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Hydrological Parameters (hydrological + parameter)
Selected AbstractsTesting a model for predicting the timing and location of shallow landslide initiation in soil-mantled landscapesEARTH SURFACE PROCESSES AND LANDFORMS, Issue 9 2003M. Casadei Abstract The growing availability of digital topographic data and the increased reliability of precipitation forecasts invite modelling efforts to predict the timing and location of shallow landslides in hilly and mountainous areas in order to reduce risk to an ever-expanding human population. Here, we exploit a rare data set to develop and test such a model. In a 1·7 km2 catchment a near-annual aerial photographic coverage records just three single storm events over a 45 year period that produced multiple landslides. Such data enable us to test model performance by running the entire rainfall time series and determine whether just those three storms are correctly detected. To do this, we link a dynamic and spatially distributed shallow subsurface runoff model (similar to TOPMODEL) to an in,nite slope model to predict the spatial distribution of shallow landsliding. The spatial distribution of soil depth, a strong control on local landsliding, is predicted from a process-based model. Because of its common availability, daily rainfall data were used to drive the model. Topographic data were derived from digitized 1 : 24 000 US Geological Survey contour maps. Analysis of the landslides shows that 97 occurred in 1955, 37 in 1982 and ,ve in 1998, although the heaviest rainfall was in 1982. Furthermore, intensity,duration analysis of available daily and hourly rainfall from the closest raingauges does not discriminate those three storms from others that did not generate failures. We explore the question of whether a mechanistic modelling approach is better able to identify landslide-producing storms. Landslide and soil production parameters were ,xed from studies elsewhere. Four hydrologic parameters characterizing the saturated hydraulic conductivity of the soil and underlying bedrock and its decline with depth were ,rst calibrated on the 1955 landslide record. Success was characterized as the most number of actual landslides predicted with the least amount of total area predicted to be unstable. Because landslide area was consistently overpredicted, a threshold catchment area of predicted slope instability was used to de,ne whether a rainstorm was a signi,cant landslide producer. Many combinations of the four hydrological parameters performed equally well for the 1955 event, but only one combination successfully identi,ed the 1982 storm as the only landslide-producing storm during the period 1980,86. Application of this parameter combination to the entire 45 year record successfully identi,ed the three events, but also predicted that two other landslide-producing events should have occurred. This performance is signi,cantly better than the empirical intensity,duration threshold approach, but requires considerable calibration effort. Overprediction of instability, both for storms that produced landslides and for non-producing storms, appears to arise from at least four causes: (1) coarse rainfall data time scale and inability to document short rainfall bursts and predict pressure wave response; (2) absence of local rainfall data; (3) legacy effect of previous landslides; and (4) inaccurate topographic and soil property data. Greater resolution of spatial and rainfall data, as well as topographic data, coupled with systematic documentation of landslides to create time series to test models, should lead to signi,cant improvements in shallow landslides forecasting. Copyright © 2003 John Wiley & Sons, Ltd. [source] Quantitative microbial faecal source tracking with sampling guided by hydrological catchment dynamicsENVIRONMENTAL MICROBIOLOGY, Issue 10 2008G. H. Reischer Summary The impairment of water quality by faecal pollution is a global public health concern. Microbial source tracking methods help to identify faecal sources but the few recent quantitative microbial source tracking applications disregarded catchment hydrology and pollution dynamics. This quantitative microbial source tracking study, conducted in a large karstic spring catchment potentially influenced by humans and ruminant animals, was based on a tiered sampling approach: a 31-month water quality monitoring (Monitoring) covering seasonal hydrological dynamics and an investigation of flood events (Events) as periods of the strongest pollution. The detection of a ruminant-specific and a human-specific faecal Bacteroidetes marker by quantitative real-time PCR was complemented by standard microbiological and on-line hydrological parameters. Both quantitative microbial source tracking markers were detected in spring water during Monitoring and Events, with preponderance of the ruminant-specific marker. Applying multiparametric analysis of all data allowed linking the ruminant-specific marker to general faecal pollution indicators, especially during Events. Up to 80% of the variation of faecal indicator levels during Events could be explained by ruminant-specific marker levels proving the dominance of ruminant faecal sources in the catchment. Furthermore, soil was ruled out as a source of quantitative microbial source tracking markers. This study demonstrates the applicability of quantitative microbial source tracking methods and highlights the prerequisite of considering hydrological catchment dynamics in source tracking study design. [source] Evaluating local hydrological modelling by temporal gravity observations and a gravimetric three-dimensional modelGEOPHYSICAL JOURNAL INTERNATIONAL, Issue 1 2010M. Naujoks SUMMARY An approach for the evaluation of local hydrological modelling is presented: the deployment of temporal terrestrial gravity measurements and gravimetric 3-D modelling in addition to hydrological point observations. Of particular interest is to what extent such information can be used to improve the understanding of hydrological process dynamics and to evaluate hydrological models. Because temporal gravity data contain integral information about hydrological mass changes they can be considered as a valuable augmentation to traditional hydrological observations. On the other hand, hydrological effects need to be eliminated from high-quality gravity time-series because they interfere with small geodynamic signals. In areas with hilly topography and/or inhomogeneous subsoil, a simple reduction based on hydrological point measurements is usually not sufficient. For such situations, the underlying hydrological processes in the soil and the disaggregated bedrock need to be considered in their spatial and temporal dynamics to allow the development of a more sophisticated reduction. Regarding these issues interdisciplinary research has been carried out in the surroundings of the Geodynamic Observatory Moxa, Germany. At Moxa, hydrologically induced gravity variations of several 10 nm s,2 are observed by the stationarily operating superconducting gravimeter and by spatially distributed and repeated high-precision measurements with transportable relative instruments. In addition, hydrological parameters are monitored which serve as input for a local hydrological catchment model for the area of about 2 km2 around the observatory. From this model, spatial hydrological variations are gained in hourly time steps and included as density changes of the subsoil in a well-constrained gravimetric 3-D model to derive temporal modelled gravity variations. The gravity variations obtained from this combined modelling correspond very well to the observed hydrological gravity changes for both, short period and seasonal signals. From the modelling the amplitude of the impact on gravity of hydrological changes occurring in different distances to the gravimeter location can be inferred. Possible modifications on the local hydrological model are discussed to further improve the quality of the model. Furthermore, a successful reduction of local hydrological effects in the superconducting gravimeter data is developed. After this reduction global seasonal fluctuations are unmasked which are in correspondence to GRACE observations and to global hydrological models. [source] Predicting unit plot soil loss in Sicily, south ItalyHYDROLOGICAL PROCESSES, Issue 5 2008V. Bagarello Abstract Predicting soil loss is necessary to establish soil conservation measures. Variability of soil and hydrological parameters complicates mathematical simulation of soil erosion processes. Methods for predicting unit plot soil loss in Sicily were developed by using 5 years of data from replicated plots. At first, the variability of the soil water content, runoff, and unit plot soil loss values collected at fixed dates or after an erosive event was investigated. The applicability of the Universal Soil Loss Equation (USLE) was then tested. Finally, a method to predict event soil loss was developed. Measurement variability decreased as the mean increased above a threshold value but it was low also for low values of the measured variable. The mean soil loss predicted by the USLE was lower than the measured value by 48%. The annual values of the soil erodibility factor varied by seven times whereas the mean monthly values varied between 1% and 244% of the mean annual value. The event unit plot soil loss was directly proportional to an erosivity index equal to , being QRRe the runoff ratio times the single storm erosion index. It was concluded that a relatively low number of replicates of the variable of interest may be collected to estimate the mean for both high and particularly low values of the variable. The USLE with the mean annual soil erodibility factor may be applied to estimate the order of magnitude of the mean soil loss but it is not usable to estimate soil loss at shorter temporal scales. The relationship for estimating the event soil loss is a modified version of the USLE-M, given that it includes an exponent for the QRRe term. Copyright © 2007 John Wiley & Sons, Ltd. [source] Spatial Calibration and Temporal Validation of Flow for Regional Scale Hydrologic Modeling,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 4 2008C. Santhi Abstract:, Physically based regional scale hydrologic modeling is gaining importance for planning and management of water resources. Calibration and validation of such regional scale model is necessary before applying it for scenario assessment. However, in most regional scale hydrologic modeling, flow validation is performed at the river basin outlet without accounting for spatial variations in hydrological parameters within the subunits. In this study, we calibrated the model to capture the spatial variations in runoff at subwatershed level to assure local water balance, and validated the streamflow at key gaging stations along the river to assure temporal variability. Ohio and Arkansas-White-Red River Basins of the United States were modeled using Soil and Water Assessment Tool (SWAT) for the period from 1961 to 1990. R2 values of average annual runoff at subwatersheds were 0.78 and 0.99 for the Ohio and Arkansas Basins. Observed and simulated annual and monthly streamflow from 1961 to 1990 is used for temporal validation at the gages. R2 values estimated were greater than 0.6. In summary, spatially distributed calibration at subwatersheds and temporal validation at the stream gages accounted for the spatial and temporal hydrological patterns reasonably well in the two river basins. This study highlights the importance of spatially distributed calibration and validation in large river basins. [source] | |||||||||||||