Improved Seasonal Streamflow Forecasts in the Rio Sonora Basin

Project: Research project

Description

The prediction of seasonal streamflow in the North American monsoon (NAM) region is difficult due to various factors including the complexity of the watersheds, the dynamic land surface changes occurring during the monsoon, and the lack of appropriate observations and predictive models in the region to date. A key issue for understanding the impacts of the monsoon in the NAM region is to identify the role played by the land surface in transforming precipitation into available water for vegetation greening, channel streamflow and water supply in reservoirs and regional aquifers. Two related questions need to be addressed to enhance our predictive capabilities in hydrological forecasting throughout the NAM region: How does the land surface transform meteorological forcing into streamflow? and What role does the land surface play in consuming and delivering moisture and energy to the atmosphere? Both questions are fundamental to understanding warm season hydrometeorological processes and to upscaling knowledge to the North American monsoon region. Our proposal focuses on transforming hydrometeorological data obtained in a wellinstrumented basin into predictive modeling capabilities which are useful over the broader NAM region. We approach the problem of improving the streamflow predictability by using a large river basin - the Ro Sonora- as a proxy for similar systems in the NAM region exhibiting regional coherency in rainfall and streamflow. The proposed basin exhibits low predictability in terms of atmospheric teleconnections, thus requiring new physical insight obtained from field data, remote sensing and numerical modeling. In order to deliver new capabilities for streamflow forecasting in the NAM region, we seek to acquire process understanding via field measurements and remote sensing data to characterize seasonal hydrologic changes. Based on these observations, we will apply, test and analyze the predictions of a distributed hydrological model accounting for seasonal variations in meteorological forcing and land surface characteristics. Our focused efforts are aimed towards improved characterization of the seasonal and interannual variability in streamflow and other land surface processes through use of a high resolution numerical model tuned for the NAM region. To address the science questions outlined above, we propose the following project elements: (1) Utilize and expand upon an existing hydrometeorological instrument network in the Ro Sonora to quantify the spatiotemporal variations in basin hydrological processes with a focus on the seasonal evolution of the rainfall-streamflow transformation and the partitioning of surface turbulent fluxes ; (2) Analyze remotely-sensed observations from various satellite platforms over the Ro Sonora to quantify the seasonal evolution of precipitation and land surface properties with the goal of providing model forcing and validation data sets; (3) Integrate ground and remotely-sensed data into a distributed hydrological model of the Ro Sonora to forecast hydrologic conditions in a spatially-explicit framework allowing for analysis of the causative factors for seasonal and interannual streamflow variability; and (4) Extend the hydrological findings in the Ro Sonora to the broader NAM region based upon regional hydrologic observations, remote sensing analysis and selected numerical experiments. Focused studies in the Ro Sonora will lead to a predictive hydrological model that captures seasonal variations and which can be confidently transferred throughout the NAM region. Further, the proposed work will have a direct impact on our understanding of hydrological processes in a region with significant social, economic and political issues related to water resources.
StatusFinished
Effective start/end date8/1/108/31/12

Funding

  • DOC: National Oceanic Atmospheric Administration (NOAA): $23,274.00

Fingerprint

streamflow
monsoon
land surface
basin
remote sensing
forecast
seasonal variation
rainfall
upscaling
teleconnection
prediction
modeling
transform
partitioning
river basin
water supply
water resource
moisture
aquifer
watershed