INTERA Incorporated services

Water resource planning is one of the more complex activities because it often includes competing interests and limited resources. It is a combination of technical issues that are inherently quantitative balanced with other issues that are qualitative in nature, such as public perception, stakeholder support, or environmental suitability. INTERA is experienced in developing decision support methods for water resources that allow a transparent assessment of both qualitative and quantitative performance metrics in alternatives analysis. We are experts in communicating complex technical concepts to a non-technical audience using a tried and true stakeholder communication process.

The effective management of water resources frequently requires quantitative assessments of aquifer availability, aquifer sustainability, and the mechanisms of recharge and discharge, including the interaction of surface water and groundwater. These assessments require a detailed analysis of aquifer flow dynamics. Numerical models provide the best means to quantitatively represent the essential features of the actual groundwater system. Through a quantitative understanding of cause and effect relationships, these models are used to make predictions and forecasts for a defined set of conditions. When properly developed and applied, groundwater models enable complex water availability analyses to be conducted and facilitate informed water resources decision-making.

INTERA has solved many water resource problems for clients throughout the southern and western U.S. that include municipal water suppliers, state and federal agencies, and industry. Our services focus on providing predictions of the future hydrologic-system conditions needed to make sound decisions regarding water resource management using state-of-the-art data acquisition and modeling technology.

INTERA has over 20 years of experience in the development and application of statistical and geostatistical tools to hydrologic and hydrogeologic data. Our personnel have developed statistical models for time series data such as rainfall and ET, groundwater and surface water data, wetland and lake-level data, water quality, and short term and long term water demand.