The Experts below are selected from a list of 1446 Experts worldwide ranked by ideXlab platform

Elfatih A. B. Eltahir - One of the best experts on this subject based on the ideXlab platform.

  • Modeling the Hydroclimatology of the midwestern United States. Part 1: current climate
    Climate Dynamics, 2011
    Co-Authors: Jonathan M. Winter, Elfatih A. B. Eltahir
    Abstract:

    An ensemble of six 22-year numerical experiments was conducted to evaluate the ability of Regional Climate Model version 3 (RegCM3) to simulate the energy and water budgets of the midwestern United States. RegCM3 was run using two surface physics schemes: Integrated Biosphere Simulator (IBIS) and Biosphere-Atmosphere Transfer Scheme 1e (BATS1e), and two convective closure assumptions: Fritsch & Chappell (FC80) and Arakawa & Schubert (AS74). Boundary conditions were provided by the National Centers for Environmental Prediction-Department of Energy Reanalysis 2 dataset and the ECHAM5 general circulation model. A companion paper examines the American Midwest under future climate scenarios. Overall, the model that reproduces the observed seasonal cycles of the midwestern United States climate system best is RegCM3 using IBIS and the AS74 convective closure assumption. IBIS simulates shortwave radiation more accurately, while BATS1e simulates longwave radiation more accurately. Summer two-meter air temperature is overestimated by the combination of IBIS and the FC80 convective closure assumption. All models contain a wet bias and overestimate evapotranspiration during the spring. Total runoff, surface runoff, groundwater runoff, and root zone soil moisture are best simulated by RegCM3 using IBIS and the AS74 convective closure assumption. While BATS1e does capture the seasonal cycle of total runoff, gross errors in the partitioning of total runoff between surface runoff and groundwater runoff exist. The seasonal cycle of root zone soil moisture simulated by RegCM3 using IBIS and the AS74 convective closure assumption is dry, but agrees with observations during the summer. The rest of the models underestimate root zone soil moisture.National Science Foundation (U.S.) (Award EAR-04500341)Martin Family Society of Fellows for Sustainabilit

  • Modeling the Hydroclimatology of the midwestern United States. Part 1: current climate
    Climate Dynamics, 2011
    Co-Authors: Jonathan M. Winter, Elfatih A. B. Eltahir
    Abstract:

    An ensemble of six 22-year numerical experiments was conducted to evaluate the ability of Regional Climate Model version 3 (RegCM3) to simulate the energy and water budgets of the midwestern United States. RegCM3 was run using two surface physics schemes: Integrated Biosphere Simulator (IBIS) and Biosphere-Atmosphere Transfer Scheme 1e (BATS1e), and two convective closure assumptions: Fritsch & Chappell (FC80) and Arakawa & Schubert (AS74). Boundary conditions were provided by the National Centers for Environmental Prediction-Department of Energy Reanalysis 2 dataset and the ECHAM5 general circulation model. A companion paper examines the American Midwest under future climate scenarios. Overall, the model that reproduces the observed seasonal cycles of the midwestern United States climate system best is RegCM3 using IBIS and the AS74 convective closure assumption. IBIS simulates shortwave radiation more accurately, while BATS1e simulates longwave radiation more accurately. Summer two-meter air temperature is overestimated by the combination of IBIS and the FC80 convective closure assumption. All models contain a wet bias and overestimate evapotranspiration during the spring. Total runoff, surface runoff, groundwater runoff, and root zone soil moisture are best simulated by RegCM3 using IBIS and the AS74 convective closure assumption. While BATS1e does capture the seasonal cycle of total runoff, gross errors in the partitioning of total runoff between surface runoff and groundwater runoff exist. The seasonal cycle of root zone soil moisture simulated by RegCM3 using IBIS and the AS74 convective closure assumption is dry, but agrees with observations during the summer. The rest of the models underestimate root zone soil moisture.

William D. Collins - One of the best experts on this subject based on the ideXlab platform.

  • An intercomparison of GCM and RCM dynamical downscaling for characterizing the Hydroclimatology of California and Nevada
    Journal of Hydrometeorology, 2018
    Co-Authors: Alan M. Rhoades, Hans Johansen, Paul A. Ullrich, William D. Collins
    Abstract:

    © 2018 American Meteorological Society. Dynamical downscaling is a widely used technique to properly capture regional surface heterogeneities that shape the local Hydroclimatology. However, in the context of dynamical downscaling, the impacts on simulation fidelity have not been comprehensively evaluated across many user-specified factors, including the refinements of model horizontal resolution, large-scale forcing datasets, and dynamical cores. Two global-to-regional downscaling methods are used to assess these: specifically, the variable-resolution Community Earth System Model (VR-CESM) and the Weather Research and Forecasting (WRF) Model with horizontal resolutions of 28, 14, and 7 km. The modeling strategies are assessed by comparing the VR-CESM and WRF simulations with consistent physical parameterizations and grid domains. Two groups of WRF Models are driven by either the NCEP reanalysis dataset (WRF_NCEP) or VR-CESM7 results (WRF_VRCESM) to evaluate the effects of large-scale forcing datasets. The simulated hydroclimatologies are compared with reference datasets for key properties including total precipitation, snow cover, snow water equivalent (SWE), and surface temperature. The large-scale forcing datasets are critical to the WRF simulations of total precipitation but not surface temperature, controlled by the wind field and atmospheric moisture transport at the ocean boundary. No significant benefit is found in the regional average simulated Hydroclimatology by increasing horizontal resolution refinement from 28 to 7 km, probably due to the systematic biases from the diagnostic treatment of rainfall and snowfall in the microphysics scheme. The choice of dynamical core has little impact on total precipitation but significantly determines simulated surface temperature, which is affected by the snow-albedo feedback in winter and soil moisture estimations in summer.

  • Sensitivity of Mountain Hydroclimate Simulations in Variable‐Resolution CESM to Microphysics and Horizontal Resolution
    Journal of Advances in Modeling Earth Systems, 2018
    Co-Authors: Alan M. Rhoades, Hans Johansen, Paul A. Ullrich, Colin M Zarzycki, Steven A Margulis, Hugh Morrison, William D. Collins
    Abstract:

    Author(s): Rhoades, AM; Ullrich, PA; Zarzycki, CM; Johansen, H; Margulis, SA; Morrison, H; Xu, Z; Collins, WD | Abstract: © 2018. The Authors. Mountains are natural dams that impede atmospheric moisture transport and water towers that cool, condense, and store precipitation. They are essential in the western United States where precipitation is seasonal, and snowpack is needed to meet water demand. With anthropogenic climate change increasingly threatening mountain snowpack, there is a pressing need to better understand the driving climatological processes. However, the coarse resolution typical of modern global climate models renders them largely insufficient for this task, and signals a need for an advanced strategy. This paper continues the assessment of variable-resolution in the Community Earth System Model (VR-CESM) in modeling mountain Hydroclimatology to understand the role of grid-spacing at 55, 28, 14, and 7 km and microphysics, specifically the Morrison and Gettelman (, MG1, https://doi.org/10.1175/2008JCLI2105.1) scheme versus the Gettelman and Morrison (, MG2, https://doi.org/10.1175/JCLI-D-14-00102.1) scheme. Eight VR-CESM simulations were performed from 1999 to 2015 with the F_AMIP_CAM5 component set, which couples the atmosphere-land models and prescribes ocean data. Refining horizontal grid-spacing from 28 to 7 km with the MG1 scheme did not improve the simulated mountain Hydroclimatology. Substantial improvements occurred with the use of MG2 at grid-spacings ≤28 km compared to MG1 as shown with subsequent statistics. Average SWE bias diminished by 9.4X, 4.9X, and 3.5X from 55 to 7 km. The range in minimum (maximum) DJF spatial correlations increased by 0.1–0.2 in both precipitation and SWE. Mountain windward/leeward distributions and elevation profiles improved across hydroclimate variables, however not always with model resolution alone. Disconcertingly, all VR-CESM simulations exhibited a systemic mountain cold bias that worsened with elevation and will require further examination.

  • sensitivity of mountain hydroclimate simulations in variable resolution cesm to microphysics and horizontal resolution
    Journal of Advances in Modeling Earth Systems, 2018
    Co-Authors: Alan M. Rhoades, Hans Johansen, Paul A. Ullrich, Colin M Zarzycki, Steven A Margulis, Hugh Morrison, William D. Collins
    Abstract:

    Author(s): Rhoades, AM; Ullrich, PA; Zarzycki, CM; Johansen, H; Margulis, SA; Morrison, H; Xu, Z; Collins, WD | Abstract: © 2018. The Authors. Mountains are natural dams that impede atmospheric moisture transport and water towers that cool, condense, and store precipitation. They are essential in the western United States where precipitation is seasonal, and snowpack is needed to meet water demand. With anthropogenic climate change increasingly threatening mountain snowpack, there is a pressing need to better understand the driving climatological processes. However, the coarse resolution typical of modern global climate models renders them largely insufficient for this task, and signals a need for an advanced strategy. This paper continues the assessment of variable-resolution in the Community Earth System Model (VR-CESM) in modeling mountain Hydroclimatology to understand the role of grid-spacing at 55, 28, 14, and 7 km and microphysics, specifically the Morrison and Gettelman (, MG1, https://doi.org/10.1175/2008JCLI2105.1) scheme versus the Gettelman and Morrison (, MG2, https://doi.org/10.1175/JCLI-D-14-00102.1) scheme. Eight VR-CESM simulations were performed from 1999 to 2015 with the F_AMIP_CAM5 component set, which couples the atmosphere-land models and prescribes ocean data. Refining horizontal grid-spacing from 28 to 7 km with the MG1 scheme did not improve the simulated mountain Hydroclimatology. Substantial improvements occurred with the use of MG2 at grid-spacings ≤28 km compared to MG1 as shown with subsequent statistics. Average SWE bias diminished by 9.4X, 4.9X, and 3.5X from 55 to 7 km. The range in minimum (maximum) DJF spatial correlations increased by 0.1–0.2 in both precipitation and SWE. Mountain windward/leeward distributions and elevation profiles improved across hydroclimate variables, however not always with model resolution alone. Disconcertingly, all VR-CESM simulations exhibited a systemic mountain cold bias that worsened with elevation and will require further examination.

Jonathan M. Winter - One of the best experts on this subject based on the ideXlab platform.

  • Modeling the Hydroclimatology of the midwestern United States. Part 1: current climate
    Climate Dynamics, 2011
    Co-Authors: Jonathan M. Winter, Elfatih A. B. Eltahir
    Abstract:

    An ensemble of six 22-year numerical experiments was conducted to evaluate the ability of Regional Climate Model version 3 (RegCM3) to simulate the energy and water budgets of the midwestern United States. RegCM3 was run using two surface physics schemes: Integrated Biosphere Simulator (IBIS) and Biosphere-Atmosphere Transfer Scheme 1e (BATS1e), and two convective closure assumptions: Fritsch & Chappell (FC80) and Arakawa & Schubert (AS74). Boundary conditions were provided by the National Centers for Environmental Prediction-Department of Energy Reanalysis 2 dataset and the ECHAM5 general circulation model. A companion paper examines the American Midwest under future climate scenarios. Overall, the model that reproduces the observed seasonal cycles of the midwestern United States climate system best is RegCM3 using IBIS and the AS74 convective closure assumption. IBIS simulates shortwave radiation more accurately, while BATS1e simulates longwave radiation more accurately. Summer two-meter air temperature is overestimated by the combination of IBIS and the FC80 convective closure assumption. All models contain a wet bias and overestimate evapotranspiration during the spring. Total runoff, surface runoff, groundwater runoff, and root zone soil moisture are best simulated by RegCM3 using IBIS and the AS74 convective closure assumption. While BATS1e does capture the seasonal cycle of total runoff, gross errors in the partitioning of total runoff between surface runoff and groundwater runoff exist. The seasonal cycle of root zone soil moisture simulated by RegCM3 using IBIS and the AS74 convective closure assumption is dry, but agrees with observations during the summer. The rest of the models underestimate root zone soil moisture.National Science Foundation (U.S.) (Award EAR-04500341)Martin Family Society of Fellows for Sustainabilit

  • Modeling the Hydroclimatology of the midwestern United States. Part 1: current climate
    Climate Dynamics, 2011
    Co-Authors: Jonathan M. Winter, Elfatih A. B. Eltahir
    Abstract:

    An ensemble of six 22-year numerical experiments was conducted to evaluate the ability of Regional Climate Model version 3 (RegCM3) to simulate the energy and water budgets of the midwestern United States. RegCM3 was run using two surface physics schemes: Integrated Biosphere Simulator (IBIS) and Biosphere-Atmosphere Transfer Scheme 1e (BATS1e), and two convective closure assumptions: Fritsch & Chappell (FC80) and Arakawa & Schubert (AS74). Boundary conditions were provided by the National Centers for Environmental Prediction-Department of Energy Reanalysis 2 dataset and the ECHAM5 general circulation model. A companion paper examines the American Midwest under future climate scenarios. Overall, the model that reproduces the observed seasonal cycles of the midwestern United States climate system best is RegCM3 using IBIS and the AS74 convective closure assumption. IBIS simulates shortwave radiation more accurately, while BATS1e simulates longwave radiation more accurately. Summer two-meter air temperature is overestimated by the combination of IBIS and the FC80 convective closure assumption. All models contain a wet bias and overestimate evapotranspiration during the spring. Total runoff, surface runoff, groundwater runoff, and root zone soil moisture are best simulated by RegCM3 using IBIS and the AS74 convective closure assumption. While BATS1e does capture the seasonal cycle of total runoff, gross errors in the partitioning of total runoff between surface runoff and groundwater runoff exist. The seasonal cycle of root zone soil moisture simulated by RegCM3 using IBIS and the AS74 convective closure assumption is dry, but agrees with observations during the summer. The rest of the models underestimate root zone soil moisture.

Alan M. Rhoades - One of the best experts on this subject based on the ideXlab platform.

  • An intercomparison of GCM and RCM dynamical downscaling for characterizing the Hydroclimatology of California and Nevada
    Journal of Hydrometeorology, 2018
    Co-Authors: Alan M. Rhoades, Hans Johansen, Paul A. Ullrich, William D. Collins
    Abstract:

    © 2018 American Meteorological Society. Dynamical downscaling is a widely used technique to properly capture regional surface heterogeneities that shape the local Hydroclimatology. However, in the context of dynamical downscaling, the impacts on simulation fidelity have not been comprehensively evaluated across many user-specified factors, including the refinements of model horizontal resolution, large-scale forcing datasets, and dynamical cores. Two global-to-regional downscaling methods are used to assess these: specifically, the variable-resolution Community Earth System Model (VR-CESM) and the Weather Research and Forecasting (WRF) Model with horizontal resolutions of 28, 14, and 7 km. The modeling strategies are assessed by comparing the VR-CESM and WRF simulations with consistent physical parameterizations and grid domains. Two groups of WRF Models are driven by either the NCEP reanalysis dataset (WRF_NCEP) or VR-CESM7 results (WRF_VRCESM) to evaluate the effects of large-scale forcing datasets. The simulated hydroclimatologies are compared with reference datasets for key properties including total precipitation, snow cover, snow water equivalent (SWE), and surface temperature. The large-scale forcing datasets are critical to the WRF simulations of total precipitation but not surface temperature, controlled by the wind field and atmospheric moisture transport at the ocean boundary. No significant benefit is found in the regional average simulated Hydroclimatology by increasing horizontal resolution refinement from 28 to 7 km, probably due to the systematic biases from the diagnostic treatment of rainfall and snowfall in the microphysics scheme. The choice of dynamical core has little impact on total precipitation but significantly determines simulated surface temperature, which is affected by the snow-albedo feedback in winter and soil moisture estimations in summer.

  • Sensitivity of Mountain Hydroclimate Simulations in Variable‐Resolution CESM to Microphysics and Horizontal Resolution
    Journal of Advances in Modeling Earth Systems, 2018
    Co-Authors: Alan M. Rhoades, Hans Johansen, Paul A. Ullrich, Colin M Zarzycki, Steven A Margulis, Hugh Morrison, William D. Collins
    Abstract:

    Author(s): Rhoades, AM; Ullrich, PA; Zarzycki, CM; Johansen, H; Margulis, SA; Morrison, H; Xu, Z; Collins, WD | Abstract: © 2018. The Authors. Mountains are natural dams that impede atmospheric moisture transport and water towers that cool, condense, and store precipitation. They are essential in the western United States where precipitation is seasonal, and snowpack is needed to meet water demand. With anthropogenic climate change increasingly threatening mountain snowpack, there is a pressing need to better understand the driving climatological processes. However, the coarse resolution typical of modern global climate models renders them largely insufficient for this task, and signals a need for an advanced strategy. This paper continues the assessment of variable-resolution in the Community Earth System Model (VR-CESM) in modeling mountain Hydroclimatology to understand the role of grid-spacing at 55, 28, 14, and 7 km and microphysics, specifically the Morrison and Gettelman (, MG1, https://doi.org/10.1175/2008JCLI2105.1) scheme versus the Gettelman and Morrison (, MG2, https://doi.org/10.1175/JCLI-D-14-00102.1) scheme. Eight VR-CESM simulations were performed from 1999 to 2015 with the F_AMIP_CAM5 component set, which couples the atmosphere-land models and prescribes ocean data. Refining horizontal grid-spacing from 28 to 7 km with the MG1 scheme did not improve the simulated mountain Hydroclimatology. Substantial improvements occurred with the use of MG2 at grid-spacings ≤28 km compared to MG1 as shown with subsequent statistics. Average SWE bias diminished by 9.4X, 4.9X, and 3.5X from 55 to 7 km. The range in minimum (maximum) DJF spatial correlations increased by 0.1–0.2 in both precipitation and SWE. Mountain windward/leeward distributions and elevation profiles improved across hydroclimate variables, however not always with model resolution alone. Disconcertingly, all VR-CESM simulations exhibited a systemic mountain cold bias that worsened with elevation and will require further examination.

  • sensitivity of mountain hydroclimate simulations in variable resolution cesm to microphysics and horizontal resolution
    Journal of Advances in Modeling Earth Systems, 2018
    Co-Authors: Alan M. Rhoades, Hans Johansen, Paul A. Ullrich, Colin M Zarzycki, Steven A Margulis, Hugh Morrison, William D. Collins
    Abstract:

    Author(s): Rhoades, AM; Ullrich, PA; Zarzycki, CM; Johansen, H; Margulis, SA; Morrison, H; Xu, Z; Collins, WD | Abstract: © 2018. The Authors. Mountains are natural dams that impede atmospheric moisture transport and water towers that cool, condense, and store precipitation. They are essential in the western United States where precipitation is seasonal, and snowpack is needed to meet water demand. With anthropogenic climate change increasingly threatening mountain snowpack, there is a pressing need to better understand the driving climatological processes. However, the coarse resolution typical of modern global climate models renders them largely insufficient for this task, and signals a need for an advanced strategy. This paper continues the assessment of variable-resolution in the Community Earth System Model (VR-CESM) in modeling mountain Hydroclimatology to understand the role of grid-spacing at 55, 28, 14, and 7 km and microphysics, specifically the Morrison and Gettelman (, MG1, https://doi.org/10.1175/2008JCLI2105.1) scheme versus the Gettelman and Morrison (, MG2, https://doi.org/10.1175/JCLI-D-14-00102.1) scheme. Eight VR-CESM simulations were performed from 1999 to 2015 with the F_AMIP_CAM5 component set, which couples the atmosphere-land models and prescribes ocean data. Refining horizontal grid-spacing from 28 to 7 km with the MG1 scheme did not improve the simulated mountain Hydroclimatology. Substantial improvements occurred with the use of MG2 at grid-spacings ≤28 km compared to MG1 as shown with subsequent statistics. Average SWE bias diminished by 9.4X, 4.9X, and 3.5X from 55 to 7 km. The range in minimum (maximum) DJF spatial correlations increased by 0.1–0.2 in both precipitation and SWE. Mountain windward/leeward distributions and elevation profiles improved across hydroclimate variables, however not always with model resolution alone. Disconcertingly, all VR-CESM simulations exhibited a systemic mountain cold bias that worsened with elevation and will require further examination.

A. Sankarasubramanian - One of the best experts on this subject based on the ideXlab platform.

  • Monthly Hydroclimatology of the continental United States
    Advances in Water Resources, 2018
    Co-Authors: Thomas Petersen, Naresh Devineni, A. Sankarasubramanian
    Abstract:

    Abstract Physical/semi-empirical models that do not require any calibration are of paramount need for estimating hydrological fluxes for ungauged sites. We develop semi-empirical models for estimating the mean and variance of the monthly streamflow based on Taylor Series approximation of a lumped physically based water balance model. The proposed models require mean and variance of monthly precipitation and potential evapotranspiration, co-variability of precipitation and potential evapotranspiration and regionally calibrated catchment retention sensitivity, atmospheric moisture uptake sensitivity, groundwater-partitioning factor, and the maximum soil moisture holding capacity parameters. Estimates of mean and variance of monthly streamflow using the semi-empirical equations are compared with the observed estimates for 1373 catchments in the continental United States. Analyses show that the proposed models explain the spatial variability in monthly moments for basins in lower elevations. A regionalization of parameters for each water resources region show good agreement between observed moments and model estimated moments during January, February, March and April for mean and all months except May and June for variance. Thus, the proposed relationships could be employed for understanding and estimating the monthly Hydroclimatology of ungauged basins using regional parameters.

  • 2002: Annual Hydroclimatology of the United States
    2016
    Co-Authors: A. Sankarasubramanian, Richard M. Vogel
    Abstract:

    [1] An overview of the annual Hydroclimatology of the United States is provided. Time series of monthly streamflow, temperature, and precipitation are developed for 1337 watersheds in the United States. This unique data set is then used to evaluate several approaches for estimating the long-term water balance and the interannual variability of streamflow. Traditional relationships which predict either actual evapotranspiration or the interannual variability of streamflow from an aridity index f PE=P are shown to perform poorly for basins with low soil moisture storage capacity. A water balance model is used to formulate new relationships for predicting actual evapotranspiration and the interannual variability of streamflow. These relationships depend on both the aridity index f PE=P and a new soil moisture storage index. A physically based approach for estimating the soil moisture storage index is introduced which requires monthly time series of precipitation, potential evapotranspiration, and an estimate of maximum soil moisture holding capacity. The net results are improved expressions for the long-term water balance and the interannual variability of streamflow which do not require eithe

  • Improving Groundwater Predictions Utilizing Seasonal Precipitation Forecasts from General Circulation Models Forced with Sea Surface Temperature Forecasts
    2016
    Co-Authors: Naser Almanaseer, A. Sankarasubramanian, M. Asce, Jerad Bales
    Abstract:

    Abstract: Recent studies have found a significant association between climatic variability and basin Hydroclimatology, particularly ground-water levels, over the southeast United States. The research reported in this paper evaluates the potential in developing 6-month-ahead groundwater-level forecasts based on the precipitation forecasts from ECHAM 4.5 General Circulation Model Forced with Sea Surface Temperature forecasts. Ten groundwater wells and nine streamgauges from the USGS Groundwater Climate Response Network and Hydro-Climatic Data Network were selected to represent groundwater and surface water flows, respectively, having minimal anthropogenic influences within the Flint River Basin in Georgia, United States. The writers employ two low-dimensional models [principle component regression (PCR) and canonical correlation analysis (CCA)] for predicting groundwater and streamflow at both seasonal and monthly time

  • Hydroclimatology of the continental United States
    Geophysical Research Letters, 2003
    Co-Authors: A. Sankarasubramanian, Richard M. Vogel
    Abstract:

    [1] The overall water balance and the sensitivity of watershed runoff to changes in climate are investigated using national databases of climate and streamflow for 1,337 watersheds in the U.S. We document that 1% changes in precipitation result in 1.5–2.5% changes in watershed runoff, depending upon the degree of buffering by storage processes and other factors. Unlike previous research, our approach to estimating climate sensitivity of streamflow is nonparametric and does not depend on a hydrologic model. The upper bound for precipitation elasticity of streamflow is shown to be the inverse of the runoff ratio. For over a century, investigators [Pike, 1964; Budyko, 1974; Ol'dekop, 1911; and Schreiber, 1904] have suggested that variations in watershed aridity alone are sufficient to predict spatial variations in long-term watershed runoff. We document that variations in soil moisture holding capacity are just as important as variations in watershed aridity in explaining the mean and variance of annual watershed runoff.

  • Annual Hydroclimatology of the United States
    Water Resources Research, 2002
    Co-Authors: A. Sankarasubramanian, Richard M. Vogel
    Abstract:

    [1] An overview of the annual Hydroclimatology of the United States is provided. Time series of monthly streamflow, temperature, and precipitation are developed for 1337 watersheds in the United States. This unique data set is then used to evaluate several approaches for estimating the long-term water balance and the interannual variability of streamflow. Traditional relationships which predict either actual evapotranspiration or the interannual variability of streamflow from an aridity index are shown to perform poorly for basins with low soil moisture storage capacity. A water balance model is used to formulate new relationships for predicting actual evapotranspiration and the interannual variability of streamflow. These relationships depend on both the aridity index and a new soil moisture storage index. A physically based approach for estimating the soil moisture storage index is introduced which requires monthly time series of precipitation, potential evapotranspiration, and an estimate of maximum soil moisture holding capacity. The net results are improved expressions for the long-term water balance and the interannual variability of streamflow which do not require either calibration or streamflow data.