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...
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 ...
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...
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...
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 ...
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.
... 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]). ...
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...
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
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...
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 ...
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...
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...
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 ...
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.
... 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]). ...
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...
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
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Papers by Emad Habib