Assessing plot-scale impacts of land use on overland flow generation in Central Panama

Land use in Panama has changed dramatically with ongoing deforestation and conversion to cropland and cattle pastures, potentially altering the soil properties that drive the hydrological processes of infiltration and overland flow. We compared plot-scale overland flow generation between hillslopes in forested and actively cattle-grazed watersheds in Central Panama. Soil physical and hydraulic properties, soil moisture and overland flow data were measured along hillslopes of each land-use type. Soil characteristics and rainfall data were input into a simple, 1-D representative model, HYDRUS-1D, to simulate overland flow that we used to make inferences about overland flow response at forest and pasture sites. Runoff ratios (overland flow/rainfall) were generally higher at the pasture site, although no overall trends were observed between rainfall characteristics and runoff ratios across the two land uses at the plot scale. Saturated hydraulic conductivity (K_s) and bulk density were different between the forest and pasture sites (p < 10⁻⁴). Simulating overland flow in HYDRUS-1D produced more outputs similar to the overland flow recorded at the pasture site than the forest site. Results from our study indicate that, at the plot scale, Hortonian overland flow is the main driver for overland flow generation at the pasture site during storms with high-rainfall totals. We infer that the combination of a leaf litter layer and the activation of shallow preferential flow paths resulting in shallow saturation-excess overland flow are likely the main drivers for plot scale overland flow generation at the forest site. Results from this study contribute to the broader understanding of the delivery of freshwater to streams, which will become increasingly important in the tropics considering freshwater resource scarcity and changing storm intensities.     

Catchment scale controls the temporal connection of transpiration and diel fluctuations in streamflow

Diel fluctuations can comprise a significant portion of summer discharge in small to medium catchments. The source of these signals and the manner in which they are propagated to stream gauging sites is poorly understood. In this work, we analysed stream discharge from 15 subcatchments in Dry Creek, Idaho, Reynolds Creek, Idaho, and HJ Andrews, Oregon. We identified diel signals in summer low flow, determined the lag between diel signals and evapotranspiration demand and identified seasonal trends in the evolution of the lag at each site. The lag between vegetation water use and streamflow response increases throughout summer at each subcatchment, with the rate of increase as a function of catchment stream length and other catchment characteristics such as geology, vegetation and stream geomorphology. These findings support the hypothesis that variations in stream velocity are the key control on the seasonal evolution of the observed lags. Copyright © 2012 John Wiley & Sons, Ltd.     

Statistical normalization of spherically invariant non-Gaussian clutter

Conventional detection in active sonar involves comparing the normalized matched filter output power to a fixed preset threshold. Threshold crossings from contacts of interest are labeled as detections and those from undesired clutter echoes as false alarms. To maintain a constant false-alarm rate (CFAR) in the presence of strong transient clutter, the system can either increase the threshold or apply some function that suppresses this background down to an acceptable level. The latter approach leads to a more consistent background on the display, which enables operator-assisted detection. Background clutter suppression should not come at the expense of contact detection; to maximize the probability of detection (PD) for a given probability of false alarm (PFA), the likelihood ratio test (LRT) is used. However, the LRT does not address display issues, since the threshold that achieves a desired PFA varies with the input distribution. Ideally, the LRT output is monotonically transformed using a "statistical normalizer" (SN) that returns a consistent CFAR background without degrading the optimized PD. Within the radar community, clutter suppression is proposed using a LRT tuned to a K-distributed spherically invariant random vector (SIRV) model. However, this model does not lend itself to SN, as a closed-form expression for the LRT output density does not exist. In contrast, the proposed SIRV clutter model, with Pareto distributed power, leads to a closed-form density from which the SN function is readily derived. This combined Pareto-LRT/SN detector nearly matches the optimized PD performance of the K-distributed LRT and maintains a consistent CFAR background for display purposes.     

Sub-weekly to interannual variability of a high-energy shoreline

Sixty-one Global Positioning System (GPS), sub-aerial beach surveys were completed at 7 km long Ocean Beach, San Francisco, CA (USA), between April 2004 and March 2009. The five-year time series contains over 1 million beach elevation measurements and documents detailed changes in beach morphology over a variety of spatial, temporal, and physical forcing scales. Results show that seasonal processes dominate at Ocean Beach, with the seasonal increase and decrease in wave height being the primary driver of shoreline change. Storm events, while capable of causing large short-term changes in the shoreline, did not singularly account for a large percentage of the overall observed change. Empirical orthogonal function (EOF) analysis shows that the first two modes account for approximately three-quarters of the variance in the data set and are represented by the seasonal onshore/offshore movement of sediment (60%) and the multi-year trend of shoreline rotation (14%). The longer-term trend of shoreline rotation appears to be related to larger-scale bathymetric change. An EOF-based decomposition technique is developed that is capable of estimating the shoreline position to within one standard deviation of the range of shoreline positions observed at most locations along the beach. The foundation of the model is the observed relationship between the temporal amplitudes of the first EOF mode and seasonally-averaged offshore wave height as well as the linear trend of shoreline rotation. This technique, while not truly predictive because of the requirement of real-time wave data, is useful because it can predict shoreline position to within reasonable confidence given the absence of field data once the model is developed at a particular site.     

The marine chemistry of dimethylsulfide

Dimethylsulfide (DMS) was determined in surface seawater and vertical hydrographic profiles in the Atlantic Ocean during two cruises from Hamburg to Montevideo (Uruguay), and from Miami (Florida) into the Sargasso Sea. These data cover most of the ecological zones of the Atlantic. DMS concentrations are related to the levels of marine primary production, in agreement with its release by marine phytoplankton in laboratory cultures. The vertical distribution of DMS in the euphotic zone follows that of primary production, with a maximum at or near the ocean surface and a decrease with depth. Below the level of 1% light penetration, DMS levels decline gradually, but DMS remains detectable even in the bottom waters. The mean DMS concentration in surface water is 84.4, and in deep water 3.2 ng S (DMS) 1^?1. No steep gradients of DMS exist near the sea surface on scales of centimeters to tenths of millimeters. At a drift station, DMS was observed to be diurnally variable, with an increase in concentration in the euphotic zone throughout the day. DMS is actively turned over in the surface ocean with a residence time of a few days, but it is apparently very stable in the deep sea. DMS is the major volatile sulfur compound in the ocean, and its transfer across the air-sea interface contributes significantly to the atmospheric sulfur budget.