Domain-specific Metaware for Hydrologic Applications

نویسندگان

  • Daniel Andresen
  • Mitchell L. Neilsen
  • Gurdip Singh
  • Prasanta K. Kalita
چکیده

The DHARMA domain-specific middleware system is intended to allow hydrologic field engineers to tackle water-management problems on a scale previously impossible without sophisticated computational management systems. DHARMA provides automatic data acquisition via the Internet; data fusion from online, local, and cached resources; smart caching of intermediate results; parallel process execution; automatic transformation and piping of data between different hydrologic simulation models; and interfaces with existing metacomputing systems. Our target watershed model, WEPP, is limited to very small watersheds with current computer technology. A revolutionary change in hydrologic modeling on the watershed scale will be brought about by applying various watershed models to large watersheds, such as the Lake Decatur Watershed which covers 925 square miles. Even with unlimited computing resources, the current version of WEPP cannot be directly applied to model the Lake Decatur Watershed because the current implementation of WEPP is limited to a maximum of 75 hillslopes. To address this issue, we have now integrated support for multiple simulation models in our software; for example, we can use WEPP to model individual hillslopes and another model, such as SITES, to model the connecting channels (reaches) and dams (structures), playing to the strengths of both models. In this paper we discuss the evolving software architecture of DHARMA and its interaction with the Web and Grid infrastructures.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Dharma: a Grid-enabled Domain-specific Metaware for Hydrology

The DHARMA domain-specific middleware system is intended to allow hydrologic field engineers to tackle water-management problems on a scale previously impossible without sophisticated computational management systems. DHARMA provides automatic data acquisition via the Internet; data fusion from online, local, and cached resources; smart caching of intermediate results; parallel process executio...

متن کامل

Deep Unsupervised Domain Adaptation for Image Classification via Low Rank Representation Learning

Domain adaptation is a powerful technique given a wide amount of labeled data from similar attributes in different domains. In real-world applications, there is a huge number of data but almost more of them are unlabeled. It is effective in image classification where it is expensive and time-consuming to obtain adequate label data. We propose a novel method named DALRRL, which consists of deep ...

متن کامل

Role of Ontologies in Creating Hydrologic Metadata

Recent developments and discussions on nationwide scales increasingly stress the need for semantic interoperability among communities due to the lack of specific domain descriptions of the data being processed. These shortcomings are largely based on the fact that each community typically only focuses on its specific needs with little or no attention paid to making these community-specific data...

متن کامل

Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function

Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth's surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show ...

متن کامل

Hydrologic Modeling of Climate Scenarios for Two Illinois Watersheds

Watershed modeling applications for the Fox and Iroquois River watersheds in Illinois were used to evaluate the response in simulated streamflow to various climate scenarios. The climate scenarios applied to both watersheds are based on simulations from two global climate models, the Japan and Hadley models, which respectively represent comparatively “dry” and “wet” scenarios of future climatic...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2002