An upstream–downstream/observation–model approach to quantify the human influence on drought

Kingston, Daniel G.; Mager, Sarah; Loft, Jessie; Underwood, Greg

doi:10.1080/02626667.2020.1849706

Cited by 4 publications

(2 citation statements)

References 26 publications

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“…Promoting research on targeted invasive species monitoring and allowing communities to collect thatch grass at pinch points, particularly those situated in protected areas, to reduce fuel load could be helpful in reducing species invasion and wildfires in the basin. Moreover, sustainable water management strategies (for example, introducing a water quota) in the upstream areas would ensure continual supply downstream to reduce the chances of drought conditions which promote spread of Category A transitions [87]. For example, this study found that spread of Category A transitions in the southern part is bound by the Okavango delta which is a demonstration of how lots of water facilitates maintenance of habitats for vegetation species that are endemic to this area [88].…”

Section: Discussionmentioning

confidence: 72%

Detecting Connectivity and Spread Pathways of Land Use/Cover Change in a Transboundary Basin Based on the Circuit Theory

2022

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Understanding the spatial spread pathways and connectivity of Land Use/Cover (LULC) change within basins is critical to natural resources management. However, existing studies approach LULC change as distinct patches but ignore the connectivity between them. It is crucial to investigate approaches that can detect the spread pathways of LULC change to aid natural resource management and decision-making. This study aims to evaluate the utility of the Circuit Theory to detect the spread and connectivity of LULC change within the Okavango basin. Patches of LULC change sites that were derived from change detection of LULC based on the Deep Neural Network (DNN) for the period between 2004 and 2020 were used. The changed sites were categorized based on the nature of the change of the classes, namely Category A (natural classes to artificial classes), Category B (artificial classes to natural classes), and Category C (natural classes to natural classes). In order to generate the resistance layer; an ensemble of machine learning algorithms was first calibrated with social-ecological drivers of LULC change and centroids of LULC change patches to determine the susceptibility of the landscape to LULC change. An inverse function was then applied to the susceptibility layer to derive the resistance layer. In order to analyze the connectivity and potential spread pathways of LULC change, the Circuit Theory (CT) model was built for each LULC change category. The CT model was calibrated using the resistance layer and patches of LULC change in Circuitscape 4.0. The corridor validation index was used to evaluate the performance of CT modeling. The use of the CT model calibrated with a resistance layer (derived from susceptibility modeling) successfully established the spread pathways and connectivity of LULC change for all the categories (validation index > 0.60). Novel maps of LULC change spread pathways in the Okavango basin were generated. The spread pathways were found to be concentrated in the northwestern, central, and southern parts of the basin for Category A transitions. As for category B transitions, the spread pathways were mainly concentrated in the northeastern and southern parts of the basin and along the major rivers. While for Category C transitions were found to be spreading from the central towards the southern parts, mainly in areas associated with semi-arid climatic conditions. A total of 186 pinch points (Category A: 57, Category B: 71, Category C: 58) were detected. The pinch points can guide targeted management LULC change through the setting up of conservation areas, forest restoration projects, drought monitoring, and invasive species control programs. This study provides a new decision-making method for targeted LULC change management in transboundary basins. The findings of this study provide insights into underlying processes driving the spread of LULC change and enhanced indicators for the evaluation of LULC spread in complex environments. Such information is crucial to inform land use planning, monitoring, and sustainable natural resource management, particularly water resources.

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Section: Discussionmentioning

confidence: 72%

Detecting Connectivity and Spread Pathways of Land Use/Cover Change in a Transboundary Basin Based on the Circuit Theory

2022

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“…To quantify the influence that agriculture and other human activities have on the frequency, distribution, and/or propagation of drought hazard, physical and engineering scientists have mostly employed numerical indexes (Al‐Faraj & Tigkas, 2016; Deo et al, 2009; Edalat & Stephen, 2019; Ghale et al, 2019; Guo, Huang, Huang, Wang, Fang, et al, 2019; Guo, Huang, Huang, Wang, Wang, & Fang, 2019; Huang et al, 2016; Jehanzaib, Shah, Kwon, & Kim, 2020; Li et al, 2019; Liu, Shi, & Sivakumar, 2020; Liu, Zhang, et al, 2020; Margariti et al, 2019; Mehran et al, 2015; Muhammad et al, 2020; Satgé et al, 2017; Shi et al, 2018; Tijdeman et al, 2018; Wan et al, 2017; Wang, Duan, et al, 2020; Wu et al, 2019; Xu et al, 2019; Yang et al, 2017; Zhao et al, 2019; Zou et al, 2018), statistical or geospatial analyses (Deo et al, 2009; Ghale et al, 2019; Jehanzaib, Shah, Kwon, & Kim, 2020; Kandakji et al, 2021; Liu et al, 2016; Liu, Zhang, et al, 2020; Mehran et al, 2015; Panda et al, 2007; Satgé et al, 2017; Wang, Duan, et al, 2020; Wang, Jiang, et al, 2020; Yang et al, 2017; Zou et al, 2018), and hydro‐meteorological models (Cook et al, 2009; Firoz et al, 2018; Ghale et al, 2019; He et al, 2017; Jehanzaib, Shah, Yoo, & Kim, 2020; Jiang et al, 2019; Kakaei et al, 2019; Kingston et al, 2021; Margariti et al, 2019; Mehran et al, 2015; Muhammad et al, 2020; Taufik et al, 2020; Tu et al, 2018; Wada et al, 2013; Wan et al, 2017; Wanders & Wada, 2015; Wang, Duan, et a...…”

Section: From Dry Weather To Water Shortages: Social Production and P...mentioning

confidence: 99%

Drought and society: Scientific progress, blind spots, and future prospects

Savelli

Rusca

Cloke

et al. 2022

WIREs Climate Change

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Human activities have increasingly intensified the severity, frequency, and negative impacts of droughts in several regions across the world. This trend has led to broader scientific conceptualizations of drought risk that account for human actions and their interplays with natural systems. This review focuses on physical and engineering sciences to examine the way and extent to which these disciplines account for social processes in relation to the production and distribution of drought risk. We conclude that this research has significantly progressed in terms of recognizing the role of humans in reshaping drought risk and its socioenvironmental impacts. We note an increasing engagement with and contribution to understanding vulnerability, resilience, and adaptation patterns. Moreover, by advancing (socio)hydrological models, developing numerical indexes, and enhancing data processing, physical and engineering scientists have determined the extent of human influences in the propagation of drought hazard. However, these studies do not fully capture the complexities of anthropogenic transformations. Very often, they portray society as homogeneous, and decision-making processes as apolitical, thereby concealing the power relations underlying the production of drought and the uneven distribution of its impacts. The resistance in engaging explicitly with politics and social power-despite their major role in producing anthropogenic droughtcan be attributed to the strong influence of positivist epistemologies in engineering and physical sciences. We suggest that an active engagement with critical social sciences can further theorizations of drought risk by shedding light on the structural and historical systems of power that engender every socioenvironmental transformation.

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Drought propagation under global warming: Characteristics, approaches, processes, and controlling factors

Zhuang

Hao

Singh

et al. 2022

Science of The Total Environment

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An upstream–downstream/observation–model approach to quantify the human influence on drought

Cited by 4 publications

References 26 publications

Detecting Connectivity and Spread Pathways of Land Use/Cover Change in a Transboundary Basin Based on the Circuit Theory

Detecting Connectivity and Spread Pathways of Land Use/Cover Change in a Transboundary Basin Based on the Circuit Theory

Drought and society: Scientific progress, blind spots, and future prospects

Drought propagation under global warming: Characteristics, approaches, processes, and controlling factors

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