Water Resources Management: Integrated and Adaptive Decision Making

Karthe, Daniel; Bogárdi, János J.; Borchardt, Dietrich

doi:10.1007/978-3-030-60147-8_12

Cited by 6 publications

(5 citation statements)

References 118 publications

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“…Our results, which show that learning adaptive models have less observed variance in the nature system (e.g., Q M ), align with the philosophy of “adaptive management” strategies in facing increasing climate change uncertainty (Giordano & Shah, 2014; Karthe et al., 2021). However, it is also important to consider the causes of decreasing nature system uncertainty.…”

Section: Discussionsupporting

confidence: 83%

“…This might lead to a false conclusion that the adaptive model is more reliable (i.e., less uncertain). Second, although utilizing learning adaptive models shows a decreasing trend in Q M uncertainty, they could be impacted by uncertainty from incomplete knowledge of proposed model structural assumptions, such as a learning structure (Karthe et al., 2021), which would not be directly revealed in the modeling results. Such introduced assumption‐based uncertainty could be a barrier to interpreting modeling results and implementing adaptive management strategies (Allen & Gunderson, 2011; Lee, 2001).…”

Section: Discussionmentioning

confidence: 99%

“…As the complexity of a method and the number of parameters increase, the challenge of handling model uncertainty and variability increases (McLean & McAuley, 2012; Srikrishnan & Keller, 2021). This challenge is aggravated in CHNS modeling since there is often interest in both natural (e.g., streamflow) and human (e.g., water diversions) system outputs, and the co‐evolved natural and human dynamics in the complex system heavily rely on structural assumptions of the model (e.g., how humans react to environmental changes; Karthe et al., 2021; Messina et al., 2008). These model parameters and structural uncertainties significantly affect confidence in the inference and interpretation of model results (Allen & Gunderson, 2011; Allison et al., 2018; Kelly et al., 2013; Sun et al., 2016).…”

Section: Introductionmentioning

confidence: 99%

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The Effects of Model Complexity on Model Output Uncertainty in Co‐Evolved Coupled Natural‐Human Systems

Lin

Yang

2022

Earth's Future

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In the anthropogenic era, most major basins experience human activity, requiring an understanding of interactions between human society and the natural environment, that is, co-evolution in coupled natural-human systems (CNHS;Bauch et al., 2016;Wada et al., 2017). With the recognition of the socio-physical nature of emerging water challenges, many methods and modeling techniques, including system dynamics modeling, agent-based modeling, Bayesian networks, and so on (Blair & Buytaert, 2016;Kelly et al., 2013), have been proposed to address complex water management issues, often in the style of the Harvard Water Program (Brown et al., 2015;Milly et al., 2008;Reuss, 2003). Among them, coupling an agent-based model (ABM) with a process-based model (e.g., hydrological model) is a promising method to investigate emerging phenomena and heterogeneous human behaviors in CNHS (Berglund, 2015;Giuliani et al., 2016;Yang et al., 2020). In this coupling framework, each agent (e.g., irrigation district or reservoir) serves as a decision-making unit with a set of rules and attributes governing its behavior (e.g., diversion request or release) and interacts with other agents in a shared physical environment (e.g., river basin). As a result, various ABMs have been developed with agents that have different

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Section: Discussionsupporting

confidence: 83%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Effects of Model Complexity on Model Output Uncertainty in Co‐Evolved Coupled Natural‐Human Systems

Lin

Yang

2022

Earth's Future

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“…Besides tracking changes in the indices over time, water sustainability indices can also be used to assist in decision-making based on evidence [19,20]. This is particularly important in the context of complex and dynamic socio-environmental systems that require integrated and adaptive approaches [21]. While index-based assessment tools may not capture the full system complexity, they are pragmatic approaches for evaluating water management policies, governance frameworks, and institutional capacities [22,23].…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Water Sustainability Indices: A Systematic Review

Jarzebski,

Karthe,

Chapagain

et al. 2024

Water

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The achievement of water sustainability necessitates the development and application of comprehensive assessment tools to monitor and evaluate the impact of water resource management. This article presents a comprehensive comparative analysis of various water sustainability indices, emphasizing their underlying principles, methodologies, and potential applications. Our study reveals the diverse landscape of existing indices, illustrating that even indices with similar names can vary significantly in scope and methodology. Via a systematic review of 124 publications, this study provides insights into existing composite indices related to water sustainability, highlighting their specific applications and potential contributions to water resource management and sustainability. The information gathered from the selected papers was synthesized and analyzed thematically to identify common patterns through keyword co-occurrence mapping, SDG mapping, standard review protocols, and cluster analyses. Through a cluster analysis, we identified six distinct clusters of indices, highlighting the need for careful consideration in selecting appropriate ones. Moreover, our analysis of co-occurring keywords underscores the close relationship between sustainable development, water resources, water supply, and water conservation within the context of water-related indices. Notably, these indices address not only sustainable development goal six but also a number of other interconnected goals. It was also found that “sustainability index” is a common name for different nature water indices. This review also identifies research gaps in the existing literature. However, significant limitations exist, including a lack of historical application and future projections for many current water sustainability indicators. Without the ability to track changes over time and project the future, identifying areas of improvement and measuring progress toward long-term water sustainability goals becomes challenging. Furthermore, many indices are complex and designed for watershed or regional levels, limiting their adaptability to different contexts. Despite these challenges, indices remain valuable tools for assessing and managing water resources sustainably, addressing various dimensions of sustainability, and supporting decision-making processes across different sectors and contexts.

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“…Besides tracking changes in the indices over time, water sustainability indices can also be used to assist in decision-making based on evidence (Vollmer et al 2016, Waas et al 2014. This is particularly important in the context of complex and dynamic socio-environmental systems that require integrated and adaptive approaches (Karthe et al 2021). While index-based assessment tools may not capture the full system complexity, they are pragmatic approaches for evaluating water management policies, governance frameworks, and institutional capacities (Jiménez et al 2020;Panda et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Water Sustainability Indices: A Systematic Review

Jarzebski,

Karthe,

Chapagain

et al. 2023

Preprint

Self Cite

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The achievement of water sustainability necessitates the development and application of comprehensive assessment tools to monitor and evaluate the impact of water resources management. This paper provides a comparative analysis of a wide range of water sustainability indices described in recent scientific literature, focusing on their underlying principles, methodologies, and potential applications. By systematic review of 124 publications, this study provides insights into existing composite indices related to water sustainability, highlighting their specific applications and potential contributions to water resource management and sustainability. The information gathered from the selected papers was synthesized and analysed thematically to identify common patterns through keyword co-occurrence mapping, SDG mapping, standard review protocol, and cluster analyses. This review also identified research gaps in the existing literature. The analysed indices represent a range of sectors and dimensions related to water resource management. This study found that indices serve as a tool for assessing and managing water resources sustainably, addressing diverse aspects of sustainability, and aiding decision-making in different sectors and contexts.

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Water Resources Management: Integrated and Adaptive Decision Making

Cited by 6 publications

References 118 publications

The Effects of Model Complexity on Model Output Uncertainty in Co‐Evolved Coupled Natural‐Human Systems

The Effects of Model Complexity on Model Output Uncertainty in Co‐Evolved Coupled Natural‐Human Systems

Comparative Analysis of Water Sustainability Indices: A Systematic Review

Comparative Analysis of Water Sustainability Indices: A Systematic Review

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