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Papers by Emad Habib

Results of numerous evaluation studies indicated that satellite-rainfall products are contaminate... more Results of numerous evaluation studies indicated that satellite-rainfall products are contaminated with significant systematic and random errors. Therefore, such products may require refinement and correction before being used for hydrologic applications. In the present study, we explore a rainfall-runoff modeling application using the Climate Prediction Center-MORPHing (CMORPH) satellite rainfall product. The study area is the Gilgel Abbay catchment situated at the source basin of the Upper Blue Nile basin in Ethiopia, Eastern Africa. Rain gauge networks in such area are typically sparse. We examine different bias correction schemes applied locally to the CMORPH product. These schemes vary in the degree to which spatial and temporal variability in the CMORPH bias fields are accounted for. Three schemes are tested: space and time-invariant, time-variant and spatially invariant, and space and time variant. Bias-corrected CMORPH products were used to calibrate and drive the Hydrologiska Byråns Vattenbalansavdelning (HBV) rainfall-runoff model. Applying the space and time-fixed bias correction scheme resulted in slight improvement of the CMORPH-driven runoff simulations, but in some instances

2010 Annual Conference & Exposition Proceedings

His research is in the areas of hydrology and hydrometeorology with emphasis on in-situ and remot... more His research is in the areas of hydrology and hydrometeorology with emphasis on in-situ and remote sensing measurements of rainfall, hydrological applications of radar-rainfall information, hydrologic modeling, uncertainty assessment and validation of rainfall remotely-sensed products, and hydrological applications of statistical methods. He teaches undergraduate and advanced graduate courses in hydrology and probabilistic methods. He is the co-chair of the Uncertainty Assessment Task of the Coastal Louisiana Ecosystem Assessment and Restoration Model and a member on the American Society of Civil Engineers Environmental Water Resources Institute "Doppler Radar" Task Committee. He has several peer-reviewed publications and serves as a regular reviewer on journals such as Journal of Hydrologic Engineering,

Eos, 2017

Students use real data sets to explore how population changes, power generation, and water-saving... more Students use real data sets to explore how population changes, power generation, and water-saving strategies affect surface and groundwater use.

Radar-rainfall information presents a significant potential for improving our ability to provide ... more Radar-rainfall information presents a significant potential for improving our ability to provide accurate and timely flood predictions. Similar to other measuring devices, radar data also has many uncertainties. One of the main sources of uncertainties is due to natural and sampling variations in the estimation of rainfall rates from radar reflectivity factors. The National Weather Service (NWS) WSR-88D estimates rainfall rates by employing a relationship between Reflectivity factor Z (mm m) and rainfall rate R (mm h) of the form Z=AR (Ulbrich and Miller, 2001). Both Z and R are defined as different moments of the drop size distribution (DSD) in a sampled volume. Typical default values used by the NWS are A=300 and b=1.4 (for system with deep convection) and A=250 and b=1.2 (for tropical events). Earlier work by Atlas et al. (1999) showed that there can be dramatic changes in Z-R parameters between storms as well as within individual storms. The variability in Z-R relationship is at...

Remote Sensing, 2020

This article presents an online teaching tool that introduces students to basic concepts of remot... more This article presents an online teaching tool that introduces students to basic concepts of remote sensing and its applications in hydrology. The learning module is intended for junior/senior undergraduate students or junior graduate students with no (or little) prior experience in remote sensing, but with some basic background of environmental science, hydrology, statistics, and programming. This e-learning environment offers background content on the fundamentals of remote sensing, but also integrates a set of existing online tools for visualization and analysis of satellite observations. Specifically, students are introduced to a variety of satellite products and techniques that can be used to monitor and analyze changes in the hydrological cycle. At completion of the module, students are able to visualize remote sensing data (both in terms of time series and spatial maps), detect temporal trends, interpret satellite images, and assess errors and uncertainties in a remote sensing...

The era of ”big data” promises to provide new hydrologic insights, and open web-based platforms a... more The era of ”big data” promises to provide new hydrologic insights, and open web-based platforms are being developed and adopted by the hydrologic science community to harness these datasets and data services. This shift accompanies advances in hydrology education and the growth of web-based hydrology learning modules, but their capacity to utilize emerging open platforms and data services to enhance student learning through data-driven activities remains largely untapped. Given that generic equations may not easily translate into local or regional solutions, teaching students to explore how well models or equations work in particular settings or to answer specific problems using real data is essential. This paper introduces an open web-based learning module developed to advance data-driven hydrologic process learning, targeting upper level undergraduate and early graduate students in hydrology and engineering. The module was developed and deployed on the HydroLearn open educational ...

Remote Sensing, 2020

Radar-based Quantitative Precipitation Estimates (QPE) provide rainfall products with high tempor... more Radar-based Quantitative Precipitation Estimates (QPE) provide rainfall products with high temporal and spatial resolutions as opposed to sparse observations from rain gauges. Radar-based QPE’s have been widely used in many hydrological and meteorological applications; however, using these high-resolution products in the development of Precipitation Frequency Estimates (PFE) is impeded by their typically short-record availability. The current study evaluates the robustness of a spatial bootstrap regional approach, in comparison to a pixel-based (i.e., at site) approach, to derive PFEs using hourly radar-based multi-sensor precipitation estimation (MPE) product over the state of Louisiana in the US. The spatial bootstrap sampling technique augments the local pixel sample by incorporating rainfall data from surrounding pixels with decreasing importance when distance increases. We modeled extreme hourly rainfall data based on annual maximum series (AMS) using the generalized extreme va...

Remote Sensing, 2020

Radar-rainfall products provide valuable information for hydro-ecological modeling and ecosystem ... more Radar-rainfall products provide valuable information for hydro-ecological modeling and ecosystem applications, especially over coastal regions that lack adequate in-situ rainfall observations. This study evaluates two radar-based rainfall products, the Multi-Sensor Stage IV and the Multi-Radar Multi-Sensor (MRMS), over the Louisiana coastal region in the United States. Surface reference rainfall observations from two independent rain gage networks were used in the analysis. The evaluation included distribution-based comparisons between radar and gage observations at different time scales (hourly to monthly), bias decomposition to quantify the contribution of different error sources, and conditional evaluation of systematic and random components of the estimation errors. Both products report large levels of random errors at the hourly scale; however, the performance of the radar-rainfall products improves significantly with the increase in time scales. After decomposing the total bia...

Journal of Hydroinformatics, 2017

Two years of K-Band micro rain radar-2 (MRR) data are used to investigate the vertical variabilit... more Two years of K-Band micro rain radar-2 (MRR) data are used to investigate the vertical variability of rain in an atmospheric column and assess MRR rainfall estimates accuracy from both direct rainfall measurement using the Mie Theory (i.e., MRR RR) and a Z-R relationship (Z = 300 R1.4) (i.e., MRR Rz). Two different height resolutions (HR) settings are used. A nearby Doppler weather radar KEWX (S-band) using the same Z-R relationship is found to underestimate rainfall by up to 32.2%, while MRR estimates are much closer to collocated gauge measurements. For the first three gates, MRR RR underestimates rainfall by 5.7%–60.1% for the HR of 35 meters and by 31.2%–47.9% for the 100 meter resolution, while MRR RR overestimates rainfall for higher gates at the 100 m resolution, and MRR Rz underestimates rainfall at all gates due to errors of the Z-R relationship (Z = aRb). Gates higher than 2,000 m are affected by bright band and mixed phase rainfall. Examination of the rainfall statistics ...

Journal of Coastal Research, 2017

Recent decades have witnessed the development and implementation of several regional-scale, coast... more Recent decades have witnessed the development and implementation of several regional-scale, coastal-restoration planning projects that deal with human-natural coupled ecosystems. With their rich contexts, societal importance and preavailable data and modeling resources, these projects offer unique, multidisciplinary learning opportunities that are yet to be tapped into, especially at the undergraduate level. The current study presents an effort to capitalize on these regional-scale projects and use their resources in undergraduate educational settings. The study describes the development of a set of Web-based learning modules that are situated in the Chenier Plain coastal ecosystem in Louisiana. Going through a comprehensive. coast-wide restoration-planning effort, coastal Louisiana is a unique ecosystem that captures the interactions between inland hydrology and coastal and wetland processes. Centered on the current crisis of coastal land loss in the region, the modules immerse students in a suite of active-learning experiences in which they prepare and analyze data, reproduce model simulations, interpret results, and balance the beneficial and detrimental impacts of several real-world coastal-restoration projects. The modules cover a wide array of topics, including system-scale analysis of water and salt budgets, use of numerical models in coastal hydrologic settings, linkages between hydrologic variability and vegetation regimes, and assessments of different restoration strategies. The article presents lessons learned, challenges, and students' perspectives from pilot classroom implementations to guide similar future efforts on using large-scale, coastal-ecosystem projects to enrich current educational practices in the field of coastal hydrology and other related topics.

Environmental Research Letters, 2016

Groundwater is increasingly being overdrafted in the Southeastern U.S., despite abundant rainfall... more Groundwater is increasingly being overdrafted in the Southeastern U.S., despite abundant rainfall and the apparent availability of surface water. Using the state of Louisiana as an example, the current study quantifies the stresses on water resources and investigates the potential for opportunities to use surface water in lieu of groundwater pumping. The assessment is based on a fine watershed scale (12-digit Hydrological Unit Code [HUC] boundaries) water balance between the availability of surface and groundwater and surface water and groundwater demand. Water demand includes environmental flows, as well as public supply, rural domestic, industrial, power generation, agricultural, and aquaculture sectors. The seasonality of water stress is also addressed by incorporating monthly variations in surface water supply and irrigation demands. We develop several new weighting schemes to disaggregate the water withdrawals, provided by the U.S. Geological Survey on a county scale, to the HUC12 scale. The analysis on the smaller HUC12 scale is important for identifying areas with high water stress that would otherwise be masked at a larger scale (e.g. the county or HUC8 watershed scales). The results indicate that the annual water stress in Louisiana is below one (i.e. there is more water available than is used) for most watersheds; however, some watersheds (15 of the HUC12 units) show stresses greater than one, indicating an insufficient water supply to meet existing demands. The areas of the highest water stress are largely attributable to water consumption for power generating plants or irrigation. Moreover, estimating the stresses on surface water and groundwater sources separately confirms our speculation of abundant surface water and demonstrates a significant over-drafting/deficit of groundwater in many of the states aquifer systems. These results have implications for identifying new opportunities for reallocation of surface water use to reduce groundwater pumping and improve water sustainability in the region. Seasonal fluctuations in surface water supply and water withdrawals for irrigation highlight the fact that the water system is under more stress during the summer season. This observation underscores the need for infrastructure for shortterm surface water storage in agricultural regions. The water budget analysis presented here can be useful for stakeholders in developing water management plans and can also help to inform the development of a water code that will enable Louisiana to successfully manage and conserve its water resources for the future.

2016 ASEE Annual Conference & Exposition Proceedings

He received his Sc.D. and M.S. in Civil Engineering (Water Resources and Hydrology) from the Mass... more He received his Sc.D. and M.S. in Civil Engineering (Water Resources and Hydrology) from the Massachusetts Institute of Technology and his B.Sc Eng in Civil Engineering from the University of Natal in South Africa. His research and teaching are in the area of surface water hydrology. His research focuses on advancing the capability for hydrologic prediction by developing models that take advantage of new information and process understanding enabled by new technology. He has developed a number of models and software packages including the TauDEM hydrologic terrain analysis and channel network extraction package that has been implemented in parallel, and a snowmelt model. He is lead on the National Science Foundation HydroShare project to expand the data sharing capability of Hydrologic Information Systems to additional data types and models and to include social interaction and collaboration functionality. He teaches Hydrology and Geographic Information Systems in Water Resources.

Sensors, 2016

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining at... more With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9,. .. , 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

World Environmental and Water Resources Congress 2007, 2007

This study focuses on using NEXRAD radar-rainfall information to investigate the impact of rainfa... more This study focuses on using NEXRAD radar-rainfall information to investigate the impact of rainfall spatial variability and limited sampling on salinity prediction in an estuarine system. The site of this study is the Barataria basin, which is a wetland-dominated estuarine ecosystem in southwest Louisiana. Salinity prediction was found to rely heavily upon accurately estimating basin rainfall, due to rainfall being the largest source of freshwater and the most variable component in the net supply of fresh water to the basin. Rain gauge density scenarios of limited rainfall samplings were simulated from the fully-distributed radar data and corresponding salinity predictions were assessed. Results indicated that a high degree of uncertainty existed in salinity prediction associated with the typical average U.S. rain gauge density (1.3 gauges/1000 km 2 ). By slightly increasing rain gauge density beyond the typical density, a significant amount of salinity prediction uncertainty could be reduced.

Journal of Sea Research, 2010

... There, the dissolved nitrogen load exported from the Louisiana coastal region fuels a growing... more ... There, the dissolved nitrogen load exported from the Louisiana coastal region fuels a growing hypoxia zone ( 21,000 km 2 ; [Rabalais et al., 2002a], [Rabalais et al., 2002b], [Scavia et al., 2004], [Hyfield et al., 2008] and [Turner et al., 2008]). ...

Journal of Hydrometeorology, 2012

The rain gauge network associated with the Walnut Gulch Experimental Watershed (WGEW) in southeas... more The rain gauge network associated with the Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona provides a unique opportunity for direct comparisons of in situ measurements and satellite-based instantaneous rain rate estimates like those from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR). The WGEW network is the densest rain gauge network in the PR coverage area for watersheds greater than 10 km2. It consists of 88 weighing rain gauges within a 149-km2 area. On average, approximately 10 gauges can be found in each PR field of view (~5-km diameter). All gauges are very well synchronized with 1-min reporting intervals. This allows generating very-high-temporal-resolution rain rate fields and obtaining accurate estimates of the area-average rain rate for the entire watershed and for a single PR field of view. In this study, instantaneous rain rate fields from the PR and the spatially interpolated gauge measurements (on a 100 m × 100 m grid, updat...

Journal of Hydrology, 2008

This article was published in an Elsevier journal. The attached copy is furnished to the author f... more This article was published in an Elsevier journal. The attached copy is furnished to the author for non-commercial research and education use, including for instruction at the author's institution, sharing with colleagues and providing to institution administration. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: http://www.elsevier.com/copyright

Journal of Coastal Research, 2007

Reliable forecasts of salinity changes are essential for restoring and sustaining natural resourc... more Reliable forecasts of salinity changes are essential for restoring and sustaining natural resources of estuaries and coastal ecosystems. Because of the physical complexity of such ecosystems, information on uncertainty associated with salinity forecasts should be assessed and incorporated into management and restoration decisions. The objective of this study was to investigate uncertainty in salinity forecasts imposed by limitations on data available to calibrate and apply a mass balance salinity model in the Barataria basin, Louisiana. The basin is an estuarine wetlanddominated ecosystem located directly west of the Mississippi Delta complex. The basin has been experiencing significant losses of wetland at a rate of nearly 23 km 2 /y. A Bayesian-based methodology was applied to study the effect of data-related uncertainty on both the retrieval of model parameters and the subsequent model predictions. We focused on uncertainty caused by limited sampling and coverage of salinity calibration data and by sparse rain gauge data within the basin. The results indicated that data limitations lead to significant uncertainty in the identification of model parameters, causing moderate to large systematic and random errors in model results. The most significant effect was related to lack of accurate information on rainfall, a major source of fresh water in the basin. The approach and results of this study can be used to identify necessary improvements in monitoring of complex estuarine systems that can decrease forecast uncertainty and allow managers greater accuracy in planning restoration of coastal resources.

Computers & Geosciences, 2003

To aid in modeling studies over the Mississippi River Basin, we have developed an archival precip... more To aid in modeling studies over the Mississippi River Basin, we have developed an archival precipitation data set for the GEWEX Continental-Scale International Project. The data set spans from 1996–2000, a 5-year continuous period of record. Inputs for the data set are the National Reflectivity Composite that we obtained in Hierarchical Data Format. The size of the input data is

Hydrology and Earth System Sciences, 2012

HydroViz is a Web-based, student-centered, educational tool designed to support active learning i... more HydroViz is a Web-based, student-centered, educational tool designed to support active learning in the field of Engineering Hydrology. The design of HydroViz is guided by a learning model that is based on learning with data and simulations, using real-world natural hydrologic systems to convey theoretical concepts, and using Web-based technologies for dissemination of the hydrologic education developments. This model, while being used in a hydrologic education context, can be adapted in other engineering educational settings. HydroViz leverages the free Google Earth resources to enable presentation of geospatial data layers and embed them in web pages that have the same look and feel of Google Earth. These design features significantly facilitate the dissemination and adoption of HydroViz by any interested educational institutions regardless of their access to data or computer models. To facilitate classroom usage, Hy-droViz is populated with a set of course modules that can be used incrementally within different stages of an engineering hydrology curriculum. A pilot evaluation study was conducted to determine the effectiveness of the HydroViz tool in delivering its educational content, to examine the buy-in of the program by faculty and students, and to identify specific project components that need to be further pursued and improved. A total of 182 students from seven freshmen and senior-level undergraduate classes in three universities participated in the study. HydroViz was effective in facilitating students' learning and understanding of hydrologic concepts and increasing related skills. Students had positive perceptions of various features of HydroViz and they believe that HydroViz fits well in the curriculum. In general, HydroViz tend to be more effective with students in senior-level classes than students in freshmen classes. Lessons gained from this pilot study provide guidance for future adaptation and expansion studies to scale-up the application and utility of Hy-droViz and other similar systems into various hydrology and water-resource engineering curriculum settings. The paper presents a set of design principles that contribute to the development of other active hydrology educational systems.

Results of numerous evaluation studies indicated that satellite-rainfall products are contaminate... more Results of numerous evaluation studies indicated that satellite-rainfall products are contaminated with significant systematic and random errors. Therefore, such products may require refinement and correction before being used for hydrologic applications. In the present study, we explore a rainfall-runoff modeling application using the Climate Prediction Center-MORPHing (CMORPH) satellite rainfall product. The study area is the Gilgel Abbay catchment situated at the source basin of the Upper Blue Nile basin in Ethiopia, Eastern Africa. Rain gauge networks in such area are typically sparse. We examine different bias correction schemes applied locally to the CMORPH product. These schemes vary in the degree to which spatial and temporal variability in the CMORPH bias fields are accounted for. Three schemes are tested: space and time-invariant, time-variant and spatially invariant, and space and time variant. Bias-corrected CMORPH products were used to calibrate and drive the Hydrologiska Byråns Vattenbalansavdelning (HBV) rainfall-runoff model. Applying the space and time-fixed bias correction scheme resulted in slight improvement of the CMORPH-driven runoff simulations, but in some instances

2010 Annual Conference & Exposition Proceedings

His research is in the areas of hydrology and hydrometeorology with emphasis on in-situ and remot... more His research is in the areas of hydrology and hydrometeorology with emphasis on in-situ and remote sensing measurements of rainfall, hydrological applications of radar-rainfall information, hydrologic modeling, uncertainty assessment and validation of rainfall remotely-sensed products, and hydrological applications of statistical methods. He teaches undergraduate and advanced graduate courses in hydrology and probabilistic methods. He is the co-chair of the Uncertainty Assessment Task of the Coastal Louisiana Ecosystem Assessment and Restoration Model and a member on the American Society of Civil Engineers Environmental Water Resources Institute "Doppler Radar" Task Committee. He has several peer-reviewed publications and serves as a regular reviewer on journals such as Journal of Hydrologic Engineering,

Eos, 2017

Students use real data sets to explore how population changes, power generation, and water-saving... more Students use real data sets to explore how population changes, power generation, and water-saving strategies affect surface and groundwater use.

Radar-rainfall information presents a significant potential for improving our ability to provide ... more Radar-rainfall information presents a significant potential for improving our ability to provide accurate and timely flood predictions. Similar to other measuring devices, radar data also has many uncertainties. One of the main sources of uncertainties is due to natural and sampling variations in the estimation of rainfall rates from radar reflectivity factors. The National Weather Service (NWS) WSR-88D estimates rainfall rates by employing a relationship between Reflectivity factor Z (mm m) and rainfall rate R (mm h) of the form Z=AR (Ulbrich and Miller, 2001). Both Z and R are defined as different moments of the drop size distribution (DSD) in a sampled volume. Typical default values used by the NWS are A=300 and b=1.4 (for system with deep convection) and A=250 and b=1.2 (for tropical events). Earlier work by Atlas et al. (1999) showed that there can be dramatic changes in Z-R parameters between storms as well as within individual storms. The variability in Z-R relationship is at...

Remote Sensing, 2020

This article presents an online teaching tool that introduces students to basic concepts of remot... more This article presents an online teaching tool that introduces students to basic concepts of remote sensing and its applications in hydrology. The learning module is intended for junior/senior undergraduate students or junior graduate students with no (or little) prior experience in remote sensing, but with some basic background of environmental science, hydrology, statistics, and programming. This e-learning environment offers background content on the fundamentals of remote sensing, but also integrates a set of existing online tools for visualization and analysis of satellite observations. Specifically, students are introduced to a variety of satellite products and techniques that can be used to monitor and analyze changes in the hydrological cycle. At completion of the module, students are able to visualize remote sensing data (both in terms of time series and spatial maps), detect temporal trends, interpret satellite images, and assess errors and uncertainties in a remote sensing...

The era of ”big data” promises to provide new hydrologic insights, and open web-based platforms a... more The era of ”big data” promises to provide new hydrologic insights, and open web-based platforms are being developed and adopted by the hydrologic science community to harness these datasets and data services. This shift accompanies advances in hydrology education and the growth of web-based hydrology learning modules, but their capacity to utilize emerging open platforms and data services to enhance student learning through data-driven activities remains largely untapped. Given that generic equations may not easily translate into local or regional solutions, teaching students to explore how well models or equations work in particular settings or to answer specific problems using real data is essential. This paper introduces an open web-based learning module developed to advance data-driven hydrologic process learning, targeting upper level undergraduate and early graduate students in hydrology and engineering. The module was developed and deployed on the HydroLearn open educational ...

Remote Sensing, 2020

Radar-based Quantitative Precipitation Estimates (QPE) provide rainfall products with high tempor... more Radar-based Quantitative Precipitation Estimates (QPE) provide rainfall products with high temporal and spatial resolutions as opposed to sparse observations from rain gauges. Radar-based QPE’s have been widely used in many hydrological and meteorological applications; however, using these high-resolution products in the development of Precipitation Frequency Estimates (PFE) is impeded by their typically short-record availability. The current study evaluates the robustness of a spatial bootstrap regional approach, in comparison to a pixel-based (i.e., at site) approach, to derive PFEs using hourly radar-based multi-sensor precipitation estimation (MPE) product over the state of Louisiana in the US. The spatial bootstrap sampling technique augments the local pixel sample by incorporating rainfall data from surrounding pixels with decreasing importance when distance increases. We modeled extreme hourly rainfall data based on annual maximum series (AMS) using the generalized extreme va...

Remote Sensing, 2020

Radar-rainfall products provide valuable information for hydro-ecological modeling and ecosystem ... more Radar-rainfall products provide valuable information for hydro-ecological modeling and ecosystem applications, especially over coastal regions that lack adequate in-situ rainfall observations. This study evaluates two radar-based rainfall products, the Multi-Sensor Stage IV and the Multi-Radar Multi-Sensor (MRMS), over the Louisiana coastal region in the United States. Surface reference rainfall observations from two independent rain gage networks were used in the analysis. The evaluation included distribution-based comparisons between radar and gage observations at different time scales (hourly to monthly), bias decomposition to quantify the contribution of different error sources, and conditional evaluation of systematic and random components of the estimation errors. Both products report large levels of random errors at the hourly scale; however, the performance of the radar-rainfall products improves significantly with the increase in time scales. After decomposing the total bia...

Journal of Hydroinformatics, 2017

Two years of K-Band micro rain radar-2 (MRR) data are used to investigate the vertical variabilit... more Two years of K-Band micro rain radar-2 (MRR) data are used to investigate the vertical variability of rain in an atmospheric column and assess MRR rainfall estimates accuracy from both direct rainfall measurement using the Mie Theory (i.e., MRR RR) and a Z-R relationship (Z = 300 R1.4) (i.e., MRR Rz). Two different height resolutions (HR) settings are used. A nearby Doppler weather radar KEWX (S-band) using the same Z-R relationship is found to underestimate rainfall by up to 32.2%, while MRR estimates are much closer to collocated gauge measurements. For the first three gates, MRR RR underestimates rainfall by 5.7%–60.1% for the HR of 35 meters and by 31.2%–47.9% for the 100 meter resolution, while MRR RR overestimates rainfall for higher gates at the 100 m resolution, and MRR Rz underestimates rainfall at all gates due to errors of the Z-R relationship (Z = aRb). Gates higher than 2,000 m are affected by bright band and mixed phase rainfall. Examination of the rainfall statistics ...

Journal of Coastal Research, 2017

Recent decades have witnessed the development and implementation of several regional-scale, coast... more Recent decades have witnessed the development and implementation of several regional-scale, coastal-restoration planning projects that deal with human-natural coupled ecosystems. With their rich contexts, societal importance and preavailable data and modeling resources, these projects offer unique, multidisciplinary learning opportunities that are yet to be tapped into, especially at the undergraduate level. The current study presents an effort to capitalize on these regional-scale projects and use their resources in undergraduate educational settings. The study describes the development of a set of Web-based learning modules that are situated in the Chenier Plain coastal ecosystem in Louisiana. Going through a comprehensive. coast-wide restoration-planning effort, coastal Louisiana is a unique ecosystem that captures the interactions between inland hydrology and coastal and wetland processes. Centered on the current crisis of coastal land loss in the region, the modules immerse students in a suite of active-learning experiences in which they prepare and analyze data, reproduce model simulations, interpret results, and balance the beneficial and detrimental impacts of several real-world coastal-restoration projects. The modules cover a wide array of topics, including system-scale analysis of water and salt budgets, use of numerical models in coastal hydrologic settings, linkages between hydrologic variability and vegetation regimes, and assessments of different restoration strategies. The article presents lessons learned, challenges, and students' perspectives from pilot classroom implementations to guide similar future efforts on using large-scale, coastal-ecosystem projects to enrich current educational practices in the field of coastal hydrology and other related topics.

Environmental Research Letters, 2016

Groundwater is increasingly being overdrafted in the Southeastern U.S., despite abundant rainfall... more Groundwater is increasingly being overdrafted in the Southeastern U.S., despite abundant rainfall and the apparent availability of surface water. Using the state of Louisiana as an example, the current study quantifies the stresses on water resources and investigates the potential for opportunities to use surface water in lieu of groundwater pumping. The assessment is based on a fine watershed scale (12-digit Hydrological Unit Code [HUC] boundaries) water balance between the availability of surface and groundwater and surface water and groundwater demand. Water demand includes environmental flows, as well as public supply, rural domestic, industrial, power generation, agricultural, and aquaculture sectors. The seasonality of water stress is also addressed by incorporating monthly variations in surface water supply and irrigation demands. We develop several new weighting schemes to disaggregate the water withdrawals, provided by the U.S. Geological Survey on a county scale, to the HUC12 scale. The analysis on the smaller HUC12 scale is important for identifying areas with high water stress that would otherwise be masked at a larger scale (e.g. the county or HUC8 watershed scales). The results indicate that the annual water stress in Louisiana is below one (i.e. there is more water available than is used) for most watersheds; however, some watersheds (15 of the HUC12 units) show stresses greater than one, indicating an insufficient water supply to meet existing demands. The areas of the highest water stress are largely attributable to water consumption for power generating plants or irrigation. Moreover, estimating the stresses on surface water and groundwater sources separately confirms our speculation of abundant surface water and demonstrates a significant over-drafting/deficit of groundwater in many of the states aquifer systems. These results have implications for identifying new opportunities for reallocation of surface water use to reduce groundwater pumping and improve water sustainability in the region. Seasonal fluctuations in surface water supply and water withdrawals for irrigation highlight the fact that the water system is under more stress during the summer season. This observation underscores the need for infrastructure for shortterm surface water storage in agricultural regions. The water budget analysis presented here can be useful for stakeholders in developing water management plans and can also help to inform the development of a water code that will enable Louisiana to successfully manage and conserve its water resources for the future.

2016 ASEE Annual Conference & Exposition Proceedings

He received his Sc.D. and M.S. in Civil Engineering (Water Resources and Hydrology) from the Mass... more He received his Sc.D. and M.S. in Civil Engineering (Water Resources and Hydrology) from the Massachusetts Institute of Technology and his B.Sc Eng in Civil Engineering from the University of Natal in South Africa. His research and teaching are in the area of surface water hydrology. His research focuses on advancing the capability for hydrologic prediction by developing models that take advantage of new information and process understanding enabled by new technology. He has developed a number of models and software packages including the TauDEM hydrologic terrain analysis and channel network extraction package that has been implemented in parallel, and a snowmelt model. He is lead on the National Science Foundation HydroShare project to expand the data sharing capability of Hydrologic Information Systems to additional data types and models and to include social interaction and collaboration functionality. He teaches Hydrology and Geographic Information Systems in Water Resources.

Sensors, 2016

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining at... more With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9,. .. , 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

World Environmental and Water Resources Congress 2007, 2007

This study focuses on using NEXRAD radar-rainfall information to investigate the impact of rainfa... more This study focuses on using NEXRAD radar-rainfall information to investigate the impact of rainfall spatial variability and limited sampling on salinity prediction in an estuarine system. The site of this study is the Barataria basin, which is a wetland-dominated estuarine ecosystem in southwest Louisiana. Salinity prediction was found to rely heavily upon accurately estimating basin rainfall, due to rainfall being the largest source of freshwater and the most variable component in the net supply of fresh water to the basin. Rain gauge density scenarios of limited rainfall samplings were simulated from the fully-distributed radar data and corresponding salinity predictions were assessed. Results indicated that a high degree of uncertainty existed in salinity prediction associated with the typical average U.S. rain gauge density (1.3 gauges/1000 km 2 ). By slightly increasing rain gauge density beyond the typical density, a significant amount of salinity prediction uncertainty could be reduced.

Journal of Sea Research, 2010

... There, the dissolved nitrogen load exported from the Louisiana coastal region fuels a growing... more ... There, the dissolved nitrogen load exported from the Louisiana coastal region fuels a growing hypoxia zone ( 21,000 km 2 ; [Rabalais et al., 2002a], [Rabalais et al., 2002b], [Scavia et al., 2004], [Hyfield et al., 2008] and [Turner et al., 2008]). ...

Journal of Hydrometeorology, 2012

The rain gauge network associated with the Walnut Gulch Experimental Watershed (WGEW) in southeas... more The rain gauge network associated with the Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona provides a unique opportunity for direct comparisons of in situ measurements and satellite-based instantaneous rain rate estimates like those from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR). The WGEW network is the densest rain gauge network in the PR coverage area for watersheds greater than 10 km2. It consists of 88 weighing rain gauges within a 149-km2 area. On average, approximately 10 gauges can be found in each PR field of view (~5-km diameter). All gauges are very well synchronized with 1-min reporting intervals. This allows generating very-high-temporal-resolution rain rate fields and obtaining accurate estimates of the area-average rain rate for the entire watershed and for a single PR field of view. In this study, instantaneous rain rate fields from the PR and the spatially interpolated gauge measurements (on a 100 m × 100 m grid, updat...

Journal of Hydrology, 2008

This article was published in an Elsevier journal. The attached copy is furnished to the author f... more This article was published in an Elsevier journal. The attached copy is furnished to the author for non-commercial research and education use, including for instruction at the author's institution, sharing with colleagues and providing to institution administration. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: http://www.elsevier.com/copyright

Journal of Coastal Research, 2007

Reliable forecasts of salinity changes are essential for restoring and sustaining natural resourc... more Reliable forecasts of salinity changes are essential for restoring and sustaining natural resources of estuaries and coastal ecosystems. Because of the physical complexity of such ecosystems, information on uncertainty associated with salinity forecasts should be assessed and incorporated into management and restoration decisions. The objective of this study was to investigate uncertainty in salinity forecasts imposed by limitations on data available to calibrate and apply a mass balance salinity model in the Barataria basin, Louisiana. The basin is an estuarine wetlanddominated ecosystem located directly west of the Mississippi Delta complex. The basin has been experiencing significant losses of wetland at a rate of nearly 23 km 2 /y. A Bayesian-based methodology was applied to study the effect of data-related uncertainty on both the retrieval of model parameters and the subsequent model predictions. We focused on uncertainty caused by limited sampling and coverage of salinity calibration data and by sparse rain gauge data within the basin. The results indicated that data limitations lead to significant uncertainty in the identification of model parameters, causing moderate to large systematic and random errors in model results. The most significant effect was related to lack of accurate information on rainfall, a major source of fresh water in the basin. The approach and results of this study can be used to identify necessary improvements in monitoring of complex estuarine systems that can decrease forecast uncertainty and allow managers greater accuracy in planning restoration of coastal resources.

Computers & Geosciences, 2003

To aid in modeling studies over the Mississippi River Basin, we have developed an archival precip... more To aid in modeling studies over the Mississippi River Basin, we have developed an archival precipitation data set for the GEWEX Continental-Scale International Project. The data set spans from 1996–2000, a 5-year continuous period of record. Inputs for the data set are the National Reflectivity Composite that we obtained in Hierarchical Data Format. The size of the input data is

Hydrology and Earth System Sciences, 2012

HydroViz is a Web-based, student-centered, educational tool designed to support active learning i... more HydroViz is a Web-based, student-centered, educational tool designed to support active learning in the field of Engineering Hydrology. The design of HydroViz is guided by a learning model that is based on learning with data and simulations, using real-world natural hydrologic systems to convey theoretical concepts, and using Web-based technologies for dissemination of the hydrologic education developments. This model, while being used in a hydrologic education context, can be adapted in other engineering educational settings. HydroViz leverages the free Google Earth resources to enable presentation of geospatial data layers and embed them in web pages that have the same look and feel of Google Earth. These design features significantly facilitate the dissemination and adoption of HydroViz by any interested educational institutions regardless of their access to data or computer models. To facilitate classroom usage, Hy-droViz is populated with a set of course modules that can be used incrementally within different stages of an engineering hydrology curriculum. A pilot evaluation study was conducted to determine the effectiveness of the HydroViz tool in delivering its educational content, to examine the buy-in of the program by faculty and students, and to identify specific project components that need to be further pursued and improved. A total of 182 students from seven freshmen and senior-level undergraduate classes in three universities participated in the study. HydroViz was effective in facilitating students' learning and understanding of hydrologic concepts and increasing related skills. Students had positive perceptions of various features of HydroViz and they believe that HydroViz fits well in the curriculum. In general, HydroViz tend to be more effective with students in senior-level classes than students in freshmen classes. Lessons gained from this pilot study provide guidance for future adaptation and expansion studies to scale-up the application and utility of Hy-droViz and other similar systems into various hydrology and water-resource engineering curriculum settings. The paper presents a set of design principles that contribute to the development of other active hydrology educational systems.