944 resultados para runoff erosivity parameter
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A type of macro drainage solution widely used in urban areas with predomi-nance of closed catchments (basins without outlet) is the implementation of detention and infiltration reservoirs (DIR). This type of solution has the main function of storing surface runoff and to promote soil infiltration and, consequently, aquifer recharge. The practice is to avoid floods in the drainage basin low-lying areas. The catchment waterproofing reduces the distributed groundwater recharge in urban areas, as is the case of Natal city, RN. However, the advantage of DIR is to concentrate the runoff and to promote aquifer recharge to an amount that can surpass the distributed natu-ral recharge. In this paper, we proposed studying a small urban drainage catchment, named Experimental Mirassol Watershed (EMW) in Natal, RN, whose outlet is a DIR. The rainfall-runoff transformation processes, water accumulation in DIR and the pro-cess of infiltration and percolation in the soil profile until the free aquifer were mod-eled and, from rainfall event observations, water levels in DIR and free aquifer water level measurements, and also, parameter values determination, it is was enabled to calibrate and modeling these combined processes. The mathematical modeling was carried out from two numerical models. We used the rainfall-runoff model developed by RIGHETTO (2014), and besides, we developed a one-dimensional model to simu-late the soil infiltration, percolation, redistribution soil water and groundwater in a combined system to the reservoir water balance. Continuous simulation was run over a period of eighteen months in time intervals of one minute. The drainage basin was discretized in blocks units as well as street reaches and the soil profile in vertical cells of 2 cm deep to a total depth of 30 m. The generated hydrographs were transformed into inlet volumes to the DIR and then, it was carried out water balance in these time intervals, considering infiltration and percolation of water in the soil profile. As a re-sult, we get to evaluate the storage water process in DIR as well as the infiltration of water, redistribution into the soil and the groundwater aquifer recharge, in continuous temporal simulation. We found that the DIR has good performance to storage excess water drainage and to contribute to the local aquifer recharge process (Aquifer Dunas / Barreiras).
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Arctic lowland landscapes have been modified by thermokarst lake processes throughout the Holocene. Thermokarst lakes form as a result of ice-rich permafrost degradation and they may expand over time through thermal and mechanical shoreline erosion. We studied proximal and distal sedimentary records from a thermokarst lake located on the Arctic Coastal Plain of northern Alaska to reconstruct the impact of catchment dynamics and morphology on the lacustrine depositional environment and to quantify carbon accumulation in thermokarst lake sediments. Short cores were collected for analysis of pollen, sedimentological and geochemical proxies. Radiocarbon and Pb/Cs dating, as well as extrapolation of measured historic lake expansion rates, were applied to estimate a minimum lake age of ~ 1,400 calendar years BP. The pollen record is in agreement with the young lake age as it does not include evidence of the "alder high" that occurred in the region ~ 4.0 cal ka BP. The lake most likely initiated from a remnant pond in a drained thermokarst lake basin (DTLB) and deepened rapidly as evidenced by accumulation of laminated sediments. Increasing oxygenation of the water column as shown by higher Fe/Ti and Fe/S ratios in the sediment indicate shifts in ice regime with increasing water depth. More recently, the sediment source changed as the thermokarst lake expanded through lateral permafrost degradation, alternating from redeposited DTLB sediments, to increased amounts of sediment from eroding, older upland deposits, followed by a more balanced combination of both DTLB and upland sources. The characterizing shifts in sediment sources and depositional regimes in expanding thermokarst lakes were therefore archived in the thermokarst lake sedimentary record. This study also highlights the potential for Arctic lakes to recycle old carbon from thawing permafrost and thermokarst processes.
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Single-molecule manipulation experiments of molecular motors provide essential information about the rate and conformational changes of the steps of the reaction located along the manipulation coordinate. This information is not always sufficient to define a particular kinetic cycle. Recent single-molecule experiments with optical tweezers showed that the DNA unwinding activity of a Phi29 DNA polymerase mutant presents a complex pause behavior, which includes short and long pauses. Here we show that different kinetic models, considering different connections between the active and the pause states, can explain the experimental pause behavior. Both the two independent pause model and the two connected pause model are able to describe the pause behavior of a mutated Phi29 DNA polymerase observed in an optical tweezers single-molecule experiment. For the two independent pause model all parameters are fixed by the observed data, while for the more general two connected pause model there is a range of values of the parameters compatible with the observed data (which can be expressed in terms of two of the rates and their force dependencies). This general model includes models with indirect entry and exit to the long-pause state, and also models with cycling in both directions. Additionally, assuming that detailed balance is verified, which forbids cycling, this reduces the ranges of the values of the parameters (which can then be expressed in terms of one rate and its force dependency). The resulting model interpolates between the independent pause model and the indirect entry and exit to the long-pause state model
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The authors thank Professor Iber^e Luiz Caldas for the suggestions and encouragement. The authors F.F.G.d.S., R.M.R., J.C.S., and H.A.A. acknowledge the Brazilian agency CNPq and state agencies FAPEMIG, FAPESP, and FAPESC, and M.S.B. also acknowledges the EPSRC Grant Ref. No. EP/I032606/1.
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Acknowledgements The authors would like to thank Jonathan Dick, Josie Geris, Jason Lessels, and Claire Tunaley for data collection and Audrey Innes for lab sample preparation. We also thank Christian Birkel for discussions about the model structure and comments on an earlier draft of the paper. Climatic data were provided by Iain Malcolm and Marine Scotland Fisheries at the Freshwater Lab, Pitlochry. Additional precipitation data were provided by the UK Meteorological Office and the British Atmospheric Data Centre (BADC).We thank the European Research Council ERC (project GA 335910 VEWA) for funding the VeWa project.
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Peer reviewed
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We thank the European Research Council ERC (project GA 335910 VEWA) for funding the VeWa project.
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River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first assemble an unprecedented collection of river flow observations, combining information from three distinct data bases. Observed monthly runoff rates are first tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 12) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950 - December 2015) on a 0.5° x 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring.
Resumo:
River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first collect an unprecedented collection of river flow observations, combining information from three distinct data bases. Observed monthly runoff rates are first tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 11) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950-December 2014) on a 0.5° × 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring.
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The need for continuous recording rain gauges makes it difficult to determine the rainfall erosivity factor (R-factor) of the (R)USLE model in areas without good temporal data coverage. In mainland Spain, the Nature Conservation Institute (ICONA) determined the R-factor at few selected pluviographs, so simple estimates of the R-factor are definitely of great interest. The objectives of this study were: (1) to identify a readily available estimate of the R-factor for mainland Spain; (2) to discuss the applicability of a single (global) estimate based on analysis of regional results; (3) to evaluate the effect of record length on estimate precision and accuracy; and (4) to validate an available regression model developed by ICONA. Four estimators based on monthly precipitation were computed at 74 rainfall stations throughout mainland Spain. The regression analysis conducted at a global level clearly showed that modified Fournier index (MFI) ranked first among all assessed indexes. Applicability of this preliminary global model across mainland Spain was evaluated by analyzing regression results obtained at a regional level. It was found that three contiguous regions of eastern Spain (Catalonia, Valencian Community and Murcia) could have a different rainfall erosivity pattern, so a new regression analysis was conducted by dividing mainland Spain into two areas: Eastern Spain and plateau-lowland area. A comparative analysis concluded that the bi-areal regression model based on MFI for a 10-year record length provided a simple, precise and accurate estimate of the R-factor in mainland Spain. Finally, validation of the regression model proposed by ICONA showed that R-ICONA index overpredicted the R-factor by approximately 19%.