Spatial–temporal variability and hydrologic connectivity of runoff generation areas in a North Alabama pasture—implications for phosphorus transport

This study delineated spatially and temporally variable runoff generation areas in the Sand Mountain region pasture of North Alabama under natural rainfall conditions, and demonstrated that hydrologic connectivity is important for generating hillslope response when infiltration‐excess (IE) runoff mechanism dominates. Data from six rainfall events (13·7–32·3 mm) on an intensively instrumented pasture hillslope (0·12 ha) were analysed. Analysis of data from surface runoff sensors, tipping bucket rain gauge and HS‐flume demonstrated spatial and temporal variability in runoff generation areas. Results showed that the maximum runoff generation area, which contributed to runoff at the outlet of the hillslope, varied between 67 and 100%. Furthermore, because IE was the main runoff generation mechanism on the hillslope, the data showed that as the rainfall intensity changed during a rainfall event, the runoff generation areas expanded or contracted. During rainfall events with high‐intensity short‐ to medium‐duration, 4–8% of total rainfall was converted to runoff at the outlet. Rainfall events with medium‐ to low‐intensity, medium‐duration were found less likely to generate runoff at the outlet. In situ soil hydraulic conductivity (k) was measured across the hillslope, which confirmed its effect on hydrologic connectivity of runoff generation areas. Combined surface runoff sensor and k‐interpolated data clearly showed that during a rainfall event, lower k areas generate runoff first, and then, depending on rainfall intensity, runoff at the outlet is generated by hydrologically connected areas. It was concluded that in IE‐runoff‐dominated areas, rainfall intensity and k can explain hydrologic response. The study demonstrated that only connected areas of low k values generate surface runoff during high‐intensity rainfall events. Identification of these areas would serve as an important foundation for controlling nonpoint source pollutant transport, especially phosphorus. The best management practices can be developed and implemented to reduce transport of phosphorus from these hydrologically connected areas. Copyright © 2009 John Wiley & Sons, Ltd.     

Accounting for sparsely observed rainfall space—time variability in a rainfall—runoff model of a semiarid Tunisian basin/Prise en compte d'observations peu denses de la variabilité spatiotemporelle de la pluie dans une modélisation pluie—débit d'un bassin semi-aride Tunisien

Abstract

The management of water excesses and deficits is a major task in semiarid Mediterranean regions, where the variability of rainfall inputs is high at different time and space scales. Thus intense hydrometeorological events, which generate both potential resource and hazards, are of major interest. A simple method is proposed, with the example of the Skhira basin (192 km²) in central Tunisia, to account for the event space–time variability of rainfall in a rainfall–runoff model, in order to check its influence on the shape, magnitude and timing of resulting hydrographs. The transfer function used is a geomorphology-based unit hydrograph with an explicit territorial significance. Simulations made for highly variable events show the relevance of this method, seen as the first step of a downward approach, and its robustness with respect to the quality and the density of rainfall data.     

Daily variability of river concentrations and fluxes: indicators based on the segmentation of the rating curve

The variability of water chemistry on a daily scale is rarely addressed due to the lack of records. Appropriate tools, such as typologies and dimensionless indicators, which permit comparisons between stations and between river materials, are missing. Such tools are developed here for daily concentrations (C), specific fluxes or yields (Y) and specific river flow (q). The data set includes 128 long‐term daily records, for suspended particulate matter (SPM), total dissolved solids (TDS), dissolved and total nutrients, totalling 1236 years of records. These 86 river basins (10³–10⁶ km²) cover a wide range of environmental conditions in semi‐arid and temperate regions. The segmentation—truncation of C–q rating curves into two parts at median flows (q₅₀) generates two exponents (b_50inf and b_50sup) that are different for 66% of the analysed rating curves. After segmentation, the analysis of records results in the definition of nine major C–q types combining concentrating, diluting or stable patterns, showing inflexions, chevron and U shapes. SPM and TDS are preferentially distributed among a few types, while dissolved and total nutrients are more widely distributed. Four dimensionless indicators of daily variability combine median (C₅₀, Y₅₀), extreme (C₉₉, Y₉₉) and flow‐weighted (C*, Y*) concentrations and yields (e.g. C₉₉/C₅₀, Y*/Y₅₀). They vary over two to four orders of magnitude in the analysed records, discriminating stations and river material. A second set of four indicators of relative variability [e.g. (Y*/Y₅₀)/(q*/q₅₀)], takes into account the daily flow variability, as expressed by q*/q₅₀ and q₉₉/q₅₀, which also vary over multiple orders of magnitude. The truncated exponent b_50sup is used to describe fluxes at higher flows accounting for 75% (TDS) to 97% (SPM) of interannual fluxes. It ranges from ? 0·61 to + 1·86 in the database. It can be regarded as the key amplificator (positive b_50sup) or reductor (negative b_50sup) of concentrations or yields variability. C₅₀, Y₅₀, b_50sup can also be estimated in discrete surveys, which provides a new perspective for quantifying and mapping water quality variability at daily scale. Copyright © 2011 John Wiley & Sons, Ltd.     

A 200-year precipitation index for the central English Lake District / Un indice de précipitation de 200 ans pour la Région des Lacs en Angleterre

Abstract

Abstract The geographical context and hydroclimatology of the English Lake District means that the region is an important monitor of changes to nationally significant environmental assets. Using monthly rainfall series for sites in and around the central Lake District, a continuous ~200-year precipitation index was constructed for a representative station close to Grasmere. The bridged series shows a significant decline in summer rainfall since the 1960s, offset by increases in winter and spring that are strongly linked to North Atlantic forcing. Over longer time periods, the index exhibits several notable dry (1850s, 1880s, 1890s, 1930s, 1970s) and wet (1820s, 1870s, 1920s, 1940s, 1990s) decades. These patterns are strongly reflected by reservoir inflow series and by indicators of the biological status of the region’s freshwater lakes. It is argued that long-term climate indices will become increasingly important as managers seek to evaluate recent and project environmental changes within the context of long-term natural variability.     

Generation of correlated properties in heterogeneous porous media

The spatial distribution of rock properties in porous media, such as permeability and porosity, often is strongly variable. Therefore, these properties usefully may be considered as a random field. However, this variability is correlated frequently on length scales comparable to geological lengths (for example, scales of sand bodies or facies). To solve various engineering problems (for example, in the oil recovery process) numerical models of a porous medium often are used. A need exists then to understand correlated random fields and to generate them over discretized numerical grids. The paper describes the general mathematical methods required to do this, with one particular method (the nearest neighbor model) described in detail. How parameters of the mathematical model may be related to rock property statistics for the nearest neighbor model is shown. The method is described in detail in one, two, and three dimensions. Examples are given of how model parameters may be determined from real data.     

Modeling long term lake variations by physically based stochastic dynamic models

Several physically based stochastic dynamic models (SDM) are described including year-to-year variations of water volume in terminal and non-terminal lakes, streamflow of lake-fed rivers, and salinity of an inland sea (the Sea of Azov). All of these models are based upon the SDM of water volume of terminal lakes developed by Kritzky and Menkel in 1946 in co-operation with Kolomogorov. Explicit formulae are derived for second order statistical moments of the output processes, including variance, correlation function, spectra, etc., under the assumption that the forcing functions from stationary random sequences. The least-squares prediction problem is solved for both stationary and non-stationary cases. Some of the processes are shown to possess high statistical predictability. Actual predictions are compared with independent observations. Problems for further study are stated.     

Interannual variability of monsoons in Malaysia and its relationship with ENSO

Interannual variations of the monsoons have been studied utilising homogeneous rainfall records of 41 years (1951–1991) from Malaysia and upper air data of stations in Asia, Australia and Western Pacific. Sources of upper air data are U.S. Department of Commerce and Kuala Lumpur Northern Winter Monsoon Activity Centre. Extreme wet and dry years have been identified and the influence of ENSO on Malaysian annual rainfall has been discussed. Influence of ENSO on the performance of northern summer and winter monsoons has also been studied from Malaysian rainfall data. Further, regional circulation patterns associated with El Nino and La Nina years have also been identified. No linear trend has been found in the annual rainfall of 16 stations in Malaysia. Most El Nino years are associated with below median and La Nina years with above median rainfall at most stations in Malaysia. ENSO has greater influence over East Malaysia than peninsular Malaysia. Interannual variability of rainfall with reference to ENSO conditions has been discussed in details. Also, circulation features have been identified to foresee El Nino/La Nina events.     

Applications of satellite data in the study of monsoon variability

This paper discusses the use of satellite data for studying climate change, with particular emphasis on the inter-annual variability of the Indian southwest monsoon. Precipitation estimates made from INSAT-1B radiance data are shown to bring out the variations that occurred in the monsoon rainfall of 1987 and 1988. Outgoing Longwave Radiation derived from INSAT-1B shows good correspondence with precipitation patterns.     

Issues of Spatial and Temporal Variability in Climate Impact Studies

The accuracy of impact estimates relating climate change to regional-scale agricultural production is constrained by the temporal and spatial resolution of climate change projections. Several techniques have been used to compensate for these limitations in order to provide reasonable estimates of the impact of climate change on crop yield. One approach assumes that variability over time can substitute for spatial variability, thereby reducing the need to estimate the impacts at a spatially dense network of stations—an assumption that has not been generally tested. This study evaluates this assumption using methods similar to those employed in the climate impact literature. The findings suggest that current practices are generally defensible if the goal is to provide a range of possible crop responses to climate change. However, the results also show that the assumption is highly sensitive to specific interactions at the soil-plant-atmosphere interface and, consequently, does not hold under certain circumstances.