نتایج جستجو برای: daily streamflow

تعداد نتایج: 200787  

2010
A. J. Teuling I. Lehner J. W. Kirchner S. I. Seneviratne

[1] Heterogeneity in small‐scale subsurface flow processes does not necessarily lead to complex system behavior at larger scales. Here we use the simple dynamical systems approach recently proposed by Kirchner (WRR, 2009) to analyze, characterize, and simulate streamflow dynamics in the Swiss Rietholzbach catchment. The Rietholzbach data set used here provides 32 years of continuous and high‐qu...

2011
Hoori Ajami Peter A. Troch Thomas Maddock Thomas Meixner Chris Eastoe

[1] Despite the importance of mountainous catchments for providing freshwater resources, especially in semi-arid regions, little is known about key hydrological processes such as mountain block recharge (MBR). Here we implement a data-based method informed by isotopic data to quantify MBR rates using recession flow analysis. We applied our hybrid method in a semi-arid sky island catchment in so...

A Malekian, M Kazemzadeh

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 ...

2007
Xianglian Li Xiusheng Yang Wei Gao

Effective management of water resources in arid and semi-arid areas demands studies that cross over the disciplinaries of natural and social sciences. An integrated Hydrological, Ecological and Economical (HEE) modeling system at regional scale has been developed to assess water resources use and ecosystem production in arid and semi-arid areas. As a physically-based distributed modeling system...

Journal: :Physica A: Statistical Mechanics and its Applications 2019

Journal: :Water 2023

Rainfall–runoff modeling has been of great importance for flood control and water resource management. However, the selection hydrological models is challenging to obtain superior simulation performance especially with rapid development machine learning techniques. Three under different categories methods, including support vector regression (SVR), extreme gradient boosting (XGBoost), long-shor...

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