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• 1. [Article] Streamflow Modeling of Johnson Creek Subwatersheds Using the Precipitation Runoff Modeling System

  Johnson Creek, in the Portland, Oregon metropolitan region, has several pollutants on the U.S. Environmental Protection Agency’s (EPA) 303(d) list including excess heat, low dissolved oxygen, and harmful ...

  Citation × Citation Citation Abstract Copy Title: Streamflow Modeling of Johnson Creek Subwatersheds Using the Precipitation Runoff Modeling System Author: Malone, Theophilus M Year: 2014 Johnson Creek, in the Portland, Oregon metropolitan region, has several pollutants on the U.S. Environmental Protection Agency’s (EPA) 303(d) list including excess heat, low dissolved oxygen, and harmful bacteria. Understanding streamflow response to precipitation events is an important component to evaluating water quality trends and calculating the Total Maximum Daily Load (TMDL) for pollutants of concern. Investigating the streamflow-precipitation relationship on the subwatershed scale can give insight to the hydrologic response of a given watershed. However, developing rating curves for several subwatersheds can be cost and time prohibitive. The objective of this project was to develop a hydrologic model using the Precipitation Runoff Modeling System (PRMS), developed by the United States Geological Survey (USGS) to validate streamflow estimates for subwatersheds lacking a significant period of record. ESRI’s ArcMap, a geographic information system (GIS), was used to characterize the target drainage basins and extract basin-specific parameters for upper watersheds of Johnson Creek. The Johnson Creek Upper Watershed (JCUW) model was calibrated to an existing streamflow gage at Regner Road, in Gresham, Oregon. Calibrated parameters were substituted into a second PRMS model characterizing the Sunshine Creek Subwatershed, which lies within the JCUW. The Sunshine Creek model was used to validate a flow time-series derived from a pressure transducer and a rating curve. Title: Streamflow Modeling of Johnson Creek Subwatersheds Using the Precipitation Runoff Modeling System Author: Malone, Theophilus M Year: 2014 Johnson Creek, in the Portland, Oregon metropolitan region, has several pollutants on the U.S. Environmental Protection Agency’s (EPA) 303(d) list including excess heat, low dissolved oxygen, and harmful bacteria. Understanding streamflow response to precipitation events is an important component to evaluating water quality trends and calculating the Total Maximum Daily Load (TMDL) for pollutants of concern. Investigating the streamflow-precipitation relationship on the subwatershed scale can give insight to the hydrologic response of a given watershed. However, developing rating curves for several subwatersheds can be cost and time prohibitive. The objective of this project was to develop a hydrologic model using the Precipitation Runoff Modeling System (PRMS), developed by the United States Geological Survey (USGS) to validate streamflow estimates for subwatersheds lacking a significant period of record. ESRI’s ArcMap, a geographic information system (GIS), was used to characterize the target drainage basins and extract basin-specific parameters for upper watersheds of Johnson Creek. The Johnson Creek Upper Watershed (JCUW) model was calibrated to an existing streamflow gage at Regner Road, in Gresham, Oregon. Calibrated parameters were substituted into a second PRMS model characterizing the Sunshine Creek Subwatershed, which lies within the JCUW. The Sunshine Creek model was used to validate a flow time-series derived from a pressure transducer and a rating curve. Close

• 2. [Article] A Review of Urban Water Body Challenges and Approaches: (1) Rehabilitation and Remediation

  We review how urbanization alters aquatic ecosystems, as well as actions that managers can take to remediate urban waters. Urbanization affects streams by fundamentally altering longitudinal and lateral ...

  Citation × Citation Citation Abstract Copy Title: A Review of Urban Water Body Challenges and Approaches: (1) Rehabilitation and Remediation Author: Hughes, Robert M., Dunham, Susie, Maas-Hebner, Kathleen G., Yeakley, J. Alan, Schreck, Carl B., Harte, Michael, Molina, Nancy, Shock, Clinton C., Kaczynski, Victor W., Schaeffer, Jeff Year: 2014 We review how urbanization alters aquatic ecosystems, as well as actions that managers can take to remediate urban waters. Urbanization affects streams by fundamentally altering longitudinal and lateral processes that in turn alter hydrology, habitat, and water chemistry; these effects create physical and chemical stressors that in turn affect the biota. Urban streams often suffer from multiple stressor effects that have collectively been termed an “urban stream syndrome,” in which no single factor dominates degraded conditions. Resource managers have multiple ways of combating the urban stream syndrome. These approaches range from whole-watershed protection to reach-scale habitat rehabilitation, but the prescription must be matched to the scale of the factors that are causing the problem, and results will likely not be immediate because of lengthy recovery times. Although pristine or reference conditions are far from attainable, urban stream rehabilitation is a worthy goal because appropriate actions can provide ecosystem improvements as well as increased ecosystem service benefits for human society. Title: A Review of Urban Water Body Challenges and Approaches: (1) Rehabilitation and Remediation Author: Hughes, Robert M., Dunham, Susie, Maas-Hebner, Kathleen G., Yeakley, J. Alan, Schreck, Carl B., Harte, Michael, Molina, Nancy, Shock, Clinton C., Kaczynski, Victor W., Schaeffer, Jeff Year: 2014 We review how urbanization alters aquatic ecosystems, as well as actions that managers can take to remediate urban waters. Urbanization affects streams by fundamentally altering longitudinal and lateral processes that in turn alter hydrology, habitat, and water chemistry; these effects create physical and chemical stressors that in turn affect the biota. Urban streams often suffer from multiple stressor effects that have collectively been termed an “urban stream syndrome,” in which no single factor dominates degraded conditions. Resource managers have multiple ways of combating the urban stream syndrome. These approaches range from whole-watershed protection to reach-scale habitat rehabilitation, but the prescription must be matched to the scale of the factors that are causing the problem, and results will likely not be immediate because of lengthy recovery times. Although pristine or reference conditions are far from attainable, urban stream rehabilitation is a worthy goal because appropriate actions can provide ecosystem improvements as well as increased ecosystem service benefits for human society. Close

• 3. [Article] Towards Improving Drought Forecasts Across Different Spatial and Temporal Scales

  Recent water scarcities across the southwestern U.S. with severe effects on the living environment inspire the development of new methodologies to achieve reliable drought forecasting in seasonal scale. ...

  Citation × Citation Citation Abstract Copy Title: Towards Improving Drought Forecasts Across Different Spatial and Temporal Scales Author: Madadgar, Shahrbanou Year: 2014 Recent water scarcities across the southwestern U.S. with severe effects on the living environment inspire the development of new methodologies to achieve reliable drought forecasting in seasonal scale. Reliable forecast of hydrologic variables, in general, is a preliminary requirement for appropriate planning of water resources and developing effective allocation policies. This study aims at developing new techniques with specific probabilistic features to improve the reliability of hydrologic forecasts, particularly the drought forecasts. The drought status in the future is determined by certain hydrologic variables that are basically estimated by the hydrologic models with rather simple to complex structures. Since the predictions of hydrologic models are prone to different sources of uncertainties, there have been several techniques examined during past several years which generally attempt to combine the predictions of single (multiple) hydrologic models to generate an ensemble of hydrologic forecasts addressing the inherent uncertainties. However, the imperfect structure of hydrologic models usually lead to systematic bias of hydrologic predictions that further appears in the forecast ensembles. This study proposes a post-processing method that is applied to the raw forecast of hydrologic variables and can develop the entire distribution of forecast around the initial single-value prediction. To establish the probability density function (PDF) of the forecast, a group of multivariate distribution functions, the so-called copula functions, are incorporated in the post-processing procedure. The performance of the new post-processing technique is tested on 2500 hypothetical case studies and the streamflow forecast of Sprague River Basin in southern Oregon. Verified by some deterministic and probabilistic verification measures, the method of Quantile Mapping as a traditional post-processing technique cannot generate the qualified forecasts as comparing with the copula-based method. The post-processing technique is then expanded to exclusively study the drought forecasts across the different spatial and temporal scales. In the proposed drought forecasting model, the drought status in the future is evaluated based on the drought status of the past seasons while the correlations between the drought variables of consecutive seasons are preserved by copula functions. The main benefit of the new forecast model is its probabilistic features in analyzing future droughts. It develops conditional probability of drought status in the forecast season and generates the PDF and cumulative distribution function (CDF) of future droughts given the past status. The conditional PDF can return the highest probable drought in the future along with an assessment of the uncertainty around that value. Using the conditional CDF for forecast season, the model can generate the maps of drought status across the basin with particular chance of occurrence in the future. In a different analysis of the conditional CDF developed for the forecast season, the chance of a particular drought in the forecast period can be approximated given the drought status of earlier seasons. The forecast methodology developed in this study shows promising results in hydrologic forecasts and its particular probabilistic features are inspiring for future studies. Title: Towards Improving Drought Forecasts Across Different Spatial and Temporal Scales Author: Madadgar, Shahrbanou Year: 2014 Recent water scarcities across the southwestern U.S. with severe effects on the living environment inspire the development of new methodologies to achieve reliable drought forecasting in seasonal scale. Reliable forecast of hydrologic variables, in general, is a preliminary requirement for appropriate planning of water resources and developing effective allocation policies. This study aims at developing new techniques with specific probabilistic features to improve the reliability of hydrologic forecasts, particularly the drought forecasts. The drought status in the future is determined by certain hydrologic variables that are basically estimated by the hydrologic models with rather simple to complex structures. Since the predictions of hydrologic models are prone to different sources of uncertainties, there have been several techniques examined during past several years which generally attempt to combine the predictions of single (multiple) hydrologic models to generate an ensemble of hydrologic forecasts addressing the inherent uncertainties. However, the imperfect structure of hydrologic models usually lead to systematic bias of hydrologic predictions that further appears in the forecast ensembles. This study proposes a post-processing method that is applied to the raw forecast of hydrologic variables and can develop the entire distribution of forecast around the initial single-value prediction. To establish the probability density function (PDF) of the forecast, a group of multivariate distribution functions, the so-called copula functions, are incorporated in the post-processing procedure. The performance of the new post-processing technique is tested on 2500 hypothetical case studies and the streamflow forecast of Sprague River Basin in southern Oregon. Verified by some deterministic and probabilistic verification measures, the method of Quantile Mapping as a traditional post-processing technique cannot generate the qualified forecasts as comparing with the copula-based method. The post-processing technique is then expanded to exclusively study the drought forecasts across the different spatial and temporal scales. In the proposed drought forecasting model, the drought status in the future is evaluated based on the drought status of the past seasons while the correlations between the drought variables of consecutive seasons are preserved by copula functions. The main benefit of the new forecast model is its probabilistic features in analyzing future droughts. It develops conditional probability of drought status in the forecast season and generates the PDF and cumulative distribution function (CDF) of future droughts given the past status. The conditional PDF can return the highest probable drought in the future along with an assessment of the uncertainty around that value. Using the conditional CDF for forecast season, the model can generate the maps of drought status across the basin with particular chance of occurrence in the future. In a different analysis of the conditional CDF developed for the forecast season, the chance of a particular drought in the forecast period can be approximated given the drought status of earlier seasons. The forecast methodology developed in this study shows promising results in hydrologic forecasts and its particular probabilistic features are inspiring for future studies. Close