Balaji Rajagopalan

Balaji Rajagopalan

Ph.D. Utah State University, 1995
Associate Professor of Civil, Environmental and Architectural Engineering

E-mail: rajagopalan.balaji@colorado.edu
Office: ECOT 541
Phone: 303-492-5968
Web: Prof. Rajagopalan
(Dept. of Civil, Environmental, and Architectural Engineering)

 

Research Interests

  • Stochastic Hydrology and Hydroclimatology
  • Nonparametric functional estimation techniques (probability density Functions, regression, scenarios generation, forecasting)
  • Understanding low frequency climate variability and its signatures on regional hydrology
  • Incorporating climate information in water resources/hydrologic decision making
  • Understanding spatio-temporal variability in Indian summer monsoon
  • Nonlinear Dynamics - recovering dynamics from data
  • Bayesian techniques for optimal combination of information from multiple sources and decision making

Statistical climate modeling and its application to hydrology, water resources eng. related issues; Stochastic modeling of rainfall and other weather variables; scaling issues in rainfall; Spatial estimation of hydro-climate variables; nonparametric estimation of density and regression functions for Multivariate Time series analysis of climate data; Identifying inter-annual variability in hydro climate variables and nonlinear dynamical modeling and forecasting; Inferring long range climate variability through statistical analysis of paleo proxy data.

Current Research: A decision support system for mitigating stream-temperature impacts on fish habitat in the Sacramento River, with graduate student Raymond Jason Caldwell.

Increasing demands on the limited and variable water supply across the U.S. West can result in insufficient stream flow to sustain healthy fish habitat and populations. In the late summer and early fall, high air temperature and low flow conditions can cause rapid increases in water temperature, creating critical conditions, particularly for cold-water fish such as salmon. In addition, construction of dams and diversions along rivers for the purpose of storing and distributing the limited supply of water can further deteriorate natural flow regimes and often obstruct important migratory pathways for fish reproduction and development. The thermal impacts on the ecology of river ecosystems have been well-documented, yet there is no comprehensive modeling framework in place for skillfully modeling climate-related impacts. In regulated systems, such as the Sacramento River system, these impacts are an interaction of volume and temperature of water release from the reservoir and the subsequent exchange with the environment downstream. In this research, we develop an integrated decision support system for modeling and mitigating water-temperature impacts
and demonstrate it on the Sacramento River system. The approach has four broad components that can be coupled to produce decision tools toward efficient management of water resources for stream-temperature mitigation. These are: 1) a suite of statistical models for modeling stream-temperature attributes by using hydrology and climate variables of critical importance for fish habitat, such as average daily stream temperature and number of hours of temperature threshold exceedance, etc.; 2) a reservoir thermal model for modeling the thermal structure and, consequently, the waterrelease temperature; 3) a stochastic weather generator to simulate weather sequences that are consistent with long-range (e.g., seasonal) outlooks; and 4) a set of decision rules (i.e., rubric) for water releases from the reservoir in response to weather sequences and the reservoir thermal structure obtained from the above components. These components are coupled to develop tools that will help water managers plan for efficient mitigation of stream-temperature impacts on fish habitat. The decision support system incorporates forecast uncertainties and reservoir operating options to help mitigate streamtemperature impacts for fish habitat, while efficiently using the water and cold-pool storage in the reservoir. We find that using the decision support system substantially reduces the number of violations of thermal criteria, while ensuring maintenance of the cold-pool storage throughout the summer.

References Caldwell, RJ. 2013. An integrated framework for modeling and mitigating water temperature impacts in the Sacramento River. Ph.D. dissertation, University of Colorado Boulder.

map of Sacramento riverMap of the study area on the Sacramento River.

 

Publications

Click here for a complete list of published works »

Rajagopalan is a professor at the University of Colorado at Boulder.