Mapping Blue Economy Potential Using Spatial Statistical Downscaling Model: Analysis of the Impact of Climate Change on Freshwater Fish Resources

Mutiara Aghnyn; Rofah Nur Rachmawati; Achmad Abdurrazzaq; Nameeta Brahme; Aparna Dixit; Arti Hadap

doi:10.58524/ijhes.v3i1.440

Authors

Mutiara Aghnyn Department of Mathematics, Indonesia Defense University
Rofah Nur Rachmawati Department of Mathematics, Indonesia Defense University
Achmad Abdurrazzaq Department of Mathematics, Indonesia Defense University http://orcid.org/0000-0002-9227-023X
Nameeta Brahme Department of Physics and Astrophysics, Pt. Ravishankar Shukla University http://orcid.org/0000-0003-2326-8328
Aparna Dixit Department of Basic Sciences and Humanities, Pranveer Singh Institute of Technology Kanpur http://orcid.org/0000-0002-6685-6552
Arti Hadap Department of Physics, Narsee Monjee Institute of Management Studies

DOI:

https://doi.org/10.58524/ijhes.v3i1.440

Keywords:

blue economy, climate change, integrated nested laplace approximation (inla), spatial modeling, statistical downscaling

Abstract

Blue Economy is a sustainable economic concept that focuses on utilizing economic resources in marine, coastal and land ecosystems. Sustainable use of freshwater resources in the blue economy for inland waters supports economic growth with environmental balance. The Statistical Downscaling method is used to understand the impact of climate change on freshwater fish resources. To carry out mapping of the potential of the blue economy, it is carried out by statistical downscaling modeling with satellite variables with Integrated Nested Laplace Approximation parameter estimates. The response variable is satellite variables in the form of average rainfall. The modeling results show that Kalipuro District has the highest blue economy potential, while Kalibaru has the lowest. From the research results, that satellite data on average rainfall is a strong basis for printing statistical downscaling, increasing efficiency with open source digital data sources. Satellite data integration, maximizing analysis and comprehensive blue economy potential efficiency.

References

Adibrata, S., Lingga, R., and Nugraha, M. A. (2022). Penerapan blue economy dengan budidaya udang vaname (Litopenaeus vannamei). Journal of Tropical Marine Science, 5(1), 45–54. https://doi.org/10.33019/jour.trop.mar.sci.v5i1.2964

Barange, Bahri, Beveridge, MCM, Cochrane, KL, Funge-Smith, Poulain, and eds. (2018). Impacts of climate change on fisheries and aquaculture: synthesis of current knowledge, adaptation and mitigation options. Food and Agriculture of United Nations.

Benzaken, D., Adam, J. P., Virdin, J., and Voyer, M. (2024). From concept to practice: Financing sustainable blue economy in lessons learnt from the Seychelles experience. Marine Policy, 163. https://doi.org/10.1016/j.marpol.2024.106072

Blangiardo, M., and cameletti, M. (2015). Spatial and Spatio-temporal Bayesian Models with R-INLA.

Eum, H. Il, Gupta, A., and Dibike, Y. (2020). Effects of univariate and multivariate statistical downscaling methods on climatic and hydrologic indicators for Alberta, Canada. Journal of Hydrology, 588. https://doi.org/10.1016/j.jhydrol.2020.125065

Fudge, M., Ogier, E., and Alexander, K. A. (2023). Marine and coastal places: Wellbeing in a blue economy. Environmental Science and Policy, 144, 64–73. https://doi.org/10.1016/j.envsci.2023.03.002

Gandhi, V. (2015). Interfacing Brain and Machine. In Brain-Computer Interfacing for Assistive Robotics (pp. 7–63). Elsevier. https://doi.org/10.1016/b978-0-12-801543-8.00002-8

Hadijati, M., and Fitriyani, N. (2011). Prediction of Daily Rainfall in Dodokan Watershed Based on Statistical Downscaling Model: An Effort to Manage Watershed Ecosystems. In Eastern Journal of Agricultural and Biological Sciences. EJABS.

Hespanhol, L., Vallio, C. S., Costa, L. M., and Saragiotto, B. T. (2019). Understanding and interpreting confidence and credible intervals around effect estimates. In Brazilian Journal of Physical Therapy (Vol. 23, Issue 4, pp. 290–301). Revista Brasileira de Fisioterapia. https://doi.org/10.1016/j.bjpt.2018.12.006

Kim, J., Yoo, D., Hong, K., and Chun, B. C. (2023). Health behaviors and the risk of COVID-19 incidence: A Bayesian hierarchical spatial analysis. Journal of Infection and Public Health, 16(2), 190–195. https://doi.org/10.1016/j.jiph.2022.12.013

Kullenberg, G. (2001). Contributions of marine and coastal area research and observations towards sustainable development of large coastal cities. In Ocean & Coastal Management (Vol. 44).

Prayuda, R., Sary, D. V., and Riau, U. I. (2019). Strategi Indonesia dalam Implementasi Konsep Blue Economy terhadap Pemberdayaan Masyarakat Pesisir di Era Masyarakat Ekonomi ASEAN. Indonesian Journal of International Relations, 3(2), 46–64.

Riebler, A., Sørbye, S. H., Simpson, D., and Rue, H. (2016). An intuitive Bayesian spatial model for disease mapping that accounts for scaling. Mathematics and Statistic. http://arxiv.org/abs/1601.01180

Riebler, A., Sørbye, S. H., Simpson, D., Rue, H., Lawson, A. B., Lee, D., and MacNab, Y. (2016). An intuitive Bayesian spatial model for disease mapping that accounts for scaling. Statistical Methods in Medical Research, 25(4), 1145–1165. https://doi.org/10.1177/0962280216660421

Saha, D., and Manickavasagan, A. (2021). Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review. In Current Research in Food Science (Vol. 4, pp. 28–44). Elsevier B.V. https://doi.org/10.1016/j.crfs.2021.01.002

Sukiyono, K., Romdhon, M. M., Mulyasari, G., Yuliarso, M. Z., Nabiu, M., Trisusilo, A., Reflis, Napitupulu, D. M., Nugroho, Y., Puspitasari, M. S., Sugiardi, S., Arifudin, and Masliani. (2024). Smallholder palm oil and sustainable development goals (SDGs) achievement: An empirical analysis. Sustainable Futures, 8. https://doi.org/10.1016/j.sftr.2024.100233

Tefera, G. W., Ray, R. L., and Wootten, A. M. (2024). Evaluation of statistical downscaling techniques and projection of climate extremes in central Texas, USA. Weather and Climate Extremes, 43. https://doi.org/10.1016/j.wace.2023.100637

Wijayanti, A., and Ramlah, R. (2022). Pengaruh Concept Blue Economy Dan Green Economy Terhadap Perekonomian Masyarakat Kepulauan Seribu. Owner, 6(3), 1732–1743. https://doi.org/10.33395/owner.v6i3.906

Yuan, D., and Mancuso, N. (2023). SuSiE PCA: A scalable Bayesian variable selection technique for principal component analysis. IScience, 26(11). https://doi.org/10.1016/j.isci.2023.108181

Zhang, M., Guo, Z. Y., Dong, G. T., and Tan, J. G. (2023). Projected heat wave increasing trends over China based on combined dynamical and multiple statistical downscaling methods. Advances in Climate Change Research, 14(5), 758–767. https://doi.org/10.1016/j.accre.2023.09.001