Geology topics

Hsiao-Hsuan Wang

Publications and source records attributed to Hsiao-Hsuan Wang.

4 recordsLinked to original sources

USGS2026

A catalogue of Do's and Don'ts in the modeling of environmental systems

Modeling plays a vital role in understanding and managing complex environmental systems, but its credibility and quality depend heavily on a comprehensive set of defensible model activities and practices, especially when the system of interest is plagued with uncertainties and conflicting stakeholder perspectives. This paper proposes a catalogue of Do's and Don'ts to guide modelers in addressing the many pertinent considerations through the whole modeling cycle. This practical tool provides advice on approaching modeling effectively through adhering to good modeling practice. It emphasizes model choices that align with the model purpose and context, and the justification and documentation of modeling decisions and assumptions. Managing uncertainty is a core consideration. The identification, assessment and reporting of these uncertainties is important across the entire modeling process, which spans problem framing, technical design, implementation and application phases. Such good practices are critical for transparency and reliability of the modeling.

Environmental Modelling and Software↗

USGS2024

Balancing ecology and practicality to rank waterbodies for preventative invasive species management

‘Early detection and rapid response’ (EDRR) is the most successful framework for preventative invasive species management, but prioritizing localized EDRR actions with limited resources is challenging. An approach that ranks individual locations, such as waterbodies, for EDRR by combining an invasive species' establishment risk with the practicality of managing it could help set reasonable priorities. Here, we worked with regional practitioners in Arkansas, USA, and the broader Southeastern USA to co-produce a workflow for preventative aquatic invasive species management that (1) estimates establishment risk under current and future climates with a species distribution model, (2) scores waterbodies according to difficulty of eradicating an aquatic invasive species if it were introduced and (3) combines establishment risk and eradication difficulty scores to rank waterbodies according to preventative management priority. As our focal species, we used giant salvinia ( Salvinia molesta ), a floating aquatic fern ranked among the worst weeds in the world due to its negative socio-ecological impacts and difficulty to eradicate once established. Current establishment risk is low for much of our study area, but under future climate scenarios (RCP 8.5), areas with >60% giant salvinia establishment risk increased from 546 km 2 to 30,219 km 2 between 2023 and 2040 in Arkansas. We found giant salvinia establishment risk and eradication difficulty are independent of each other ( r = 0.28), and it follows that, alone, early detection tools such as species distribution models are insufficient for managers to prioritize sites for EDRR. Practical implication : We envision our approach fitting into a potential EDRR workflow that cascades from broad- to local-scale. To illustrate, (1) horizon scanning and/or climate matching generates lists of high-risk invasive species; (2) species lists are narrowed according to eradication feasibility scores; (3) for all remaining species, all waterbodies across a geography of interest receive prioritization rankings based on establishment risk and eradication difficulty scores. Given that climate change makes predicting invasive species' distributions a moving target, combining co-produced eradication difficulty scoring with species distribution modelling will balance rigour with practicality when prioritizing locations for EDRR.

Arkansas, Louisiana, Mississippi, Missouri, Oklaho↗

USGS2024

Setting a pluralist agenda for water governance: Why power and scale matter

Global water systems are facing unprecedented pressures, including climate change-driven drought and escalating flood risk, environmental contamination, and over allocation. Water management and governance typically lack integration across spatial scales, including relationships between surface and ground water systems. They also routinely ignore connectivity across temporal scales, including the need for intergenerational water planning. As a global and interdisciplinary group of scientists, we seek to highlight how power and scale dynamics influence and determine water outcomes. We argue that attending to complex water systems challenges requires understanding the function and influence of power at different temporal and spatial scales. Building this understanding is key to designing multi-scalar, reflexive, and pluralistic policy solutions that avoid ineffective or unintended outcomes. We use a co-learning process to reveal important lessons for the challenge of interdisciplinary research and set a pluralist agenda for understanding power and scale in future water governance.

WIREs Water↗

USGS2021

Socio-technical scales in socio-environmental modeling: Managing a system-of-systems modeling approach

System-of-systems approaches for integrated assessments have become prevalent in recent years. Such approaches integrate a variety of models from different disciplines and modeling paradigms to represent a socio-environmental (or social-ecological) system aiming to holistically inform policy and decision-making processes. Central to the system-of-systems approaches is the representation of systems in a multi-tier framework with nested scales. Current modeling paradigms, however, have disciplinary-specific lineage, leading to inconsistencies in the conceptualization and integration of socio-environmental systems. In this paper, a multidisciplinary team of researchers, from engineering, natural and social sciences, have come together to detail socio-technical practices and challenges that arise in the consideration of scale throughout the socio-environmental modeling process. We identify key paths forward, focused on explicit consideration of scale and uncertainty, strengthening interdisciplinary communication, and improvement of the documentation process. We call for a grand vision (and commensurate funding) for holistic system-of-systems research that engages researchers, stakeholders, and policy makers in a multi-tiered process for the co-creation of knowledge and solutions to major socio-environmental problems.

Environmental Modelling and Software↗