Variation of streamflow and sediment load in the Yellow River basin has received considerable attention due to its drastic reduction during the past several decades. This paper presents a detailed investigation on the changes of streamflow and sediment load from 1952 to 2011 using monthly observations at four gauging stations along the Yellow River. The results show significant decreasing trend...

Nowadays, as the available water resources throughout the World are becoming depleted, in order to manage and plan water resource better, more and more attention is being paid into the fluctuating characteristics of water discharges. However, the preexisting research was mainly focused on the last half century. In this paper, the natural streamflow observed since 1470 at the Sanmenxia station i...

Because of global warming, the hydrologic behavior of the Rhine basin is expected to shift from a combined snowmeltand rainfall-driven regime to a more rainfall-dominated regime. Previous impact assessments have indicated that this leads, on average, to increasing streamflow by ;30% in winter and spring and decreasing streamflow by a similar value in summer. In this study, high-resolution (0.08...

Abstract. Conventional streamflow models operate under the assumption of constant variance or season-dependent variances (e.g. ARMA (AutoRegressive Moving Average) models for deseasonalized streamflow series and PARMA (Periodic AutoRegressive Moving Average) models for seasonal streamflow series). However, with McLeod-Li test and Engle’s Lagrange Multiplier test, clear evidences are found for t...

The introduction of complex land surface parameterization schemes into regional climate models (RCMs) has been focused on improving the modeling of land surface feedbacks to the atmosphere. As such the modeling of streamflow was considered a by-product of the water balance and until recently it received relatively little attention. Comparison of four RCMs (RegCM2, MM5/BATS, MM5/SHEELS and MM5/O...

Abstrak Precise and correct estimation of streamflow is important for the operative progression in water resources systems. The artificial intelligence approaches; such as artificial neural networks (ANN) have been applied for efficiently tackling the hydrological matters like streamflow forecasting in this study at upper Yangtze River. The objective is to investigate the certainty of monthly s...

* Documentation of the degree and direction of effects of ozone on transpiration of canopies of mature forest trees is critically needed to model ozone effects on forest water use and growth in a warmer future climate. * Patterns of sap flow in stems and soil moisture in the rooting zones of mature trees, coupled with late-season streamflow in three forested watersheds in east Tennessee, USA, w...

Monthly streamflow has elements of stochasticity, seasonality, and periodicity. Spectral analysis and time series analysis can, respectively, be employed to characterize the periodical pattern and the stochastic pattern. Both Burg entropy spectral analysis (BESA) and configurational entropy spectral analysis (CESA) combine spectral analysis and time series analysis. This study compared the pred...

Increases in extreme precipitation events of floods and droughts are expected to occur worldwide. The increase in extreme events will result in changes in streamflow that are expected to affect water availability for human consumption and aquatic ecosystem function. We present an analysis that may greatly improve current streamflow models by quantifying the impact of the interaction between for...

Streamflow forecasting is very important for water resources management and flood defence. In this paper two forecasting methods are compared: ARIMA versus a multilayer perceptron neural network. This comparison is done by forecasting a streamflow of a Mexican river. Surprising results showed that in a monthly basis, ARIMA has lower prediction errors than this Neural Network. Key-Words: Auto re...