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Comparison of machine learning and process-based SWAT model in simulating streamflow in the Upper Indus Basin

This study appraised and compared the performance of process-based hydrological SWAT (soil and water assessment tool) with a machine learning-based multi-layer perceptron (MLP) models for simulating streamflow in the Upper Indus Basin. The study period ranges from 1998 to 2013, where SWAT and MLP models were calibrated/trained and validated/tested for multiple sites during 1998–2005 and 2006–2013,

An ecofeminist position in critical practice: Challenging corporate truth in the Anthropocene

Drawing on selected discourses of non-essentialist ecofeminism, this article proposes and substantiates an ecofeminist position. This distinct position is shown to bring with it a capacity to challenge widely uncontested, corporate-produced truths regarding the benefits and the legitimacy of certain commercial activities. Three historical cases inform the discussion: the fights led by Rachel Carso

Application of Machine Learning and Remote Sensing in Hydrology

Water is vital to all life on earth, but its management is becoming more difficult owing to the behavior of water in nature such as water dynamics, water movements, and different forms of water in nature. In addition, population growth, the impact of climate change, and the inappropriate use of water resources add more complexity to water resource management. The integration of natural sciences ne

The key to scaling in the digital era : Simultaneous automation, individualization and interdisciplinarity

In this paper, we develop a theoretical framework that explains how digital technologies can help small businesses generate competitive advantages for scaling. To gain and sustain competitive advantages, small businesses traditionally had to choose between cost leadership and differentiation strategies. Digital technologies enable small businesses to reduce their costs and at the same time enhance