Abstract: The study focused on investigating the presence of change patterns in 600 unimpaired streamflow stations across the continental U.S. at different time intervals to understand the change patterns that can provide significant insight regarding climate variability and change. Each station had continuous streamflow data of at least 30 years (the entire dataset covered a range of 109 years). Presence of trends and shifts were detected in water year and the four seasons (fall, winter, spring, and summer) analyzing the water year and seasonal mean flows. Two non-parametric tests, namely, the Mann-Kendall test and the Pettitt’s test were used to identify the trends and the shifts, respectively. The results showed an increasing trend in the northeast and upper-mid regions, whereas southeast and northwest regions underwent a decrease. Shifts followed similar patterns as trends with higher number of stations with significant change. Fall and spring showed the highest number of stations with increasing and decreasing change, respectively, in the seasonal analyses. Results of this study may assist water managers to understand the streamflow change patterns across the continental U.S., especially at the regional scale since this study covers a long range of years with a large number of stations in each region.
Abstract: This study investigates how the performance of a set of models depends on the catchments to which these models are applied. It examines (i) whether it is possible to identify a single best model for each of the catchments, or whether results are dominated by equifinality; and (ii) whether the ranking of model performance can be related to a set of predictors, such as climate and catchment characteristics. In order to explore these questions, we applied 12 model structures to 99 catchments in Germany, ranging in size from 10 km2 to 1826 km2. We examined model performance in terms of streamflow predictions, based on various indices. Our results indicate that for some catchments many structures perform equally well, whereas for other catchments a single structure clearly outperforms the others. We could not identify clear relationships between relative model performance and catchment characteristics. This result led us to conclude that for the spatial scales considered, it is difficult to base the selection of a lumped conceptual model based on a priori assessment, and we recommend a posteriori selection based on model comparisons.
Abstract: A hydrological ensemble prediction system is running operationally at the Royal Meteorological Institute of Belgium (RMI) for ten catchments in the Meuse basin. It makes use of the conceptual semi-distributed hydrological model SCHEME and the European Centre for Medium Range Weather Forecasts (ECMWF) ensemble prediction system (ENS). An ensemble of 51 discharge forecasts is generated daily. We investigate the improvements attained through postprocessing the discharge forecasts, using the archived ECMWF reforecasts for precipitation and other necessary meteorological variables. We use the 5-member reforecasts that have been produced since 2012, when the horizontal resolution of ENS was increased to the N320 resolution (≈30 km over Belgium). The reforecasts were issued weekly, going back 20 years, and we use a calibration window of five weeks. We use these as input to create a set of hydrological reforecasts. The implemented calibration method is an adaption of the variance inflation method. The parameters of the calibration are estimated based on the hydrological reforecasts and the observed discharge. The postprocessed forecasts are verified based on a two-and-a-half year period of data, using archived 51 member ENS forecasts. The skill is evaluated using summary scores of the ensemble mean and probabilistic scores: the Brier Score and the Continuous Ranked Probability Score (CRPS). We find that the variance inflation method gives a significant improvement in probabilistic discharge forecasts. The Brier score, which measures probabilistic skill for forecasts of discharge threshold exceedance, is improved for the entire forecast range during the hydrological summer period, and the first three days during hydrological winter. The CRPS is also significantly improved during summer, but not during winter. We conclude that it is valuable to apply the postprocessing method during hydrological summer. During winter, the method is also useful for forecasting exceedance probabilities of higher thresholds, but not for lead times beyond five days. Finally, we also note the presence of some large outliers in the postprocessed discharge forecasts, arising from the fact that the postprocessing is performed on the logarithmically transformed discharges. We suggest some ways to deal with this in the future for our operational setting.
Abstract: A considerable number of studies have been made of institutional arrangements that can prevent excessive groundwater pumping based on Hardin’s seminal work, the “tragedy of the commons.” In contrast, this paper is concerned with groundwater quality control for which policy studies are very limited. This paper not only clarifies institutional challenges specific to groundwater contamination, but also demonstrates how government and industry could solve them using a case study of Hadano, Kanagawa Prefecture, Japan, which has pioneered countermeasures for groundwater pollution in Japan. Hadano solved the challenges by enacting an innovative local ordinance with three pillars: Proxy purification by the city government, fundraising for purification activities and a retroactive system. Lessons learnt from the Hadano case will be very useful to policy makers because these problems already occur in other urban areas, or are likely to occur in the near future.
Abstract: A pair of hydro-meteorological modeling systems were calibrated and evaluated for the Ayalon basin in central Israel to assess the advantages and limitations of one-way versus two-way coupled modeling systems for flood prediction. The models used included the Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS) model and the Weather Research and Forecasting (WRF) Hydro modeling system. The models were forced by observed, interpolated precipitation from rain-gauges within the basin, and with modeled precipitation from the WRF atmospheric model. Detailed calibration and evaluation was carried out for two major winter storms in January and December 2013. Then, both modeling systems were executed and evaluated in an operational mode for the full 2014/2015 rainy season. Outputs from these simulations were compared to observed measurements from the hydrometric station at the Ayalon basin outlet. Various statistical metrics were employed to quantify and analyze the results: correlation, Root Mean Square Error (RMSE) and the Nash–Sutcliffe (NS) efficiency coefficient. Foremost, the results presented in this study highlight the sensitivity of hydrological responses to different sources of simulated and observed precipitation data, and demonstrate improvement, although not significant, at the Hydrological response, like simulated hydrographs. With observed precipitation data both calibrated models closely simulated the observed hydrographs. The two-way coupled WRF/WRF-Hydro modeling system produced improved both the precipitation and hydrological simulations as compared to the one-way WRF simulations. Findings from this study, as well as previous studies, suggest that the use of two-way atmospheric-hydrological coupling has the potential to improve precipitation and, therefore, hydrological forecasts for early flood warning applications. However, more research needed in order to better understand the land-atmosphere coupling mechanisms driving hydrometeorological processes on a wider variety precipitation and terrestrial hydrologic systems.
Abstract: Determination of overland sheet flow depths, velocities and celerities across the hillslope in watershed modeling is important towards estimation of surface storage, travel times to streams and soil detachment rates. It requires careful characterization of the flow processes. Similarly, determination of the temporal variation of hillslope-riparian-stream hydrologic connectivity requires estimation of the shallow subsurface soil hydraulic conductivity and soil-water retention (i.e., drainable porosities) parameters. Field rainfall and runoff simulation studies provide considerable information and insight into these processes; in particular, that sheet flows are likely laminar and that shallow hydraulic conductivities and storage can be determined from the plot studies. Here, using a 1 m by 2 m long runoff simulation flume, we found that for overland flow rates per unit width of roughly 30–60 mm2/s and bedslopes of 10%–66% with varying sand roughness depths that all flow depths were predicted by laminar flow equations alone and that equivalent Manning’s n values were depth dependent and quite small relative to those used in watershed modeling studies. Even for overland flow rates greater than those typically measured or modeled and using Manning’s n values of 0.30–0.35, often assumed in physical watershed model applications for relatively smooth surface conditions, the laminar flow velocities were 4–5 times greater, while the laminar flow depths were 4–5 times smaller. This observation suggests that travel times, surface storage volumes and surface shear stresses associated with erosion across the landscape would be poorly predicted using turbulent flow assumptions. Filling the flume with fine sand and conducting runoff studies, we were unable to produce sheet flow, but found that subsurface flows were onflow rate, soil depth and slope dependent and drainable porosities were only soil depth and slope dependent. Moreover, both the sand hydraulic conductivity and drainable porosities could be readily determined from measured capillary pressure displacement pressure head and assumption of pore-size distributions (i.e., Brooks-Corey lambda values of 2–3).