How does anisotropy in bedrock river granitic outcrops influence pothole genesis and development?

Pothole formation and development may be influenced by joint sets and other heterogeneities within bedrock, as well as by hydraulics. Previous research indicates that most potholes found in rivers of the mountainous Spanish Central System exhibit preferred orientations associated with dominant joints and correlate more strongly with variations in substrate resistance than with hydraulics. Weathering and erosion weaken rock surfaces, which leads to decreased mechanical resistance. We start from the hypothesis that different mechanisms of pothole formation may create around the pothole a distinctive signature in terms of ultrasound pulse velocity and surface hardness. We develop a conceptual model and test it using potholes for which we know the mechanism of formation, demonstrating that the spatial and statistical distributions of dynamical mechanical properties and surface hardness of a pothole may provide insight into its genesis. Copyright © 2016 John Wiley & Sons, Ltd.     

Systematic increase in model complexity helps to identify dominant streamflow mechanisms in two small forested basins

This study shows how the use of increasing model complexity allows us to hypothesize about dominant streamflow mechanisms in two small Brazilian forested basins. Nine different structures from SUPERFLEX, an objective framework to systematically increase hydrological model complexity, were tested and we extended the flexible modelling methodology to error models as well. We show that applying a rigorous methodology in a model evaluation framework, with residual analysis and control of model complexity, is essential for testing a model as a hypothesis for dominant hydrological controls. Our results indicate that the model architecture was more important than the increase in the number of model parameters. Better performing models were those with a parallel structure, which confirms our a priori belief about the dominant runoff mechanisms of the studied catchments, characterized by a rapid response to rainfall, but also a constant river discharge fed by water storage on the thick soil layer.     

Precipitation as a proxy for climate variables: application for hydrological modelling

It has been proposed that linear regression curves can be used to estimate monthly climate variables from observed precipitation. This approach was explored by applying the MGB hydrological model to the Paraná Basin (Brazil). Linear regressions were obtained for 54 climate gauges, and most of them showed at least six months of significant correlation between monthly climate variables (sunlight hours and relative humidity) and precipitation. The regression equations were applied to 5201 raingauges to estimate monthly climate variables and evapotranspiration, and the results were compared with a scenario using long-term climate averages only. The main differences occurred in wetter periods, where negative correlations between monthly precipitation and evapotranspiration were obtained when using precipitation as a proxy. Long-term changes in the hydrological regime were assessed and showed that the effect of precipitation on relative humidity and sunlight hours seems to have a minor effect on the alterations observed in river discharge in the Paraná Basin.     

Forecasting annual precipitation to improve the operation of dams in the Comahue region,Argentina

ABSTRACT

This paper attempts to design statistical models to forecast annual precipitation in the Neuquen and Limay river basins in the Comahue region of Argentina. These forecasts are especially useful as they are used to better organize the operation of hydro-electric dams, the agriculture in irrigated valleys and the safety of the population. In this work, multiple linear regression statistical models are built to forecast mean annual rainfall over the two river basins. Since the maximum precipitation occurs in the winter (June–August), forecasting models have been developed for the beginning of March and for the beginning of June, just before the rainy season starts. The results show that the sea-surface temperatures of the Indian and Pacific oceans are good predictors for March models and explain 42.8% of the precipitation index variance. The efficiency of the models increases in June, adding more predictors related to the autumn circulation.     

Using InSAR to identify hydrological connectivity and barriers in a highly fragmented wetland

Hydrological connectivity is a critical determinant of wetland functions and health, especially in wetlands that have been heavily fragmented and regulated by human activities. However, investigating hydrological connectivity in these wetlands is challenging due to the costs of high-resolution and large-scale monitoring required in order to identify hydrological barriers within the wetlands. To overcome this challenge, we here propose an interferometric synthetic aperture radar (InSAR)-based methodology to map hydrologic connectivity and identify hydrological barriers in fragmented wetlands. This methodology was applied along 70 transects across the Baiyangdian, the largest freshwater wetland in northern China, using Sentinel 1A and 1B data, covering the period 2016–2019. We generated 58 interferograms providing information on relative water level changes across the transects that showed the high coherence needed for the assessment of hydrological connectivity. We mapped the permanent and conditional (temporary) barriers affecting connectivity. In total, 11% of all transects are permanently disconnected by hydrological barriers across all interferograms and 58% of the transects are conditionally disconnected. Areas covered by reed grasslands show the most undisturbed hydrological connectivity while some of these barriers are the result of ditches and channels within the wetland and low water levels during different periods of the year. This study highlights the potential of the application of Wetland InSAR to determine hydrological connectivity and location of hydrological barriers in highly fragmented wetlands, and facilitates the study of hydrological processes from large spatial scales and long-time scales using remote sensing technique.     

Floodplain construction by recent,rapid vertical accretion: Waipaoa River,New Zealand

The rate of vertical accretion (typically 14–18 mm h⁻¹) during eight floods in the Waipaoa River basin, with recurrence intervals of 5 to 60 years, was determined by relating the floodplain stratigraphy at McPhail's bend to the 1948–1995 flood history. Overbank deposits remaining after a flood that occurred in March 1996 suggest a rate of vertical accretion of 15 mm h⁻¹. By contrast, because the flow velocity across the floodplain was too high to permit deposition from suspension, during the record flood of March 1988 the rate of vertical accretion was only 6 mm h⁻¹. The sequence of deposition is highly discontinuous, and the rapid vertical accretion is a response to a late 19th to early 20th century phase of deforestation in the headwaters that probably initiated a far greater change in suspended sediment yield than in discharge. Cross-section surveys conducted since 1948 indicate that the high suspended sediment load of the Waipaoa River also promoted in-channel deposition, which effected a progressive reduction in bankfull channel width although, due to the overbank deposition, channel capacity remained constant. © 1998 John Wiley & Sons, Ltd.     

Tidal and annual variability of the population structure of Eurytemora affinis in the middle part of the Seine Estuary during 2005

Annual variability in abundance and population structure of the copepod Eurytemora affinis was studied in the maximum turbidity zone of the Seine Estuary in 2005. An Eulerian sampling strategy was applied monthly from March to July and from September to December. Chlorophyll a and suspended particulate matter (SPM) concentration, copepod abundance and stage distribution, and phytoplankton abundance were measured in sub-surface and near-bottom water during the ebb phase. Total E. affinis abundance was at a maximum in March and April (>200 × 10³ ind. m⁻³), and decreased from May to September (<25 × 10³ ind. m⁻³). This decrease corresponds to annual increases in temperature, salinity, chlorophyll a concentration and phytoplankton abundance, which was dominated by large diatoms, and decreases in SPM and river discharge. The phenology observed in 2005 was almost two months earlier compared to previous studies in the 1990s, when E. affinis reached maximum abundance in May and June. The low proportion of nauplii (<50%) in the population and high abundance of ovigerous females suggests that low recruitment is probably related to anomalously low temperatures in late winter (<5 °C). Whatever the horizontal position of the population in the estuary, adult and late copepodid stages are distributed in higher salinity than naupliar stages. Overall E. affinis population abundance was driven by parameters that characterize water masses at the tidal scale and by river discharge and chlorophyll a at the annual scale. By integrating the tidal effect, the high-frequency sampling protocol used appears to be optimal for investigating annual variability of planktonic communities in megatidal estuaries.     

Geostatistical Simulation of Acoustic Log Data for Seismic Depth Conversion

Seismic reflection methods measure the time a seismic wave takes to travel through the ground, from the user defined source to a series of signal monitoring sensors known as geophones. The measured times need to be depth converted to allow for integration with other geological data. In order to convert from time to depth, an estimate of the rock volume velocity field must be made. The velocity field estimate can be made by assignment of velocity estimates to a geological model independent of the seismic processing. This article presents the results of using the acoustic geophysical log data extrapolated via sequential Gaussian simulation to derive the velocity field. The uncertainties associated with the velocity estimates were significant and provided the means to assess confidence limits for the actual depth determination. The technique is assessed by application to a major coal deposit, approximately 2.1 m thick and 210 m deep. Considering only the uncertainty associated with estimating the velocity field, half of the confidence interval values showed approximately 1 m of uncertainty in depth. The application of sequential Gaussian simulation to model the 3D distribution of acoustic velocity can be extended to other geophysical log parameters or derived estimates.