Surface Water Flow Balance of a River Basin Using a Shallow Water Approach and GPU Parallel Computing; Pescara River (Italy) as Test Case

The analysis and prevention of hydrogeological risks plays a very important role and, currently, much attention is paid to advanced numerical models that correspond more to physical reality and whose aim is to reproduce complex environmental phenomena even for long times and on large spatial scales. Within this context, the feasibility of performing an effective balance of surface water flow relating to several months was explored, based on accurate hydraulic and mathematical-numerical models applied to a system at the scale of a hydrographic basin. To pursue this target, a 2D Riemann–Godunov shallow-water approach, solved in parallel on a graphical processing unit (GPU), able to drastically reduce calculation time, and implemented into the RiverFlow2D code (2017 version), was selected. Infiltration and evapotranspiration were included but in a simplified way, in order to face the calibration and validation simulations and because, despite the parallel approach, it is very demanding even for the computer time requirement. As a test case the Pescara river basin, located in Abruzzo, Central Italy, covering an area of 813 km2 and well representative of a typical medium-sized basin, was selected. The topography was described by a 10 × 10 m digital terrain model (DTM), covered by about 1,700,000 triangular elements, equipped with 11 rain gauges, distributed over the entire area, with some hydrometers and some fluviometric stations. Calibration, and validation were performed considering the flow data measured at a station located in close proximity to the mouth of the river. The comparison between the numerical and measured data, and also from a statistical point of view, was quite satisfactory. A further important outcome was the capability to highlight any differences between the numerical flow-rate balance carried out on the basis of the contributions of all known sources and the values actually measured. This characteristic of the applied modeling allows better calibration and verification not only of the effectiveness of much more simplified approaches, but also the entire network of measurement stations and could suggest the need for a more in-depth exploration of the territory in question. It would also enable the eventual identification of further hidden supplies of water inventory from underground sources and, accordingly, to enlarge the hydrographic and hydrogeological border of the basin under study. Moreover, the parallel computing platform would also allow the development of effective early warning systems, for example, of floods.

Iowa Experience on Local Calibration of AASHTOWare Pavement ME Design (PMED) for Jointed Plain Concrete Pavements

The AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement performance models and the associated AASHTOWare pavement ME design (PMED) software are nationally calibrated using design inputs and distress data largely obtained from National Long-Term Pavement Performance (LTPP) to predict Jointed Plain Concrete Pavement (JPCP) performance measures. To improve the accuracy of nationally-calibrated JPCP performance models for various local conditions, further calibration and validation studies in accordance with the local conditions are highly recommended, and multiple updates have been made to the PMED since its initial release in 2011, with the latest version (i.e., Ver. 2.5.X) becoming available in 2019. Validation of JPCP performance models after such software updates is necessary as part of PMED implementation, and such local calibration and validation activities have been identified as the most difficult or challenging parts of PMED implementation. As one of the states at the forefront of implementing the MEPDG and PMED, Iowa has conducted local calibration of JPCP performance models extending from MEPDG to updated versions of PMED. The required MEPDG and PMED inputs and the historical performance data for the selected JPCP sections were extracted from a variety of sources and the accuracy of the nationally-calibrated MEPDG and PMED performance prediction models for Iowa conditions was evaluated. To improve the accuracy of model predictions, local calibration factors of MEPDG and PMED performance prediction models were identified and gained local calibration experiences of MEPDG and PMED in Iowa are presented and discussed here to provide insight of local calibration for other State Highway Agencies (SHAs).

Model Calibration and Validation for the Fuzzy-EGARCH-ANN Model

This work shown as the fuzzy-EGARCH-ANN (fuzzy-exponential generalized autoregressive conditional heteroscedastic-artificial neural network) model does not require continuous model calibration if the corresponding DE algorithm is used appropriately, but other models such as GARCH, EGARCH, and EGARCH-ANN need continuous model calibration and validation so they fit the data and reality very well up to the desired accuracy. Also, a robust analysis of volatility forecasting of the daily S&P 500 data collected from Yahoo Finance for the daily spanning period 1/3/2006 to 20/2/2020. To our knowledge, this is the first study that focuses on the daily S&P 500 data using high-frequency data and the fuzzy-EGARCH-ANN econometric model. Finally, the research finds that the best performing model in terms of one-step-ahead forecasts based on realized volatility computed from the underlying daily data series is the fuzzy-EGARCH-ANN (1,1,2,1) model with Student’s t-distribution.

Calibration and validation of the mini-fiber EC image analysis instrument mean fiber diameter through direct or primary measurements

The Minifiber EC (MFEC) is a portable instrument for measuring the diameter of animal fibers. Its accuracy and precision have been estimated but by comparing its measurements with those of laboratory devices that had been calibrated on other devices in turn, not on a direct or primary measure of diameter. This work attempts to test direct measurements by gravimetry, Vernier mini caliper, microscope and the classic microprojector, using a non-deformable, high resistance synthetic fiber (Kevlar) for direct measurement. The MFEC instrument is calibrated with each mean fiber diameter obtained in direct measurements and its results are compared. The conclusions drawn are that it is possible to calibrate the MFEC instrument with direct measurements on Kevlar and measurement accuracy or tolerance of 0.28 microns is obtained. This indicates a very low biased mean fiber diameter measurement by MFEC.

Hydrologic modeling by means of a hybrid downscaling approach: an application to the Sai Gon–Dong Nai Rivers Basin

The spatial and temporal availability and reliability of hydrological data are substantial contribution to the accuracy of watershed modeling; unfortunately, such data requirements are challenging and perhaps impossible in many regions of the world. In this study, hydrological conditions are simulated using the hydrologic model-WEHY, whose data input are obtained from a hybrid downscaling technique to provide reliable and high temporal and spatial resolution hydrological data. The hybrid downscaling technique is coupled a hydroclimate and a machine learning models; wherein the global atmospheric reanalysis data, including ERA-Interim, ERA-20C, and CFSR are used for initial and boundary conditions of dynamical downscaling utilizing the Weather Research and Forecasting model (WRF). The machine learning model (ANN) then follows to further downscale the WRF outputs to a finer resolution over the studied watershed. An application of the combination of mentioned techniques is applied to the third-largest river basin in Vietnam, the Sai Gon–Dong Nai Rivers Basin. The validation of hybrid model is in the ‘satisfactory’ range. After the estimation of geomorphology and land cover within the watershed, WEHY's calibration and validation are performed based on observed rainfall data. The simulation results matched well with flow observation data with respect to magnitude for both the rising and recession time segments. In comparison among the three selected reanalysis data sets, the best calibration and validation results were obtained from the CFSR data set. These results are closer to the observation data than those using only the dynamic downscaling technique in combination with the WEHY model.

Application of Different Modelling Methods to Arbitrate Various Hydrological Attributes Using CMORPH and TRMM Satellite Data in Upper Omo-Gibe Basin of Ethiopia

Rainfall is a basic input parameter for hydrological modelling that exerts a great influence on the dependability of hydrological simulations. Limited availability of accurate and reliable precipitation data in Abelti watershed of Omo Gibe basin of Ethiopia coerces to use satellite rainfall data to design watershed management practices. The primary objective of this research is to find a better output by comparing and evaluating Climate Prediction Centre Morphing techniques (CMORPH) and Tropical Rainfall Measuring Mission (TRMM). Satellite precipitation products (SPPs) and inputs were incorporated to simulate stream flow. Sensitivity and uncertainty analysis, calibration, and validation of the model were conducted using Soil and Water Assessment Tool (SWAT), Calibration and Uncertainty Program 2012 (SWAT-CUP-2012), particularly the Sequential/Uncertainty Fitting (SUFI-2) algorithm for all rainfall inputs independently. The calibration and validation period was taken as 2003–2010 and 2011–2018, respectively. On the basis of the modelling results of SWAT and uncertainty analysis, TRRM relatively performed well than that of CMORPH. The result illustrated that the SWAT model thoroughly predicted the catchment runoff simulation for all SPPs. However, TRMM-based simulations capture the shape of the observed stream flow hydrograph, and there was slight under and overestimation of the stream flow volume simulated SPPs followed by the reduction of model performance statistics. Bias-corrected satellite rainfall-based simulations significantly improved the model performance as well as the volume of stream flow simulated. The detail study exhibited that the in situ-based simulation outperformed satellite products in terms of the objective functions in the study area.