Pablo Gamazo

Application of the GoRoSo Feedforward Algorithm to Compute the Gate Trajectories for a Quick Canal Closing in the Case of an Emergency

AbstractThe canal delivery system in the Left Hemidelta area of the Ebro River in Spain consists of a tree-shaped net of open canals. The overall system can be quickly isolated in the case of an emergency by closing the upstream pool. Transients, in which the initial state is hydraulically far from the final state, are difficult to handle and cannot be made in only one gate movement in order to protect the canal lining. Therefore, they have to be as smooth as possible. GoRoSo is a feedforward control algorithm for irrigation canals based on sequential quadratic programming. With this tool, it is possible to calculate the gate trajectories that smoothly carry the canal from the initial state to the final state by keeping the water depth constant at checkpoints. The paper shows the efficient implementation of GoRoSo in both the closure and opening operations of the canal delivery system.

Alternative Method to the Clément’s First Demand Formula for Estimating the Design Flow Rate in On-Demand Pressurized Irrigation Systems

Abstract It has been well documented in specialized literature that, under certain circumstances, the Clement’s first demand formula fails in estimating flow in water distribution networks. Through numerical examples, the authors show that the method fails when the number of hydrants supplied by a pipe is small or when the nominal flow rate of the hydrants is nonhomogeneous. In such cases, the normality hypothesis of the design flow rate random variable, an assumption needed by Clement’s formula, cannot be made. An alternative method for calculating the design flow rate as a nonnormal random variable is presented. The method works very well in all analyzed examples, mainly because the normality hypothesis is not required. The paper also provides a free-software R-script using freely available software that allows applying the proposed method to user-defined cases. The script helps to understand the method’s theoretical basis and can be used as a tool for checking the assumption of normality of data. There...

Operation of an irrigation canal by means of the passive canal control

Abstract Modern irrigation techniques involve large spatial and temporal demand variations in distribution networks. This makes the flow unsteady and generates perturbations that travel upstream along the network. Perturbations can also be generated by variable water inflows. This is the case when water is pumped into the network under variable energy rates, generating perturbations that travel downstream on the network. The passive canal control is a design criteria and a flow distribution method that make most of the storage capacity needed in any irrigation project, in order to mitigate the perturbations coming from both directions. In this paper, the passive canal control is applied to the design and operation of the Xerta-Sénia Canal Irrigation Project considering an unsteady free-surface flow model. The key aspect of the project is the location of irrigation reservoirs in-line with the canals at the same level, allowing water flow from canals to reservoir and vice versa. Three performance scenarios are evaluated, and the results of a simulation model are presented.

Potencial del efluente de los parques geotermales del Sistema Acuífero Guaraní para la calefacción de invernáculos

La energia geotermica disponible en Uruguay es de baja entalpia y se asocia al area de confinamiento del Sistema Acuifero Guarani, al noroeste del pais. Los principales usos del agua termal son el recreacional y la balneoterapia, los cuales generan un efluente que es vertido al ambiente con altas temperaturas. En este trabajo se evaluo el uso del efluente para la calefaccion de invernaculos y se presentan los balances termicos de invernaculos con y sin aporte de calefaccion. A su vez, se calcula el ahorro energetico obtenido frente a un sistema de calefaccion convencional. De acuerdo a los resultados, el poder contar con energia geotermica de baja entalpia para calefaccionar invernaculos representa un ahorro de energia electrica de 4,46 kW.h/m2 o de 0,61 l/m2 de gasoil en el mes de maxima demanda energetica. La investigacion permitio dilucidar la oportunidad de una accion que se viene esbozando como atenuante en el control de heladas y que permite mejorar la calidad de la fruta de tomate, reduciendo el impacto ambiental por el vertido directo del agua termal en los cursos de agua.

Evaluation of Bacterial Contamination as an Indicator of Viral Contamination in a Sedimentary Aquifer in Uruguay

In Uruguay, groundwater is frequently used for agricultural activities, as well as for human consumption in urban and rural areas. As in many countries worldwide, drinking water microbiological quality is evaluated only according to bacteriological standards and virological analyses are not mentioned in the legislation. In this work, the incidence of human viral (Rotavirus A, Norovirus GII, and human Adenovirus) and bacterial (total and thermotolerant coliform and Pseudomonas aeruginosa) contamination in groundwater in the Salto district, Uruguay, as well as the possible correlation between these groups of microorganisms, was studied. From a total of 134 groundwater samples, 42 (32.1%) were positive for Rotavirus, only 1 (0.7%) for both Rotavirus and Adenovirus, and 96 (72.6%) samples were positive for bacterial indicators. Results also show that Rotavirus presence was not associated with changes in chemical composition of the aquifer water. Bacteriological indicators were not adequate to predict the presence of viruses in individual groundwater samples (well scale), but a deeper spatial–temporal analysis showed that they are promising candidates to assess the viral contamination degree at aquifer scale, since from the number of wells with bacterial contamination the number of wells with viral contamination could be estimated.

A comparison of various schemes for solving the transport equation in many-core platforms

This paper addresses the resolution of the transport (advection–diffusion) equation in 3D by the use of the finite difference method as a discretization technique. In particular, our focus is the comparison of different time schemes (implicit, explicit and predictor-corrector) from the viewpoint of the numerical accuracy and the performance scalability in the use of massively parallel platforms. More in detail, each scheme is implemented in two parallel codes (C+CUDA and C+OpenMP), and in a sequential one (in C). We evaluated the performance of each implementation using several sizes of grid, and also, we measured the precision of these schemes for different discretization levels. The obtained results show that the GPU-based implementations offer significant speed-ups as compared to the CPU counterpart. Moreover, the explicit methods offer a much better performance scalability on this kind of massively parallel devices. This situation reveals that explicit methods can outperform implicit ones even if the accuracy is considered at least in contexts of non stiff problems.

On the appropriate definition of soil profile configuration and initial conditions for land surface–hydrology models in cold regions

Arctic and subarctic regions are amongst the most susceptible regions on Earth to global warming and climate change. Understanding and predicting the impact of climate change in these regions require a proper process representation of the interactions between climate, carbon cycle, and hydrology in Earth system models. This study focuses on land surface models (LSMs) that represent the lower boundary condition of general circulation models (GCMs) and regional climate models (RCMs), which simulate climate change evolution at the global and regional scales, respectively. LSMs typically utilize a standard soil configuration with a depth of no more than 4 m, whereas for cold, permafrost regions, field experiments show that attention to deep soil profiles is needed to understand and close the water and energy balances, which are tightly coupled through the phase change. To address this gap, we design and run a series of model experiments with a one-dimensional LSM, called CLASS (Canadian Land Surface Scheme), as embedded in the MESH (Modélisation Environmentale Communautaire – Surface and Hydrology) modelling system, to (1) characterize the effect of soil profile depth under different climate conditions and in the presence of parameter uncertainty; (2) assess the effect of including or excluding the geothermal flux in the LSM at the bottom of the soil column; and (3) develop a methodology for temperature profile initialization in permafrost regions, where the system has an extended memory, by the use of paleo-records and bootstrapping. Our study area is in Norman Wells, Northwest Territories of Canada, where measurements of soil temperature profiles and historical reconstructed climate data are available. Our results demonstrate a dominant role for parameter uncertainty, that is often neglected in LSMs. Considering such high sensitivity to parameter values and dependency on the climate condition, we show that a minimum depth of 20 m is essential to adequately represent the temperature dynamics. We further show that our proposed initialization procedure is effective and robust to uncertainty in paleo-climate reconstructions and that more than 300 years of reconstructed climate time series are needed for proper model initialization.

Assessing the explicit finite difference method on a massive parallel platform

This work addresses the resolution of the transport (advection-diffusion) equation in 3D using an explicit scheme for the finite d ifference method. Our initative is motivated by the advantages offered by this scheme for parallel processing. We propose three implementations, a sequential code (in C) and two parallel versions (C-CUDA and C with OpenMP). The experimental comparison is focused on the performance of each implementation using different grid sizes, and in the case of the OpenMP implementation, several number of threads. Additionally, we measured the accurancy of this scheme when the detail of the discretization grows. The results show that the parallel implementations reach significant speed up compared with the sequential counterpart. In addition, the GPU variant offers an further runtime reduction of up to 10x.