Streamflow trends and climate linkages in the source region of the Yellow River,China

Much of the discussion on hydrological trends and variability in the source region of the Yellow River centres on the mean values of the mainstream flows. Changes in hydrological extremes in the mainstream as well as in the tributary flows are largely unexplored. Although decreasing water availability has been noted, the nature of those changes is less explored. This article investigates trends and variability in the hydrological regimes (both mean values and extreme events) and their links with the local climate in the source region of the Yellow River over the last 50 years (1959–2008). This large catchment is relatively undisturbed by anthropogenic influences such as abstraction and impoundments, enabling the characterization of widely natural, climate‐driven trends. A total of 27 hydrological variables were used as indicators for the analysis. Streamflow records from six major headwater catchments and climatic data from seven stations were studied. The trend results vary considerably from one river basin to another, and become more accentuated with longer time period. Overall, the source region of the Yellow River is characterized by an overall tendency towards decreasing water availability. Noteworthy are strong decreasing trends in the winter (dry season) monthly flows of January to March and September as well as in annual mean flow, annual 1‐, 3‐, 7‐, 30‐ and 90‐day maxima and minima flows for Maqu and Tangnag catchments over the period 1959–2008. The hydrological variables studied are closely related to precipitation in the wet season (June, July, August and September), indicating that the widespread decrease in wet season precipitation is expected to be associated with significant decrease in streamflow. To conclude, decreasing precipitation, particularly in the wet season, along with increasing temperature can be associated with pronounced decrease in water resources, posing a significant challenge to downstream water uses. Copyright © 2011 John Wiley & Sons, Ltd.     

Encoding daily rainfall records via adaptations of the fractal multifractal method

A deterministic geometric approach, the fractal–multifractal (FM) method, already found useful in modeling storm events, is adapted here in order to encode, for the first time, highly intermittent daily rainfall records gathered over a water year and containing many days of zero rain. Through application to data sets gathered at Laikakota in Bolivia and Tinkham in Washington, USA, it is demonstrated that the modified FM approach can represent erratic rainfall records faithfully, while using only a few FM parameters. It is shown that the modified FM approach, by capturing the rain accumulated over the season, ends up preserving other statistical attributes as well as the overall “texture” of the records, leading to FM sets that are indistinguishable from observed sets and certainly within the limits of accuracy of measured rainfall. This fact is further corroborated comparing 20 consecutive years at Laikakota and a modified FM representation, via common statistical qualifiers, such as histogram, entropy function, and inter-arrival times.