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Hydrological response to earthquakes has long been observed, yet the mechanisms responsible still remain unclear and likely vary in space and time. This study explores the base flow response in small upland catchments of the Coastal Range of south-central Chile after the M-W 8.8 Maule earthquake of 27 February 2010. An initial decline in streamflow followed by an increase of up to 400% of the discharge measured immediately before the earthquake occurred, and diurnal streamflow oscillations intensified after the earthquake. Neither response time, nor time to maximum streamflow discharge showed any relationship with catchment topography or size, suggesting non-uniform release of water across the catchments. The fast response, unaffected stream water temperatures and a simple diffusion model point to the sandy saprolite as the source of the excess water. Base flow recession analysis reveals no evidence for substantial enhancement of lateral hydraulic conductivity in the saprolite after the earthquake. Seismic energy density reached similar to 170 J/m(3) for the main shock and similar to 0.9 J/m(3) for the aftershock, exceeding the threshold for liquefaction by undrained consolidation only during the main shock. Although increased hydraulic gradient due to ground acceleration-triggered, undrained consolidation is consistent with empirical magnitude-distance relationships for liquefaction, the lack of independent evidence for liquefaction means that enhanced vertical permeability (probably in combination with co-seismic near-surface dilatancy) cannot be excluded as a potential mechanism. Undrained consolidation may have released additional water from the saturated saprolite into the overlying soil, temporarily reducing water transfer to the creeks but enlarging the cross-section of the saturated zone, which in turn enhanced streamflow after establishment of a new hydraulic equilibrium. The enlarged saturated zone facilitated water uptake by roots and intensified evapotranspiration.
Hydrological models are commonly used to perform real-time runoff forecasting for flood warning. Their application requires catchment characteristics and precipitation series that are not always available. An alternative approach is nonparametric modelling based only on runoff series. However, the following questions arise: Can nonparametric models show reliable forecasting? Can they perform as reliably as hydrological models? We performed probabilistic forecasting one, two and three hours ahead for a runoff series, with the aim of ascribing a probability density function to predicted discharge using time series analysis based on stochastic dynamics theory. The derived dynamic terms were compared to a hydrological model, LARSIM. Our procedure was able to forecast within 95% confidence interval 1-, 2- and 3-h ahead discharge probability functions with about 1.40 m(3)/s of range and relative errors (%) in the range [-30; 30]. The LARSIM model and the best nonparametric approaches gave similar results, but the range of relative errors was larger for the nonparametric approaches.
Flood generation in mountainous headwater catchments is governed by rainfall intensities, by the spatial distribution of rainfall and by the state of the catchment prior to the rainfall, e. g. by the spatial pattern of the soil moisture, groundwater conditions and possibly snow. The work presented here explores the limits and potentials of measuring soil moisture with different methods and in different scales and their potential use for flood simulation. These measurements were obtained in 2007 and 2008 within a comprehensive multi-scale experiment in the Weisseritz headwater catchment in the Ore-Mountains, Germany. The following technologies have been applied jointly thermogravimetric method, frequency domain reflectometry (FDR) sensors, spatial time domain reflectometry (STDR) cluster, ground-penetrating radar (GPR), airborne polarimetric synthetic aperture radar (polarimetric SAR) and advanced synthetic aperture radar (ASAR) based on the satellite Envisat. We present exemplary soil measurement results, with spatial scales ranging from point scale, via hillslope and field scale, to the catchment scale. Only the spatial TDR cluster was able to record continuous data. The other methods are limited to the date of over-flights (airplane and satellite) or measurement campaigns on the ground. For possible use in flood simulation, the observation of soil moisture at multiple scales has to be combined with suitable hydrological modelling, using the hydrological model WaSiM-ETH. Therefore, several simulation experiments have been conducted in order to test both the usability of the recorded soil moisture data and the suitability of a distributed hydrological model to make use of this information. The measurement results show that airborne-based and satellite-based systems in particular provide information on the near-surface spatial distribution. However, there are still a variety of limitations, such as the need for parallel ground measurements (Envisat ASAR), uncertainties in polarimetric decomposition techniques (polarimetric SAR), very limited information from remote sensing methods about vegetated surfaces and the non-availability of continuous measurements. The model experiments showed the importance of soil moisture as an initial condition for physically based flood modelling. However, the observed moisture data reflect the surface or near-surface soil moisture only. Hence, only saturated overland flow might be related to these data. Other flood generation processes influenced by catchment wetness in the subsurface such as subsurface storm flow or quick groundwater drainage cannot be assessed by these data. One has to acknowledge that, in spite of innovative measuring techniques on all spatial scales, soil moisture data for entire vegetated catchments are still today not operationally available. Therefore, observations of soil moisture should primarily be used to improve the quality of continuous, distributed hydrological catchment models that simulate the spatial distribution of moisture internally. Thus, when and where soil moisture data are available, they should be compared with their simulated equivalents in order to improve the parameter estimates and possibly the structure of the hydrological model.
We generated medium-range forecasts of runoff for a 50 km(2) headwater catchment upstream of a reservoir using numerical weather predictions (NWPs) of the past as input to an operational hydrological model. NWP data originating from different sources were tested. For a period of 8.5 years, we computed daily forecasts with a lead time of +120 h based on an empirically downscaled version of the ECMWF's ensemble prediction system. For the last 3.5 years of the test period, we also tried the deterministic COSMO-EU forecast disseminated by the German Weather Service for lead times of up to +72 h. Common measures of skill indicate superiority of the ensemble runoff forecast over single-value forecasts for longer lead times. However, regardless of which NWP data were being used, the probability of event detection (POD) was found to be generally lower than 50%. In many cases, values in the range of 20-30% were obtained. At the same time, the false alarms ratio (FAR) was often found to be considerably high. The observed uncertainties in the hydrological forecasts were shown to originate from both the insufficient quality of precipitation forecasts as well as deficiencies in hydrological modeling and quantitative precipitation estimation. With respect to the anticipatory control of reservoirs in the studied catchment, the value of the tested runoff forecasts appears to be limited. This is due to the unfavorably low POD/FAR ratio in conjunction with a high cost-loss ratio. However, our results indicate that, in many cases, major runoff events related to snow melt can be successfully predicted as early as 4-5 days in advance.
In this paper, we analyse the effectiveness of flood management measures based on the concept known as "retaining water in the landscape". The investigated measures include afforestation, micro-ponds and small-reservoirs. A comparative and model-based methodological approach has been developed and applied for three meso-scale catchments located in different European hydro-climatological regions: Poyo (184 km(2)) in the Spanish Mediterranean, Upper Iller (954 km(2)) in the German Alps and Kamp (621 km(2)) in Northeast-Austria representing the Continental hydro-climate. This comparative analysis has found general similarities in spite of the particular differences among studied areas. In general terms, the flood reduction through the concept of "retaining water in the landscape" depends on the following factors: the storage capacity increase in the catchment resulting from such measures, the characteristics of the rainfall event, the antecedent soil moisture condition and the spatial distribution of such flood management measures in the catchment. In general, our study has shown that, this concept is effective for small and medium events, but almost negligible for the largest and less frequent floods: this holds true for all different hydro-climatic regions, and with different land-use, soils and morphological settings.
Channel transmission losses in drylands take place normally in extensive alluvial channels or streambeds underlain by fractured rocks. They can play an important role in streamflow rates, groundwater recharge, freshwater supply and channel-associated ecosystems. We aim to develop a process-oriented, semi-distributed channel transmission losses model, using process formulations which are suitable for data-scarce dryland environments and applicable to both hydraulically disconnected losing streams and hydraulically connected losing(/gaining) streams. This approach should be able to cover a large variation in climate and hydro-geologic controls, which are typically found in dryland regions of the Earth. Our model was first evaluated for a losing/gaining, hydraulically connected 30 km reach of the Middle Jaguaribe River (MJR), Ceara, Brazil, which drains a catchment area of 20 000 km(2). Secondly, we applied it to a small losing, hydraulically disconnected 1.5 km channel reach in the Walnut Gulch Experimental Watershed (WGEW), Arizona, USA. The model was able to predict reliably the streamflow volume and peak for both case studies without using any parameter calibration procedure. We have shown that the evaluation of the hypotheses on the dominant hydrological processes was fundamental for reducing structural model uncertainties and improving the streamflow prediction. For instance, in the case of the large river reach (MJR), it was shown that both lateral stream-aquifer water fluxes and groundwater flow in the underlying alluvium parallel to the river course are necessary to predict streamflow volume and channel transmission losses, the former process being more relevant than the latter. Regarding model uncertainty, it was shown that the approaches, which were applied for the unsaturated zone processes (highly nonlinear with elaborate numerical solutions), are much more sensitive to parameter variability than those approaches which were used for the saturated zone (mathematically simple water budgeting in aquifer columns, including backwater effects). In case of the MJR-application, we have seen that structural uncertainties due to the limited knowledge of the subsurface saturated system interactions (i.e. groundwater coupling with channel water; possible groundwater flow parallel to the river) were more relevant than those related to the subsurface parameter variability. In case of the WEGW application we have seen that the non-linearity involved in the unsaturated flow processes in disconnected dryland river systems (controlled by the unsaturated zone) generally contain far more model uncertainties than do connected systems controlled by the saturated flow. Therefore, the degree of aridity of a dryland river may be an indicator of potential model uncertainty and subsequent attainable predictability of the system.