scholarly journals Community-University Partnership in Water Education and Linkage Process. Study Case: Manglaralto, Santa Elena, Ecuador

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 1998
Author(s):  
Paúl Carrión-Mero ◽  
Fernando Morante-Carballo ◽  
Gricelda Herrera-Franco ◽  
María Jaya-Montalvo ◽  
Denise Rodríguez ◽  
...  
Keyword(s):  
Water Resources ◽  
Relevant Information ◽  
Human Interaction ◽  
Aquifer Recharge ◽  
Engineering Structures ◽  
Water Education ◽  
University Partnership ◽  
Community Projects ◽  
Education Culture ◽  
The Impact

Universities have the mission to serve society by being pragmatic, diverse, and multidisciplinary. Similar to society in general, these centers have a common challenge: finding a way to articulate projects that favor the demands and needs of vulnerable rural sectors. In this case, the community-university partnership is based on the interaction of the Manglaralto population, represented by the Junta Administradora del Agua Potable Regional de Manglaralto and the Escuela Superior Politécnica del Litoral (ESPOL), both from Ecuador. Specifically, it is based on a collaborative relationship since 2005, through the Centro de Investigación y Proyectos Aplicados a Ciencias de la Tierra (CIPAT) of the ESPOL. This work aims to evaluate the community-university partnership through the results obtained in community work projects. In addition, it describes the resolution of problems reached on the sustainability of water resources in the parish of Manglaralto (Ecuador). The methodology was based on (i) the description of the existing community-university interaction framework, (ii) the analysis of the community projects that CIPAT developed in the period 2017–2020, and finally, (iii) the evaluation of the impact of the actions carried out on the sustainability of the coastal aquifer. The community-university partnership has generated relevant information (e.g., water reserves, extraction processes, aquifer recharge, and care of the resource) for the community and has allowed for the strengthening and transmitting of knowledge in different specialties (education, culture, and environment). In the 2017–2020 period, four community projects were carried out with students, researchers, and the inhabitants of the rural area of Manglaralto. These projects allowed wells for water extraction and engineering structures such as dikes and green filters that help the use and recharge the aquifer. In addition, the initiatives carried out made it possible to inform the population of the importance of the sustainable exploitation of water resources. In general, this work made it possible to identify a natural laboratory of human interaction in which the results obtained are based on the collaboration and contribution of all the participating actors.

Modeling the impact of aquifer recharge, in-stream water savings, and canal lining on water resources in the Walla Walla Basin

2018 ◽  
Vol 4 (2) ◽  
pp. 275-289 ◽  
Author(s):  
Jacob Scherberg ◽  
Jason Keller ◽  
Steven Patten ◽  
Troy Baker ◽  
Michael Milczarek
Keyword(s):  
Water Resources ◽  
Stream Water ◽  
Aquifer Recharge ◽  
Water Savings ◽  
The Impact ◽  
Walla Walla

scholarly journals An Evaluation Methodology for Interactive Reinforcement Learning with Simulated Users

Biomimetics ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 13
Author(s):  
Adam Bignold ◽  
Francisco Cruz ◽  
Richard Dazeley ◽  
Peter Vamplew ◽  
Cameron Foale
Keyword(s):  
Reinforcement Learning ◽  
Information Source ◽  
Human Interaction ◽  
Evaluation Methodology ◽  
External Information ◽  
Preliminary Evaluation ◽  
Learning Agents ◽  
Learning Agent ◽  
Knowledge Bias ◽  
The Impact

Interactive reinforcement learning methods utilise an external information source to evaluate decisions and accelerate learning. Previous work has shown that human advice could significantly improve learning agents’ performance. When evaluating reinforcement learning algorithms, it is common to repeat experiments as parameters are altered or to gain a sufficient sample size. In this regard, to require human interaction every time an experiment is restarted is undesirable, particularly when the expense in doing so can be considerable. Additionally, reusing the same people for the experiment introduces bias, as they will learn the behaviour of the agent and the dynamics of the environment. This paper presents a methodology for evaluating interactive reinforcement learning agents by employing simulated users. Simulated users allow human knowledge, bias, and interaction to be simulated. The use of simulated users allows the development and testing of reinforcement learning agents, and can provide indicative results of agent performance under defined human constraints. While simulated users are no replacement for actual humans, they do offer an affordable and fast alternative for evaluative assisted agents. We introduce a method for performing a preliminary evaluation utilising simulated users to show how performance changes depending on the type of user assisting the agent. Moreover, we describe how human interaction may be simulated, and present an experiment illustrating the applicability of simulating users in evaluating agent performance when assisted by different types of trainers. Experimental results show that the use of this methodology allows for greater insight into the performance of interactive reinforcement learning agents when advised by different users. The use of simulated users with varying characteristics allows for evaluation of the impact of those characteristics on the behaviour of the learning agent.

scholarly journals Analysing the Impact of Climate Change on Hydrological Ecosystem Services in Laguna del Sauce (Uruguay) Using the SWAT Model and Remote Sensing Data

2021 ◽  
Vol 13 (10) ◽  
pp. 2014
Author(s):  
Celina Aznarez ◽  
Patricia Jimeno-Sáez ◽  
Adrián López-Ballesteros ◽  
Juan Pablo Pacheco ◽  
Javier Senent-Aparicio
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Ecosystem Services ◽  
Water Resources ◽  
Swat Model ◽  
Remote Sensing Data ◽  
Erosion Control ◽  
Sensing Data ◽  
Extreme Precipitation Events ◽  
The Impact

Assessing how climate change will affect hydrological ecosystem services (HES) provision is necessary for long-term planning and requires local comprehensive climate information. In this study, we used SWAT to evaluate the impacts on four HES, natural hazard protection, erosion control regulation and water supply and flow regulation for the Laguna del Sauce catchment in Uruguay. We used downscaled CMIP-5 global climate models for Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 projections. We calibrated and validated our SWAT model for the periods 2005–2009 and 2010–2013 based on remote sensed ET data. Monthly NSE and R2 values for calibration and validation were 0.74, 0.64 and 0.79, 0.84, respectively. Our results suggest that climate change will likely negatively affect the water resources of the Laguna del Sauce catchment, especially in the RCP 8.5 scenario. In all RCP scenarios, the catchment is likely to experience a wetting trend, higher temperatures, seasonality shifts and an increase in extreme precipitation events, particularly in frequency and magnitude. This will likely affect water quality provision through runoff and sediment yield inputs, reducing the erosion control HES and likely aggravating eutrophication. Although the amount of water will increase, changes to the hydrological cycle might jeopardize the stability of freshwater supplies and HES on which many people in the south-eastern region of Uruguay depend. Despite streamflow monitoring capacities need to be enhanced to reduce the uncertainty of model results, our findings provide valuable insights for water resources planning in the study area. Hence, water management and monitoring capacities need to be enhanced to reduce the potential negative climate change impacts on HES. The methodological approach presented here, based on satellite ET data can be replicated and adapted to any other place in the world since we employed open-access software and remote sensing data for all the phases of hydrological modelling and HES provision assessment.

scholarly journals Personality and Dementia: an Approach to Differential Profile of the Caregiver

2011 ◽  
Vol 1 (3) ◽  
pp. 85-94
Author(s):  
Elena de Andrés-Jiménez ◽  
Rosa Mª Limiñana-Gras ◽  
Encarna Fernández-Ros
Keyword(s):  
Relevant Information ◽  
Personality Profile ◽  
Family Carers ◽  
Psychological Variables ◽  
People With Dementia ◽  
The Family ◽  
Study Population ◽  
The One ◽  
The Impact

The aim of this study is to determine the existence of a characteristic personality profile of family carers of people with dementia. The correct knowledge and use of psychological variables which affect the carer, helps to promote appropriate actions to mitigate the impact of care and improve the carer’s quality of life and likewise the one of the person cared for. The study population consists of 69 family carers of people with dementia, members of various associations and care centers. The results allow us to identify a characteristic personality profile for these carers and it reveals a specific psychological working in this sample, although we cannot directly relate it with the tasks of caring for people with this disease, this profile gives us very relevant information to pay more attention to the needs of this group. Moreover, the analysis of personality styles depends on the sex of the family carer, showing, once again, that the woman is in a situation of most vulnerability.

scholarly journals Simulation of Pan-Evaporation Using Penman and Hamon Equations and Artificial Intelligence Techniques

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 793
Author(s):  
Abdul Razzaq Ghumman ◽  
Mohammed Jamaan ◽  
Afaq Ahmad ◽  
Md. Shafiquzzaman ◽  
Husnain Haider ◽  
...  
Keyword(s):  
Wind Speed ◽  
Water Resources ◽  
Arid Regions ◽  
Fuzzy Inference ◽  
Sunshine Duration ◽  
Pan Evaporation ◽  
Estimation Of Parameters ◽  
Inference System ◽  
Daunting Task ◽  
The Impact

The evaporation losses are very high in warm-arid regions and their accurate evaluation is vital for the sustainable management of water resources. The assessment of such losses involves extremely difficult and original tasks because of the scarcity of data in countries with an arid climate. The main objective of this paper is to develop models for the simulation of pan-evaporation with the help of Penman and Hamon’s equations, Artificial Neural Networks (ANNs), and the Artificial Neuro Fuzzy Inference System (ANFIS). The results from five types of ANN models with different training functions were compared to find the best possible training function. The impact of using various input variables was investigated as an original contribution of this research. The average temperature and mean wind speed were found to be the most influential parameters. The estimation of parameters for Penman and Hamon’s equations was quite a daunting task. These parameters were estimated using a state of the art optimization algorithm, namely General Reduced Gradient Technique. The results of the Penman and Hamon’s equations, ANN, and ANFIS were compared. Thirty-eight years (from 1980 to 2018) of manually recorded pan-evaporation data regarding mean daily values of a month, including the relative humidity, wind speed, sunshine duration, and temperature, were collected from three gauging stations situated in Al Qassim, Saudi Arabia. The Nash and Sutcliffe Efficiency (NSE) and Mean Square Error (MSE) evaluated the performance of pan-evaporation modeling techniques. The study shows that the ANFIS simulation results were better than those of ANN and Penman and Hamon’s equations. The findings of the present research will help managers, engineers, and decision makers to sustainability manage natural water resources in warm-arid regions.

scholarly journals Concurrent neuroimaging and neurostimulation reveals a causal role for dlPFC in coding of task-relevant information

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Jade B. Jackson ◽  
Eva Feredoes ◽  
Anina N. Rich ◽  
Michael Lindner ◽  
Alexandra Woolgar
Keyword(s):  
Magnetic Stimulation ◽  
Dorsolateral Prefrontal Cortex ◽  
Relevant Information ◽  
Irrelevant Information ◽  
Visual Object ◽  
Information Coding ◽  
Frontoparietal Cortex ◽  
Dorsolateral Prefrontal ◽  
The Impact

AbstractDorsolateral prefrontal cortex (dlPFC) is proposed to drive brain-wide focus by biasing processing in favour of task-relevant information. A longstanding debate concerns whether this is achieved through enhancing processing of relevant information and/or by inhibiting irrelevant information. To address this, we applied transcranial magnetic stimulation (TMS) during fMRI, and tested for causal changes in information coding. Participants attended to one feature, whilst ignoring another feature, of a visual object. If dlPFC is necessary for facilitation, disruptive TMS should decrease coding of attended features. Conversely, if dlPFC is crucial for inhibition, TMS should increase coding of ignored features. Here, we show that TMS decreases coding of relevant information across frontoparietal cortex, and the impact is significantly stronger than any effect on irrelevant information, which is not statistically detectable. This provides causal evidence for a specific role of dlPFC in enhancing task-relevant representations and demonstrates the cognitive-neural insights possible with concurrent TMS-fMRI-MVPA.

Opportunities for harnessing the increased contribution of glacier and snowmelt flows in the Ganges basin

Water Policy ◽  
2013 ◽  
Vol 15 (S1) ◽  
pp. 9-25 ◽  
Author(s):  
Bharat R. Sharma ◽  
Devaraj de Condappa
Keyword(s):  
Climate Change ◽  
Aquifer Recharge ◽  
Eastern India ◽  
Ganges Basin ◽  
Additional Water ◽  
Set Up ◽  
Tehri Dam ◽  
The Ganges ◽  
The Impact ◽  
The Himalaya

The topography of the Ganges basin is highly variable, with the steep mountainous region of the Himalaya upstream and the large fertile plains in eastern India and Bangladesh downstream. The contribution from the glaciers to streamflows is supposed to be significant but there is uncertainty surrounding the impact of climate change on glaciers. An application of the Water Evaluation and Planning model was set up which contained an experimental glaciers module. The model also examined the possible impacts of an increase in temperature. The contribution from glaciated areas is significant (60–75%) in the Upper Ganges but reduces downstream, falling to about 19% at Farakka. Climate change-induced rise in temperature logically increases the quantity of snow and ice that melts in glaciated areas. However, this impact decreases from upstream (+8% to +26% at Tehri dam) to downstream (+1% to +4% at Farakka). Such increases in streamflows may create flood events more frequently, or of higher magnitude, in the upper reaches. Potential strategies to exploit this additional water may include the construction of new dams/reservoir storage and the development of groundwater in the basin through managed aquifer recharge. The riparian states of India, Nepal and Bangladesh could harness this opportunity to alleviate physical water scarcity and improve productivity.

Sign in / Sign up

Export Citation Format

Share Document