for these LCP catchments with shallow water tables. Low gradient topography and shallow water table characteristics of LCP watersheds allow for unique hydrologic conditions that must be assessed and managed differently than higher gradient watersheds.     

A future perspective on lithium-ion battery waste flows from electric vehicles

As a proactive step towards understanding future waste management challenges, this paper presents a future oriented material flow analysis (MFA) used to estimate the volume of lithium-ion battery (LIB) wastes to be potentially generated in the United States due to electric vehicle (EV) deployment in the near and long term future. Because future adoption of LIB and EV technology is uncertain, a set of scenarios was developed to bound the parameters most influential to the MFA model and to forecast “low,” “baseline,” and “high” projections of future end-of-life battery outflows from years 2015 to 2040. These models were implemented using technology forecasts, technical literature, and bench-scale data characterizing battery material composition. Considering the range from the most conservative to most extreme estimates, a cumulative outflow between 0.33 million metric tons and 4 million metric tons of lithium-ion cells could be generated between 2015 and 2040. Of this waste stream, only 42% of the expected materials (by weight) is currently recycled in the U.S., including metals such as aluminum, cobalt, copper, nickel, and steel. Another 10% of the projected EV battery waste stream (by weight) includes two high value materials that are currently not recycled at a significant rate: lithium and manganese. The remaining fraction of this waste stream will include materials with low recycling potential, for which safe disposal routes must be identified. Results also indicate that because of the potential “lifespan mismatch” between battery packs and the vehicles in which they are used, batteries with high reuse potential may also be entering the waste stream. As such, a robust end-of-life battery management system must include an increase in reuse avenues, expanded recycling capacity, and ultimate disposal routes that minimize risk to human and environmental health.     

EXAMPLES OF LANDFILL-GENERATED PLUMES IN LOW-RELIEF AREAS,SOUTHEAST FLORIDA1

ABSTRACT: Areas of low topographic relief have low water-table gradients and make the direction of movement of contaminants from land fills in the ground water difficult to predict from regional gradients alone. The landfill, nearby free-flowing ditches or canals, variations in hydraulic conductivity, and the influence of nearby pumping wells can all affect the direction of flow. In low-gradient areas the concepts of “upgradient” and “downgradient” are less useful in planning the location of monitoring wells than in areas of higher relief. Low-relief areas also may be affected by the discharge of mineralized water from deeper aquifers, naturally or through irrigation, which can mask geochemical surveys intended to detect landfill leachate. Examples of effects of low topographic relief are noted in southeast Florida where water-table gradients are 7×10^?-⁴ to 5×10^?-⁴ feet per foot. Water-table mounding beneath the landfill and the drainage effects of nearby ditches and well have created multiple leachate plumes in Stuart where one plume migrated in a direction opposite to the apparent regional gradient. In Coral Springs analysis suggests a bifurcating plume migrating along two narrow zones. In Fort Pierce it was difficult to detect leachate because of mineralized irrigation water and fertilizer runoff from an adjacent citrus grove.     

Variable Source Area Hydrology Modeling with the Water Erosion Prediction Project Model

In nondegraded watersheds of humid climates, subsurface flow patterns determine where the soil saturates and where surface runoff is occurring. Most models necessarily use infiltration‐excess (i.e., Hortonian) runoff for predicting runoff and associated constituents because subsurface flow algorithms are not included in the model. In this article, we modify the Water Erosion Prediction Project (WEPP) model to simulate subsurface flow correctly and to predict the spatial and temporal location of saturation, the associated lateral flow and surface runoff, and the location where the water can re‐infiltrate. The modified model, called WEPP‐UI, correctly simulated the hillslope drainage data from the Coweeta Hydrologic Laboratory hillslope plot. We applied WEPP‐UI to convex, concave, and S‐shaped hillslope profiles, and found that multiple overland flow elements are needed to simulate distributed lateral flow and runoff well. Concave slopes had the greatest runoff, while convex slopes had the least. Our findings concur with observations in watersheds with saturation‐excess overland flow that most surface runoff is generated on lower concave slopes, whereas on convex slopes runoff infiltrates before reaching the stream. Since the WEPP model is capable of simulating both saturation‐excess and infiltration‐excess runoff, we expect that this model will be a powerful tool in the future for managing water quality.     

UNSATURATED FLOW THROUGH SOLID WASTE LANDFILLS: MODEL AND SENSITIVITY ANALYSIS1

ABSTRACT: The movement of precipitation water infiltrating through the material (refuse) of solid waste landfills is examined via numerical solution of the equations of continuity, and motion (Darcy's Law). The solution of the equations is obtained by a fully implicit, finite-difference scheme. Both unsaturated and saturated surface conditions are considered, making the scheme suitable for real-time simulation of net precipitation and moisture redistribution events. A sensitivity analysis showed that for unsaturated surface conditions the solution is primarily affected by hydraulic conductivity and capillary diffusivity, and is relatively independent of the space and time steps. In addition, the precipitation averaging process is shown to be critical in the correct computation of moisture transport during the time period where the transition from unsaturated to saturated conditions occurs. The model presented herein is suitable for analysis of water movement through landfills, and the design of bottom collection systems.     

Using Multiple Watershed Models to Predict Water,Nitrogen, and Phosphorus Discharges to the Patuxent Estuary1

Boomer, Kathleen M.B., Donald E. Weller, Thomas E. Jordan, Lewis Linker, Zhi‐Jun Liu, James Reilly, Gary Shenk, and Alexey A. Voinov, 2012. Using Multiple Watershed Models to Predict Water, Nitrogen, and Phosphorus Discharges to the Patuxent Estuary. Journal of the American Water Resources Association (JAWRA) 1‐25. DOI: 10.1111/j.1752‐1688.2012.00689.x Abstract: We analyzed an ensemble of watershed models that predict flow, nitrogen, and phosphorus discharges. The models differed in scope and complexity and used different input data, but all had been applied to evaluate human impacts on discharges to the Patuxent River or to the Chesapeake Bay. We compared predictions to observations of average annual, annual time series, and monthly discharge leaving three basins. No model consistently matched observed discharges better than the others, and predictions differed as much as 150% for every basin. Models that agreed best with the observations in one basin often were among the worst models for another material or basin. Combining model predictions into a model average improved overall reliability in matching observations, and the range of predictions helped describe uncertainty. The model average was not the closest to the observed discharge for every material, basin, and time frame, but the model average had the highest Nash–Sutcliffe performance across all combinations. Consistently poor performance in predicting phosphorus loads suggests that none of the models capture major controls. Differences among model predictions came from differences in model structures, input data, and the time period considered, and also to errors in the observed discharge. Ensemble watershed modeling helped identify research needs and quantify the uncertainties that should be considered when using the models in management decisions.     

IMPACTS OF CLIMATE CHANGE ON AQUATIC ECOSYSTEM FUNCTIONING AND HEALTH1

ABSTRACT: We review published analyses of the effects of climate change on goods and services provided by freshwater ecosystems in the United States. Climate-induced changes must be assessed in the context of massive anthropogenic changes in water quantity and quality resulting from altered patterns of land use, water withdrawal, and species invasions; these may dwarf or exacerbate climate-induced changes. Water to meet instream needs is competing with other uses of water, and that competition is likely to be increased by climate change. We review recent predictions of the impacts of climate change on aquatic ecosystems in eight regions of North America. Impacts include warmer temperatures that alter lake mixing regimes and availability of fish habitat; changed magnitude and seasonality of runoff regimes that alter nutrient loading and limit habitat availability at low flow; and loss of prairie pothole wetlands that reduces waterfowl populations. Many of the predicted changes in aquatic ecosystems are a consequence of climatic effects on terrestrial ecosystems; shifts in riparian vegetation and hydrology are particularly critical. We review models that could be used to explore potential effects of climate change on freshwater ecosystems; these include models of instream flow, bioenergetics models, nutrient spiraling models, and models relating riverine food webs to hydrologic regime. We discuss potential ecological risks, benefits, and costs of climate change and identify information needs and model improvements that are required to improve our ability to predict and identify climate change impacts and to evaluate management options.     

Hydrologic modeling as a predictive basis for ecological restoration of salt marshes

Roads, bridges, causeways, impoundments, and dikes in the coastal zone often restrict tidal flow to salt marsh ecosystems. A dike with tide control structures, located at the mouth of the Herring River salt marsh estuarine system (Wellfleet, Massachusetts) since 1908, has effectively restricted tidal exchange, causing changes in marsh vegetation composition, degraded water quality, and reduced abundance of fish and macroinvertebrate communities. Restoration of this estuary by reintroduction of tidal exchange is a feasible management alternative. However, restoration efforts must proceed with caution as residential dwellings and a golf course are located immediately adjacent to and in places within the tidal wetland. A numerical model was developed to predict tide height levels for numerous alternative openings through the Herring River dike. Given these model predictions and knowledge of elevations of flood-prone areas, it becomes possible to make responsible decisions regarding restoration. Moreover, tidal flooding elevations relative to the wetland surface must be known to predict optimum conditions for ecological recovery. The tide height model has a universal role, as demonstrated by successful application at a nearby salt marsh restoration site in Provincetown, Massachusetts. Salt marsh restoration is a valuable management tool toward maintaining and enhancing coastal zone habitat diversity. The tide height model presented in this paper will enable both scientists and resource professionals to assign a degree of predictability when designing salt marsh restoration programs.     

A PARAMETRIC MODEL CALIBRATED WITH A PHYSICALLY BASED MODEL FOR RUNOFF PREDICTION FROM UNGAGED STREAMS1

ABSTRACT: Recent developments in the numerical solution of the governing partial differential equations for overland and channel flow should make possible physically based models which predict runoff from ungaged streams. However, these models, which represent the watershed by sets of intersecting planes, are complex and require much computer time. Parametric models exist that have the advantage of being relatively simple, and once calibrated are inexpensive to use and require limited data input. In this study, a procedure was developed for calibrating a parametric model against a physically based model, utilizing base areas of one acre and one square mile, with the expectation that base areas can be combined to model real watersheds. Simulation experiments with the physically based model showed that, for the one-acre base area, the dominant parameter (cell storage ratio, K) related to the slope and friction of the planes, whereas for one square-mile areas, the dominant parameters (K plus a lag factor, L) relate to channel properties. These parameters decreased exponentially as rainfall intensity increased.     

Potential for enhanced phytoremediation of landfills using biosolids – a review

Despite the use of recyclable materials increasing worldwide, waste disposal to landfill remains the most common method of waste management because it is simple and relatively inexpensive. Although landfill disposal is an effective waste management system, if not managed correctly, a number of potential detrimental environmental impacts have been identified including soil and ground water contamination, leachate generation, and gas emissions. In particular, improper post-closure treatment of landfills or deterioration of the conventional clay landfill capping were shown to result in land degradation which required remediation to secure contaminants within the landfill site.Phytoremediation is an attractive technology for landfill remediation, as it can stabilize soil and simultaneously remediate landfill leachate. In addition, landfill phytoremediation systems can potentially be combined with landfill covers (Phytocapping) for hydrological control of infiltrated rainfall. However, for the successful application of any phytoremediation system, the effective establishment of appropriate, desired vegetation is critical. This is because the typically harsh and sterile nature of landfill capping soil limits the sustainable establishment of vegetation. Therefore, the physicochemical properties of landfill capping soils often need to be improved by incorporating soil amendments. Biosolids are a common soil amendment and will often meet these demanding conditions because they contain a variety of plant nutrients such as nitrogen, phosphate, potassium, as well as a large proportion of organic matter. Such amendment will also ameliorate the physical properties of the capping soils by increasing porosity, moisture content, and soil aggregation. Contaminants which potentially originate from biosolids will also be remediated by activities congruent with the establishment of plants and bacteria.     

Gradient modeling: A new approach to fire modeling and wilderness resource management

Managers of wilderness resources must maintain, preserve, and sometimes restore pristine ecosystems while providing for public use and enjoyment of these areas. These managers require a resource information system that can store, retrieve and integrate basic data, synthesize components to solve particular problems, and provide simulations and predictions of natural processes and management actions. Traditional information systems based on land classification and type-mapping do not provide these capabilities.Gradient modeling, a new approach to resource management and forest fire simulation, has been developed to meet these needs in Glacier National Park. The method links four major components: (1) a terrestrial site inventory coded from aerial photographs that offers 10-m resolution; (2) gradient models of vegetation and fuel that derive quantitative stand compositional data from the parameters stored in the coded inventory; (3) a fuel moisture and microclimate model that extrapolates basestation weather data to remote sites using the parameters stored in the inventory; and (4) fire behavior and fire ecology models that integrate the data from the inventory and models to calculate real-time fire behavior and ecological succession following a fire.     

WATERSHED RESPONSES TO CLIMATE CHANGE AT GLACIER NATIONAL PARK1

ABSTRACT: We have developed an approach which examines ecosystem function and the potential effects of climatic shifts. The Lake McDonald watershed of Glacier National Park was the focus for two linked research activities: acquisition of baseline data on hydrologic, chemical and aquatic organism attributes that characterize this pristine northern rocky mountain watershed, and further developing the Regional Hydro-Ecosystem Simulation System (RHESSys), a collection of integrated models which collectively provide spatially explicit, mechanistically-derived outputs of ecosystem processes, including hydrologic outflow, soil moisture, and snow-pack water equivalence. In this unique setting field validation of RHESSys, outputs demonstrated that reasonable estimates of SWE and streamflow are being produced. RHESSys was used to predict annual stream discharge and temperature. The predictions, in conjunction with the field data, indicated that aquatic resources of the park may be significantly affected. Utilizing RHESSys to predict potential climate scenarios and response of other key ecosystem components can provide scientific insights as well as proactive guidelines for national park management.     

The effects of leachate recirculation with supplemental water addition on methane production and waste decomposition in a simulated tropical landfill

In order to increase methane production efficiency, leachate recirculation is applied in landfills to increase moisture content and circulate organic matter back into the landfill cell. In the case of tropical landfills, where high temperature and evaporation occurs, leachate recirculation may not be enough to maintain the moisture content, therefore supplemental water addition into the cell is an option that could help stabilize moisture levels as well as stimulate biological activity. The objectives of this study were to determine the effects of leachate recirculation and supplemental water addition on municipal solid waste decomposition and methane production in three anaerobic digestion reactors. Anaerobic digestion with leachate recirculation and supplemental water addition showed the highest performance in terms of cumulative methane production and the stabilization period time required. It produced an accumulated methane production of 54.87 l/kg dry weight of MSW at an average rate of 0.58 l/kg dry weight/d and reached the stabilization phase on day 180. The leachate recirculation reactor provided 17.04 l/kg dry weight at a rate of 0.14l/kg dry weight/d and reached the stabilization phase on day 290. The control reactor provided 9.02 l/kg dry weight at a rate of 0.10 l/kg dry weight/d, and reached the stabilization phase on day 270. Increasing the organic loading rate (OLR) after the waste had reached the stabilization phase made it possible to increase the methane content of the gas, the methane production rate, and the COD removal. Comparison of the reactors' efficiencies at maximum OLR (5 kgCOD/m(3)/d) in terms of the methane production rate showed that the reactor using leachate recirculation with supplemental water addition still gave the highest performance (1.56 l/kg dry weight/d), whereas the leachate recirculation reactor and the control reactor provided 0.69 l/kg dry weight/d and 0.43 l/kg dry weight/d, respectively. However, when considering methane composition (average 63.09%) and COD removal (average 90.60%), slight differences were found among these three reactors.     

RUNOFF MODELING OF A MOUNTAINOUS CATCHMENT USING TOPMODEL: A CASE STUDY1

ABSTRACT: The rainfall‐runoff response of the Tygarts Creek Catchment in eastern Kentucky is studied using TOPMODEL, a hydrologic model that simulates runoff at the catchment outlet based on the concepts of saturation excess overland flow and subsurface flow. Unlike the traditional application of this model to continuous rainfall‐runoff data, the use of TOPMOEL in single event runoff modeling, specifically floods, is explored here. TOPMODEL utilizes a topographic index as an indicator of the likely spatial distribution of rainfall excess generation in the catchment. The topographic index values within the catchment are determined using the digital terrain analysis procedures in conjunction with digital elevation model (DEM) data. Select parameters in TOPMODEL are calibrated using an iterative procedure to obtain the best‐fit runoff hydrograph. The calibrated parameters are the surface transmissivity, T_O, the transmissivity decay parameter, m, and the initial moisture deficit in the root zone, S_r0. These parameters are calibrated using three storm events and verified using three additional storm events. Overall, the calibration results obtained in this study are in general agreement with the results documented from previous studies using TOPMODEL. However, the parameter values did not perform well during the verification phase of this study.     

A COMPARISON OF MODELS PREDICTING GROUND WATER LEVELS ON HILLSIDE SLOPES1

ABSTRACT: A comparative study of ground water level predictions on hillside slopes using two models is presented. The models are a simplified mass balance model that has components for evapotran-spiration, recharge, and drainage; and a two-dimensional finite difference model that employs kriging to estimate soil parameters and accounts for non-uniform thickness of the soil layer. These models are representative of a wide range of modeling capabilities and are used to illustrate the sensitivity of ground water level predictions to the sophistication of the modeling techniques. The drainage and recharge components of the two models are evaluated and the importance of unsaturated flow in recharge computations is underscored. Piezometric observations in a small drainage depression on the slope of Kennel Creek Valley in Tongass National Forest, Alaska, were used to evaluate the two models. The results show that, although the predictions differ from the field observations, the simple physically-based mass balance model predicts the ground water levels as well as the two-dimensional model. It is suggested that caution should be exercised in using complex models to validate simpler models.     

Multi-objective optimization of waste and resource management in industrial networks – Part I: Model description

This article presents a general multi-objective mixed-integer linear programming (MILP) optimization model aimed at providing decision support for waste and resources management in industrial networks. The MILP model combines material flow analysis, process models of waste treatments and other industrial processes, life cycle assessment, and mathematical optimization techniques within a unified framework. The optimization is based on a simplified representation of industrial networks that makes use of linear process models to describe the flows of mass and energy. Waste-specific characteristics, e.g. heating value or heavy metal contamination, are considered explicitly along with potential technologies or process configurations. The systems perspective, including both provision of waste treatment and industrial production, enables constraints imposed upon the systems, e.g. available treatment capacities, to be explicitly considered in the model. The model output is a set of alternative system configurations in terms of distribution of waste and resources that optimize environmental and economic performance. The MILP also enables quantification of the improvement potential compared to a given reference state. Trade-offs between conflicting objectives are identified through the generation of a set of Pareto-efficient solutions. This information supports the decision making process by revealing the quantified performance of the efficient trade-offs without relying on weighting being expressed prior to the analysis. Key features of the modeling approach are illustrated in a hypothetical case. The optimization model described in this article is applied in a subsequent paper (Part II) to assess and optimize the thermal treatment of sewage sludge in a region in Switzerland.