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Description
Climate and its influence on hydrology and weathering is a key driver of surface processes on Earth. Despite its clear importance to hazard generation, fluvial sediment transport and erosion, the drawdown of atmospheric CO2 via the rock cycle, and feedbacks between climate and tectonics, quantifying climatic controls on long-term erosion rates has proven to be one of the grand problems in geomorphology. In fact, recent attempts addressing this problem using cosmogenic radionuclide (CRN) derived erosion rates suggest very weak climatic controls on millennial-scale erosion rates contrary to expectations. In this work, two challenges are addressed that may be impeding progress on this problem.
The first challenge is choosing appropriate climate metrics that are closely tied to erosional processes. For example, in fluvial landscapes, most runoff events do little to no geomorphic work due to erosion thresholds, and event-scale variability dictates how frequently these thresholds are exceeded. By analyzing dense hydroclimatic datasets in the contiguous U.S. and Puerto Rico, we show that event-scale runoff variability is only loosely related to event-scale rainfall variability. Instead, aridity and fractional evapotranspiration (ET) losses are much better predictors of runoff variability. Importantly, simple hillslope-scale soil water balance models capture major aspects of the observed relation between runoff variability and fractional ET losses. Together, these results point to the role of vegetation water use as a potential key to relating mean hydrologic partitioning with runoff variability.
The second challenge is that long-term erosion rates are expected to balance rock uplift rates as landscapes approach topographic steady state, regardless of hydroclimatic setting. This is illustrated with new data along the Main Gulf Escarpment, Baja, Mexico. Under this conceptual framework, climate is not expected to set the erosion rate, but rather the erosional efficiency of the system, or the steady-state relief required for erosion to keep up with tectonically driven uplift rates. To assess differences in erosional efficiency across landscapes experiencing different climatic regimes, we contrast new CRN data from tectonically active landscapes in Baja, Mexico and southern California (arid) with northern Honduras (very humid) alongside other published global data from similar hydroclimatic settings. This analysis shows how climate does, in fact, set functional relationships between topographic metrics like channel steepness and long-term erosion rates. However, we also show that relatively small differences in rock erodibility and incision thresholds can easily overprint hydroclimatic controls on erosional efficiency motivating the need for more field based constraints on these important variables.
The first challenge is choosing appropriate climate metrics that are closely tied to erosional processes. For example, in fluvial landscapes, most runoff events do little to no geomorphic work due to erosion thresholds, and event-scale variability dictates how frequently these thresholds are exceeded. By analyzing dense hydroclimatic datasets in the contiguous U.S. and Puerto Rico, we show that event-scale runoff variability is only loosely related to event-scale rainfall variability. Instead, aridity and fractional evapotranspiration (ET) losses are much better predictors of runoff variability. Importantly, simple hillslope-scale soil water balance models capture major aspects of the observed relation between runoff variability and fractional ET losses. Together, these results point to the role of vegetation water use as a potential key to relating mean hydrologic partitioning with runoff variability.
The second challenge is that long-term erosion rates are expected to balance rock uplift rates as landscapes approach topographic steady state, regardless of hydroclimatic setting. This is illustrated with new data along the Main Gulf Escarpment, Baja, Mexico. Under this conceptual framework, climate is not expected to set the erosion rate, but rather the erosional efficiency of the system, or the steady-state relief required for erosion to keep up with tectonically driven uplift rates. To assess differences in erosional efficiency across landscapes experiencing different climatic regimes, we contrast new CRN data from tectonically active landscapes in Baja, Mexico and southern California (arid) with northern Honduras (very humid) alongside other published global data from similar hydroclimatic settings. This analysis shows how climate does, in fact, set functional relationships between topographic metrics like channel steepness and long-term erosion rates. However, we also show that relatively small differences in rock erodibility and incision thresholds can easily overprint hydroclimatic controls on erosional efficiency motivating the need for more field based constraints on these important variables.
ContributorsRossi, Matthew (Author) / Whipple, Kelin X (Thesis advisor) / DeVecchio, Duane E (Committee member) / Vivoni, Enrique R (Committee member) / Arrowsmith, J Ramon (Committee member) / Heimsath, Arjun M (Committee member) / Arizona State University (Publisher)
Created2014
Description
This doctoral thesis investigates the predictability characteristics of floods and flash floods by coupling high resolution precipitation products to a distributed hydrologic model. The research hypotheses are tested at multiple watersheds in the Colorado Front Range (CFR) undergoing warm-season precipitation. Rainfall error structures are expected to propagate into hydrologic simulations with added uncertainties by model parameters and initial conditions. Specifically, the following science questions are addressed: (1) What is the utility of Quantitative Precipitation Estimates (QPE) for high resolution hydrologic forecasts in mountain watersheds of the CFR?, (2) How does the rainfall-reflectivity relation determine the magnitude of errors when radar observations are used for flood forecasts?, and (3) What are the spatiotemporal limits of flood forecasting in mountain basins when radar nowcasts are used into a distributed hydrological model?. The methodology consists of QPE evaluations at the site (i.e., rain gauge location), basin-average and regional scales, and Quantitative Precipitation Forecasts (QPF) assessment through regional grid-to-grid verification techniques and ensemble basin-averaged time series. The corresponding hydrologic responses that include outlet discharges, distributed runoff maps, and streamflow time series at internal channel locations, are used in light of observed and/or reference data to diagnose the suitability of fusing precipitation forecasts into a distributed model operating at multiple catchments. Results reveal that radar and multisensor QPEs lead to an improved hydrologic performance compared to simulations driven with rain gauge data only. In addition, hydrologic performances attained by satellite products preserve the fundamental properties of basin responses, including a simple scaling relation between the relative spatial variability of runoff and its magnitude. Overall, the spatial variations contained in gridded QPEs add value for warm-season flood forecasting in mountain basins, with sparse data even if those products contain some biases. These results are encouraging and open new avenues for forecasting in regions with limited access and sparse observations. Regional comparisons of different reflectivity -rainfall (Z-R) relations during three summer seasons, illustrated significant rainfall variability across the region. Consistently, hydrologic errors introduced by the distinct Z-R relations, are significant and proportional (in the log-log space) to errors in precipitation estimations and stream flow magnitude. The use of operational Z-R relations without prior calibration may lead to wrong estimation of precipitation, runoff magnitude and increased flood forecasting errors. This suggests that site-specific Z-R relations, prior to forecasting procedures, are desirable in complex terrain regions. Nowcasting experiments show the limits of flood forecasting and its dependence functions of lead time and basin scale. Across the majority of the basins, flood forecasting skill decays with lead time, but the functional relation depends on the interactions between watershed properties and rainfall characteristics. Both precipitation and flood forecasting skills are noticeably reduced for lead times greater than 30 minutes. Scale dependence of hydrologic forecasting errors demonstrates reduced predictability at intermediate-size basins, the typical scale of convective storm systems. Overall, the fusion of high resolution radar nowcasts and the convenient parallel capabilities of the distributed hydrologic model provide an efficient framework for generating accurate real-time flood forecasts suitable for operational environments.
ContributorsMoreno Ramirez, Hernan (Author) / Vivoni, Enrique R. (Thesis advisor) / Ruddell, Benjamin L. (Committee member) / Gochis, David J. (Committee member) / Mays, Larry W. (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2012