Eleonora M. C. Demaria

Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity model

[1] Current land surface models use increasingly complex descriptions of the processes that they represent. Increase in complexity is accompanied by an increase in the number of model parameters, many of which cannot be measured directly at large spatial scales. A Monte Carlo framework was used to evaluate the sensitivity and identifiability of ten parameters controlling surface and subsurface runoff generation in the Variable Infiltration Capacity model (VIC). Using the Monte Carlo Analysis Toolbox (MCAT), parameter sensitivities were studied for four U.S. watersheds along a hydroclimatic gradient, based on a 20-year data set developed for the Model Parameter Estimation Experiment (MOPEX). Results showed that simulated streamflows are sensitive to three parameters when evaluated with different objective functions. Sensitivity of the infiltration parameter (b) and the drainage parameter (exp) were strongly related to the hydroclimatic gradient. The placement of vegetation roots played an important role in the sensitivity of model simulations to the thickness of the second soil layer (thick2). Overparameterization was found in the base flow formulation indicating that a simplified version could be implemented. Parameter sensitivity was more strongly dictated by climatic gradients than by changes in soil properties. Results showed how a complex model can be reduced to a more parsimonious form, leading to a more identifiable model with an increased chance of successful regionalization to ungauged basins. Although parameter sensitivities are strictly valid for VIC, this model is representative of a wider class of macroscale hydrological models. Consequently, the results and methodology will have applicability to other hydrological models. Citation: Demaria, E. M., B. Nijssen, and T. Wagener (2007), Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity model, J. Geophys. Res., 112, D11113, doi:10.1029/2006JD007534.

The Effects of Climate Change on Seasonal Snowpack and the Hydrology of the Northeastern and Upper Midwest United States

AbstractThe potential effects of climate change on the snowpack of the northeastern and upper Midwest United States are assessed using statistically downscaled climate projections from an ensemble of 10 climate models and a macroscale hydrological model. Climate simulations for the region indicate warmer-than-normal temperatures and wetter conditions for the snow season (November–April) during the twenty-first century. However, despite projected increases in seasonal precipitation, statistically significant negative trends in snow water equivalent (SWE) are found for the region. Snow cover is likely to migrate northward in the future as a result of warmer-than-present air temperatures, with higher loss rates in northern latitudes and at high elevation. Decreases in future (2041–95) snow cover in early spring will likely affect the timing of maximum spring peak streamflow, with earlier peaks predicted in more than 80% of the 124 basins studied.

Satellite precipitation in southeastern South America: how do sampling errors impact high flow simulations?

Abstract Satellite precipitation estimates are increasingly available at temporal and spatial scales of interest to hydrological applications and with the potential for improving flood forecasts in data-sparse regions. This study evaluates the effect of sampling error on simulated large flood events. Synthetic precipitation fields were generated in Monte Carlo fashion by perturbing observed precipitation fields with sampling errors based on 1, 2 and 6 h intervals. The variable infiltration capacity hydrological model was used to assess the impact of these errors on simulated high flow events in the Iguazu basin, a rain-dominated, subtropical basin in southeastern South America. Results showed that unbiased errors in daily error-corrupted precipitation fields introduced bias in the simulated hydrologic fluxes and states. The overall bias for error-corrupted daily streamflows was positive and its magnitude increased with larger sampling intervals. However, for high flow events, the bias was negative as a result of an increase in simulated infiltration and changes in precipitation variability. Errors in precipitation also affected the magnitude and volume of the peak events but did not change the first two statistical moments of the peaks indicating that non-linearities in the hydrological system preserve the statistical properties of high flows in the basin. Caution is needed when using satellite products for hydrological applications that require the estimation of large peaks and volumes.

Impacts of landscape fragmentation on simulated precipitation fields in the Amazonian sub-basin of Ji-Paraná using the Eta model

Numerical studies on impacts of landscape fragmentation due to land use and land cover change (LUCC) on precipitation fields over the Ji-Paraná basin in the Amazon region are carried out using atmospheric Eta model. Experiments consider historical data about LUCC over the basin from 1978 to 2000 and compare simulations under LUCC conditions with simulations under pristine conditions. In agreement with previous observational studies, model results do not show statistically significant impacts on precipitation in the region. Results indicate that variability in precipitation in this region is mainly controlled by large-scale atmospheric characteristics and soil moisture conditions. However, some limitations are identified in the model simulations, mainly associated to the diurnal cycle of precipitation.

A user-friendly software package for VIC hydrologic model development

The Variable Infiltration Capacity (VIC) hydrologic and river routing model simulates the water and energy fluxes that occur near the land surface and provides useful information regarding the quantity and timing of available water within a watershed system. However, despite its popularity, wider adoption is hampered by the considerable effort required to prepare model inputs and calibrate the model parameters. This study presents a user-friendly software package, named VIC-Automated Setup Toolkit (VIC-ASSIST), accessible through an intuitive MATLAB graphical user interface. VIC-ASSIST enables users to navigate the model building process through prompts and automation, with the intention to promote the use of the model for practical, educational, and research purposes. The automated processes include watershed delineation, climate and geographical input set-up, model parameter calibration, sensitivity analysis, and graphical output generation. We demonstrate the packages utilities in various case studies. We introduce VIC-Automated Setup Toolkit (VIC-ASSIST).VIC-ASSIST framed within a MATLAB GUI aids building and calibrating the VIC model.VIC-ASSIST helps users navigate the model building processes through automation.We demonstrate the packages utilities in various case studies.

Extreme Landfalling Atmospheric River Events in Arizona: Possible Future Changes

The semiarid Salt and Verde River Basins in Arizona are susceptible to atmospheric river (AR)-related flooding. To understand the precipitation-related impacts of climate change on extreme ARs affecting Arizona, a pseudo-global warming method was used. High-resolution control and future simulations of five intense historical AR events that affected the Salt and Verde River Basins in Central Arizona were carried out using the Weather Research and Forecasting regional climate model. The pseudo-global warming approach for future simulations involved adding a temperature delta at different vertical levels to the historical initial and lateral boundary conditions of the input data while keeping constant relative humidity. The deltaswere calculated using projected changes toward end of the 21st century from an ensemble of nine Global Climate Models for the Representative Concentration Pathway (RCP) 8.5. Future simulations showed an overall increase in vertically integrated transport of vapor and upward moisture flux at cloud base over the region for all events. The changes in precipitation at both domain and basin levels were highly spatially heterogeneous. Precipitation increased in all future simulations; but in general, this increase remained less than the increase in column-integrated water vapor. It was found that in most cases, cloud ice content decreased while cloud water content increased, indicating the increased role of warm-rain processes in producing precipitation in the future simulations. Freezing levels rose by more than 600 m, and this along with increased temperature and greater role of warm-rain processes led to a decrease of more than 80% in the amount of frozen precipitation during the events.

Observed Hydrologic Impacts of Landfalling Atmospheric Rivers in the Salt and Verde River Basins of Arizona, United States: HYDROLOGIC IMPACTS OF AR SEMIARID U.S.

Atmospheric rivers (ARs), narrow atmospheric water vapor corridors, can contribute substantially to winter precipitation in the semiarid Southwest U.S., where natural ecosystems and humans compete for over-allocated water resources. We investigate the hydrologic impacts of 122 ARs that occurred in the Salt and Verde river basins in northeastern Arizona during the cold seasons from 1979 to 2009. We focus on the relationship between precipitation, snow water equivalent (SWE), soil moisture, and extreme flooding. During the cold season (October through March) ARs contribute an average of 25%/29% of total seasonal precipitation for the Salt/Verde river basins, respectively. However, they contribute disproportionately to total heavy precipitation and account for 64%/72% of extreme total daily precipitation (exceeding the 98th percentile). Excess precipitation during AR occurrences contributes to snow accumulation; on the other hand, warmer than normal temperatures during AR landfallings are linked to rain-on-snow processes, an increase in the basins’ area contributing to runoff generation, and higher melting lines. Although not all AR events are linked to extreme flooding in the basins, they do account for larger runoff coefficients. On average, ARs generate 43% of the annual maximum flows for the period studied, with 25% of the events exceeding the 10 year return period. Our analysis shows that the devastating 1993 flooding event in the region was caused by AR events. These results illustrate the importance of AR activity on the hydrology of inland semiarid regions: ARs are critical for water resources, but they can also lead to extreme flooding that affects infrastructure and human activities.