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Research Interests: Geography, Environmental Science, Remote Sensing, Climate Change, Microwave, and 15 moreSea Ice, Water Supply, Statistical Significance, SNOW, Trend Analysis, El Nino-Southern Oscillation, Air Temperature, North American Regional Reanalysis, North American, Indexation, Pacific Decadal Oscillation, Snow Depth, Snow water equivalent, surface temperature, and snowpack
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Extreme precipitation events in central Alberta have overwhelmed hydraulic structures several times in recent years, and it is expected that rainfall intensity in this region will continue to increase over the next several decades.... more
Extreme precipitation events in central Alberta have overwhelmed hydraulic structures several times in recent years, and it is expected that rainfall intensity in this region will continue to increase over the next several decades. Accurate rainfall projections, which are communicated in the form of Intensity-Duration-Frequency (IDF) curves, are thus needed to design sufficient municipal structures. Such data may be obtained through the use of Regional Climate Models (RCMs), and one in particular, the fifth-generation NCAR/Penn State mesoscale atmospheric model (MM5), is investigated here. MM5 is used to dynamically downscale ECMWF ERA-Interim reanalysis data, to evaluate its ability to accurately simulate rainfall characteristics in central Alberta, over two consecutive summers representing contrasting precipitation regimes. Precipitation simulated at the local scale is verified with Edmonton’s local rain gauge network, while larger-scale precipitation is compared with the High Res...
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Ethiopian economy and Nile River flow are mainly based on the seasonal rainfall over the Ethiopian Highlands (EH) in the form of rain-fed agriculture and 60% streamflow contribution, respectively. Using the wavelet Principal Component... more
Ethiopian economy and Nile River flow are mainly based on the seasonal rainfall over the Ethiopian Highlands (EH) in the form of rain-fed agriculture and 60% streamflow contribution, respectively. Using the wavelet Principal Component Analysis (WPCA), the non-stationary technique, to individual wavelet scale power and scale-averaged wavelet power of the gridded rainfall data, this paper examined the spatial, and temporal patterns of EH’s rainfall. Teleconnections between the UBNB seasonal rainfalls (June-September) and the El Niño- Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) were also established for the period 1900-1998. The study found that the non-stationary variations of both February-May (FMAM) and June- September (JJAS) Ethiopian rainfall can delineate EH into four major regions which geographically represent savanna, deciduous woodland, upland grassland, and tropical highland forest. Temporal characteristics of the leading wavelet principal component (WPC) s...
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WATER RESOURCES RESEARCH, VOL. 26, NO. 1, PAGES 69-86, JANUARY 1990 Hydrologie Sensitivities of the Sacramento-San Joaquin River Basin, California, to Global Warming Dennis P. Lettenmaier Department of Civil Engineering, University of... more
WATER RESOURCES RESEARCH, VOL. 26, NO. 1, PAGES 69-86, JANUARY 1990 Hydrologie Sensitivities of the Sacramento-San Joaquin River Basin, California, to Global Warming Dennis P. Lettenmaier Department of Civil Engineering, University of Washington, Seattle Thian ...
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Rainfall is the primary driver of basin hydrologic processes. This article examines a recently developed rainfall predictive tool that combines wavelet principal component analysis (WPCA), an artificial neural networks-genetic algorithm... more
Rainfall is the primary driver of basin hydrologic processes. This article examines a recently developed rainfall predictive tool that combines wavelet principal component analysis (WPCA), an artificial neural networks-genetic algorithm (ANN-GA), and statistical disaggregation into an integrated framework useful for the management of water resources around the upper Blue Nile River basin (UBNB) in Ethiopia. From the correlation field between scale-average wavelet powers (SAWPs) of the February–May (FMAM) global sea surface temperature (SST) and the first wavelet principal component (WPC1) of June–September (JJAS) seasonal rainfall over the UBNB, sectors of the Indian, Atlantic, and Pacific Oceans where SSTs show a strong teleconnection with JJAS rainfall in the UBNB (r ≥ 0.4) were identified. An ANN-GA model was developed to forecast the UBNB seasonal rainfall using the selected SST sectors. Results show that ANN-GA forecasted seasonal rainfall amounts that agree well with the obser...
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ABSTRACT Statistical methods of wavelet, independent component analysis (ICA), and empirical orthogonal function (EOF) analysis were used together with geographical information systems (GIS) to regionalize runoff variability, establish... more
ABSTRACT Statistical methods of wavelet, independent component analysis (ICA), and empirical orthogonal function (EOF) analysis were used together with geographical information systems (GIS) to regionalize runoff variability, establish baseline predisturbance hydrologic regimes, and account for runoff heterogeneity across Alberta, Canada as part of an effort to develop future adaptive forest management practices for Alberta. Both ICA and EOF identified three hydrologic clusters from 59 stations of catchment runoff data. However, ICA identified hydrologic clusters that agree better with the five ecoregions of Alberta than that of EOF. These are the Rocky Mountains and foothills, where runoff was characterized by a fairly consistent temporal variability and dominated by a strong annual cycle, southern Alberta/central Alberta, where temporal heterogeneity and a weak annual cycle dominated the runoff variability, and in southwestern Alberta, where the runoff variability was characterized by annual, 4-7, and 11-year cycles. Apparently stagnation moraine dominate hydrologic responses of most catchments in the grasslands and part of the boreal forests of western, central, and eastern Alberta. Empirical equations developed showed that stagnation moraine explained 64% of the runoff variability of selected catchments and that runoff was significantly diminished when stagnation moraines covered at least 74% of the catchment area. The identification of three spatially heterogeneous hydrologic clusters in Alberta, a province that is defined by four spatially homogeneous precipitation regimes indicates the necessity to develop forest management practices that will be suitable to manage Alberta's forests.
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We present a framework for defining effective hydrologic response area (HRA's) in landscapes at both local and regional scales. This framework summarizes research conducted at the Utikuma Research... more
We present a framework for defining effective hydrologic response area (HRA's) in landscapes at both local and regional scales. This framework summarizes research conducted at the Utikuma Research Study Area (URSA), Alberta, Canada, where sub-humid climate (P = PET), low relief and deep glaciated substrates result in the dominance of vadose zone storage, evapotranspiration and vertical, rather than lateral water
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There has been a growing concern regarding impacts of global warming on droughts, which can have devastating effects on the environment, society, and economy of nations worldwide. Drought characteristics in terms of duration, frequency,... more
There has been a growing concern regarding impacts of global warming on droughts, which can have devastating effects on the environment, society, and economy of nations worldwide. Drought characteristics in terms of duration, frequency, area, and severity are investigated using the Standardized Precipitation Evapotranspiration Index (SPEI) at seasonal (3-month) and annual (12-month) time scales for Canada over 1950–2016 derived from the Climatic Research Unit (CRU) TS4.03 gridded data. Using k-means clustering, Canada is divided into four sub-regions, each with distinct drought characteristics. Next, the influence of climate drivers such as the El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) on regional drought variability were examined using a Bayesian Dynamic Linear (BDL) model. The results show that between 1950 and 2016 (1) there has been a prevalent drying trend in southwestern Canada during winter; (2) changes in maximum drought durations have occurred with dipolar patterns, i.e., northern Canada has experienced a longer drought duration than southern Canada; (3) drought frequency, area, and severity have predominantly shown statistically significant decreasing trends, indicating that droughts in Canada have generally become less severe; and (4) the relationships between climate anomalies and drought variability have changed over time. Droughts are generally more negatively correlated to ENSO and PDO after 1970s, but more positively correlated to the Atlantic Multi-decadal Oscillation (AMO) and Arctic Oscillation (AO) after the 1980s. The results provide a better understanding of the characteristics of meteorological droughts in Canada, essential for improving the risk management and mitigation strategies on the impact of droughts.
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In the past few decades, there have been more extreme climate events occurring worldwide, including Canada, which has also suffered from many extreme precipitation events. In this paper, trend analysis, probability distribution functions,... more
In the past few decades, there have been more extreme climate events occurring worldwide, including Canada, which has also suffered from many extreme precipitation events. In this paper, trend analysis, probability distribution functions, principal component analysis, and wavelet analysis were used to investigate the spatial and temporal patterns of extreme precipitation events of Canada. Ten extreme precipitation indices were calculated using long-term daily precipitation data (1950–2012) from 164 Canadian gauging stations. Several large-scale climate patterns such as El Niño–Southern Oscillation (ENSO), Pacific decadal oscillation (PDO), Pacific–North American (PNA), and North Atlantic Oscillation (NAO) were selected to analyze the relationships between extreme precipitation and climate indices. Convective available potential energy (CAPE), specific humidity, and surface temperature were employed to investigate potential causes of trends in extreme precipitation. The results revea...
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ABSTRACT Accurately forecasting the weekly seasonal streamflow of the Upper Blue Nile basin (UBNB) in Ethiopia is essential for managing large-scale water projects of Nile basinwide countries. A wavelet-based, artificial neural network... more
ABSTRACT Accurately forecasting the weekly seasonal streamflow of the Upper Blue Nile basin (UBNB) in Ethiopia is essential for managing large-scale water projects of Nile basinwide countries. A wavelet-based, artificial neural network calibrated by genetic algorithm (ANN–GA) model and a statistical disaggregation algorithm were integrated to forecast weekly streamflow of the UBNB. The July to October (JASO) streamflow of the El Diem station of UBNB shows strong interannual oscillations prior to the 1920s and after 1990s. Two ANN-GA models were developed to forecast the UBNB JASO streamflow, the first one using the February to May (FMAM) seasonal sea surface temperature (SST) of the global oceans as predictors to directly forecast JASO streamflow, while the second, a hybrid model, is developed to forecast JASO streamflow from two sets of predictors, which consist of FMAM SST and the July to September (JJAS) seasonal rainfall previously forecasted by the wavelet-based, ANN-GA also driven by FMAM SST as predictors. The forecasted JASO streamflow were then disaggregated to weekly total streamflow using the disaggregation model, Valencia and Schaake (VS). Results indicate that seasonal forecasts with up to 4 months lead time only based on SST as predictors achieved reasonable skill (r2=0.5), while the hybrid model achieved a better performance (r2=0.8). The disaggregated streamflow from the first model explained 69% of the streamflow variance, compared to 71% when the hybrid model was used. Based on the results, the proposed hybrid model that uses both SST and a forecasted JJAS seasonal rainfall as predictors achieves a marginally better forecasting skill of the UBNB weekly streamflow. This proposed method that directly forecasts the streamflow, rather than forcing a hydrological model with rainfall forecasts is useful for the management of river basins that lack observed hydrologic data. Read More: http://ascelibrary.org/doi/abs/10.1061/(ASCE)HE.1943-5584.0001072
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ABSTRACT [1] Changes to the North American snowpacks for 1979–2007 were detected from snow water equivalent (SWE) retrieved empirically from horizontally polarized brightness temperature (TB) of a scanning multichannel microwave... more
ABSTRACT [1] Changes to the North American snowpacks for 1979–2007 were detected from snow water equivalent (SWE) retrieved empirically from horizontally polarized brightness temperature (TB) of a scanning multichannel microwave radiometer (18 and 37 GHz) and special sensor microwave imager (19 and 37 GHz) passive microwave data using the nonparametric Kendall's test. The predominant SWE trends detected agree with negative anomalies in snow cover observed in Northern Hemisphere since the 1980s, and both the SWE and snow cover results should be related to the significant increase in the surface temperature of North America (NA) observed since the 1970s. About 30% of detected decreasing trends of SWE for 1979–2007 are statistically significant, which is three times more than the significant increasing trends of SWE detected in NA. Significant decreasing SWE trends are more extensive in Canada than in the United States. The mean trend magnitudes detected for December–April are −0.4 to −0.5 mm/yr, which means an overall reduction of snow depth of about 5–8 cm in 29 years (assuming a snowpack density between 200 and 250 kg/m3), which can impact regions relying on spring snowmelt for water supply. From detected increasing (decreasing) trends of gridded temperature (precipitation) based on the North American Regional Reanalysis data set and the University of Delaware data set for NA, their respective correlations with SWE data and other findings, such as global scale decline of snow cover, longer rainfall seasons, etc., it seems the extensive decreasing trends in SWE detected mainly in Canada are more caused by increasing temperatures than by decreasing precipitation. However, climate anomalies could also contribute to the detected trends, such as PC1 of NA's SWE, which is found to be correlated to the Pacific Decadal Oscillation index and marginally correlated to the Pacific North American pattern.
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ABSTRACT
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... several CP schemes, five of which were used in this study: AK, BM, Gr, FritschChappell (FC), Copyright © 2005 John Wiley & Sons, Ltd. Hydrol. Process. 20, 19611978 (2006) Page 3. CUMULUS PARAMETERIZATION SCHEMES FOR... more
... several CP schemes, five of which were used in this study: AK, BM, Gr, FritschChappell (FC), Copyright © 2005 John Wiley & Sons, Ltd. Hydrol. Process. 20, 19611978 (2006) Page 3. CUMULUS PARAMETERIZATION SCHEMES FOR SIMULATING MONSOON RAINFALL ...
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... comparison of a complex physics-based land surface model and a conceptual, lumped-parameter hydrological model at the basin-scale. ... rainfall-runoff model that does not explicitly consider spatial variability of terrain features,... more
... comparison of a complex physics-based land surface model and a conceptual, lumped-parameter hydrological model at the basin-scale. ... rainfall-runoff model that does not explicitly consider spatial variability of terrain features, land-use, soil heterogeneities, and energy fluxes. ...
Research Interests: Heterogeneity, Atmosphere, Calibration, Classification, Land Use, and 6 moreSoils, Sol, Rainfall, Vegetation, Runoff, and hydrographs
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Research Interests: Irrigation, Water resources, Statistical Analysis, Agriculture, Water Resources Management, and 15 moreMultidisciplinary, Global Warming, Strategy, Global change, Water Supply, Land Use, Surface Water, Streamflow, Resource Management, SNOW, Climatic Change, Water Conservation, Seasonal variation, Catchment Hydrology, and Climate Warming
The leaf area of forest canopies is both main attribute of stands controlling water balance through transpiration and interception, and "engine" driving stand growth, stand dynamics, and forest... more
The leaf area of forest canopies is both main attribute of stands controlling water balance through transpiration and interception, and "engine" driving stand growth, stand dynamics, and forest succession. While transpiration and interception dynamics are classic themes in forest hydrology, we present results from our eco-hydrological research on boreal trees to highlight how more recent eco-physiological insights into species specific