[1] Estimators of low-streamflow statistics are often required for water quality and quantity management at gauged and ungauged sites. Here the technique of baseflow correlation is investigated as an estimator of the 7-day, 10-year low-streamflow statistic at ungauged sites. This method uses an information transfer technique to estimate streamflow statistics at an ungauged site by correlating a...

been reviewed in final form. Permission, as indicated by the signatures and dates given below, is now granted to submit final copies to the College of Graduate Studies for approval. Abstract Changes in streamflow across the western US illustrate a need to better understand how drought indices derived from climate data track streamflow. Three drought metrics, the (SPEI), and Palmer Drought Sever...

[1] The Great Salt Lake is a closed basin lake in which level and volume fluctuate due to differences between inflows and outflows. The only outflow is evaporation, which depends directly on lake area and salinity, both of which depend on lake volume. The lake’s level, volume, and area adjust to balance, on average, precipitation and streamflow inflows by evaporation. In this paper, we examine ...

in the recent decade, special attention is paid to reverse logistic due to economic benefits of recovery and recycling of used products as well as environmental legislation and social concerns. on the other hand، many researches claim that separately and sequential planning of forward and reverse logistic causes sub-optimality. effective transport activities are also one of the most important c...

the structure of a self-routing interconnection network with a recurrent neural network," in Pro-Abstract A modiied Recurrent Neural Network (RNN) is used to learn a Self-Routing Interconnection Network (SRIN) from a set of routing examples. The RNN is modiied so that it has several distinct initial states. This is equivalent to a single RNN learning multiple diierent synchronous sequential mac...

Streamflow processes are commonly accepted as nonlinear. However, it is not clear what kind of nonlinearity is acting underlying the streamflow processes and how strong the nonlinearity is for the streamflow processes at different timescales. Streamflow data of four rivers are investigated in order to study the character and type of nonlinearity that are present in the streamflow dynamics. The ...

In the recent decade, special attention is paid to reverse logistic due to economic benefits of recovery and recycling of used products as well as environmental legislation and social concerns. On the other hand، many researches claim that separately and sequential planning of forward and reverse logistic causes sub-optimality. Effective transport activities are also one of the most important c...

Long-term streamflow data are vital for analysis of hydrological droughts. Using an artificial neural network (ANN) model and nine tree-ring indices, this study reconstructed the annual streamflow of the Sacramento River for the period from 1560 to 1871. Using the reconstructed streamflow data, the copula method was used for bivariate drought analysis, deriving a hydrological drought return per...

The predictability of a chaotic series is limited to a few future time steps due to its sensitivity to initial conditions and the exponential divergence of the trajectories. Over the years, streamflow has been considered as a stochastic system in many approaches. In this study, the chaotic nature of daily streamflow is investigated using autocorrelation function, Fourier spectrum, correlation d...

In this paper, we analyzed the streamflow droughts based on the Percent of Normal Index (PNI) and clustering approaches in the Kurdistan Province, Iran, over the 1981-2010. The Kolmogorov-Smirnov (K-S) test was considered for streamflow time series and the results of K-S test indicated that streamflow time series did follow the normal distribution at the 0.05 significance level. Generally, the ...