Abstract.The interaction between vegetation and hydrologic processes is particularly tight in water-limited environments where a positive-feedback links soil moisture and vegetation. The vegetation of these systems is commonly patterned, that is, arranged in a two phase mosaic composed of patches with high biomass cover interspersed within a lowcover or bare soil component. These patterns are strongly linked to the redistribution of runoff and resources from source areas (bare patches) to sink areas (vegetation patches) and play an important role in controlling erosion.In this paper, the dynamics of these systems is investigated using a new modeling framework that couples landform and vegetation evolution, explicitly accounting for the dynamics of runon-runoff areas. The objective of this study is to analyze water-limited systems on hillslopes with mild slopes, in which overland flow occurs predominantly in only one direction and vegetation displays a banded pattern. Our simulations reproduce bands that can be either stationary or upstream migrating depending on the magnitude of the runoffinduced seed dispersal. We also found that stationary banded systems redistribute sediment so that a stepped microtopography is developed. The modelling results are the first to incorporate the effects of runoff redistribution and variable infiltration rates on the development of both the vegetation patterns and microtopography. The microtopography for stationary bands is characterized by bare soil on the lower gradient areas and vegetation on steeper gradients areas. For the case of migrating vegetation bands the model generates hillslope profiles with planar topography. The success at generating not only the observed patterns of vegetation, but also patterns of runoff and sediment redistribution suggests that the hydrologic and erosion mechanisms represented in the Correspondence to: P. M. Saco (patricia.saco@newcastle.edu.au) model are correctly capturing some of the key processes driving these ecosystems.

[1] We investigate the coupling of river network structure and hydraulic geometry thereby relaxing the assumption of spatially invariant celerities and hydrodynamic dispersion coefficients. The presence of spatially varying celerities induces a dispersion effect, referred to as kinematic dispersion, on the network travel time distribution. Its contribution to the total dispersion is comparable to that due to the heterogeneity of path lengths, that is, geomorphologic dispersion, and significantly larger than the hydrodynamic dispersion. If this contribution is ignored, the hydrograph shows a higher peak flow, a shorter time to peak, and shorter duration.INDEX TERMS: 1824 Hydrology: Geomorphology (1625); 1860 Hydrology: Runoff and streamflow; 1848 Hydrology: Networks; KEYWORDS: hydrograph, geomorphologic instantaneous unit hydrograph, instantaneous response function, geomorphologic dispersion Citation: Saco, P. M., and P. Kumar, Kinematic dispersion in stream networks, 1, Coupling hydraulic and network geometry,

Dryland ecosystems are often characterized by patchy vegetation and exposed soil. This structure enhances transport of soil resources and seeds through the landscape (primarily by wind and water, but also by animals), thus emphasizing the importance of connectivity – given its relation to the flow of these materials – as a component of dryland ecosystem function. We argue that, as with the fertile‐islands conceptual model before it, the concept of connectivity explains many phenomena observed in drylands. Further, it serves as an organizing principle to understand dryland structure and function at scales from individual plants to entire landscapes. The concept of connectivity also helps to organize thinking about interactions among processes occurring at different scales, such as when processes at one scale are overridden by processes at another. In these cases, we suggest that state change occurs when fine‐scale processes fail to adjust to new external conditions through resource use or redistribution at the finer scale. The connectivity framework has practical implications for land management, especially with respect to decision making concerning the scale and location of agricultural production or habitat restoration in the world's drylands.

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The future of coastal wetlands and their ecological value depend on their capacity to adapt to the interacting effects of human impacts and sea-level rise. Even though extensive wetland loss due to submergence is a possible scenario, its magnitude is highly uncertain due to limited understanding of hydrodynamic and bio-geomorphic interactions over time. In particular, the effect of man-made drainage modifications on hydrodynamic attenuation and consequent wetland evolution is poorly understood. Predictions are further complicated by the presence of a number of vegetation types that change over time and also contribute to flow attenuation. Here, we show that flow attenuation affects wetland vegetation by modifying its wetting-drying regime and inundation depth, increasing its vulnerability to sea-level rise. Our simulations for an Australian subtropical wetland predict much faster wetland loss than commonly used models that do not consider flow attenuation.

[1] When the flow parameters, such as celerity and hydrodynamic dispersion coefficient, are allowed to vary spatially within a basin, three mechanisms, namely, geomorphologic, kinematic, and hydrodynamic dispersion, contribute to the variance of the instantaneous response function. The relative contributions of the three dispersion mechanisms as a function of scale, or Strahler order of the basin, are studied. This analysis is performed for two study basins, the Vermilion and the Mackinaw river basins, in central Illinois. Log linear trends for all the dispersion coefficients as a function of scale are observed. These trends can be cast in the form of Horton law type of relations. The asymptotic behavior of the dispersion coefficients of basins with self-similar network structure is consistent with the observations.

We deal here with the issue of determinism versus randomness in time series. One wishes to identify their relative weights in a given time series. Two different tools have been advanced in the literature to such effect, namely, i) the "causal" entropycomplexity plane [Rosso et al. Phys. Rev. Lett. 99 (2007) 154102] and ii) the estimation of the decay rate of missing ordinal patterns [Amigó et al. Europhys. Lett. 79 (2007) 50001, and Carpi et al. Physica A 389 (2010) 2020-2029. In this work we extend the use of these techniques to address the analysis of deterministic finite time series contaminated with additive noises of different degree of correlation. The chaotic series studied here was via the logistic map (r = 4) to which we added correlated noise (colored noise with f −k Power Spectrum, 0 ≤ k ≤ 2) of varying amplitudes. In such a fashion important insights pertaining to the deterministic component of the original time series can be gained. We find that in the entropycomplexity plane this goal can be achieved without additional computations.