Hydrological modelling with SWAT under conditions of limited data availability: evaluation of results from a Chilean case study

2008 ◽  
Vol 53 (3) ◽  
pp. 588-601 ◽  
Author(s):  
ALEJANDRA STEHR ◽  
PATRICK DEBELS ◽  
FRANCISCO ROMERO ◽  
HERNAN ALCAYAGA
2014 ◽  
Vol 59 (3-4) ◽  
pp. 731-750 ◽  
Author(s):  
A. Efstratiadis ◽  
A. Tegos ◽  
A. Varveris ◽  
D. Koutsoyiannis

APAC 2019 ◽  
2019 ◽  
pp. 449-455
Author(s):  
K. Kusuhara ◽  
M. Sakuraba ◽  
S. Onaka ◽  
S. Ichikawa ◽  
Y. Awazu

2020 ◽  
Vol 7 (1) ◽  
pp. 25-38
Author(s):  
Mijana Matošević Radić ◽  
Ivona Jukić ◽  
Antonija Roje

Social entrepreneurship is a relatively new topic of interest within the academic and the literature on it is limited. With the increase of interest in recent years from various interest groups, the concept of social enterprise has become more widespread. The purpose of this paper is to explore the link between social entrepreneurship and voluntourism, as one of the types of special interest tourism. Voluntourism, according to the concept of sustainable community development, relate all the stakeholders of such development. Moreover, social entrepreneurship could become an important vehicle for sustainable development of destinations. This paper proposes that niche tourism products and more specifically, voluntourism projects, under the prism of social entrepreneurship, can become the means towards Croatian product diversification and long-term environmental, social and economic sustainability. Quantitative research was conducted and the methodology entails a case study approach. Results indicate that there is a limited number of projects concerning social entrepreneurship in voluntourism in Croatia and also that discussed projects are not recognized. This study assessed the situation in Croatia and although it was comprehensive under conditions of limited data availability, it cannot speak to social entrepreneurship in voluntourism globally, but it can offer a foundation for future research in this area.


2021 ◽  
pp. 1-16
Author(s):  
Hajer Al-Faham

How does surveillance shape political science research in the United States? In comparative and international politics, there is a rich literature concerning the conduct of research amid conditions of conflict and state repression. As this literature locates “the field” in distant contexts “over there,” the United States continues to be saturated with various forms of state control. What this portends for American politics research has thus far been examined by a limited selection of scholars. Expanding on their insights, I situate “the field” in the United States and examine surveillance of American Muslims, an understudied case of racialized state control. Drawing on qualitative data from a case study of sixty-nine interviews with Arab and Black American Muslims, I argue that surveillance operated as a two-stage political mechanism that mapped onto research methodologically and substantively. In the first stage, surveillance reconfigured the researcher-researchee dynamic, hindered recruitment and access, and limited data-collection. In the second stage, surveillance colored the self-perceptions, political attitudes, and civic engagement of respondents, thereby indicating a political socialization unfolding among Muslims. The implications of this study suggest that researchers can mitigate against some, but not all, of the challenges presented by surveillance and concomitant forms of state control.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1044
Author(s):  
Yassine Bouabdallaoui ◽  
Zoubeir Lafhaj ◽  
Pascal Yim ◽  
Laure Ducoulombier ◽  
Belkacem Bennadji

The operation and maintenance of buildings has seen several advances in recent years. Multiple information and communication technology (ICT) solutions have been introduced to better manage building maintenance. However, maintenance practices in buildings remain less efficient and lead to significant energy waste. In this paper, a predictive maintenance framework based on machine learning techniques is proposed. This framework aims to provide guidelines to implement predictive maintenance for building installations. The framework is organised into five steps: data collection, data processing, model development, fault notification and model improvement. A sport facility was selected as a case study in this work to demonstrate the framework. Data were collected from different heating ventilation and air conditioning (HVAC) installations using Internet of Things (IoT) devices and a building automation system (BAS). Then, a deep learning model was used to predict failures. The case study showed the potential of this framework to predict failures. However, multiple obstacles and barriers were observed related to data availability and feedback collection. The overall results of this paper can help to provide guidelines for scientists and practitioners to implement predictive maintenance approaches in buildings.


2016 ◽  
Vol 8 (4) ◽  
pp. 279 ◽  
Author(s):  
Gijs Simons ◽  
Wim Bastiaanssen ◽  
Le Ngô ◽  
Christopher Hain ◽  
Martha Anderson ◽  
...  

AAPG Bulletin ◽  
2005 ◽  
Vol 89 (10) ◽  
pp. 1257-1274 ◽  
Author(s):  
Saibal Bhattacharya ◽  
John H. Doveton ◽  
Timothy R. Carr ◽  
Willard R. Guy ◽  
Paul M. Gerlach

Author(s):  
Alex van Dulmen ◽  
Martin Fellendorf

In cases where budgets and space are limited, the realization of new bicycle infrastructure is often hard, as an evaluation of the existing network or the benefits of new investments is rarely possible. Travel demand models can offer a tool to support decision makers, but because of limited data availability for cycling, the validity of the demand estimation and trip assignment are often questionable. This paper presents a quantitative method to evaluate a bicycle network and plan strategic improvements, despite limited data sources for cycling. The proposed method is based on a multimodal aggregate travel demand model. Instead of evaluating the effects of network improvements on the modal split as well as link and flow volumes, this method works the other way around. A desired modal share for cycling is set, and the resulting link and flow volumes are the basis for a hypothetical bicycle network that is able to satisfy this demand. The current bicycle network is compared with the hypothetical network, resulting in preferable actions and a ranking based on the importance and potentials to improve the modal share for cycling. Necessary accompanying measures for other transport modes can also be derived using this method. For example, our test case, a city in Austria with 300,000 inhabitants, showed that a shift of short trips in the inner city toward cycling would, without countermeasures, provide capacity for new longer car trips. The proposed method can be applied to existing travel models that already contain a mode choice model.


2019 ◽  
Vol 105 ◽  
pp. 123-132 ◽  
Author(s):  
Gelayol Golkarnarenji ◽  
Minoo Naebe ◽  
Khashayar Badii ◽  
Abbas S. Milani ◽  
Reza N. Jazar ◽  
...  

Author(s):  
Rachel Shin ◽  
Cory Searcy

A growing number of companies in the brewery industry have made commitments to measure and reduce their greenhouse gas (GHG) emissions. However, many brewers, particularly craft brewers with relatively low rates of production, have struggled to meet these commitments. The purpose of this research was to investigate the challenges and benefits of measuring and reducing GHG emissions in the craft brewery industry. The research was conducted in Ontario, Canada, which has seen strong recent growth in the craft brewery industry. A case study and semi-structured interviews among Ontario Craft Brewers were conducted. The case study found that indirect (scope 3 emissions under the WBCSD & WRI GHG Protocol) GHG sources accounted for 46.4% of total GHGs, with major sources from barley agriculture, malted barley transportation, and bottle production. Direct emissions (scope 1) accounted for only 14.9% of GHGs, while scope 2 emissions, comprised mainly of energy consumption, accounted for 38.7% of GHGs. The case study and interviews found that the main challenges in calculating brewery GHGs are secondary data availability, technical knowledge, and finances. The study also found that the main benefits for Ontario breweries to measure their GHGs include sustainability marketing and preserving the environment. The interviews also found a poor understanding of carbon regulation among Ontario Craft Brewers, which is interesting considering that Ontario implemented a provincial cap and trade program in 2017.


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