Francisco Olivera, Ph.D., P.E.
Division of Environmental and Water Resources Engineering
Associate Professor of Civil Engineering
Texas A&M University
College Station, Texas 77843-3136
Ferreira, C. M., J. Irish and F. Olivera, Quantifying the potential impact of land cover changes due to sea-level rise on storm surge on lower Texas coast bays, Coastal Engineering 94 (2014): 102 - 111.
In this study we investigated the impacts of potential changes of land cover due to sea-level rise (SLR) on storm surge (i.e., the rise of water above normal sea level, namely mean-sea level and the astronomical tide, caused by hurricane winds and pressure) response inside bays on the lower Texas coast. We applied a hydrodynamic and wave model (ADCIRC+SWAN) forced by hurricane wind and pressure fields to quantify the importance of SLR-induced land cover changes, considering its impacts by changing bottom friction and the transfer of wind momentum to the water column, on the peak surge inside coastal bays. The SLR increments considered, 0.5 m to 2.0 m, significantly impacted the surge response inside the bays. The contribution of land cover changes due to SLR to the surge response, on average, ranged from a mean surge increase of 2% (SLR of 0.5 m) to 15 % (SLR of 2.0 m), in addition to the SLR increments. The increase in surge response strongly depended on storm condition, with larger increases for more intense storms, and geographical location. Although land cover changes had little impact on the surge increase for SLR increments lower than 1.0 m, intense storms resulted in surge increase of up to 10% even for SLR below 1.0 m, but in most cases, the geometry changes were the major factor impacting the surge response due to SLR. We also found a strong relationship between changes in bottom friction and the surge response intensification; demonstrating the importance of considering land cover changes in coastal regions that are highly susceptible to SLR when planning for climate change.
Barranco, L.M., J. Alvarez-Rodriguez, F. Olivera, A. Potenciano, L. Quintas and F. Estrada, Assessment of the Expected Runoff Change in Spain Using Climate Simulations, Journal of Hydrologic Engineering 19 (7): 1481 - 1490.
An assessment of the potential effect of climate change on runoff in Spain in the 21st century has been conducted. Runoff depths were calculated with a precipitation runoff model that used as input downscaled Global Climate Model (GCM) outputs. The spatial and temporal resolution of the calculations was one square kilometer and one month, respectively. The assessment consisted of comparing runoff values of the baseline period, 1961-1990, with those of three 21st century periods, 2011-2040, 2041-2070 and 2071-2100, all estimated with simulated temperature and precipitation time series. Twelve climate simulations (i.e., combinations of a GCM, a greenhouse gas emissions scenario and a downscaling algorithm), and whose variability reflects the uncertainty over the future climate, were considered. Based on our results, a decline in runoff is to be expected throughout the country. With respect to the baseline period, and depending on the climate simulation considered, runoff depths are expected to change in the range of +1% to -22% in 2011-2040, -5% to -34% in 2041-2070, and 0% to -40% in 2071-2100.
Estévez, J., F. Moreno-Pérez, J. Roldán-Cañas, A. Serrat-Capdevila, J. González, F. Francés, F. Olivera, J.V. Giráldez, La hidrología y su papel en ingeniería del agua, Ingenieria del Agua 18 (1): 1 - 14 (In Spanish).
La Hidrología es una ciencia esencial en Ingeniería del Agua, la cual abarca un amplio abanico de temas de investigación que engloban los diversos estadios del agua en el ciclo Hidrológico, tanto en atmósfera, superficie y suelo. Con motivo del relanzamiento de la revista Ingeniería del Agua se presenta un breve artículo de carácter introductorio en el que se muestran algunas de la líneas de investigación actuales en Hidrología, dedicadas a lluvia, interceptación de agua por la vegetación, sensores en Hidrología, agua subterránea, entre otras. Dicha revisión no pretende ser exhaustiva, dado el tamaño limitado de este formato de publicación, sino motivar la publicación en Ingeniería del Agua de artículos dentro de la temática Hidrología.
Ferreira, C., J. Irish and F. Olivera, Uncertainty in Hurricane Surge Simulation Due to Land Cover Specification, Journal of Geophysical Reserach: Oceans 119: 1812 - 1827.
Hurricane storm surge is one of the most costly natural hazards in the United States. Numerical modeling to predict and estimate hurricane surge flooding is currently widely used for research, planning, decision making, and emergency response. Land cover plays an important role in hurricane surge numerical modeling because of its impacts on the forcing (changes in wind momentum transfer to water column) and dissipation (bottom friction) mechanisms of storm surge. In this study, the hydrodynamic model ADCIRC was used to investigate predicted surge response in bays on the central and lower Texas coast using different land cover data sets: (1) Coastal Change Analysis Program for 1996, 2001, and 2006; (2) the National Land Cover Dataset for 1992, 2001, and 2006; and (3) the National Wetlands Inventory for 1993. Hypothetical storms were simulated with varying the storm track, forward speed, central pressure, and radius to maximum wind, totaling 140 simulations. Data set choice impacts the mean of maximum surges throughout the study area, and variability in the surge prediction due to land cover data set choice strongly depends on storm characteristics and geographical location of the bay in relation to storm track. Errors in surge estimation due to land cover choice are approximately 7% of the surge value, with change in surge prediction varying by as much as 1 m, depending on location and storm condition. Finally, the impact of land cover choice on the accuracy of simulating surges for Hurricane Bret in 1999 is evaluated.
Ferreira, C., F. Olivera and J. Irish, Arc StormSurge: Integrating Hurricane Storm Surge Modeling and GIS, Journal of the American Water Resources Association 50 (1): 219 - 233.
Arc StormSurge is a data model that integrates Geographic Information Systems (GIS) and the hurricane wave and surge model SWAN+ADCIRC, which is the coupling of the Simulating Waves Nearshore (SWAN) wave model and the Advanced Circulation (ADCIRC) hydrodynamic model. The Arc StormSurge data model is a geodatabase, which is a relational database that can contain georeferenced information. It includes feature classes in feature datasets and tables, all related among them through relationship classes, and raster catalogs and grids. In addition to the data model schema, Arc StormSurge includes a number of pre and post-processing tools that help integrate spatial data and numerical modeling. As an illustration, Arc StormSurge was used to support the modeling of Hurricane Bret, which made landfall in the Corpus Christi area in Texas in 1999. By using Arc StormSurge, it was possible to take advantage of already available geo-referenced information (e.g., base maps, land cover datasets, and monitoring station locations) for the model setup, and for identifying spatial patterns in the model results by presenting them in map format.
Cho, H. and F. Olivera, Application of multi-modal optimization for uncertainty estimation of computationally expensive hydrologic models, Journal of Water Resources Planning and Management 140 (3): 313 - 321.
The Generalized Likelihood Uncertainty Estimation (GLUE) framework has been widely used in hydrologic studies. However, an extensive random sampling causes a high computational burden, which prohibits the efficient application of GLUE to costly distributed hydrologic models such as the Soil and Water Assessment Tool (SWAT). In this study, a multi-modal optimization algorithm called Isolated-Speciation-based Particle Swarm Optimization (ISPSO) is employed to take samples from the search space. A comparison between the ISPSO-GLUE, proposed here, and traditional GLUE approaches shows that the two approaches generate similar uncertainty bounds, but that the convergence rate to stable uncertainty bounds is much faster for ISPSO-GLUE than for GLUE. That is, ISPSO-GLUE needs a much smaller number of samples than GLUE to arrive to a very similar answer. Although the ISPSO-GLUE slightly underestimated the prediction uncertainty and missed a number of observed values, the proposed approach is considered to be a good alternative to the typical GLUE approach that employs random sampling.
Kim D., F. Olivera, H. Cho, and S. Lee, Effect of the Inter-annual Variability of Rainfall Statistics on Stochastically Generated Rainfall Time Series – Part 2. Impact on Watershed Response Variables, Stochastic Environmental Research and Risk Assessment 27 (7): 1611-1619.
This study analyzes how the stochastically generated rainfall time series accounting for the inter-annual variability of rainfall statistics can improve the prediction of watershed response variables such as peak flow and runoff depth. The Modified Bartlett-Lewis rectangular pulse (MBLRP) rainfall generation model was improved such that it can account for the inter-annual variability of the observed rainfall statistics. Then, the synthetic rainfall time series was generated using the MBLRP model, which was used as input rainfall data for SCS hydrologic models to produce runoff depth and peak flow in a virtual watershed. These values were compared to the ones derived from the synthetic rainfall time series that is generated from the traditional MBLRP rainfall modeling. The result of the comparison indicates that the rainfall time series reflecting the inter-annual variability of rainfall statistics reduces the biasedness residing in the predicted peak flow values derived from the synthetic rainfall time series generated using the traditional MBLRP approach by 26% to 47%. In addition, it was observed that the overall variability of the peak flow and run off depth distribution was better represented when the inter-annual variability of rainfall statistics are considered.
Kim D., F. Olivera and H. Cho, Effect of the Inter-annual Variability of Rainfall Statistics on Stochastically Generated Rainfall Time Series – Part 1. Impact on Peak and Extreme Rainfall Values, Stochastic Environmental Research and Risk Assessment 27 (7): 1601-1610.
A noble approach of stochastic rainfall generation that can account for inter-annual variability of the observed rainfall is proposed. Firstly, we show that the monthly rainfall statistics that is typically used as the basis of the calibration of the parameters of the Poisson cluster rainfall generators has significant inter-annual variability and that lumping them into a single value could be an oversimplification. Then, we propose a noble approach that incorporates the inter-annual variability to the traditional approach of Poisson cluster rainfall modeling by adding the process of simulating rainfall statistics of individual months. Among 132 gage-months used for the model verification, the proportion that the suggested approach successfully reproduces the observed design rainfall values within 20% error varied between 0.67 and 0.83 while the same value corresponding to the traditional approach varied between 0.21 and 0.60. This result suggests that the performance of the rainfall generation models can be largely improved not only by refining the model structure but also by incorporating more information about the observed rainfall, especially the inter-annual variability of the rainfall statistics.
Govindasamy, A.V., J.L. Briaud, D. Kim, F. Olivera, P. Gardoni and J. Delphia, Observation Method for Estimating Future Scour Depth at Existing Bridges, Journal of Geotechnical and Geoenvironmental Engineering 139 (7): 1165-1175.
Bridge scour can cause damage to bridge foundations and abutments. Bridges with foundations that are unstable for calculated and/or observed scour conditions are termed scour critical bridges. There are approximately 17,000 scour critical bridges in the United States. This designation comes in part from the use of over-conservative methods that predict excessive scour depths in erosion resistant materials. Other methods capable of overcoming this over-conservatism are relatively uneconomical because they require site-specific erosion testing. This paper proposes a new bridge scour assessment method. The new method, termed the Observation Method for Scour (OMS), was developed for the Texas Department of Transportation’s statewide bridge scour assessment program. The proposed method does not require site-specific erosion testing and accounts for time-dependent scour in erosion resistant materials. OMS was developed for use as a first order assessment in combination with a routine bridge inspection program. OMS uses charts that extrapolate or interpolate measured scour depths at the bridge to obtain the scour depth corresponding to a specified future flood event. The scour vulnerability depends on the comparison between the predicted and allowable scour depths. This paper also includes a new hydraulic-hydrologic analysis procedure for the determination of flow parameters required in OMS. This procedure was developed specifically for the State of Texas. The new hydraulic-hydrologic analysis procedure could possibly be applied to other regions that have sufficient flow gages. The 9 case histories used to validate OMS showed good agreement between predicted and measured values. OMS was then applied to 16 bridges, 10 of which were scour critical bridges that had sufficient information for OMS to be carried out. Six out of these 10 bridges were found to be stable according to OMS.
Kim D., F. Olivera, H. Cho, and S. Socolofsky, Regionalization of the Modified Bartlett-Lewis Rectangular Pulse Stochastic Rainfall Model, Terrestrial, Atmospheric, and Oceanic Sciences 24 (3): 421-436 .
Parameters of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) stochastic rainfall simulation model were regionalized across the contiguous United States. 3,444 National Climate Data Center (NCDC) rain gauges were used to obtain spatial and seasonal patterns of the model parameters. The MBLRP model was calibrated to minimize the discrepancy between the precipitation depth statistics between observed and MBLRP-generated precipitation time series. These statistics included the mean, variance, probability of zero rainfall and autocorrelation at 1-, 3-, 12- and 24-hour accumulation intervals. The Ordinary Kriging interpolation technique was used to generate maps of the six MBLRP model parameters for each of the 12 months of the year. All parameters had clear to discernible regional tendency; except for one related to the rain cell duration distribution. Parameter seasonality, though, was not obvious and it was more apparent in some locations than in others, depending on the seasonality of the rainfall statistics. Cross-validation was used to assess the validity of the parameter maps. The results indicate that the suggested maps reproduce well the statistics of the observed rainfall for different accumulation intervals, except for the lag-1 autocorrelation coefficient. The boundary of the expected residual, with 95% confidence, between the observed rainfall statistics and the statistics of the simulated rainfall based on the map parameters was approximately ±0.064 mm/hr, ±1.63mm2/hr2, ±0.16, and ±0.030 for mean, variance, lag-1 autocorrelation, and probability of zero rainfall at hourly accumulation level, respectively. The estimated parameter values were also used to estimate storm and rain cell characteristics.
Kim, D. and F. Olivera, On the Relative Importance of the Different Rainfall Statistics in the Calibration of Stochastic Rainfall Generation Models, Journal of Hydrologic Engineering 17: 368 - 376, 2012
Stochastic rainfall generators are used in hydrologic analysis because they can provide precipitation input to models whenever data are not available, and their parameters are calculated so that the long-term statistics of the synthetic rainfall time series match those of the rainfall records. However, although mentioned in the literature, the relative importance of each rainfall statistic on the watershed response has not been addressed yet and no guidance on how to account for it has been provided. In this paper, this relative importance is estimated and used to ponder each statistic differently in the calibration of rainfall generators so that it better reflects the watershed hydrology. Rainfall records of 1,249 rain gauges throughout the contiguous United States were used in the study. It was found that, when synthetic rainfall time series are generated by weighting the precipitation statistics according to their relative importance, predicted runoff depths and peak flows are underestimated by 4% and 3%, respectively; while, when they are generated by giving the same weight to all statistics, the underestimation is of 20% and 14%, respectively. These results, based on a significant number of rain gauges, confirm the benefit of weighing the statistics differently for watershed analysis.
Cho, H., D. Kim, F. Olivera and S. Guikema, Enhanced speciation in particle swarm optimization for multi-modal problems, European Journal of Operations Research 213 (2011): 15-23, 2011.
In this paper, we present a novel multi-modal optimization algorithm for finding multiple local optima in objective function surfaces. We build from Species-based particle swarm optimization (SPSO) by using deterministic sampling to generate new particles during the optimization process, by implementing proximity-based speciation coupled with speciation of isolated particles, and by including “turbulence regions” around already found solutions to prevent unnecessary function evaluations. Instead of using error threshold values, the new algorithm uses the particle’s experience, geometric mean, and “exclusion factor” to detect local optima and stop the algorithm. The performance of each extension is assessed with leave-it-out tests, and the results are discussed. We use the new algorithm called Isolated-Speciation-based particle swarm optimization (ISPSO) and a benchmark algorithm called Niche particle swarm optimization (NichePSO) to solve a six-dimensional rainfall characterization problem for 192 rain gages across the United States. We show why it is important to find multiple local optima for solving this real-world complex problem by discussing its high multi-modality. Solutions found by both algorithms are compared, and we conclude that ISPSO is more reliable than NichePSO at finding optima with a significantly lower objective function value
Mousavi, M.E., J.L. Irish, A.E. Frey, F. Olivera and B.L. Edge, Global warming and hurricanes: The potential impact of hurricane intensification and sea level rise on coastal flooding, Climatic Change 104: 575 – 597, 2011.
Tens of millions of people around the world are already exposed to coastal flooding from tropical cyclones. Global warming has the potential to increase hurricane flooding, both by hurricane intensification and by sea level rise. In this paper, the impact of hurricane intensification and sea level rise are evaluated using hydrodynamic surge models and by considering the future climate projections of the Intergovernmental Panel on Climate Change. For the Corpus Christi, Texas, United States study region, mean projections indicate hurricane flood elevation (meteorologically generated storm surge plus sea level rise) will, on average, rise by 0.3 m by the 2030s and by 0.8 m by the 2080s. For catastrophic-type hurricane surge events, flood elevations are projected to rise by as much as 0.5 m and 1.8 m by the 2030s and 2080s, respectively.
Irish, J.L., A.E. Frey, J.D. Rosati, F. Olivera, L.M. Dunkin, J.M. Kaihatu, C.M. Ferreira and B.L. Edge Potential Implications of global warming and barrier island degradation on future hurricane inundation, Ocean and Coastal Management 53 (2010): 645 -657, 2010.
Hurricane flooding is a leading natural threat to coastal communities. Recent evidence of sea level rise coupled with potential future global warming indicate that sea level rise will accelerate and hurricanes may intensify over the coming decades. In regions fronted by barrier islands, the protective capacity of these islands may diminish as they are degraded by rising sea level. Here we present a hydrodynamic and geospatial analysis of the relative role of barrier island degradation on potential future hurricane flooding. For the City of Corpus Christi, Texas, USA, hurricane flooding is projected to rise between 20% and 70% by the 2030s, resulting in an increase in property damages and impacted population. These findings indicate that adaptive management strategies should be developed and adopted for mitigating loss of natural barrier islands when these islands act as protective features for populated bayside communities. Finally, this study illustrates a method for applying models to forecast future storm protection benefits of barrier island restoration projects.
Frey, A.E., F. Olivera, J.L. Irish, L.M. Dunkin, J.M. Kaihatu, C.M. Ferreira and B.L. Edge The impact of climate change on hurricane flooding inundation, population affected and property damages, Journal of the American Water resources Association 46 (5): 1049 - 1059, 2010.
The effect of climate change on storm-surge flooding and the implications for population and structural damages, on the city of Corpus Christi, Texas, was investigated. The study considered the influence of sea level rise and hurricane intensification, both influenced by climate change. Combinations of future carbon dioxide equivalent emission rates and carbon dioxide doubling sensitivities, based on findings of the Intergovernmental Panel on Climate Change, were considered to define future climate scenarios. A suite of physically based numerical models for hurricane winds and the resulting waves, surge, and morphological change at the coast were used to determine flooded areas, population affected and property damages for Hurricanes Bret, Beulah and a version of Carla shifted south from its original track, under present and predicted future climate conditions. A comparison of the economic damages for current climate conditions and for the 2080s climate scenario shows that, for Carla (shifted), there will be an increase in the range of $270 – 1,100 million; for Beulah, of $100 – 390 million; and, for Bret, of $30 – 280 million. A similar analysis was also conducted for 2030s predicted climate scenarios. Overall, the comparison of the results for the different climate conditions indicates what the destructive consequences of climate change could be, even within the somewhat short timeframe of 80 years considered here.
Larentis, D.G., W. Collischonn, F. Olivera and C.E.M. Tucci, GIS-based procedures for hydropower potential spotting, Energy 35 (2010): 4237 - 4243, 2010.
The increasing demand for energy, especially from renewable and sustainable sources, spurs the development of small hydropower plants and encourages investment in new survey studies. Preliminary hydropower survey studies usually carry huge uncertainties about the technical, economic and environmental feasibility of the undeveloped potential. This paper presents a methodology for large-scale survey of hydropower potential sites to be applied in the inception phase of hydroelectric development planning. The sequence of procedures to identify hydropower sites is based on remote sensing and regional streamflow data and was automated within a GIS-based computational program: Hydrospot. The program allows spotting more potential sites along the drainage network than it would be possible in a traditional survey study, providing different types of dam-powerhouse layouts and two types (operating modes) of projects: run-of-the-river and storage projects. Preliminary results from its applications in a hydropower-developed basin in Brazil have shown Hydrospot’s limitations and potentialities in giving support to the mid-to-long-term planning of the electricity sector.
Zaitchik, B.F., M. Rodell and F. Olivera, Evaluation of the Global Land Data Assimilation System using global river discharge data and a Source to Sink routing scheme, Water Resources Research 6: W05507, 2010.
Advanced land surface models (LSMs) offer detailed estimates of distributed hydrological fluxes and storages. These estimates are extremely valuable for studies of climate and water resources, but they are difficult to verify, as field measurements of soil moisture, evapotranspiration, and surface and subsurface runoff are sparse in most regions. In contrast, river discharge is a hydrologic flux that is recorded regularly and with good accuracy for many of the world’s major rivers. These measurements of discharge spatially integrate all upstream hydrological processes. As such, they can be used to evaluate distributed LSMs, but only if the simulated runoff is properly routed through the river basins. In this study, a rapid, computationally efficient Source-To-Sink (STS) routing scheme is presented that generates estimates of river discharge at gauge locations based on gridded runoff output. We applied the scheme as a post-processor to archived output of the Global Land Data Assimilation System (GLDAS). GLDAS integrates satellite and ground based data within multiple offline LSMs to produce fields of land surface states and fluxes. The application of the STS routing scheme allows for evaluation of GLDAS products in regions that lack distributed in situ hydrological measurements. We found that the four LSMs included in GLDAS yield very different estimates of river discharge, and that there are distinct geographic patterns in the accuracy of each model as evaluated against gauged discharge. The choice of atmospheric forcing dataset also had a significant influence on the accuracy of simulated discharge.
Choi, J., F. Olivera and S. Socolofsky, Storm Identification and Tracking Algorithm for Modeling of Rainfall Fields using 1-hour NEXRAD Rainfall Data in Texas, Journal of Hydrologic Engineering 14 (7): 721 - 730, 2009.
A method to identify and track rainfall structures using one-hour accumulated NEXt generation RADar (NEXRAD) rainfall data is presented and used to analyze the dynamics of storm features over an area in Texas. Storm features are identified from a Gaussian mixture model using the expectation maximization algorithm. The method assigns NEXRAD pixels to storm features while simultaneously producing a smooth fitted function to the rainfall intensity distribution. Once the storm features are identified, they are tracked using inverse cost functions and using the fact that continuous features overlap each other from frame to frame in the accumulated data. The inverse cost functions also account for storm feature merging, splitting, birth, and death. Application of this storm identification and tracking algorithm for Brazos County (1,500 km2) in southeastern Texas distinguishes several characteristics of the storm feature dynamics. From September through April, storm features are predominantly of a frontal nature, with storm features following geostrophic flow along low pressure fronts moving in from the north. In summer (May-August), storm features are convective in nature following random track directions. Both types of storm features have durations of one to three hours in Brazos County due to the county’s relatively small size compared to the measured average storm speed of 40 km/hr and due to the fact that most storms only intersect the county over part of their area.
Cho, H. and F. Olivera, Effect of the spatial variability of land use, soil type and precipitation on streamflows in small watersheds, Journal of the American Water Resources Association 45 (3): 673 - 686, 2009.
The spatial variability of the data used in models includes the spatial discretization of the system into subsystems, the data resolution, and the spatial distribution of hydrologic features and parameters. In this study, we investigate the effect of the spatial distribution of land use, soil type, and precipitation on the simulated flows at the outlet of “small watersheds” (i.e., watersheds with times of concentration shorter than the model computational time step). The Soil and Water Assessment Tool (SWAT) model was used to estimate runoff and hydrographs. Different representations of the spatial data resulted in comparable model performances and even the use of uniform land use and soil type maps, instead of spatially distributed, was not noticeable. It was found that, although spatially distributed data help understand the characteristics of the watershed and provide valuable information to distributed hydrologic models, when the watershed is small, realistic representations of the spatial data do not necessarily improve the model performance. The results obtained from this study provide insights on the relevance of taking into account the spatial distribution of land use, soil type, and precipitation when modeling small watersheds.
Cho, H., F. Olivera and S. Guikema, A derivation of the number of minima of the Griewank function, Applied Mathematics and Computation 204 (2008): 694 - 701, 2008.
The Griewank function is commonly used to test the ability of different solution procedures to find local optima. It is important to know the exact number of minima of the function to support its use as a test function. However, to the best of our knowledge, no attempts have been made to analytically derive the number of minima. Because of the complex nature of the function surface, a numerical method is developed to restrict domain spaces to hyperrectangles satisfying certain conditions. Within these domain spaces, an analytical method to count the number of minima is derived and proposed as a recursive functional form. The numbers of minima for two search spaces are provided as a reference.
Merwade, V., F. Olivera, M. Arabi and S. Edleman, Uncertainty in Flood Inundation Mapping – Current Issues and Future Directions, Journal of Hydrologic Engineering 13 (7): 608 - 620, 2008.
This paper presents key issues associated with uncertainty in flood inundation mapping. Currently, flood inundation extent is represented as a deterministic map without consideration to the inherent uncertainties associated with various uncertain variables (precipitation, stream flow, topographic representation, modeling parameters and techniques, and geospatial operations) that are used to produce it. Therefore, it is unknown how the uncertainties associated with topographic representation, flow prediction, hydraulic model and inundation mapping techniques are transferred to the flood inundation map. In addition, the propagation of these individual uncertainties and how they affect the overall uncertainty in the final flood inundation map is not well understood. By using a sample dataset for Strouds Creek in North Carolina, we highlight key uncertainties associated with flood inundation mapping. In addition, we articulate the idea of probabilistic flood inundation map, and present an integrated framework approach that will connect data, models and uncertainty analysis techniques in producing probabilistic flood inundation mapping. The proposed framework will address both the propagation of uncertainty or errors from model inputs and parameters up to the final output, and also the assessment of the relative importance of input uncertainties on the output uncertainty.
Choi, J., S. Socolofsky and F. Olivera, Hourly Disaggregation of Daily Rainfall in Texas Using Measured Hourly Precipitation at Other Locations, Journal of Hydrologic Engineering 13 (6): 476 - 487, 2008.
A method to disaggregate daily rainfall into hourly precipitation is evaluated across Texas. Based on Socolofsky et al. (2001), the method chooses representative storm intensity patterns from measured hourly databases to generate the synthetic data using a single parameter for the smallest expected one-hour event. The model is applied across Texas using historic hourly precipitation data; performance is evaluated by the model’s ability to reproduce hourly rainfall statistics. Based on a cluster analysis to determine which precipitation databases should be used for disaggregation, no trends in space or among gauge characteristics (e.g. period of record, precipitation statistics) were identified. As a result, a Texas state database containing all the measured hourly data in Texas is proposed for use by disaggregation. The state database is verified for a selection of gauges and performed as well at a given station as using that station’s measured rainfall for the disaggregation. The method is further applied to estimate intensity–duration curves which show that the method matches the majority of storm intensities needed to track soil moisture and diverges by less than 17% for the extreme runoff-generating events.
Olivera, F., J. Choi, D. Kim and M. Li, Estimation of Average Rainfall Areal Reduction Factors in Texas Using NEXRAD Data, Journal of Hydrologic Engineering 13 (6): 438 - 448, 2008.
Precipitation areal reduction factors (ARFs) for the 685,000 km2 of Texas were calculated using NEXRAD rainfall estimates. The study was based on 18,531 storms of different durations that took place in different seasons and regions of Texas. The rainfall field was considered anisotropic, and the storms were assumed of elliptical shape. It was found that, in addition to the storm duration and area, other factors such as the season, region and precipitation depth have a statistically significant effect on the ARFs. Elongated ellipses and orientation angles somewhat parallel to the Texas gulf coast were found more frequent in winter, when warm and cold fronts produce frontal storms, than in summer. The effect of the precipitation depth on the ARFs was found to be stronger in summer than in winter. Even though part of the ARF variability could be explained by seasonality, regionality and precipitation depth, the uniqueness of each storm event appears to be an important cause of it. Lower ARF values were observed compared to previous studies.
Li, M-H., M. Barrett, P. Rammohan, F. Olivera and H. Landphair, Documenting Stormwater Quality on Texas Highways and Adjacent Vegetated Roadsides, Journal of Environmental Engineering 134 (1): 48 - 59, 2008.
The primary objective of this study is the documentation of stormwater quality of vegetated roadsides of two Texas highways (State Highway 6 in College Station and Loop 360 in Austin. Both had high average daily traffic (ADT). Three sites each in Austin and College Station were monitored using passive "first flush" stormwater samplers for 16 months. Results from this study indicate that a significant removal of sediment and heavy metals occur over the width of vegetated roadsides. In contrast, vegetated roadsides seem ineffective in reducing nutrient (nitrogen and phosphorus) concentrations. The results also show that vegetation density has a direct effect on the performance of vegetated roadsides. When roadsides are densely covered with grasses above 90%, significant sediment removal is expected often within the first four meters of the edge of pavement. A stepwise regression analysis identifies the antecedent dry period (ADP) as the most significant predictor to pollutant concentration. The pollutant event mean concentration (EMC) was found to decrease with increasing ADP for all pollutants at the College Station sites, but not the Austin ones.
Olivera, F. and B. DeFee, Urbanization and Its Effect on Runoff in the Whiteoak Bayou Watershed, Texas, Journal of the American Water Resources Association 43 (1): 170 - 182, 2007.
The capacity of a watershed to urbanize without changing its hydrologic response and the relationship between that response and the spatial configuration of the developed areas was studied. The study was conducted in the Whiteoak Bayou watershed (223 km2), located northwest of Houston, Texas, over an analysis period from 1949 to 2000. Annual development data were derived from parcel data collected by the Harris County Appraisal District. Using these data, measures of the spatial configuration of the watershed urban areas were calculated for each year. Based on regression models, it was determined that the annual runoff depths and annual peak flows depended on the annual precipitation depth, the developed area and the maximum 12-hour precipitation depth on the day and day before the peak flow took place. It was found that, since the early 1970s, when the watershed reached a 10% impervious area, annual runoff depths and peak flows have increased by 146% and 159%, respectively. However, urbanization is responsible for only 77% and 32% of the increase, respectively, while precipitation changes are responsible for the remaining 39% and 96%, respectively. Likewise, an analysis of the development data showed that, starting in the early 1970s, urbanization in the watershed consisted more of connecting already developed areas than of creating new ones, which increases the watershed’s conveyance capacity and explains the change in its response. Before generalizing conclusions, though, further research on other urban watersheds with different urbanization models appears to be necessary.
Olivera, F., M. Valenzuela, R. Srinivasan, J. Choi, H. Cho, S. Koka, and A. Agrawal, ArcGIS-SWAT: A Geodata Model and GIS Interface for SWAT, Journal of the American Water Resources Association 42 (2): 295 - 309, 2006.
This paper presents ArcGIS-SWAT, a geodata model and GIS interface for the Soil and Water Assessment Tool (SWAT). The ArcGIS-SWAT data model is a system of geodatabases that store SWAT geographic, numeric and text input data and results in an organized fashion. Thus, it is proposed that a single and comprehensive geodatabase be used as the repository of a SWAT simulation. The ArcGIS-SWAT interface uses programming objects that conform to the Component Object Model (COM) design standard, which facilitate the use of functionality of other Windows-based applications within ArcGIS-SWAT. In particular, the use of MS Excel and MATLAB functionality for data analysis and visualization of results is demonstrated. Likewise, it is proposed to conduct hydrologic model integration through the sharing of information with a not-model-specific hub data model where information common to different models can be stored and from where it can be retrieved. As an example, it is demonstrated how the Hydrologic Modeling System (HMS) – a computer application for flood analysis – can use information originally developed by ArcGIS-SWAT for SWAT. The application of ArcGIS-SWAT to the Seco Creek watershed in Texas is presented.
Olivera, F., S. Koka and J. Nelson, WaterNet: A GIS Application for the Analysis of Hydrologic Networks Using Vector Spatial Data, Transactions in GIS 10 (3): 355-375, 2006.
Traditionally, stream and sub-watershed characterization in GIS has been done using a DEM-based terrain analysis approach; however, there is a large amount of existing vector hydrographic data difficult to accurately reproduce using DEMs. WaterNet is a GIS/hydrologic application for the integration and analysis of stream and sub-watershed networks in vector format. Even with vector data, hydrologic inconsistencies between streams and sub-watersheds do exist, and are revealed in the form of streams crossing drainage divides and sub-watersheds with more than one outlet. WaterNet rectifies these inconsistencies and couples the two datasets. Most algorithms involving traces of dendritic networks employ a form of tree traversal which requires topologic information to be organized into specialized data structures. On the contrary, WaterNet develops topologic relationships from GIS attributes table, which, in combination with sorting and querying algorithms, make the calculation process efficient and easy to implement. With the topologic relationships of the streams and sub-watersheds, WaterNet can perform traces to calculate cumulative network parameters, such as flow lengths and drainage areas. WaterNet was applied to the catchment of the Texas Gulf coast for a total of 100 cataloging units (411,603 km2) and 60,145 stream lines (183,228 km).
Olivera, F. and S. Koka, Advective and Hydrodynamic Dispersive Processes in Watershed Responses, Journal of Hydrologic Engineering 9 (6): 534-544, 2004.
A model for estimating the watershed response is presented and used for assessing how the watershed size and spatial variability of the hydrodynamic parameters (i.e., wave celerity and dispersion coefficient) affects the comparative importance of advective processes with respect to hydrodynamic dispersive processes. A parameter W was defined to quantify this comparative importance. This parameter represents the fraction of the watershed response variance that is explained by advection. A series of simulations were performed for basins of different sizes and different spatial distributions of their hydrologic parameters. It was found that, for spatially uniform hydrodynamic parameters, the effect of hydrodynamic dispersion decreases compared to that of advection as the watershed size increases, and vice versa; and that, for non-uniform hydrodynamic parameters, the spatial distribution of the parameter values over the watershed, in conjunction with the watershed size, determines which process – advection or hydrodynamic dispersion – prevails.
Leão, R.A.O., A.S. Teixeira, E.M. de Andrade and F. Olivera, Automatic delimitation and characterization of a catchment located at the Fazenda Experimental Vale do Curu in Pentecoste County - Brazil, Revista Ciência Agronômica 35 (1): 26-35, 2004.
This paper aims at comparing the output of two methodologies in the delimitation and characterization of a catchment located at the Fazenda Experimental Vale do Curu in Pentecoste County - Brazil (3o48�49.1�S; 39o20�17.8�W). Results from the extension CRWR-PrePro under ARCVIEW environment were compared with the traditional (planimeter and curvimeter) procedure. The database was extracted from a topographic map scaled to 1:5,000 and elevation contours spaced every 5 m. The topographic map was sampled to produce a 50 x 50 m grid of elevation by interpolating between contours and generating a Digital Elevation Map (DEM). Using the extension CRWR-PrePro under ArcView GIS 3.2 two catchments above 300 ha were identified. One of the catchments was selected for further analysis. The watershead was characterized using both CRWR-PrePro and the planimeter/curvimeter procedure, and the following parameters were computed: drainage divide length, catchment�s area, number of stream, total stream length, drainage density, main stream length, mean main stream slope, catchment�s length, mean catchment�s slope, form ratio and elongation ratio. Results shown that there CRWR-PrePro underestimation the parameters catchment�s area (5.4%), mean main stream slope (8.7%), mean catchment�s slope, (5.4%), form ratio (16.7%) e elongation ratio (8.1%) and overestimation the parameter drainage divide length (24.6%), total stream length (17.4%), drainage density (24.1%), main stream length (8.4%) e catchment�s area (4.8%). The number of streams was the same to the two methods, leading to the conclusion that both methodologies produce closer results with the advantage of standardization, easier and faster analysis by using the CRWR-PrePro extension upon availability of a Digital Elevation Map.
Olivera, F. and R. Raina, Development of Large-Scale Gridded River Networks from Vector Stream Data, Journal of the American Water Resources Association 39 (5): 1235-1248, 2003.
Network Tracing Method (NTM) has been developed to determine gridded coarse
river networks for modeling large hydrologic systems. For a coarse-resolution
grid, the NTM determines the downstream cell of each cell, and the distance
along the actual meandering flow paths between them. As opposed to previously
developed methods, the NTM uses fine-resolution vector river networks as the
source of information of the flow patterns, rather than digital elevation
models. The main advantage of using vector river networks as input is that they
capture the hydrologic terrain features better than topographic data do,
particularly in areas of low topographic relief. The NTM was applied to
Olivera, F., M. Lear, J. Famiglietti and K. Asante, Extracting Low-Resolution River Networks from High-Resolution Digital Elevation Models, Water Resources Research 38 (11): 13/1-8, 2002.
Including global river networks in the land component of global climate models (GCMs) is necessary in order to provide a more complete representation of the hydrologic cycle. The process of creating these networks is called river-network upscaling, and consists of lowering the resolution of already available fine networks to make them compatible with GCMs. Fine resolution river networks have a level of detail appropriate for analysis on the watershed scale, but are too intensive for global hydrologic studies. A river-network upscaling algorithm, which processes fine-resolution digital elevation models to determine the flow directions that best describe the flow patterns in a coarser user-defined scale, is presented. The objectives of this study were to develop an algorithm that advances the previous work in the field by being applicable at a global scale, allowing for the upscaling to be performed in a projected environment, and generating evenly distributed flow directions.
Olivera, F., D. Maidment and D. Honeycutt, Hydro Networks, Chapter 3 in Arc Hydro - GIS for Water Resources, ed. D. Maidment, ESRI Press, Redlands, CA, 2002.
The hydro network is the backbone of Arc Hydro, created from edges and junctions. The topological connection of its HydroEdges and HydroJunctions in a geometric network enables tracing of water movement upstream and downstream through streams, rivers, and water bodies. Relationships built from the HydroJunctions connect drainage areas and point features such as stream-gauging stations to the hydro network. Locations in the hydro network are defined by a river-addressing scheme that defines where points are located on lines within drainage areas, allowing measurement of flow distance between any two points on a flow path.
Olivera, F., J. Furnans, D. Maidment, D. Djokic and Z. Ye, Drainage Systems, Chapter 4 in Arc Hydro - GIS for Water Resources, ed. D. Maidment, ESRI Press, Redlands, CA, 2002.
Water and land interact with one another: the shape of the land surface directs the drainage of water through the landscape, while the erosive power of water slowly reshapes the land surface. Streams, rivers, and water bodies lie in the valleys and hollows of the land surface, and drainage from the ridges and higher land areas flows downhill into these water systems. Digital elevation models (DEMs) are used to analyze the drainage patterns of the land-surface terrain, and drainage areas are delineated from outlets chosen either manually or automatically according to physical rules. Raster analysis using fine-resolution DEMs is practical only over limited areas, but these results may be combined with vector networks to carry out regional hydrologic studies. Drainage areas can be traced upstream and downstream, either through their attachment to the hydro network or by using area-to-area navigation, thereby identifying the region of hydrologic influence upstream and downstream of a catchment or watershed.
Tate, E., D. Maidment, F. Olivera and D. Anderson, Creating a Terrain Model for Floodplain Mapping, Journal of Hydrologic Engineering 7 (2): 100-108, 2002.
Computer models play a pivotal role in hydraulic analysis by aiding in the determination of water surface profiles associated with different flow conditions. Many hydraulic models contain a wealth of detailed cross-section data that were developed specifically for the modeling effort, typically from land surveys. Unfortunately, these high-resolution data are generally stored in hydraulic model coordinates, a format that does not maintain the geographic coordinates of the cross-sections. As a result, cross-section data typically must be digitized in order to assign them geographic coordinates. Automating this process would result in significant savings of both time and resources. The research presented in this paper offers an automated geographic information system (GIS) based approach for the development of a terrain model from output of the HEC-RAS hydraulic model. As input, the approach requires a completed HEC-RAS model, a digital elevation model (DEM) of the study area, and a GIS representation of the stream thalweg. The process begins with the conversion of terrain data from hydraulic model coordinates to geographic coordinates. A terrain model is subsequently synthesized by merging the HEC-RAS data, which describe the stream channel geometry, and comparatively lower resolution DEM data. The resulting surface model provides a good representation of the general landscape and contains additional detail within the stream channel. An example application to Waller Creek in Austin, Texas is presented.
Olivera, F., Extracting Hydrologic Information from Spatial Data for HMS Modeling, Journal of Hydrologic Engineering 6 (6): 524-530, 2001.
A methodology is presented for extracting topographic, topologic and hydrologic information from digital spatial data of a hydrologic system, for hydrologic modeling with HMS. Methods for stream and watershed delineation from digital elevation models are presented. After vectorizing the raster-based stream segments and watersheds, navigation fields are added to their tables to support topologic analysis based entirely on the information stored in the tables of the spatial datasets. Algorithms for calculation of stream segment and watershed hydrologic parameters are also discussed. These parameters are curve number, area and lag-time for the watersheds, and routing model and travel-time for the stream segments. Once the hydrologic parameters and the topology are defined, a basin model that summarizes all the information and that can be used as input for HMS is created. Using this methodology, the determination of the spatial parameters for HMS is an automatic process that accelerates the setting up of a hydrologic model and leads to reproducible results.
Olivera, F., J. Famiglietti and K. Asante, Global-Scale Flow Routing Using a Source-to-Sink Algorithm, Water Resources Research 36 (8): 2197-2207, 2000.
In this paper, the development and global application of a new approach to large-scale river routing is described. It differs from previous methods by the extent to which the information content of high-resolution global digital elevation models is exploited in a computationally-efficient framework. The model transports runoff directly from its source of generation in a land model cell to its sink on a continental margin or in an internally draining basin (and hence is referred to as source-to-sink routing) rather than from land cell to land cell (which we call cell-to-cell routing). It advances the development of earlier source-to-sink models by allowing for spatially-distributed flow velocities, attenuation coefficients and loss parameters. The method presented here has been developed for use in climate system models, with a specific goal of generating hydrographs at continental margins for input into an ocean model. However, the source-to-sink approach is flexible and can be applied at any space-time scale, and in a number of other types of large-scale hydrological and Earth system models. Hydrographs for some of the world's major river basins resulting from a global application, as well as hydrographs for the Nile River from a more detailed application, are discussed.
Olivera, F. and D. Maidment, GIS tools for HMS Modeling Support, Chapter 5 in Hydrologic and Hydraulic Modeling Support, eds. D. Maidment and D. Djokic, ESRI Press, Redlands, CA, 2000.
CRWR-PrePro is a system of ArcView scripts and associated controls, developed to extract topographic, topologic and hydrologic information from digital spatial data of a hydrologic system, and to prepare ASCII files for the basin and precipitation components of HEC-HMS. These files, when opened by HEC-HMS, automatically create a topologically correct schematic network of sub-basins and reaches attributed with hydrologic parameters, and a protocol to relate gage to sub-basin precipitation time series. Starting from the DEM, CRWR-PrePro delineates the sub-basins and the reach network, calculates parameters for each hydrologic element, determines their interconnectivity, and prepares an input file for HEC-HMS that includes the computed hydrologic parameters. CRWR-PrePro also generates an input file for the precipitation component of HEC-HMS. Two methods to interpolate precipitation records are supported: one to calculate average precipitation at the sub-basins based on Thiessen polygons, and another to calculate the routing parameters of precipitation cells for hydrograph determination. Using CRWR-PrePro, the determination of the spatial parameters for HEC-HMS is a simple and automatic process that accelerates the setting up of a hydrologic model and leads to reproducible results.
DeBarry, P.A., J. Garbrecht, L. Garcia, L.E. Johnson, J. Jorgeson, V. Krysanova, G. Leavesley, D. Maidment, E.J. Nelson, F.L. Ogden, F. Olivera, R.G. Quimpo, T.A. Seybert, W.T Sloan, D. Burrows, and E.T. Engman, GIS Modules and Distributed Models of the Watershed, American Society of Civil Engineers Water Resources Division - Surface Water Hydrology Committee, 120 pp., Reston, VA, 1999.
Recent advances in Geographic Information Systems (GIS) technology offer hydrologic engineers, watershed managers, and data collection agencies unprecedented capabilities for storing and manipulating large quantities of detailed, spatially-distributed, watershed data. However, there is a shortfall of widely accepted techniques to take full advantage of hydrologic data in GIS format for actual watershed analysis. The ASCE Task Committee (TC) on GIS Modules and Distributed Models of the Watershed was established to identify existing data sources and techniques for watershed analysis within a GIS framework. The TC also provided a forum for the presentation of recent advances in this field at national ASCE conferences. An international mail survey was conducted to identify recent developments in GIS modules and distributed hydrologic models. This report presents state-of-the-art integrated GIS hydrologic analysis software and techniques, along with an overview and discussion of GIS data types and map projections. Data commonly required for hydrologic analysis using GIS techniques and available sources are listed; limitations of available data are discussed; and the integration of watershed hydrological analysis software and GIS techniques are presented.
Olivera F. and D. Maidment, GIS-Based Spatially Distributed Model for Runoff Routing, Water Resources Research 35 (4): 1155-1164, 1999.
A method is proposed for routing spatially distributed excess precipitation over a watershed to produce runoff at its outlet. The land surface is represented by a (raster) digital elevation model from which the stream network is derived. A routing response function is defined for each digital elevation model cell, so that water movement from cell to cell can be convolved to give a response function along a flow-path, and responses from all cells can be summed to give the outlet hydrograph. An example application of analysis of runoff on Waller Creek in Austin, Texas, is presented.
Olivera, F. and D. Maidment, GIS for Hydrologic Data Development for Design of Highway Drainage Facilities, Transportation Research Record # 1625: 131-138, 1998.
A significant part of the cost of most highway projects is attributable to drainage facilities such as storm drains, highway culverts, bridges, and water quality and quantity control structures. In this paper, we present a geographic information system (GIS) for hydrologic data development for design of drainage facilities, developed to reduce the analysis time and improve its accuracy by integrating spatial data describing the watershed, with hydrologic theory. A grid-based GIS to estimate potential extreme peak discharges, and watershed parameters, peak discharges for different frequencies, isochrone lines and runoff curve numbers is presented, using data from the State of Texas as an example application.
Maidment, D., F. Olivera, A. Calver, A. Eatherall and W. Fraczek, A Unit Hydrograph Derived From a Spatially Distributed Velocity Field, Special Issue of Hydrological Processes 10 (6): 831-844, 1996.
A unit hydrograph model is proposed in which the watershed is decomposed into subareas which are individual cells or zones of neighboring cells. The unit hydrograph is found for each subarea and the response at the outlet to excess rainfall on each subarea is summed to produce the watershed runoff hydrograph. The cell to cell flow path to the watershed outlet is determined from a digital elevation model. A constant flow velocity is assigned to each cell and the time lag between subarea input and response at the watershed outlet is found by integrating the flow time along the path from the subarea to the outlet. The response function for a subarea is modeled as a lagged linear reservoir in which the flow time is equal to the sum of a time of translation and an average residence time in the reservoir. It is shown that the assumption of a spatially-varying, but time-invariant, velocity field underlying this model produces a linear system model for all subareas whose outputs can be summed in the manner indicated. An example application is presented for the 8.70-Km2 Severn watershed at Plynlimon in Wales using a 50-meter digital elevation model in which the cell velocity is calculated by modifying an average velocity according to the terrain slope and the drainage area of each cell. The resulting model reasonably reproduces the observed unit hydrograph.
Updated on November 6, 2013, by Francisco Olivera