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.     

Index models to evaluate the risk of phosphorus and nitrogen loss at catchment scales

This paper investigates index models as a tool to estimate the risk of N and P source strengths and loss at the catchment scale. The index models assist managers in improving the focus of remediation actions that reduce nutrient delivery to waterbodies. N and P source risk factors (e.g. soil nutrient concentrations) and transport risk factors (e.g. distance-to-streams) are used to determine the overall risk of nutrient loss for a case study in the Tuross River catchment of coastal southeast Australia. In the development of the N index model for Tuross, particulate N was considered important based on the observed event water quality data. In contrast to previous N index models, erosion and contributing distance were therefore included in the Tuross River catchment N index. Event-based water quality monitoring, and soil information, or in data-poor catchments conceptual understanding, are essential to represent catchment-scale processes. The techniques have high applicability in other catchments, and are complementary to other modelling techniques such as process-based semi-distributed modelling. Index models generally provide much more detailed spatial resolution than fully- or semi-distributed conceptual modelling approaches. Semi-distributed models can be used to quantify nutrient loads and provide overall direction to set the broad focus of management. Index models can then be used to refine on-the-ground investigations and investment priorities. In this way semi-distributed models can be combined with index models to provide a set of powerful tools to influence management decisions and outcomes.     

FORECASTING DEMAND FOR RECREATIONAL BOATS1

ABSTRACT: This paper suggests theoretical models to forecast the demand for recreational boats in a metropolitan area, and their expected usage in various regional water bodies and marinas. The models, which are similar to those used in transportation studies, are implemented using statistical regression analysis and can be easily applied to a wide range of case studies. The models have been used to forecast demand for boats by type and size in the Cleveland S.M.S.A. The proportion of boats attracted to boating facilities on Lake Erie has been calculated. This study is significant in suggesting a theoretically sound methodology to project facilities required for recreational boats.     

HYDRODYNAMIC MODELS OF HUMAN STABILITY IN A FLOOD1

ABSTRACT: Major loss of life can occur in a flood when people are toppled by floodwater currents. Three approximate mechanical models and two empirical models of the hydrodynamics of toppling are presented and calibrated to align with available experimental observations to assist the analysis of the risk of life loss. The mechanical models consider circular cylindrical, square cylindrical and cylindrical composite, heavy bodies assembled to represent a human immersed in a flow field and subject to drag and buoyancy forces. The models can account for the height and weight of the exposed persons, and the velocity and depth of the flow. The models are in good mutual agreement and, when calibrated, yield failure functions that can be used to calculate the probability of loss of stability.     

STOCHASTIC ANALYSIS OF TIME-AGGREGATED HYDROLOGIC DATA1

Stochastic models fitted to hydrologic data of different time scales are interrelated because the higher time scale data (aggregated data) are derived from those of lower time scale. Relationships between the statistical properties and parameters of models of aggregated data and of original data are examined in this paper. It is also shown that the aggregated data can be more accurately predicted by using a valid model of the original data than by using a valid model of the aggregated data. This property is particularly important in forecasting annual values because only a few annual values are usually available and the resulting forecasts are relatively inaccurate if models based only on annual data are used. The relationships and forecasting equations are developed for general aggregation time and can be used for hourly and daily, daily and monthly or monthly and yearly data. The method is illustrated by using monthly and yearly streamflow data. The results indicate that various statistical characteristics and parameters of the model of annual data can be accurately estimated by using the monthly data and forecasts of annual data by using monthly models have smaller one step ahead mean square error than those obtained by using annual data models.     

Regression modeling of streamflow, baseflow, and runoff using geographic information systems

Regression models for predicting total streamflow (TSF), baseflow (TBF), and storm runoff (TRO) are needed for water resource planning and management. This study used 54 streams with >20 years of streamflow gaging station records during the period October 1971 to September 2001 in Pennsylvania and partitioned TSF into TBF and TRO. TBF was considered a surrogate of groundwater recharge for basins. Regression models for predicting basin-wide TSF, TBF, and TRO were developed under three scenarios that varied in regression variables used for model development. Regression variables representing basin geomorphological, geological, soil, and climatic characteristics were estimated using geographic information systems. All regression models for TSF, TBF, and TRO had R(2) values >0.94 and reasonable prediction errors. The two best TSF models developed under scenarios 1 and 2 had similar absolute prediction errors. The same was true for the two best TBF models. Therefore, any one of the two best TSF and TBF models could be used for respective flow prediction depending on variable availability. The TRO model developed under scenario 1 had smaller absolute prediction errors than that developed under scenario 2. Simplified Area-alone models developed under scenario 3 might be used when variables for using best models are not available, but had lower R(2) values and higher or more variable prediction errors than the best models.     

APPROACHES TO MULTIVARIATE MODELING OF WATER RESOURCES TIME SERIES1

ABSTRACT: Alternative approaches suggested for modeling multiseries of water resources systems are reviewed and compared. Most approaches fall within the general framework of multivariate ARMA models. Formal modeling procedures suggest a three-stage iterative process, namely: model identification, parameter estimation and diagnostic checks. Although a number of statistical tools are already available to follow such modeling process, in general, it is not an easy task, especially if high order vector ARMA models are used. However, simpler ARMA models such as the contemporaneous and the transfer-function models may be sufficient for most applications in water resources. Two examples of modeling bivariate and trivariate streamflow series are included. Alternative modeling procedures are used and compared by using data generation techniques. The results obtained suggest that low order models, as well as contemporaneous ARMA models, reproduce quite well the main statistical characteristics of the time series analyzed. It is assumed that the same conclusions apply for most water resources time series.     

NONLINEAR SOLUTIONS OF THE BQUSSINESQ EQUATION AND COMPARISONS WITH FIELD OBSERVATIONS1

ABSTRACT: Two models based on variations of the one dimensional Boussinesq equation are presented. The models are formulated by treating each of the two nonlinearities appearing in the equation separately, and the resulting equations are solved by implicit finite difference techniques. The models have been used to predict drawdowns created from large scale pumping at an open coal mine pit dewatering project in Poland. The predictions were found to be in good agreement with data collected over a period of seven years.     

Conceptual Design of a System for Selecting Appropriate Groundwater Models in Groundwater Protection Programs

/ An effective groundwater protection program requires understanding of water flow and contaminant transport processes in the subsurface. Although many mathematical models have been developed to simulate the processes, few actually are used in groundwater protection programs due to the difficulties in data collection, model selection, and model implementation. This study presents a conceptual design of a GIS-supported model selection system that evaluates available data and mathematical models to facilitate groundwater protection programs. Steady-state groundwater and contaminant transport models applied in isotropic aquifers are placed into four classes to simulate conservative or nonconservative contaminant transports in simple or complex geohydrological conditions. After analyzing specific study objectives, available data, and model requirements, the proposed system selects a class of models that can be used in simulation and recommends any need for additional data collection. This study initiates an effort to integrate GIS, mathematical models, and expert knowledge in one system to promote the application of appropriate groundwater models. The new technology of GIS and digital data-base management makes it possible to develop such a system in practice.KEY WORDS: Groundwater models; Geographic information systems     

CONJUNCTIVE USE OF SEA AND FRESH WATER RESOURCES: AN INTEGER PROGRAMMING APPROACH1

ABSTRACT Mathematical models are formulated for selection of water resources projects to meet the future additional water requirements of a given region at the minimum present worth cost. The projects available are surface water reservoirs and desalination plants. The modles are used for selecting both the development sequence of projects and their optimum sizes. Decisions with regard to planning time horizon and discount rates are made outside of the mathematical model. The algorithm used for solving these models is an integer programming routine using the implicit enumeration technique. Some computational results are presented for a hypothetical case.     

ACCURACY AND CONSISTENCY OF WATER‐CURRENT MIETERS1

ABSTRACT: The measurement of discharge in natural streams requires hydrographers to use accurate meters that have consistent performance among meters of the same model. This paper presents the results of an investigation into the accuracy and consistency of four models of current meters‐Price Type‐AA, Price Pygmy, Marsh McBirney 2000, and Swoffer 2100. Test results for six meters of each model are presented. Variation of meter performance within a model is used as an indicator of consistency, and percent velocity error that is computed from a measured reference velocity is used as an indicator of meter accuracy. Velocities measured by each meter are also compared to the manufacturer's published or advertised accuracy limits. The investigation found the Price models to be more accurate and consistent than the other models. The Price models met their respective accuracy limits over the range of test velocities better than the other models. The Marsh McBirney model usually measured within its accuracy specification. The Swoffer meters did not meet the stringent Swoffer accuracy limits for all the velocities tested. The Swoffer model had accuracies similar to the Price Type‐AA model when individual meter rating equations were computed and used. Every model tested had meters that did not meet manufacturer accuracy limits. Because current meters are not consistently accurate within a model, hydrographers should periodically check meters against a velocity standard.     

Modelling land use change with generalized linear models--a multi-model analysis of change between 1860 and 2000 in Gallatin Valley, Montana

This paper develops an approach to modelling land use change that links model selection and multi-model inference with empirical models and GIS. Land use change is frequently studied, and understanding gained, through a process of modelling that is an empirical analysis of documented changes in land cover or land use patterns. The approach here is based on analysis and comparison of multiple models of land use patterns using model selection and multi-model inference. The approach is illustrated with a case study of rural housing as it has developed for part of Gallatin County, Montana, USA. A GIS contains the location of rural housing on a yearly basis from 1860 to 2000. The database also documents a variety of environmental and socio-economic conditions. A general model of settlement development describes the evolution of drivers of land use change and their impacts in the region. This model is used to develop a series of different models reflecting drivers of change at different periods in the history of the study area. These period specific models represent a series of multiple working hypotheses describing (a) the effects of spatial variables as a representation of social, economic and environmental drivers of land use change, and (b) temporal changes in the effects of the spatial variables as the drivers of change evolve over time. Logistic regression is used to calibrate and interpret these models and the models are then compared and evaluated with model selection techniques. Results show that different models are 'best' for the different periods. The different models for different periods demonstrate that models are not invariant over time which presents challenges for validation and testing of empirical models. The research demonstrates (i) model selection as a mechanism for rating among many plausible models that describe land cover or land use patterns, (ii) inference from a set of models rather than from a single model, (iii) that models can be developed based on hypothesised relationships based on consideration of underlying and proximate causes of change, and (iv) that models are not invariant over time.     

Land Management in the American Southwest: A State-and-Transition Approach to Ecosystem Complexity

State-and-transition models are increasingly being used to guide rangeland management. These models provide a relatively simple, management-oriented way to classify land condition (state) and to describe the factors that might cause a shift to another state (a transition). There are many formulations of state-and-transition models in the literature. The version we endorse does not adhere to any particular generalities about ecosystem dynamics, but it includes consideration of several kinds of dynamics and management response to them. In contrast to previous uses of state-and-transition models, we propose that models can, at present, be most effectively used to specify and qualitatively compare the relative benefits and potential risks of different management actions (e.g., fire and grazing) and other factors (e.g., invasive species and climate change) on specified areas of land. High spatial and temporal variability and complex interactions preclude the meaningful use of general quantitative models. Forecasts can be made on a case-by-case basis by interpreting qualitative and quantitative indicators, historical data, and spatially structured monitoring data based on conceptual models. We illustrate how science- based conceptual models are created using several rangeland examples that vary in complexity. In doing so, we illustrate the implications of designating plant communities and states in models, accounting for varying scales of pattern in vegetation and soils, interpreting the presence of plant communities on different soils and dealing with our uncertainty about how those communities were assembled and how they will change in the future. We conclude with observations about how models have helped to improve management decision-making.     

A review of sediment predictive techniques as viewed from the perspective of nonpoint pollution management

User-oriented criteria for the evaluation of physically based management models are presented. These criteria emphasize the utility rather than the elegance of the model. The standards are then applied to efforts at predicting non-point pollutant loadings. In particular a critical review of sediment pollution is used as the basis for the evaluation of sediment yield models as management tools. A wide range of sediment yield models are rated and recommendations for their use are made.     

Planning Models for Sustainable Water Resource Development

This paper intends to present a critical review of the planning models that can be used for sustainable water resource development. Three types of models are identified and assessed: (1) economic analysis models; (2) decision analysis models; and (3) systems analysis models. The methodology adopted in this paper is based on first describing the different types of models and then synthesizing and evaluating these models in terms of their theoretical underpinnings, applications, strengths and weaknesses. Each model is investigated with respect to its utility in addressing sustainability in water resource management. The study concludes that decision-based and system-based models may offer a wider spectrum of concepts than economic models in addressing multi-objective, multi-actor or 'wicked' problems in water management and resource sustainability.     

A method to create simplified versions of existing habitat suitability index (HSI) models

The habitat evaluation procedures (HEP), developed by the US Fish and Wildlife Service, are widely used in the United States to determine the impacts of major construction projects on fish and wildlife habitats. HEP relies heavily on habitat suitability index (HSI) models that use measurements of important habitat characteristics to rate habitat quality for a species on a scale of 0 (unsuitable) to 1.0 (optimal). This report describes a method to simplify existing HSI models to reduce the time and expense involved in sampling habitat variables. Simplified models for three species produced HSI values within 0.2 of those predicted by the original models 90% of the time. Simplified models are particularly useful for rapid habitat inventories and evaluations, wildlife management, and impact assessments in extensive areas or with limited time and personnel.     

Comparison of Morphodynamic Models for the Lower Yellow River1

Xia, Junqiang, Zhengbing Wang, Yanping Wang, and Xin Yu, 2012. Comparison of Morphodynamic Models for the Lower Yellow River. Journal of the American Water Resources Association (JAWRA) 1‐18. DOI: 10.1111/jawr.12002 Abstract: Significant channel adjustments often occur during flood seasons in the Lower Yellow River (LYR), and it is a challenging work to accurately simulate the morphodynamic processes in the LYR using numerical models. A comparison of two morphodynamic models (Delft3D and 2DLLCDM) for the LYR is presented herein to identify critical improvements for these models. The concepts of these models are first compared with each other. The models were then used to simulate the processes of flood routing, sediment transport, and morphological changes occurring in a braided reach of the LYR. The differences were investigated between the simulated results from these models and corresponding field measurements, and the results indicate that: (1) the hydrodynamic processes calculated by both models agree closely with the measurements if an appropriate Manning’s roughness coefficient is used; (2) the concentrations of suspended load at the downstream boundary calculated by the models agree reasonably with the observed data; and (3) the predicted cross‐sectional profiles obtained from these models do not correspond well with the measurements. Based on these findings, the weak aspects of the models are clarified, and three critical improvements are recommended, including: (1) the development of roughness predictor; (2) the refinement of graded sediment transport capacity formulation; and (3) the consideration of bank erosion module. These improvements need to be implemented in the future.     

Modeling Animal Habitats Based on Cover Types: A Critical Review

The simplest type of model describing animal habitats is a “cover-type model,” in which a species is assumed to be present in certain vegetation types and absent in others. Ecologists and managers use these models to predict animal distributions for gap analysis and conservation planning. Critics, however, have suggested that the models are overly simplistic and inaccurate. We reviewed the use of cover-type models including assessing their error rates, diagnosing the problems with these models, and determining how they should best be used by managers. To determine models’ accuracy rates, we conducted a meta-analysis of 35 studies in which cover-type models were tested against data on animal occurrences. Models had a mean accuracy rate of 0.71 ± 0.18 (SD). Rates of commission error averaged 0.20 ± 0.16, and omission errors averaged 0.09 ± 0.11. A review of the effects of errors in conservation planning suggests that the observed error rates were high enough to call into question any management decisions based on these models. Reasons for the high error rates of cover-type models include the fallibility of expert opinion, the fact that the models oversimplify how animals actually use habitats, and the dynamic nature of animal populations. Given the high rate of errors in cover-type models, any conclusions based on them should be taken with extreme caution. We suggest that these models are best used as coarse filters to identify locations for further study in the field.     

Multiple regression models for the lower heating value of municipal solid waste in Taiwan

A multiple regression analysis was used to develop two predictive models of lower heating value (LHV) for municipal solid waste (MSW), using 180 samples gathered from cities and counties in Taiwan during 2001-2002. These models are referred to as the original proposed model (OPM) and the simplified model (SM). The coefficients of multiple determinations for the OPM and SM were 0.983 and 0.975, respectively. To verify the feasibility of the models, a demonstration program based on sampling of MSW in Kaohsiung City was conducted. As a result, the OPM showed superior precision in terms of relative percentage deviation (RPD) and mean absolute percentage error (MAPE), when compared to the conventional models based on the proximate analysis, physical composition and ultimate analysis. The SM was derived by neglecting the three minor physical components used in the OPM. The resulting SM was less precise when compared to the OPM, but it was still acceptable, with a precision level better than the conventional models. It was concluded that the predictability of empirical models could be improved significantly through selection of the appropriate physical components and multiple regression analysis.