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Ahmadi L.,Logan Research | Merkley G.P.,Natural Resources Consulting Inc.
Irrigation Science | Year: 2017

This study analyzed the effects of population and urban growth on water demand for irrigation and other water users, as well as municipal wastewater quantity changes, by developing a new mathematical model. The model was developed to consider the potential for reuse of treated wastewater for agricultural irrigation, by analyzing the increasing quantity of wastewater production in an urban area. It was applied to a case study in Logan, Utah, whereby results from the model showed a total water demand of 0.7 and 1.27 m3/s in 2020 and 2050, respectively, while the model predicted that the average wastewater influent for Logan City would be more than double from 2010 to 2050. Accordingly, a model-predicted increase of 16% in the annual production of wastewater was observed from 2010 to 2025. The amount of wastewater production in 2030 was estimated to be 14.2 million m3/year, which is enough to produce food from irrigated agriculture for 11% of the future population of Logan City. This emphasizes the potential importance of reusing wastewater for irrigated agriculture. Water conservation was also studied and it showed that a 5% conservation of water volume could cover the needs of an additional 4.2 thousand people in 2030. © 2017 Springer-Verlag Berlin Heidelberg

Shaban M.Z.,MED Ingegneria S.r.l. | Merkley G.P.,Natural Resources Consulting Inc.
Irrigation Science | Year: 2016

A modern computer-based simulation tool (WaterMan) in the form of a game for on-farm water management was developed for application in training events for farmers, students, and irrigators. The WaterMan game utilizes an interactive framework, thereby allowing the user to develop scenarios and test alternatives in a convenient, risk-free environment. It includes a comprehensive soil water and salt balance calculation algorithm. It also employs heuristic capabilities for modeling all of the important aspects of on-farm water management, and to provide quantitative performance evaluations and practical water management advice to the trainees. Random events (both favorable and unfavorable) and different strategic decisions are included in the game for more realism and to provide an appropriate level of challenge according to player performance. Thus, the ability to anticipate the player skill level, and to reply with random events appropriate to the anticipated level, is provided by the heuristic capabilities used in the software. These heuristic features were developed based on a combination of two artificial intelligence approaches: (1) a pattern recognition approach and (2) reinforcement learning based on a Markov decision processes approach, specifically the Q-learning method. These two approaches were combined in a new way to account for the difference in the effect of actions taken by the player and action taken by the system in the game world. The reward function for the Q-learning method was modified to reflect the suggested classification of the WaterMan game as what is referred to as a partially competitive and partially cooperative game. © 2016 Springer-Verlag Berlin Heidelberg

Rambikur E.H.,Colorado State University | Rambikur E.H.,Natural Resources Consulting Inc. | Chavez J.L.,Colorado State University
Sensors (Switzerland) | Year: 2014

The accuracy in determining sensible heat flux (H) of three Kipp and Zonen large aperture scintillometers (LAS) was evaluated with reference to an eddy covariance (EC) system over relatively flat and uniform grassland near Timpas (CO, USA). Other tests have revealed inherent variability between Kipp and Zonen LAS units and bias to overestimate H. Average H fluxes were compared between LAS units and between LAS and EC. Despite good correlation, inter-LAS biases in H were found between 6% and 13% in terms of the linear regression slope. Physical misalignment was observed to result in increased scatter and bias between H solutions of a well-aligned and poorly-aligned LAS unit. Comparison of LAS and EC H showed little bias for one LAS unit, while the other two units overestimated EC H by more than 10%. A detector alignment issue may have caused the inter-LAS variability, supported by the observation in this study of differing power requirements between LAS units. It is possible that the LAS physical misalignment may have caused edge-of-beam signal noise as well as vulnerability to signal noise from wind-induced vibrations, both having an impact on the solution of H. In addition, there were some uncertainties in the solutions of H from the LAS and EC instruments, including lack of energy balance closure with the EC unit. However, the results obtained do not show clear evidence of inherent bias for the Kipp and Zonen LAS to overestimate H as found in other studies. © 2014 by the authors; licensee MDPI, Basel, Switzerland.

Lanini J.S.,Natural Resources Consulting Inc. | Dozier A.Q.,Colorado State University | Furey P.R.,NorthWest Research Associates, Inc. | Kampf S.K.,Colorado State University
Journal of Water Resources Planning and Management | Year: 2014

Changes in air temperature and precipitation that are due to climate change can affect operational objectives and hydropower production of reservoirs. This study uses a stochastic conceptual snowmelt-runoff model to generate inflow ensembles for a wide range of potential temperature and precipitation scenarios as a means of testing which types of climate changes could adversely affect hydropower production. The method is applied to a case study of the Dworshak Reservoir on the North Fork of the Clearwater River in central Idaho. Reservoir operations in response to the climate-change ensemble scenarios were simulated using a decision support system operations model according to current operating criteria and guidelines. The magnitude and timing of hydropower generation resulting from each temperatureand precipitation-change scenario were examined, assuming no change from historical reservoir operations. Results showed that lower precipitation and higher temperature created less runoff and therefore less hydropower generation. However, increased precipitation and decreased temperature scenarios showed limited increases in hydropower production due to turbine capacity and other operational constraints. Firm hydropower production from Dworshak steadily decreased with increasing mean annual temperature and steadily increased with increasing mean annual precipitation. Timing of spring hydropower production shifted to earlier spring and winter with increasing temperature. Because these simulations did not adapt reservoir operations from historical procedures, they are not intended to be realistic predictions of changes in hydropower generation in the future. Rather, the results demonstrate how the approach can provide guidance about which types of hydrograph changes, such as shifts in inflow timing, might warrant changes in reservoir operations. © 2014 American Society of Civil Engineers.

Bau D.,University of Sheffield | Cody B.M.,Natural Resources Consulting Inc. | Gonzalez-Nicolas A.,Colorado State University
Computational Geosciences | Year: 2015

Successful large-scale implementation of geological CO2 sequestration (GCS) will require the preliminary assessment of multiple potential injection sites. Risk assessment and optimization tools used in this effort typically require large numbers of simulations. This makes it important to choose the appropriate level of complexity when selecting the type of simulation model. A promising multi-phase semi-analytical method proposed by Nordbotten et al. (Environ. Sci. Technol. 43, 743–749 2009) to estimate key system attributes (i.e., pressure distribution, CO2 plume extent, and fluid migration) has been found to reduce computational run times by three orders of magnitude when compared to other standard numerical techniques. The premise of the work presented herein is that the existing semi-analytical leakage algorithm proposed by Nordbotten et al. (Environ. Sci. Technol. 43, 743–749 2009) may be further improved in computational efficiency by applying a fixed-point-type iterative global pressure solution to eliminate the need to solve large sets of linear equations at each time step. Results show that significant gains in computational efficiency are obtained with this new methodology. In addition, this modification provides the same enhancement to similar semi-analytical algorithms that simulate single-phase injection into multi-layer domains. © 2015, Springer International Publishing Switzerland.

Geological carbon sequestration (GCS) has been identified as having the potential to reduce increasing atmospheric concentrations of carbon dioxide (CO2). However, a global impact will only be achieved if GCS is cost-effectively and safely implemented on a massive scale. This work presents a computationally efficient methodology for identifying optimal injection strategies at candidate GCS sites having uncertainty associated with caprock permeability, effective compressibility, and aquifer permeability. A multi-objective evolutionary optimization algorithm is used to heuristically determine non-dominated solutions between the following two competing objectives: (1) maximize mass of CO2 sequestered and (2) minimize project cost. A semi-analytical algorithm is used to estimate CO2 leakage mass rather than a numerical model, enabling the study of GCS sites having vastly different domain characteristics. The stochastic optimization framework presented herein is applied to a feasibility study of GCS in a brine aquifer in the Michigan Basin (MB), USA. Eight optimization test cases are performed to investigate the impact of decision-maker (DM) preferences on Pareto-optimal objective-function values and carbon-injection strategies. This analysis shows that the feasibility of GCS at the MB test site is highly dependent upon the DM’s risk-adversity preference and degree of uncertainty associated with caprock integrity. Finally, large gains in computational efficiency achieved using parallel processing and archiving are discussed. © 2015, Springer-Verlag Berlin Heidelberg.

Carney M.C.,Bechtel Corporation | Mesghinna W.,Natural Resources Consulting Inc.
World Environmental and Water Resources Congress 2012: Crossing Boundaries, Proceedings of the 2012 Congress | Year: 2012

In semi-arid environments, rivers are often characterized by intermittent flows that may have high sediment concentrations. In such cases, dams forming storage reservoirs may be developed at off-stream locations having small watersheds, with inflows being provided from a nearby river via a diversion dam and supply canal. This design limits the sediment inflows to only those from the watershed above the reservoir and those carried by the supply canal from the source river, lengthening the life of the reservoir. Sediment concentrations in the supply canal may be reduced by desilting facilities at the diversion dam, and possibly along the canal as well. This paper presents an analysis of strategies that were considered for managing sediment inflows to a supply canal for a proposed off-stream reservoir. An unexpected finding is that a sediment trap basin, which had been proposed to be located along the supply canal, could reduce, rather than improve, the overall sediment removal efficiency of the diversion-supply system. This outcome is due to a lack of sufficient water in the source river to sluice sediment deposits from both the diversion dam pool and the sediment trap basin. This study illustrates how, in cases of scarce water supplies with high sediment loads, there can be tradeoffs between the differing needs for managing water and sediment. © 2012 ASCE.

Kapfer J.M.,Elon University | Pekar C.W.,Natural Resources Consulting Inc. | Reineke D.M.,University of Wisconsin-La Crosse | Coggins J.R.,University of Wisconsin - Milwaukee | Hay R.,Bureau of Endangered Resources
Journal of Zoology | Year: 2010

Effective wildlife conservation plans should consider both the habitat needs and spatial requirements of the species in question. Studies that focus on the correlation between the habitat preferences and movement patterns of wildlife, particularly snakes, are uncommon. We attempted to determine how habitat preferences or quality influenced movement patterns of snakes. To answer this question, we created a case model that incorporated habitat preference or avoidance information rigorously obtained for bullsnakes Pituophis catenifer sayi from 2003 to 2005 at a site in the upper Midwestern US and compared it with minimum convex polygon estimates of home-range size. We employed geographical information systems to model the amount of preferred (open bluff faces) and avoided (agricultural fields and closed canopy forests) habitats within each estimated home range and compared them via multiple linear regression. We also tested the influence of gender, length and weight on home-range size. Our results indicate that home-range size increased primarily as a function of the amount of avoided habitat. This supports the hypothesis that habitat quality has an impact on wildlife movement patterns, and the relationship between habitat needs and spatial requirements should be considered when conserving or managing species. © 2010 The Authors. Journal compilation © 2010 The Zoological Society of London.

Furey P.R.,Colorado State University | Kampf S.K.,Colorado State University | Lanini J.S.,Natural Resources Consulting Inc. | Dozier A.Q.,Natural Resources Consulting Inc.
Journal of Hydrometeorology | Year: 2012

This study presents a modeling approach for examining how changes in climate affect streamflow in mesoscale mountain basins dominated by snowmelt runoff.Aconceptual snowmelt-runoff model was developed that is forced by daily time series of temperature and precipitation. The model can be run using either observed climate data or artificial climate data generated from a GCM or a stochastic model. The model was applied to a case-study basin, the north fork of the Clearwater River in Idaho, using stochastically generated climate scenarios. Climate scenarios were generated using a contemporaneous auto-regressive integrated moving average (CARIMA) model for temperature and a precipitation model based on a two-state first-order Markov process. A baseline climate scenario was developed that represents recently observed temperature and precipitation conditions and then 15 additional climate scenarios that represent shifts in recent conditions. For each scenario, model application produced an ensemble of 50 streamflow traces each spanning 30 yr. Results show that an increase in temperature among scenarios leads to a decrease in streamflow and vice versa. Decreases in temperature shift the basin runoff to fully snowmelt dominated, whereas increases in temperature increase the frequency of midwinter runoff events. Increasing precipitation leads to increased runoff in cases where the temperature remains the same as the observed record, but not in cases where the temperature increases. The modeling approach presented here can be used by water managers to examine which types of climate change could require modifications in water planning and operations. © 2012 American Meteorological Society.

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