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Quantifying Excess Stormwater Using SCS-CN–Based Rainfall Runoff Models and Different Curve Number Determination Methods
Publisher: American Society of Civil Engineers
Abstract: Estimation of excess storm water is among the most basic hydrological challenges for hydrologists and engineers. The initial abstraction ratio
Synthetic Generation of Hydrologic Time Series Based on Nonparametric Random Generation
Publisher: American Society of Civil Engineers
Abstract: Synthetic hydrologic time series can be used to quantify the uncertainty of a water resources system. Conventional parametric models, such as autoregressive moving average or Markovian models, assume that the variable under ...
Nonlinear Model for Drought Forecasting Based on a Conjunction of Wavelet Transforms and Neural Networks
Publisher: American Society of Civil Engineers
Abstract: Droughts are destructive climatic extreme events that may cause significant damage both in natural environments and in human lives. Drought forecasting plays an important role in the control and management of water resources ...
Nonparametric Approach for Estimating Return Periods of Droughts in Arid Regions
Publisher: American Society of Civil Engineers
Abstract: Droughts cause severe damage in terms of both natural environments and human lives, and hydrologists and water resources managers are concerned with estimating the relative frequencies of these events. Univariate parametric ...
Nonparametric Approach for Bivariate Drought Characterization Using Palmer Drought Index
Publisher: American Society of Civil Engineers
Abstract: A drought is usually represented by duration and severity, and may last several months or years. Multidimensional characteristics of a drought make univariate analysis unable to reveal the significant relationship among ...
Runoff Estimation Using the NRCS Slope-Adjusted Curve Number in Mountainous Watersheds
Publisher: American Society of Civil Engineers
Abstract: In mountainous watersheds, rainfall generates runoff quickly because of the decreased depression storage, high downslope flow velocity, and smaller chance for rainwater infiltration. In order to obtain precise event-based ...
Comprehensive Evaluation of Machine Learning Techniques for Hydrological Drought Forecasting
Publisher: ASCE
Abstract: Drought is among the most hazardous climatic disasters that significantly influence various aspects of the environment and human life. Qualitative and reliable drought forecasting is important worldwide for effective ...