A distributed data component for the Open Modeling Interface

As the volume of collected data continues to increase in the environmental sciences, so too does the need for effective means for accessing those data. We have developed an Open Modeling Interface (OpenMI) data component that retrieves input data for model components from environmental information systems and delivers output data to those systems. The adoption of standards for both model component input–output interfaces and web services make it possible for the component to be reconfigured for use with different linked models and various online systems. The data component employs three techniques tailored to the unique design of the OpenMI that enable efficient operation: caching, prefetching, and buffering, making it capable of scaling to large numbers of simultaneous simulations executing on a computational grid. We present the design of the component, an evaluation of its performance, and a case study demonstrating how it can be incorporated into modeling studies

Efficient data collection from Open Modeling Interface (OpenMI) components

The management of output data from simulation models can be simplified in grid environments by automating and standardizing the way in which they are collected and stored. In the context of component-based computer models with well-defined input-output interfaces, generalpurpose data collector components can be linked to model components to retrieve output data and deliver them to online repositories via web services. We have developed a distributed data collector component that adheres to the Open Modeling Interface (OpenMI). The component buffers data to minimize the impact on a simulation’s runtime and shares the buffer across compute nodes for load-balancing and cooperative delivery of data to web services. The buffering capability resulted in minimal runtimes within a single simulation and reduced data delivery latencies for concurrently executing simulations across a cluster. In this paper we report on the design and performance of the component

Support for model coupling: An interface-based approach

216 p.A print copy of this title is available through the UO Libraries under the call number: MATH LIB. QA76.9.C65 B85 2006There is an increasing need in the scientific community for the comprehensive simulation of complex, dynamic, physical systems. Often such simulations are built through model coupling, that is, the merging of existing, component models so that their concurrent simulations affect each other. Model coupling is, however, a nontrivial task that is not adequately supported by existing frameworks which often require direct manipulation of model source code. This work presents an approach to model coupling that avoids this hurdle, allowing for the fast-prototyping of coupled models. Our approach to model coupling allows the scientist to work with a novel model representation, called the Potential Coupling Interface (PCI). The PCI is an abstraction that exposes only those aspects of a model relevant to coupling, and it is the basis for specifying couplings. Specifically, this dissertation contributes the design of a new representation, the PCI, for model coupling interfaces, the design of a domain-specific language, called the Coupling Description Language, for describing the coupling of models in terms of their PCIs, and the implementation of a prototype coupling environment for Hydrological models. We conclude that the use of the PCI model interfaces makes it possible to quickly design and execute prototypes of model couplings for further experimentation and investigation. This dissertation research aims to influence the way in which model coupling is practiced in the scientific community.Adviser: Janice Cuny Partially support by: National Science Foundation grants ACI-0081487 and SBE-031837

Efficient data access for Open Modeling Interface (OpenMI)components

Data management for linked (or coupled) simulation models can be a challenging task when deploying to grid environments. In cases where the linked models conform to a standard interface for data input and output, generalpurpose data providers can be used to supply data to the models from online sources, reducing the complexity of the deployment. We have developed a data provider component that conforms to the Open Modeling Interface (OpenMI) that is suitable for use on computational grids. Through the application of three techniques, caching, prefetching, and pipelining, the component efficiently retrieves data from standards-based web services and delivers the data to OpenMI-compliant models. Each technique resulted in varying performance improvements both within a single simulation and across multiple simulations concurrently executing on a cluster. In this paper we report on the design of the component and the evaluation of its performance

Interface-based support for model coupling: Spatial representation and compatibility issues

Model coupling is a nontrivial task that is not adequately supported in existing frameworks. Our long-term goal is to support the fast-prototyping of model couplings, enabling scientists to quickly experiment with a variety of linkings without having to make an upfront investment in reprogramming. The centerpiece of our framework, the Potential Coupling Interface (PCI), must expose all the characteristics of a model that are relevant to model coupling, but what are those characteristics? To explore different couplings, and to identify the relevant model characteristics, we conducted a study of 14 hydrological models and the pairwise couplings between them. We found that the model characteristics relevant to coupling lie in four dimensions: space, time, structure, and data. Models of the same phenomena often had similar characteristics, making it feasible to replace them within a coupling when appropriate for specific sites. We also found that resolving differences along the four dimensions, particularly with respect to space, can be complex

The Simple Script Wrapper for OpenMI: Enabling interdisciplinary modeling studies

Integrated environmental modeling enables the development of comprehensive simulations by compositing individual models within and across disciplines. The Simple Script Wrapper (SSW), developed here, provides a foundation for model linkages and integrated studies. The Open Modeling Interface (OpenMI) enables model integration but it is challenging to incorporate scripting languages commonly used for modeling and analysis such as MATLAB, Scilab, and Python. We have developed a general-purpose software component for the OpenMI that simplifies the linking of scripted models to other components. Our solution enables scientists to easily make their scripting language code linkable to OpenMI-compliant models fostering collaborative, interdisciplinary integrated modeling. The simplicity afforded by our solution is presented in a case study set in the context of irrigated agriculture. The software is available online as supplementary material and includes an example that may be followed to employ our methods

Accessible integration of agriculture, groundwater, and economic models using the Open Modeling Interface (OpenMI): methodology and initial results

Policy for water resources impacts not only hydrological processes, but the closely intertwined economic and social processes dependent on them. Understanding these process interactions across domains is an important step in establishing effective and sustainable policy. Multidisciplinary integrated models can provide insight to inform this understanding, though the extent of software development necessary is often prohibitive, particularly for small teams of researchers. Thus there is a need for practical methods for building interdisciplinary integrated models that do not incur a substantial development effort. In this work we adopt the strategy of linking individual domain models together to build a multidisciplinary integrated model. The software development effort is minimized through the reuse of existing models and existing model-linking tools without requiring any changes to the model source codes, and linking these components through the use of the Open Modeling Interface (OpenMI). This was found to be an effective approach to building an agricultural-groundwater-economic integrated model for studying the effects of water policy in irrigated agricultural systems. The construction of the integrated model provided a means to evaluate the impacts of two alternative water-use policies aimed at reducing irrigated water use to sustainable levels in the semi-arid grasslands overlying the Ogallala Aquifer of the Central US. The results show how both the economic impact in terms of yield and revenue and the environmental impact in terms of groundwater level vary spatially throughout the study region for each policy. Accessible integration strategies are necessary if the practice of interdisciplinary integrated simulation is to become widely adopted

Calibration of a crop model to irrigated water use using a genetic algorithm

Near-term consumption of groundwater for irrigated agriculture in the High Plains Aquifer supports a dynamic bio-socio-economic system, all parts of which will be impacted by a future transition to sustainable usage that matches natural recharge rates. Plants are the foundation of this system and so generic plant models suitable for coupling to representations of other component processes (hydrologic, economic, etc.) are key elements of needed stakeholder decision support systems. This study explores utilization of the Environmental Policy Integrated Climate (EPIC) model to serve in this role. Calibration required many facilities of a fully deployed decision support system: geo-referenced databases of crop (corn, sorghum, alfalfa, and soybean), soil, weather, and water-use data (4931 well-years), interfacing heterogeneous software components, and massively parallel processing (3.8×109 model runs). Bootstrap probability distributions for ten model parameters were obtained for each crop by entropy maximization via the genetic algorithm. The relative errors in yield and water estimates based on the parameters are analyzed by crop, the level of aggregation (county- or well-level), and the degree of independence between the data set used for estimation and the data being predicted

Simulation Data From Aistrup et al. Sustaining the Ogallala Aquifer Manuscript

Please see Readme.txt fileThese data are the simulation results described in the article by Aistrup et al., "Sustaining the Ogallala Aquifer: From the Wells to People, A Holistic CNH Model," accepted for publication in Hydrology and Earth System Sciences (prepublication version at https://doi.org/10.5194/hess-2017-300). The data are being publicly shared in accordance with journal policy.National Science Foundation (NSF-CNH-0909515)

Groundwater economics: an object-oriented foundation for integrated studies of irrigated agricultural systems

An integrated foundation is presented to study the impacts of external forcings on irrigated agricultural systems. Individually, models are presented that simulate groundwater hydrogeology and econometric farm level crop choices and irrigated water use. The natural association between groundwater wells and agricultural parcels is employed to couple these models using geographic information science technology and open modeling interface protocols. This approach is used to study the collective action problem of the common pool. Three different policies (existing, regulation, and incentive based) are studied in the semiarid grasslands overlying the Ogallala Aquifer in the central United States. Results show that while regulation using the prior appropriation doctrine and incentives using a water buy-back program may each achieve the same level of water savings across the study region, each policy has a different impact on spatial patterns of groundwater declines and farm level economic activity. This represents the first time that groundwater and econometric models of irrigated agriculture have been integrated at the well-parcel level and provides methods for scientific investigation of this coupled natural-human system. Results are useful for science to inform decision making and public policy debate