Bayesian uncertainty assessment of flood predictions in ungauged urban basins for conceptual rainfall-runoff models

Urbanization and the resulting land-use change strongly affect the water cycle and runoff-processes in watersheds. Unfortunately, small urban watersheds, which are most affected by urban sprawl, are mostly ungauged. This makes it intrinsically difficult to assess the consequences of urbanization. Most of all, it is unclear how to reliably assess the predictive uncertainty given the structural deficits of the applied models. In this study, we therefore investigate the uncertainty of flood predictions in ungauged urban basins from structurally uncertain rainfall-runoff models. To this end, we suggest a procedure to explicitly account for input uncertainty and model structure deficits using Bayesian statistics with a continuous-time autoregressive error model. In addition, we propose a concise procedure to derive prior parameter distributions from base data and successfully apply the methodology to an urban catchment in Warsaw, Poland. Based on our results, we are able to demonstrate that the autoregressive error model greatly helps to meet the statistical assumptions and to compute reliable prediction intervals. In our study, we found that predicted peak flows were up to 7 times higher than observations. This was reduced to 5 times with Bayesian updating, using only few discharge measurements. In addition, our analysis suggests that imprecise rainfall information and model structure deficits contribute mostly to the total prediction uncertainty. In the future, flood predictions in ungauged basins will become more important due to ongoing urbanization as well as anthropogenic and climatic changes. Thus, providing reliable measures of uncertainty is crucial to support decision making

Controlled trial of lovastatin combined with an open-label treatment of a parent-implemented language intervention in youth with fragile X syndrome.

BackgroundThe purpose of this study was to conduct a 20-week controlled trial of lovastatin (10 to 40 mg/day) in youth with fragile X syndrome (FXS) ages 10 to 17 years, combined with an open-label treatment of a parent-implemented language intervention (PILI), delivered via distance video teleconferencing to both treatment groups, lovastatin and placebo.MethodA randomized, double-blind trial was conducted at one site in the Sacramento, California, metropolitan area. Fourteen participants were assigned to the lovastatin group; two participants terminated early from the study. Sixteen participants were assigned to the placebo group. Lovastatin or placebo was administered orally in a capsule form, starting at 10 mg and increasing weekly or as tolerated by 10 mg increments, up to a maximum dose of 40 mg daily. A PILI was delivered to both groups for 12 weeks, with 4 activities per week, through video teleconferencing by an American Speech-Language Association-certified Speech-Language Pathologist, in collaboration with a Board-Certified Behavior Analyst. Parents were taught to use a set of language facilitation strategies while interacting with their children during a shared storytelling activity. The main outcome measures included absolute change from baseline to final visit in the means for youth total number of story-related utterances, youth number of different word roots, and parent total number of story-related utterances.ResultsSignificant increases in all primary outcome measures were observed in both treatment groups. Significant improvements were also observed in parent reports of the severity of spoken language and social impairments in both treatment groups. In all cases, the amount of change observed did not differ across the two treatment groups. Although gains in parental use of the PILI-targeted intervention strategies were observed in both treatment groups, parental use of the PILI strategies was correlated with youth gains in the placebo group and not in the lovastatin group.ConclusionParticipants in both groups demonstrated significant changes in the primary outcome measures. The magnitude of change observed across the two groups was comparable, providing additional support for the efficacy of the use of PILI in youth with FXS.Trial registrationUS National Institutes of Health (ClinicalTrials.gov), NCT02642653. Registered 12/30/2015

Determination of Curve Number for snowmelt-runoff floods in a small catchment

One of the widely used methods for predicting flood runoff depth from ungauged catchments is the curve number (CN) method, developed by Soil Conservation Service (SCS) of US Department of Agriculture. The CN parameter can be computed directly from recorded rainfall depths and\ud direct runoff volumes in case of existing data. In presented investigations, the CN parameter has been computed for snowmelt-runoff events based on snowmelt and rainfall measurements. All required data has been gathered for a small agricultural catchment (A = 23.4 km2) of Zagożdżonka river, located in Central Poland. The CN number received from 28 snowmelt-runoff events has been compared with CN computed from rainfall-runoff events for the same catchment. The CN parameter, estimated empirically varies from 64.0 to 94.8. The relation between CN and snowmelt depth was investigated in a similar procedure to relation between CN and rainfall depth