Phone-based outpatients’ follow-up in mental health centers during the COVID-19 quarantine

Background: The current COVID-19 pandemic is affecting mental health of global population and, particularly, of people suffering from preexisting mental disorders. Aims: This study aims to report on findings from a phone-based clinical follow-up conducted in two large catchment areas in Italy and Paraguay, during the COVID-19 lockdown, in order to provide psychiatric assessments and measure the level of stress related to the quarantine in a large sample of psychiatric outpatients. Methods: A clinical phone-based follow-up has been conducted in two large catchment areas in the province of Chieti (Vasto, Italy) and City of Asunción (Paraguay), during the COVID-19 national lockdown. The following rating scales have been employed: Hamilton Anxiety Rating Scale (HAM-A); Hamilton Depression Rating Scale (HAM-D); 18-items Brief Psychiatric Rating Scale (BPRS-18). The psychological distress related to the outbreak has been assessed employing the Impact of Event Scale – Revised (IES-R). Results: A total of 110 outpatients were consecutively included and followed among those reporting a stable phase of illness before the COVID-19 lockdown. Findings confirmed a significant increase of general psychopathology, anxiety and fear as well as mild levels of stress related to the quarantine. Also, significant weight gain during the lockdown was detected among patients. Conclusions: This study confirmed the impact of COVID-19 lockdown on mental health of people suffering from psychiatric disorders and may also add evidence on the employment of digital psychiatry in the current pandemic.

A Historical Review of Slope Based SCS Method and its Effect on CN and Runoff Potential Globally

The Soil Conservation Service - Curve Number (SCS-CN) method is extensively used to calculate the runoff from rainfall over a large catchment over the world. Slope is an important criterion for runoff but a very few attempts have been made to evaluate the effect of slope on the CN with runoff potential. The objective of this paper is to summarise the historical review on the effects of slope on CN and runoff potential in various regions by the hydrologists. This paper also depicts that how the various researchers proved the importance of consideration of slope for CN and runoff estimation. In addition, paper highlights the key features of research in future like to classify the watersheds on slope based CN, accurate Antecedent Moisture Condition (AMC) and proper initial abstraction in the various regions etc. Considering these parameters an accurate runoff estimation can be predicted and managed properly in the urban watersheds.

How extreme can unit discharge become in steep Norwegian catchments?

This study presents results of observations and analysis of the flood event in Utvik on 24 July 2017. Observations during and after the event, hydraulic simulations and hydrological modelling along with meteorological observations, are used to estimate the peak discharge of the flood. Although both observations and hydraulic simulations of flood extremes are uncertain, even the most conservative assumptions lead to discharge estimates higher than 160 m3/s at culmination of the flood from the 25 km2-large catchment. The most extreme assumptions indicate it may have been up to 400 m3/s, but there is also strong evidence for the discharge at culmination being between 200 and 250 m3/s. Observations disclosed that the majority of water came from about 50% of the catchment area giving unit discharges up to 18 to 22 m3/s,km2. If the entire catchment contributed it would be from 9 to 11 m3/s,km2. This is significantly higher than previously documented unit discharges in Norway and in the range of the highest observed peak unit discharges in southern Europe. The precipitation causing this event is estimated to be three to five times higher than a 200-year precipitation taken from the intensity–duration–frequency curves for the studied region.

Hydrodynamic Simulation of Seasonal Fluvial Process over a Large Catchment

<p>Fluvial flooding induced by intense or prolonged rainfall poses a regular threat to people’s lives and properties in almost every part of the world. Modelling provides an essential tool for simulating and predicting the hydrological processes from rainfall-runoff to flooding driven by rainfall. Prediction of seasonal or longer-term fluvial processes over large catchments has traditionally been carried out using lumped/distributed hydrological models. However, these traditional hydrological models do not consider strict momentum conservation and they are not suited for accurate simulation of highly transient and dynamic rainfall-runoff and flooding process. On the other hand, sophisticated hydraulic/ hydrodynamic models have been widely used for modelling of flood inundation including those violent flash floods from intense rainfall. But due to their inhibitive computational cost and incapability in representing certain hydrological processes, no attempt has been reported to use a fully 2D hydrodynamic model to simulate long-term fluvial processes to provide more detailed information for the analysis of flood dynamics and subsequent impact on the environment.</p><p>Therefore, this work aims to further develop and test a hydrodynamic model to simulate seasonal fluvial processes in a large catchment. The proposed long-term fluvial processes modelling system is based on the High-Performance Integrated hydrodynamic Modelling System (HiPIMS). HiPIMS solves the full 2D nonlinear shallow water equations using a finite volume shock-capturing numerical method, which is further accelerated by modern GPUs for large-scale and long-term simulations. Surface storage, overland flow and flow dynamics are automatically captured by running simulations on high-resolution topographic data. New model components are developed and coupled to HiPIMS to account for infiltration and evaporation. For infiltration, the Green-Ampt method and curve number method are implemented and compared. The enhanced HiPIMS is applied to reproduce, at 20m resolution, the seasonal fluvial processes including flooding and recovery periods in the 2500km<sup>2</sup> Eden Catchment, England for three months.</p><p>The simulation results are compared with gauge measurements of water level and discharge across the catchment to demonstrate the model’s capability in supporting long-term simulations. More simulations have been also carried out to investigate the model sensitivity to key model parameters, e.g. grid resolution, friction, infiltration and evaporation parameters.</p><p> </p>

Can a hydrological model be efficient and robust at the same time?

<p>It has been shown in various experiments that many conceptual rainfall-runoff models experience difficulties to simulate annual or longer-term variations of the streamflow (e.g. Coron et al., 2014). Whether this problem is inherent to the structure of the model in question or could be solved by a change of the calibration procedure is still a matter of debate: for example, the work of Coron (2013) tended to show that no parameter set able to solve the issue can be found, while Fowler et al. (2018) argued that such parameter sets exist, and should be identifiable by a change of objective function.</p><p>The aim of this study is to explore further the existence of such a parameter set in the case of the GR4J model (Perrin et al., 2003). Parameters sets were in particular tested against their ability to provide efficient (i.e. with good performance) and robust (i.e. transposable in time) discharge simulations over three flow ranges (low, mean and high flows). To this purpose, a large number of parameters sets of GR4J were sampled in 545 French and Australian catchments. The obtained performances were confronted to those obtained with automatic calibration with a range of objective functions focusing on diverse streamflow ranges.</p><p>Because of our large catchment set, we were able to identify a variety of cases: catchments for which highly robust parameter sets exist, catchments for which relatively robust parameter sets exist, and catchments for which no robust parameter sets can be found. Compared to the best sampled parameters sets, those derived through automatic calibration often yielded poorer performances regarding at the same time efficiency and robustness of the discharge simulations over the three flow ranges. We discuss the link between model failures and catchments characteristics, as well as the ability of the GR4J model to adequately simulate streamflow on different timescales and flow regimes.</p>