The sensitivity of landscape evolution models to spatial and temporal rainfall resolution

© Author(s) 2016. Climate is one of the main drivers for landscape evolution models (LEMs), yet its representation is often basic with values averaged over long time periods and frequently lumped to the same value for the whole basin. Clearly, this hides the heterogeneity of precipitation - but what impact does this averaging have on erosion and deposition, topography, and the final shape of LEM landscapes? This paper presents results from the first systematic investigation into how the spatial and temporal resolution of precipitation affects LEM simulations of sediment yields and patterns of erosion and deposition. This is carried out by assessing the sensitivity of the CAESAR-Lisflood LEM to different spatial and temporal precipitation resolutions - as well as how this interacts with different-size drainage basins over short and long timescales. A range of simulations were carried out, varying rainfall from 0.25 h × 5 km to 24 h × Lump resolution over three different-sized basins for 30-year durations. Results showed that there was a sensitivity to temporal and spatial resolution, with the finest leading to & gt; 100 % increases in basin sediment yields. To look at how these interactions manifested over longer timescales, several simulations were carried out to model a 1000-year period. These showed a systematic bias towards greater erosion in uplands and deposition in valley floors with the finest spatial- and temporal-resolution data. Further tests showed that this effect was due solely to the data resolution, not orographic factors. Additional research indicated that these differences in sediment yield could be accounted for by adding a compensation factor to the model sediment transport law. However, this resulted in notable differences in the topographies generated, especially in third-order and higher streams. The implications of these findings are that uncalibrated past and present LEMs using lumped and time-averaged climate inputs may be under-predicting basin sediment yields as well as introducing spatial biases through under-predicting erosion in first-order streams but over-predicting erosion in second- and third-order streams and valley floor areas. Calibrated LEMs may give correct sediment yields, but patterns of erosion and deposition will be different and the calibration may not be correct for changing climates. This may have significant impacts on the modelled basin profile and shape from long-timescale simulations

Ensemble-characterisation of satellite rainfall uncertainty and its impacts on the hydrological modelling of a sparsely gauged basin in Western Africa

Many areas of the planet lack the infrastructure required to make accurate and timely estimations of rainfall. This problem is especially acute in sub-Saharan Africa, where a paucity of rain recording radar and sufficiently dense raingauge networks combine with highly variable rainfall, a reliance on agriculture that is predominantly rain fed and systems that are prone to flooding and drought. Satellite Rainfall Estimates (SRFE) are useful as they can provide additional spatial and temporal information to drive various downstream environmental models and early warning systems (EWS). However, when operating at higher spatial and temporal resolutions SRFE contain large uncertainties which propagate through the downstream models.This thesis uses the TAMSAT1 SRFE algorithm developed by Teo (2006) to estimate the rainfall over a large, data sparse and heterogenous catchment in the Senegal Basin. The uncertainty within the TAMSAT1 SRFE is represented using a set of ensemble estimates, each unique but equiprobable based on the full conditional distribution of the recorded rainfall, produced using the TAMSIM algorithm, also developed by Teo (2006). The ensemble rainfall estimates were then used in turn to drive a Pitman Rainfall-Runoff model of the catchment hydrology.The use of ensemble rainfall estimates was shown to be incompatible with the pre-calibrated parameter values for the hydrological model. A novel approach, the EnsAll method, was developed to calibrate the hydrological model which incorporated each individual ensemble member. The EnsAll calibrated model showed the greatest skill when driven by the ensemble rainfall estimates and little bias. A comparison of the hydrographs produced from TAMSIM ensemble rainfall estimates and that from an ensemble of perturbed TAMSAT1 estimates showed that the full spatio-temporally distributed method used by TAMSIM is superior to a simpler perturbation method for characterizing SRFE uncertainty.Overall, the SRFE used were shown to outperform the rainfall estimates produced from the sparse raingauge network as a hydrological model driver. However, they did demonstrate a lack of ability to represent the large interseasonal variations in rainfall resulting in large systematic biases. These biases were observed propagating directly to the modelled hydrological ouput

Rhythms of Locomotion Expressed by Limulus polyphemus, the American Horseshoe Crab: I. Synchronization by Artificial Tides

Limulus polyphemus, the American horseshoe crab, has an endogenous clock that drives circatidal rhythms of locomotor activity. In this study, we examined the ability of artificial tides to entrain the locomotor rhythms of Limulus in the laboratory. In experiments one and two, the activity of 16 individuals of L. polyphemus was monitored with activity boxes and “running wheels.” When the crabs were exposed to artificial tides created by changes in water depth, circatidal rhythms were observed in animals exposed to 12.4-h “tidal” cycles of either water depth changes (8 of 8 animals) or inundation (7 of 8 animals). In experiment three, an additional 8 animals were exposed to water depth changes under cyclic conditions of light and dark and then monitored for 10 days with no imposed artificial tides. Most animals (5) clearly synchronized their activity to the imposed artificial tidal cycles, and 3 of these animals showed clear evidence of entrainment after the artificial tides were terminated. Overall, these results demonstrate that the endogenous tidal clock that influences locomotion in Limulus can be entrained by imposed artificial tides. In the laboratory, these tidal cues override the influence of light/dark cycles. In their natural habitat, where both tidal and photoperiod inputs are typically always present, their activity rhythms are likely to be much more complex

Hydrological modelling using ensemble satellite rainfall estimates in a sparsely gauged river basin: The need for whole-ensemble calibration

The potential for satellite rainfall estimates to drive hydrological models has been long understood, but at the high spatial and temporal resolutions often required by these models the uncertainties in satellite rainfall inputs are both significant in magnitude and spatiotemporally autocorrelated. Conditional stochastic modelling of ensemble observed fields provides one possible approach to representing this uncertainty in a form suitable for hydrological modelling. Previous studies have concentrated on the uncertainty within the satellite rainfall estimates themselves, sometimes applying ensemble inputs to a pre-calibrated hydrological model. This approach does not account for the interaction between input uncertainty and model uncertainty and in particular the impact of input uncertainty on model calibration. Moreover, it may not be appropriate to use deterministic inputs to calibrate a model that is intended to be driven by using an ensemble. A novel whole-ensemble calibration approach has been developed to overcome some of these issues. This study used ensemble rainfall inputs produced by a conditional satellite-driven stochastic rainfall generator (TAMSIM) to drive a version of the Pitman rainfall-runoff model, calibrated using the whole-ensemble approach. Simulated ensemble discharge outputs were assessed using metrics adapted from ensemble forecast verification, showing that the ensemble outputs produced using the whole-ensemble calibrated Pitman model outperformed equivalent ensemble outputs created using a Pitman model calibrated against either the ensemble mean or a theoretical infinite-ensemble expected value. Overall, for the verification period the whole-ensemble calibration provided a mean RMSE of 61.7% of the mean wet season discharge, compared to 83.6% using a calibration based on the daily mean of the ensemble estimates. Using a Brier’s Skill Score to assess the performance of the ensemble against a climatic estimate, the whole-ensemble calibration provided a positive score for the main range of discharge events. The equivalent score for calibration against the ensemble mean was negative, indicating it showed no skill versus the climatic estimate

Draft Genome Sequence of Rhodococcus sp. Strain ATCC 49988, a Quinoline-Degrading Bacterium.

We report here the 4.9-Mb genome sequence of a quinoline-degrading bacterium, Rhodococcus sp. strain ATCC 49988. The draft genome data will enable the identification of genes and future genetic modification to enhance traits relevant to heteroaromatic compound degradation

Spectroscopic Orbital Periods for 29 Cataclysmic Variables from the Sloan Digital Sky Survey

We report follow-up spectroscopy of 29 cataclysmic variables from the Sloan Digital Sky Survey (SDSS), 22 of which were discovered by SDSS and seven of which are previously known systems that were recovered in SDSS. The periods for 16 of these objects were included in the tabulation by Gänsicke et al. While most of the systems have periods less than 2 hr, only one has a period in the 80–86 minutes spike found by Gänsicke et al., and 11 have periods longer than 3 hr, indicating that the present sample is skewed toward longer-period, higher-luminosity objects. Seven of the objects have spectra resembling dwarf novae, but have apparently never been observed in outburst, suggesting that many cataclysmics with relatively low variability amplitude remain to be discovered. Some of the objects are notable. SDSS J07568+0858 and SDSS J08129+1911 were previously known to have deep eclipses; in addition to spectroscopy, we use archival data from the Catalina Real Time Transient Survey to refine their periods. We give a parallax-based distance of 195 (+54, −39) pc for LV Cnc (SDSS J09197+0857), which at Porb = 81 m has the shortest orbital period in our sample. SDSS J08091+3814 shows both the spectroscopic phase offset and phase-dependent absorption found in SW Sextantis stars. The average spectra of SDSS J08055+0720 and SDSS J16191+1351 show contributions from K-type secondaries, and SDSS J080440+0239 shows a contribution from an early M star. We use these to constrain the distances. SDSS J09459+2922 has characteristics typical of a magnetic system. SDSS11324+6249 may be a novalike variable, and if so, its orbital period (99 minutes) is unusually short for that subclass

The impact of different rainfall products on landscape modelling simulations

Rainfall products can contain significantly different spatiotemporal estimates, depending on their underlying data and final constructed resolution. Commonly used products, such as rain gauges, rain gauge networks, and weather radar, differ in their information content regarding intensities, spatial variability, and natural climatic variability, therefore producing different estimates. Landscape evolution models (LEMs) simulate the geomorphic changes in landscapes, and current models can simulate timeframes from event level to millions of years and some use rainfall inputs to drive them. However, the impact of different rainfall products on LEM outputs has never been considered. This study uses the STREAP rainfall generator, calibrated using commonly used rainfall observation products, to produce longer rainfall records than the observations to drive the CAESAR‐Lisflood LEM to examine how differences in rainfall products affect simulated landscapes. The results show that the simulation of changes to basin geomorphology is sensitive to the differences between rainfall products, with these differences expressed linearly in discharges but non‐linearly in sediment yields. Furthermore, when applied over a 1500‐year period, large differences in the simulated long profiles were observed, with the simulations producing greater sediment yields showing erosion extending further downstream. This suggests that the choice of rainfall product to drive LEMs has a large impact on the final simulated landscapes. The combination of rainfall generator model and LEMs represents a potentially powerful method for assessing the impacts of rainfall product differences on landscapes and their short‐ and long‐term evolution