Wendy Graham - Academia.edu (original) (raw)
Papers by Wendy Graham
Transactions of the ASABE
HighlightsDSSAT simulations of final N uptake, biomass, and yield for a maize-peanut rotational f... more HighlightsDSSAT simulations of final N uptake, biomass, and yield for a maize-peanut rotational field experiment with three irrigation treatments and three N fertilizer rates had good performance for the irrigated treatments (average nRMSE of 9%) but greater error for the rainfed treatments (average nRMSE of 15%).Experiments and DSSAT simulations demonstrated that N fertilizer and irrigation applications were reduced by 26% and 60%, respectively, when using a 247 kg N ha-1 fertilizer rate and a sensor-based irrigation schedule rather than conventional practices of 336 kg N ha-1 and a calendar-based irrigation method, with no impact on yield.Simulations demonstrated that N leaching during the crop rotation was reduced by 37% when an N fertilizer rate of 247 kg N ha-1 and sensor-based irrigation scheduling were used versus conventional practices.Soil N increased (=15 mg kg-1) when maize and peanut residues decayed and then leached during the fallow season. Cover or cash crops planted ...
Agu Spring Meeting Abstracts, May 1, 2008
Agu Fall Meeting Abstracts, Dec 1, 2008
ABSTRACT Regional modeling experiments were carried out to analyze the sensitivity of near surfac... more ABSTRACT Regional modeling experiments were carried out to analyze the sensitivity of near surface climate parameters to changes in land use characteristics during a decadal study period, 1993-2003 in Central Florida. Model domains are set at 3Km and 1Km resolutions under different physical configurations with a fine lower atmospheric description. We inspect changes in the patterns of atmospheric circulation close to the land surface and the energy budget at a daily scale. Model validation is carried out using hourly meteorological data. Particular attention is given to stations surrounded by urban areas exhibiting major land management changes during the decadal period, like those on the Gulf of Mexico coastal side, as well as stations on the Atlantic coast. Temperature, precipitation and wind are studied for all stations. In coastal areas, land-sea breeze processes and urban effects are surveyed. Observations reveal more frequent precipitation in Tampa Bay than other areas while the model tends to follow the observed spatial pattern. Decadal land surface change effects are difficult to determine. Under the coastal urban areas included in this study, the atmospheric vertical structure is more complex than in inland counterparts and land-sea breeze processes in general dominates their climate variability.
ABSTRACT Accurate knowledge of root zone soil moisture (RZSM) is crucial in hydrology, micrometeo... more ABSTRACT Accurate knowledge of root zone soil moisture (RZSM) is crucial in hydrology, micrometeorology, and agriculture for estimating energy and moisture fluxes at the land surface. Soil Vegetation Atmosphere Transfer (SVAT) models are typically used to simulate energy and moisture transport in soil and vegetation. Coupled SVAT and vegetation models allow inclusion of canopy effects on the fluxes. Even though these coupled models capture the biophysics fairly well, RZSM estimates diverge from reality due to errors in model conceptualization, computation, and due to uncertainty in model parameters, forcings, and initial conditions. The model estimates of RZSM can be significantly improved by assimilating remotely sensed observations that are sensitive to soil moisture changes, such as microwave brightness at frequencies < 10 GHz. The near-future NASA Soil Moisture Active/Passive (SMAP) mission will include active and passive microwave sensors at L-band (1.2 - 1.4 GHz) to provide global observations, with a repeat coverage of every 2-3 days. In this study, we use a coupled SVAT-vegetation model to estimate RZSM during a growing season of corn in North Florida. An Ensemble Kalman Filter-based assimilation algorithm was implemented to simultaneously update states and parameters every 3 days by assimilating soil moisture and L-band microwave brightness into the SVAT-vegetation model linked with a forward microwave model. Comparisons of RZSM estimates using both synthetic and field observations during the MicroWEX-5 experiment were conducted to understand the improvement in RZSM estimation using both in situ and remotely sensed measurements.
Agu Spring Meeting Abstracts, May 1, 2002
Agu Spring Meeting Abstracts, May 1, 2001
The primary objectives of an ongoing investigation at Fort Benning, GA are to identify physical, ... more The primary objectives of an ongoing investigation at Fort Benning, GA are to identify physical, chemical and biological variables associated with soil, surface/subsurface hydrology and vegetation that may be used as indicators of ecological change and to determine the likely range of natural variation for the indicator variables and compare with the range of values under anthropogenic, especially mission-related influences.
This report summarizes the activities and experiences of a UF team that visited the International... more This report summarizes the activities and experiences of a UF team that visited the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) in Hyderabad, India from July 29 to Aug. 11, 2006. The UF delegation included K. Ramesh Reddy, Chair of the Soil and Water Science (SWS) Department; Sabine Grunwald, Associate Professor and Distance Education Coordinator (SWS Department). They were joined by Wendy Graham, Director of the UF Water Institute on Aug. 5, 2006.
Journal of Hydrology, 2014
This study demonstrated the first application of a GSA technique to a transient ISSHM-LSM applica... more This study demonstrated the first application of a GSA technique to a transient ISSHM-LSM application developed for a large-scale river basin. The Morris method was used to identify the spatially and temporally variable sensitivity amongst a large number of model parameters to provide insights on hydrologic processes dominating behavior in the basin and to identify a small subset of parameters that should be evaluated in subsequent, more computationally intensive quantitative GSA and parameter estimation techniques. Results showed that in the upper region of the basin, evapotranspiration (ET), total streamflow and peak streamflow were less sensitive to surficial aquifer system characteristics, but highly sensitive to the hydraulic conductivity of the confining unit separating the surficial aquifer and the regional aquifer system and leaf area index of near stream vegetation. In the lower region of the basin, hydraulic conductivity of the regional aquifer system was found to have a significant effect on ET, total stream flow, and groundwater contributions to streamflow while surface-groundwater dynamics during storm events was most sensitive to storage properties of the regional aquifer system. Peak streamflow in the lower basin was most sensitive to the hydraulic conductivity of the confining unit in the upper basin, and the Manning's coefficient of upper basin streams, indicating that all peak storm flows originate in the upper basin. Throughout the basin ET was sensitive to soil/geologic properties and vegetation properties, with unsaturated zone processes and relevant parameters gaining importance in moisture limited conditions existing in the lower regions of the basin.
2003, Las Vegas, NV July 27-30, 2003, 2003
ABSTRACT
Water Resources Research, 1991
Knowledge of stream flow rates is critical for management of in-stream flows and mitigation of fl... more Knowledge of stream flow rates is critical for management of in-stream flows and mitigation of flooding and drought events. Unfortunately, spatially dense networks of in situ stream flow measurements are not generally available and would be prohibitively expensive to deploy and maintain. Since measurements are only available at relatively sparse spatial frequencies, a data assimilation technique that best utilizes available
ABSTRACT Accurately representing the spatial variability of precipitation is an important factor ... more ABSTRACT Accurately representing the spatial variability of precipitation is an important factor for predicting watershed response to climatic forcing, particularly in small, low-relief watersheds affected by convective storm systems. Although Global Circulation Models (GCMs) generally preserve spatial relationships between large-scale and local-scale mean precipitation trends, most GCM downscaling techniques focus on preserving only observed temporal variability on point by point basis, not spatial patterns of events. Downscaled GCM results (e.g., CMIP3 ensembles) have been widely used to predict hydrologic implications of climate variability and climate change in large snow-dominated river basins in the western United States (Diffenbaugh et al., 2008; Adam et al., 2009). However fewer applications to smaller rain-driven river basins in the southeastern US (where preserving spatial variability of rainfall patterns may be more important) have been reported. In this study a new method was developed to bias-correct GCMs to preserve both the long term temporal mean and variance of the precipitation data, and the spatial structure of daily precipitation fields. Forty-year retrospective simulations (1960-1999) from 16 GCMs were collected (IPCC, 2007; WCRP CMIP3 multi-model database: https://esg.llnl.gov:8443/), and the daily precipitation data at coarse resolution (i.e., 280km) were interpolated to 12km spatial resolution and bias corrected using gridded observations over the state of Florida (Maurer et al., 2002; Wood et al, 2002; Wood et al, 2004). In this method spatial random fields which preserved the observed spatial correlation structure of the historic gridded observations and the spatial mean corresponding to the coarse scale GCM daily rainfall were generated. The spatiotemporal variability of the spatio-temporally bias-corrected GCMs were evaluated against gridded observations, and compared to the original temporally bias-corrected and downscaled CMIP3 data for the central Florida. The hydrologic response of two southwest Florida watersheds to the gridded observation data, the original bias corrected CMIP3 data, and the new spatiotemporally corrected CMIP3 predictions was compared using an integrated surface-subsurface hydrologic model developed by Tampa Bay Water.
Water Resources Research, 2000
ABSTRACT
Journal of Climate, 2014
This study compared two types of approaches to downscale seasonal precipitation (P) and 2-m air t... more This study compared two types of approaches to downscale seasonal precipitation (P) and 2-m air temperature (T2M) forecasts from the North American Multimodel Ensemble (NMME) over the states of Alabama, Georgia, and Florida in the southeastern United States (SEUS). Each NMME model forecast was evaluated. Two multimodel ensemble (MME) schemes were tested by assigning equal weight to all forecast members (SuperEns) or by assigning equal weights to each model’s ensemble mean (MeanEns). One type of downscaling approach used was a model output statistics (MOS) method, which was based on direct spatial disaggregation and bias correction of the NMME P and T2M forecasts using the quantile mapping technique [spatial disaggregation with bias correction (SDBC)]. The other type of approach used was a perfect prognosis (PP) approach using nonparametric locally weighted polynomial regression (LWPR) models, which used the NMME forecasts of Niño-3.4 sea surface temperatures (SSTs) to predict local-...
Water Resources Research, 1993
filtering algorithm is developed to forecast groundwater levels in the Upper Floridan aquifer thr... more filtering algorithm is developed to forecast groundwater levels in the Upper Floridan aquifer throughout the St. Johns River Water Management District (SJRWMD) in Florida. The algorithm processes historic and currently available head measurements to make optimal predictions of future head levels over a grid of 554 wells spanning the SJRWMD. Measurements are obtained monthly from a subset of 20 wells and semiannually from the remaining wells. The Kalman filter incorporates an empirical spatiotemporal model of regional groundwater fluctuations derived from long-term historical data records at the 20 monthly measured wells. The algorithm (1) extrapolates the measurements provided by the 20 monthly measured wells to estimate monthly head levels at all 554 wells in the grid and (2) predicts future head levels at each well in the absence of measurements. The performance of the Kalman filtering algorithm is assessed by examining its ability to forecast piezometric head behavior at the 534 well locations where historic data were not used to estimate either the system model or the spatiotemporal correlation structure of the model residuals. structures were identified at the different time scales; however, no application of these space-time correlations to spatial estimation or temporal forecasting was made. Rouhani and Hall [1989] and Rouhani and Wackernagel [1990] expanded the kriging technique into the space-time domain by using time as the third dimension in a traditional empirical geostatistical analysis of a two-dimensional spatial sampling regime for piezometric head. Similar to multivariate time series models [Stedinger et al., 1985], their apprn•ch •11nwed forecasting and hindcasting of piezometric Copyright 1993 by the American Geophysical Union. Paper number 93WR01813. 0043-1397/93/93 WR-01813505.00 fluctuations at modeled wells, but did not allow distributed spatial estimations at unmeasured/unmodeled locations. Kalman filtering has been applied to spatiotemporal estimation problems in subsurface hydrology by Wilson et al.
![Research paper thumbnail of Reply [to “Comment on ‘Stochastic analysis of nonstationary subsurface solute transport: 1. Unconditional moments’ by W. Graham and D. McLaughlin”]](https://attachments.academia-assets.com/82702646/thumbnails/1.jpg)
](Water Resources Research, 1990
We appreciate Gedeon Dagan's constructive comments [Dagan, this issue] on our recent paper [Graha... more We appreciate Gedeon Dagan's constructive comments [Dagan, this issue] on our recent paper [Graham and McLaughlin, 1989a] (hereinafter referred to as GML). This reply addresses both of the major points he raises. It also describes in more detail the method we used to compute ensemble and single-replicate macrodispersivities.
Transactions of the ASABE
HighlightsDSSAT simulations of final N uptake, biomass, and yield for a maize-peanut rotational f... more HighlightsDSSAT simulations of final N uptake, biomass, and yield for a maize-peanut rotational field experiment with three irrigation treatments and three N fertilizer rates had good performance for the irrigated treatments (average nRMSE of 9%) but greater error for the rainfed treatments (average nRMSE of 15%).Experiments and DSSAT simulations demonstrated that N fertilizer and irrigation applications were reduced by 26% and 60%, respectively, when using a 247 kg N ha-1 fertilizer rate and a sensor-based irrigation schedule rather than conventional practices of 336 kg N ha-1 and a calendar-based irrigation method, with no impact on yield.Simulations demonstrated that N leaching during the crop rotation was reduced by 37% when an N fertilizer rate of 247 kg N ha-1 and sensor-based irrigation scheduling were used versus conventional practices.Soil N increased (=15 mg kg-1) when maize and peanut residues decayed and then leached during the fallow season. Cover or cash crops planted ...
Agu Spring Meeting Abstracts, May 1, 2008
Agu Fall Meeting Abstracts, Dec 1, 2008
ABSTRACT Regional modeling experiments were carried out to analyze the sensitivity of near surfac... more ABSTRACT Regional modeling experiments were carried out to analyze the sensitivity of near surface climate parameters to changes in land use characteristics during a decadal study period, 1993-2003 in Central Florida. Model domains are set at 3Km and 1Km resolutions under different physical configurations with a fine lower atmospheric description. We inspect changes in the patterns of atmospheric circulation close to the land surface and the energy budget at a daily scale. Model validation is carried out using hourly meteorological data. Particular attention is given to stations surrounded by urban areas exhibiting major land management changes during the decadal period, like those on the Gulf of Mexico coastal side, as well as stations on the Atlantic coast. Temperature, precipitation and wind are studied for all stations. In coastal areas, land-sea breeze processes and urban effects are surveyed. Observations reveal more frequent precipitation in Tampa Bay than other areas while the model tends to follow the observed spatial pattern. Decadal land surface change effects are difficult to determine. Under the coastal urban areas included in this study, the atmospheric vertical structure is more complex than in inland counterparts and land-sea breeze processes in general dominates their climate variability.
ABSTRACT Accurate knowledge of root zone soil moisture (RZSM) is crucial in hydrology, micrometeo... more ABSTRACT Accurate knowledge of root zone soil moisture (RZSM) is crucial in hydrology, micrometeorology, and agriculture for estimating energy and moisture fluxes at the land surface. Soil Vegetation Atmosphere Transfer (SVAT) models are typically used to simulate energy and moisture transport in soil and vegetation. Coupled SVAT and vegetation models allow inclusion of canopy effects on the fluxes. Even though these coupled models capture the biophysics fairly well, RZSM estimates diverge from reality due to errors in model conceptualization, computation, and due to uncertainty in model parameters, forcings, and initial conditions. The model estimates of RZSM can be significantly improved by assimilating remotely sensed observations that are sensitive to soil moisture changes, such as microwave brightness at frequencies < 10 GHz. The near-future NASA Soil Moisture Active/Passive (SMAP) mission will include active and passive microwave sensors at L-band (1.2 - 1.4 GHz) to provide global observations, with a repeat coverage of every 2-3 days. In this study, we use a coupled SVAT-vegetation model to estimate RZSM during a growing season of corn in North Florida. An Ensemble Kalman Filter-based assimilation algorithm was implemented to simultaneously update states and parameters every 3 days by assimilating soil moisture and L-band microwave brightness into the SVAT-vegetation model linked with a forward microwave model. Comparisons of RZSM estimates using both synthetic and field observations during the MicroWEX-5 experiment were conducted to understand the improvement in RZSM estimation using both in situ and remotely sensed measurements.
Agu Spring Meeting Abstracts, May 1, 2002
Agu Spring Meeting Abstracts, May 1, 2001
The primary objectives of an ongoing investigation at Fort Benning, GA are to identify physical, ... more The primary objectives of an ongoing investigation at Fort Benning, GA are to identify physical, chemical and biological variables associated with soil, surface/subsurface hydrology and vegetation that may be used as indicators of ecological change and to determine the likely range of natural variation for the indicator variables and compare with the range of values under anthropogenic, especially mission-related influences.
This report summarizes the activities and experiences of a UF team that visited the International... more This report summarizes the activities and experiences of a UF team that visited the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) in Hyderabad, India from July 29 to Aug. 11, 2006. The UF delegation included K. Ramesh Reddy, Chair of the Soil and Water Science (SWS) Department; Sabine Grunwald, Associate Professor and Distance Education Coordinator (SWS Department). They were joined by Wendy Graham, Director of the UF Water Institute on Aug. 5, 2006.
Journal of Hydrology, 2014
This study demonstrated the first application of a GSA technique to a transient ISSHM-LSM applica... more This study demonstrated the first application of a GSA technique to a transient ISSHM-LSM application developed for a large-scale river basin. The Morris method was used to identify the spatially and temporally variable sensitivity amongst a large number of model parameters to provide insights on hydrologic processes dominating behavior in the basin and to identify a small subset of parameters that should be evaluated in subsequent, more computationally intensive quantitative GSA and parameter estimation techniques. Results showed that in the upper region of the basin, evapotranspiration (ET), total streamflow and peak streamflow were less sensitive to surficial aquifer system characteristics, but highly sensitive to the hydraulic conductivity of the confining unit separating the surficial aquifer and the regional aquifer system and leaf area index of near stream vegetation. In the lower region of the basin, hydraulic conductivity of the regional aquifer system was found to have a significant effect on ET, total stream flow, and groundwater contributions to streamflow while surface-groundwater dynamics during storm events was most sensitive to storage properties of the regional aquifer system. Peak streamflow in the lower basin was most sensitive to the hydraulic conductivity of the confining unit in the upper basin, and the Manning's coefficient of upper basin streams, indicating that all peak storm flows originate in the upper basin. Throughout the basin ET was sensitive to soil/geologic properties and vegetation properties, with unsaturated zone processes and relevant parameters gaining importance in moisture limited conditions existing in the lower regions of the basin.
2003, Las Vegas, NV July 27-30, 2003, 2003
ABSTRACT
Water Resources Research, 1991
Knowledge of stream flow rates is critical for management of in-stream flows and mitigation of fl... more Knowledge of stream flow rates is critical for management of in-stream flows and mitigation of flooding and drought events. Unfortunately, spatially dense networks of in situ stream flow measurements are not generally available and would be prohibitively expensive to deploy and maintain. Since measurements are only available at relatively sparse spatial frequencies, a data assimilation technique that best utilizes available
ABSTRACT Accurately representing the spatial variability of precipitation is an important factor ... more ABSTRACT Accurately representing the spatial variability of precipitation is an important factor for predicting watershed response to climatic forcing, particularly in small, low-relief watersheds affected by convective storm systems. Although Global Circulation Models (GCMs) generally preserve spatial relationships between large-scale and local-scale mean precipitation trends, most GCM downscaling techniques focus on preserving only observed temporal variability on point by point basis, not spatial patterns of events. Downscaled GCM results (e.g., CMIP3 ensembles) have been widely used to predict hydrologic implications of climate variability and climate change in large snow-dominated river basins in the western United States (Diffenbaugh et al., 2008; Adam et al., 2009). However fewer applications to smaller rain-driven river basins in the southeastern US (where preserving spatial variability of rainfall patterns may be more important) have been reported. In this study a new method was developed to bias-correct GCMs to preserve both the long term temporal mean and variance of the precipitation data, and the spatial structure of daily precipitation fields. Forty-year retrospective simulations (1960-1999) from 16 GCMs were collected (IPCC, 2007; WCRP CMIP3 multi-model database: https://esg.llnl.gov:8443/), and the daily precipitation data at coarse resolution (i.e., 280km) were interpolated to 12km spatial resolution and bias corrected using gridded observations over the state of Florida (Maurer et al., 2002; Wood et al, 2002; Wood et al, 2004). In this method spatial random fields which preserved the observed spatial correlation structure of the historic gridded observations and the spatial mean corresponding to the coarse scale GCM daily rainfall were generated. The spatiotemporal variability of the spatio-temporally bias-corrected GCMs were evaluated against gridded observations, and compared to the original temporally bias-corrected and downscaled CMIP3 data for the central Florida. The hydrologic response of two southwest Florida watersheds to the gridded observation data, the original bias corrected CMIP3 data, and the new spatiotemporally corrected CMIP3 predictions was compared using an integrated surface-subsurface hydrologic model developed by Tampa Bay Water.
Water Resources Research, 2000
ABSTRACT
Journal of Climate, 2014
This study compared two types of approaches to downscale seasonal precipitation (P) and 2-m air t... more This study compared two types of approaches to downscale seasonal precipitation (P) and 2-m air temperature (T2M) forecasts from the North American Multimodel Ensemble (NMME) over the states of Alabama, Georgia, and Florida in the southeastern United States (SEUS). Each NMME model forecast was evaluated. Two multimodel ensemble (MME) schemes were tested by assigning equal weight to all forecast members (SuperEns) or by assigning equal weights to each model’s ensemble mean (MeanEns). One type of downscaling approach used was a model output statistics (MOS) method, which was based on direct spatial disaggregation and bias correction of the NMME P and T2M forecasts using the quantile mapping technique [spatial disaggregation with bias correction (SDBC)]. The other type of approach used was a perfect prognosis (PP) approach using nonparametric locally weighted polynomial regression (LWPR) models, which used the NMME forecasts of Niño-3.4 sea surface temperatures (SSTs) to predict local-...
Water Resources Research, 1993
filtering algorithm is developed to forecast groundwater levels in the Upper Floridan aquifer thr... more filtering algorithm is developed to forecast groundwater levels in the Upper Floridan aquifer throughout the St. Johns River Water Management District (SJRWMD) in Florida. The algorithm processes historic and currently available head measurements to make optimal predictions of future head levels over a grid of 554 wells spanning the SJRWMD. Measurements are obtained monthly from a subset of 20 wells and semiannually from the remaining wells. The Kalman filter incorporates an empirical spatiotemporal model of regional groundwater fluctuations derived from long-term historical data records at the 20 monthly measured wells. The algorithm (1) extrapolates the measurements provided by the 20 monthly measured wells to estimate monthly head levels at all 554 wells in the grid and (2) predicts future head levels at each well in the absence of measurements. The performance of the Kalman filtering algorithm is assessed by examining its ability to forecast piezometric head behavior at the 534 well locations where historic data were not used to estimate either the system model or the spatiotemporal correlation structure of the model residuals. structures were identified at the different time scales; however, no application of these space-time correlations to spatial estimation or temporal forecasting was made. Rouhani and Hall [1989] and Rouhani and Wackernagel [1990] expanded the kriging technique into the space-time domain by using time as the third dimension in a traditional empirical geostatistical analysis of a two-dimensional spatial sampling regime for piezometric head. Similar to multivariate time series models [Stedinger et al., 1985], their apprn•ch •11nwed forecasting and hindcasting of piezometric Copyright 1993 by the American Geophysical Union. Paper number 93WR01813. 0043-1397/93/93 WR-01813505.00 fluctuations at modeled wells, but did not allow distributed spatial estimations at unmeasured/unmodeled locations. Kalman filtering has been applied to spatiotemporal estimation problems in subsurface hydrology by Wilson et al.
Water Resources Research, 1990
We appreciate Gedeon Dagan's constructive comments [Dagan, this issue] on our recent paper [Graha... more We appreciate Gedeon Dagan's constructive comments [Dagan, this issue] on our recent paper [Graham and McLaughlin, 1989a] (hereinafter referred to as GML). This reply addresses both of the major points he raises. It also describes in more detail the method we used to compute ensemble and single-replicate macrodispersivities.