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Saturated hydraulic conductivity (K-s) is an important soil characteristic affecting soil water storage, runoff generation and erosion processes. In some areas where high-intensity rainfall coincides with low K-s values at shallow soil depths, frequent overland flow entails dense drainage networks. Consequently, linear structures such as flowlines alternate with inter-flowline areas. So far, investigations of the spatial variability of K-s mainly relied on isotropic covariance models which are unsuitable to reveal patterns resulting from linear structures. In the present study, we applied two sampling approaches so as to adequately characterize K-s spatial variability in a tropical forest catchment that features a high density of flowlines: A classical nested sampling survey and a purposive sampling strategy adapted to the presence of flowlines. The nested sampling approach revealed the dominance of small-scale variability, which is in line with previous findings. Our purposive sampling, however, detected a strong spatial gradient: surface K-s increased substantially as a function of distance to flowline; 10 m off flowlines, values were similar to the spatial mean of K-s. This deterministic trend can be included as a fixed effect in a linear mixed modeling framework to obtain realistic spatial fields of K-s. In a next step we used probability maps based on those fields and prevailing rainfall intensities to assess the hydrological relevance of the detected pattern. This approach suggests a particularly good agreement between the probability statements of K-s exceedance and observed overland flow occurrence during wet stages of the rainy season.
Forests seem to represent low-erosion systems, according to most, but not all, studies of suspended-sediment yield. We surmised that this impression reflects an accidental bias in the selection of monitoring sites towards those with prevailing vertical hydrological flowpaths, rather than a tight causal link between vegetation cover and erosion alone. To evaluate this conjecture, we monitored, over a 2-year period, a 3.3 ha old-growth rainforest catchment prone to frequent and widespread overland flow. We sampled stream flow at two and overland flow at three sites in a nested arrangement on a within-event basis, and monitored the spatial and temporal frequency of overland flow. Suspended-sediment concentrations were modeled with Random Forest and Quantile Regression Forest to be able to estimate the annual yields for the 2 years, which amounted to 1 t ha(-1) and 2 t ha(-1) in a year with below-average and with average precipitation, respectively. These estimates place our monitoring site near the high end of reported suspended-sediment yields and lend credence to the notion that low yields reflect primarily the dominance of vertical flowpaths and not necessarily and exclusively the kind of vegetative cover. Undisturbed forest and surface erosion are certainly no contradiction in terms even in the absence of mass movements.
Soils in various places of the Panama Canal Watershed feature a low saturated hydraulic conductivity (K-s) at shallow depth, which promotes overland-flow generation and associated flashy catchment responses. In undisturbed forests of these areas, overland flow is concentrated in flow lines that extend the channel network and provide hydrological connectivity between hillslopes and streams. To understand the dynamics of overland-flow connectivity, as well as the impact of connectivity on catchment response, we studied an undisturbed headwater catchment by monitoring overland-flow occurrence in all flow lines and discharge, suspended sediment, and total phosphorus at the catchment outlet. We find that connectivity is strongly influenced by seasonal variation in antecedent wetness and can develop even under light rainfall conditions. Connectivity increased rapidly as rainfall frequency increased, eventually leading to full connectivity and surficial drainage of entire hillslopes. Connectivity was nonlinearly related to catchment response. However, additional information on factors such as overland-flow volume would be required to constrain relationships between connectivity, stormflow, and the export of suspended sediment and phosphorus. The effort to monitor those factors would be substantial, so we advocate applying the established links between rain event characteristics, drainage network expansion by flow lines, and catchment response for predictive modeling and catchment classification in forests of the Panama Canal Watershed and in similar regions elsewhere.
An effective strategy for combining variance- and distribution-based global sensitivity analysis
(2020)
We present a new strategy for performing global sensitivity analysis capable to estimate main and interaction effects from a generic sampling design. The new strategy is based on a meaningful combination of varianceand distribution-based approaches. The strategy is tested on four analytic functions and on a hydrological model. Results show that the analysis is consistent with the state-of-the-art Saltelli/Jansen formula but to better quantify the interaction effect between the input factors when the output distribution is skewed. Moreover, the estimation of the sensitivity indices is much more robust requiring a smaller number of simulations runs. Specific settings and alternative methods that can be integrated in the new strategy are also discussed. Overall, the strategy is considered as a new simple and effective tool for performing global sensitivity analysis that can be easily integrated in any environmental modelling framework.
Water fluxes in highly impounded regions are heavily dependent on reservoir properties. However, for large and remote areas, this information is often unavailable. In this study, the geometry and volume of small surface reservoirs in the semi-arid region of Brazil were estimated using terrain and shape attributes extracted by remote sensing. Regression models and data classification were used to predict the volumes, at different water stages, of 312 reservoirs for which topographic information is available. The power function used to describe the reservoir shapes tends to overestimate the volumes; therefore, a modified shape equation was proposed. Among the methods tested, four were recommended based on performance and simplicity, for which the mean absolute percentage errors varied from 24 to 39%, in contrast to the 94% error achieved with the traditional method. Despite the challenge of precisely deriving the flooded areas of reservoirs, water management in highly reservoir-dense environments should benefit from volume prediction based on remote sensing.
The paper presents the sediment budget of the Isabena basin, a highly dynamic 445-km(2) catchment located in the Central Pyrenees that is patched by highly erodible areas (i.e., badlands). The budget for the period 2007-2009 is constructed following a methodology that allows the interpolation of intermittent measurements of suspended sediment concentrations and enables a subsequent calculation of sediment loads. Data allow specification of the contribution of each subbasin to the water and sediment yield in the catchment outlet. Mean annual sediment load was 235,000 t y(-1). Specific sediment yield reached 2000 t km(-2) y(-1), a value that indicates very high sedimentary activity, especially in the case of Villacarli and Lascuarre subcatchments, were most badlands are located. The specific sediment yield obtained for the entire Isabena is 527 t km(-2) y(-1), a high value for such a mesoscale basin. Results show that a small part of the area (i.e., 1%) controls most of the catchment's gross sediment contribution. Sediment delivery ratio (ratio between sediment input from primary sources and basin export) has been estimated at around 90%, while in-channel storage represents the 5% of the annual load on average. The high connectivity between sediment sources (i.e., badlands) and transfer paths (i.e., streamcourses) exacerbates the influence of the local sediment production on the catchment's sediment yield, a quite unusual fact for a basin of this scale.
Suspended sediment transport in a highly erodible catchment : the River Isábena (Southern Pyrenees)
(2009)
Understanding and quantifying sediment load is important in catchments draining highly erodible materials that eventually contribute to siltation of downstream reservoirs. Within this context, the suspended sediment transport and its temporal dynamics have been studied in the River Isabena (445 km(2), south-central Pyrenees, Ebro basin) by means of direct sampling and turbidity recording during a 3-year dry period. The average flood-suspended sediment concentration was 8 g l(-1). with maximum instantaneous values above 350 g l(-1). The high scatter between discharge and suspended sediment concentrations (up to five orders of magnitude) has not permitted the use of rating curve methods to estimate the total load. Interpolation techniques yielded a mean annual sediment load of 184,253 t y(-1) for the study period, with a specific yield of 414 t km(-2) y(-1). This value resembles those reported for small torrents in nearby mountainous environments and is the result of the high connectivity between the badland source areas and stream courses, a fact that maximises sediment conveyance through the catchment. Floods dominated the sediment transport and yield. However, sediment transport was more constant through time than that observed in Mediterranean counterparts; this can be attributed to the role of base flows that entrain fine sediment temporarily stored in the channel and force the river to carry high sediment concentrations (i.e., generally in the order of 0.5 g l(-1)), even under minimum flow conditions.
A set of seasonal drought forecast models was assessed and verified for the Jaguaribe River in semiarid northeastern Brazil. Meteorological seasonal forecasts were provided by the operational forecasting system used at FUNCEME (Ceará’s research foundation for meteorology)and by the European Centre for Medium-Range Weather Forecasts (ECMWF). Three downscaling approaches (empirical quantile mapping, extended downscaling and weather pattern classification) were tested and combined with the models in hindcast mode for the period 1981 to 2014. The forecast issue time was January and the forecast period was January to June. Hydrological drought indices were obtained by fitting a multivariate linear regression to observations. In short, it was possible to obtain forecasts for (a) monthly precipitation,(b) meteorological drought indices, and (c) hydrological drought indices. The skill of the forecasting systems was evaluated with regard to root mean square error (RMSE), the Brier skill score (BSS) and the relative operating characteristic skill score (ROCSS). The tested forecasting products showed similar performance in the analyzed metrics. Forecasts of monthly precipitation had little or no skill considering RMSE and mostly no skill with BSS. A similar picture was seen when forecasting meteorological drought indices: low skill regarding RMSE and BSS and significant skill when discriminating hit rate and false alarm rate given by the ROCSS (forecasting drought events of, e.g., SPEI1 showed a ROCSS of around 0.5). Regarding the temporal variation of the forecast skill of the meteorological indices, it was greatest for April, when compared to the remaining months of the rainy season, while the skill of reservoir volume forecasts decreased with lead time. This work showed that a multi-model ensemble can forecast drought events of timescales relevant to water managers in northeastern Brazil with skill. But no or little skill could be found in the forecasts of monthly precipitation or drought indices of lower scales, like SPI1. Both this work and those here revisited showed that major steps forward are needed in forecasting the rainy season in northeastern Brazil.
The Isabena catchment (445 km(2)), Spain, features highly diverse spatial heterogeneity in land use, lithology and rainfall. Consequently, the relative contribution in terms of water and sediment yield varies immensely between its subcatchments, and also temporally. This study presents the synthesis of similar to 2.5 years of monitoring rainfall, discharge and suspended sediment concentration (SSC) in the five main subcatchments of the Isabena and its outlet.
Continuous discharge at the subcatchment outlets, nine tipping bucket rainfall and automatic SSC samplers (complemented by manual samples), were collected from June 2011 until November 2013. The water stage records were converted to discharge using a rating curve derived with Bayesian regression. For reconstructing sediment yields, the data from the intermittent SSC sampling needed to be interpolated. We employed non-parametric multivariate regression (Quantile Regression Forests, QRF) using the discharge and rainfall data plus different aggregation levels of these as ancillary predictors. The subsequent Monte Carlo simulations allowed the determination of monthly sediment yields and their uncertainty.
The Isabena catchment shows high erosion dynamics with great variability in space and time, with stark contrasts even between adjacent subcatchments. The natural conditions make water and sediment monitoring and instrumentation very challenging; the measurement of discharge is particularly prone to considerable uncertainties. The QRF method employed for reconstructing sedigraphs and monthly yields proved well suited for the task.
The results of streamflow trend studies are often characterized by mostly insignificant trends and inexplicable spatial patterns. In our study region, Western Austria, this applies especially for trends of annually averaged runoff. However, analysing the altitudinal aspect, we found that there is a trend gradient from higher-altitude to lower-altitude stations, i.e. a pattern of mostly positive annual trends at higher stations and negative ones at lower stations. At midaltitudes, the trends are mostly insignificant. Here we hypothesize that the streamflow trends are caused by the following two main processes: on the one hand, melting glaciers produce excess runoff at higher-altitude watersheds. On the other hand, rising temperatures potentially alter hydrological conditions in terms of less snowfall, higher infiltration, enhanced evapotranspiration, etc., which in turn results in decreasing streamflow trends at lower-altitude watersheds. However, these patterns are masked at mid-altitudes because the resulting positive and negative trends balance each other. To support these hypotheses, we attempted to attribute the detected trends to specific causes. For this purpose, we analysed trends of filtered daily streamflow data, as the causes for these changes might be restricted to a smaller temporal scale than the annual one. This allowed for the explicit determination of the exact days of year (DOYs) when certain streamflow trends emerge, which were then linked with the corresponding DOYs of the trends and characteristic dates of other observed variables, e.g. the average DOY when temperature crosses the freezing point in spring. Based on these analyses, an empirical statistical model was derived that was able to simulate daily streamflow trends sufficiently well. Analyses of subdaily streamflow changes provided additional insights. Finally, the present study supports many modelling approaches in the literature which found out that the main drivers of alpine streamflow changes are increased glacial melt, earlier snowmelt and lower snow accumulation in wintertime.