[1] Geomorphologists have long recognized that the geometry of channel network planforms can vary significantly between regions depending on the local lithologic and tectonic conditions. This tendency has led to the classification of channel networks using terms such as dendritic, parallel, pinnate, rectangular, and trellis. Unfortunately, available classification methods are scale dependent and have little connection to any underlying quantitative theory of drainage network geometry or evolution. In this study, a new method is developed to classify drainage networks on the basis of their deviations from self-similarity. The planform geometry of dendritic networks is known to be approximately self-similar. It is our hypothesis that parallel, pinnate, rectangular, and trellis networks correspond to distinct deviations from this self-similarity. To identify such deviations, three measures of channel networks are applied to 10 networks from each classification. These measures are the incremental accumulation of drainage area along channels, the irregularity of channel courses, and the angles formed by merging channels. The results confirm and characterize the self-similarity of dendritic networks. Parallel and pinnate networks are found to exhibit anisotropic scaling. Rectangular and trellis networks are approximately self-similar although deviations from self-similarity are observed. Rectangular networks have more sinuous channels than dendritic networks across all scales, and trellis networks have a slower rate of area accumulation than dendritic networks across all scales. Such observations are used to build and test simple classification trees, which are found to perform well in classifying networks.Citation: Mejía, A. I., and J. D. Niemann (2008), Identification and characterization of dendritic, parallel, pinnate, rectangular, and trellis networks based on deviations from planform self-similarity,

In 2013, the International Association of Hydrological Sciences (IAHS) launched the hydrological decade 2013-2022 with the theme "Panta Rhei: Change in Hydrology and Society". The decade recognizes the urgency of hydrological research to understand and predict the interactions of society and water, to support sustainable water resource use under changing climatic and environmental conditions. This paper reports on the first Panta Rhei biennium 2013-2015, providing a comprehensive resource that describes the scope and direction of Panta Rhei. We bring together the knowledge of all the Panta Rhei working groups, to summarize the most pressing research questions and how the hydrological community is progressing towards those goals. We draw out interconnections between different strands of research, and reflect on the need to take a global view on hydrology in the current era of human impacts and environmental change. Finally, we look back to the six driving science questions identified at the outset of Panta Rhei, to quantify progress towards those aims.

The quality of ensemble streamflow forecasts in the U.S. mid-Atlantic region (MAR) is investigated for short- to medium-range forecast lead times (6–168 h). To this end, a regional hydrological ensemble prediction system (RHEPS) is assembled and implemented. The RHEPS in this case comprises the ensemble meteorological forcing, a distributed hydrological model, and a statistical postprocessor. As the meteorological forcing, precipitation, and near-surface temperature outputs from the National Oceanic and Atmospheric Administration (NOAA)/National Centers for Environmental Prediction (NCEP) 11-member Global Ensemble Forecast System Reforecast, version 2 (GEFSRv2), are used. The Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) is used as the distributed hydrological model, and a statistical autoregressive model with an exogenous variable is used as the postprocessor. To verify streamflow forecasts from the RHEPS, eight river basins in the MAR are selected, ranging in drainage area from ~262 to 29 965 km2 and covering some of the major rivers in the MAR. The verification results for the RHEPS show that, at the initial lead times (1–3 days), the hydrological uncertainties have more impact on forecast skill than the meteorological ones. The former become less pronounced, and the meteorological uncertainties dominate, across longer lead times (>3 days). Nonetheless, the ensemble streamflow forecasts remain skillful for lead times of up to 7 days. Additionally, postprocessing increases forecast skills across lead times and spatial scales, particularly for the high-flow conditions. Overall, the proposed RHEPS is able to improve streamflow forecasting in the MAR relative to the deterministic (unperturbed GEFSRv2 member) forecasting case.

Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3.

For the development of sustainable, efficient risk management strategies for the hydrological extremes of droughts and floods, it is essential to understand the temporal changes of impacts, and their respective causes and interactions. In particular, little is known about changes in vulnerability and their influence on drought and flood impacts. We present a fictitious dialogue between two experts, one in droughts and the other in floods, showing that the main obstacles to scientific advancement in this area are both a lack of data and a lack of commonly accepted approaches. The drought and flood experts "discuss" available data and methods and we suggest a complementary approach. This approach consists of collecting a large number of single or multiple paired-event case studies from catchments around the world, undertaking detailed analyses of changes in impacts and drivers, and carrying out a comparative analysis. The advantages of this approach are that it allows detailed context-and location-specific assessments based on the paired-event analyses, and reveals general, transferable conclusions based on the comparative analysis of various case studies. Additionally, it is quite flexible in terms of data and can accommodate differences between floods and droughts.