Prediction of the Sea Level from the PUMMA System Using SARIMA

The rising sea levels can threaten millions of people residing along the coast or lowlands. The risk can be mitigated by the sea-level prediction done by collecting information on the likelihood of rising sea levels. The Ministry of Marine Affairs and Fisheries of Indonesia has developed Perangkat Ukur Murah untuk Muka Air Laut (Inexpensive Device for Sea Level Measurement, PUMMA) to measure sea levels. PUMMA is located in remote monitoring stations based on Indonesian maritime area. The PUMMA system currently lacks a prediction feature. This objective of this study is to model the sea-level prediction using the dataset for one year, from July 2021 until July 2022. The seasonal autoregressive integrated moving average (SARIMA) method was used because SARIMA proved to be a flexible and versatile method for a dataset having noncomplex nature and seasonal patterns. This study has developed several models of the SARIMA. The model performance was evaluated using the mean absolute percentage error (MAPE), R-squared, mean square error (MSE), and root mean square error (RMSE) metrics. The SARIMA(1, 1, 0)(1, 1, 1)12 model achieved the lowest prediction error with an R-squared of 0.508, MSE of 0.0479, and RMSE of 0.069. Based on the performance, SARIMA(1, 1, 0)(1, 1, 1)12 model is feasible for predicting sea levels using the PUMMA dataset

Using Remote Sensing Techniques to Improve Hydrological Predictions in a Rapidly Changing World

Remotely sensed geophysical datasets are being produced at increasingly fast rates to monitor various aspects of the Earth system in a rapidly changing world. The efficient and innovative use of these datasets to understand hydrological processes in various climatic and vegetation regimes under anthropogenic impacts has become an important challenge, but with a wide range of research opportunities. The ten contributions in this Special Issue have addressed the following four research topics: (1) Evapotranspiration estimation; (2) rainfall monitoring and prediction; (3) flood simulations and predictions; and (4) monitoring of ecohydrological processes using remote sensing techniques. Moreover, the authors have provided broader discussions on how to capitalize on state-of-the-art remote sensing techniques to improve hydrological model simulations and predictions, to enhance their skills in reproducing processes for the fast-changing world

Modelling the ecology, dynamics and assessment of Nephrops norvegicus (Linnaeus 1758) in the waters around Ireland

Nephrops norvegicus is a valuable market species in the North-East Atlantic and it is of economic importance to Ireland. The present study investigated the status of the Aran ground stock, frequently ranked within the top two commercially valuable “fish” landed. Since 2002, under water TV surveys have been developed to provide a fishery independent estimate of burrow abundance in areas that exhibited a steady decrease in Nephrops over two decades contrasting with the increasing landings. In order to identify stock status and provide reliable information to management, we used a number of different approaches in the fields of time series analysis, spatial analysis and fisheries stock assessment. We examined the temporal fluctuations in a 16 year time series of landings in Aran grounds and found fluctuating cycles within an overall decreasing trend. This stock dynamic was also compared with the other main areas of harvest off the coast of Ireland (Smalls ground, Porcupine Bank, and the west Irish Sea) disclosing a regional common trend in the pattern of the stocks for connecting areas. Regional climatic influences (e.g NAO, AO and AMO) have been detected on various time scales ranging from month to years and the time series analysis method appears effective for detecting changes in fishing behaviours. Spatial analysis of the burrow density over the stock area revealed patchy distribution varying in size and intensity over the years with a spatio-temporal trend marked by a depletion of abundance in midfield with noticeable consequences for fishing vessel activity at a regional level. This spatial approach enabled the evaluation of the influence of the mud content of the seabed on the density of burrows and to explore the potential impact of the prevailing current circulation pattern during the planktonic stage of Nephrops on the level of recruitment by using remote sensing data. For an optimal fisheries management strategy, demographic information for the exploited species is necessary and for Nephrops, effective stock assessment is hampered because of the difficulty in age determination. A biomass model with a Schaefer surplus yield component and a data limited CMSY method were chosen to address the lack of age data and to predict biomass and related key fisheries reference points. Both approaches underline the ongoing decline of Nephrops abundance and reveal warning signals of unsustainable fishing exploitation

The Drought Risk Analysis, Forecasting, and Assessment under Climate Change

This Special Issue is a platform to fill the gaps in drought risk analysis with field experience and expertise. It covers (1) robust index development for effective drought monitoring; (2) risk analysis framework development and early warning systems; (3) impact investigations on hydrological and agricultural sectors; (4) environmental change impact analyses. The articles in the Special Issue cover a wide geographic range, across China, Taiwan, Korea, and the Indo-China peninsula, which covers many contrasting climate conditions. Hence, the results have global implications: the data, analysis/modeling, methodologies, and conclusions lay a solid foundation for enhancing our scientific knowledge of drought mechanisms and relationships to various environmental conditions

The predictability of UK drought using European weather patterns

PhD thesisThis thesis explores the use of a 167-year daily weather pattern (WP) classification (MO-30) in UK meteorological drought prediction. As MO-30 was recently introduced, necessary analyses as a precursor to building a forecast model are conducted. First, an exploratory analysis of MO30’s fundamental characteristics and its relation to UK precipitation and drought climatology is carried out. Second, two novel methods to find weekly to seasonal persistence in MO-30 are used in order to assess if there is any inherent predictability within MO-30. Third, a statistical model based on historical analogues for predicting 30-day periods of WPs is constructed, from which precipitation forecasts are derived. Finally, a dynamical ensemble prediction system is applied to forecast WPs, with resultant precipitation estimated in the same way as for the statistical method. MO-30 is shown to be suitable for precipitation-based analyses in the UK. Furthermore, intraWP precipitation variability, defined by the interquartile range, is lower in MO-30 compared to another commonly used WP classification. Six WPs are associated with nationwide drought, with several other WPs linked to regional drought. Results from the persistence analysis show that there are multi-month periods when small sets of four to six WPs dominate, and some of these periods coincide with notable meteorological events, including droughts and storms. Some WPs also behave as ‘attractors’, showing increased probability of reoccurrence despite other WPs occurring in-between. The statistical method for WP and precipitation forecasts is no more skilful than climatology, suggesting that the model did not adequately exploit the persistence identified previously. However, WPs are shown to be potentially useful for drought forecasting, as an idealised, perfect prognostic model (with WP observations as inputs rather than predictions) substantially improves skill, with a skill score of almost 0.5 (out of one) for north-eastern regions. Using a dynamical model to predict WPs, while keeping the precipitation estimation procedure the same as for the purely statistical method, yields overall higher skill compared to a benchmark statistical method for predicting droughts. The model also outperforms direct (modelled) dynamical precipitation forecasts for lead-times greater than 16 days during winter and autumn, with the greatest skill advantage for western regions. This is despite the relatively modest skill scores of all forecast models (rarely above 0.4). Again, high skill scores, of almost 0.8 on occasions, are achieved by the perfect prognostic model, demonstrating the potential for incorporating WPs into precipitation and drought forecast systems

Drought Risk Management in Reflect Changing of Meteorological Conditions

Droughts are one of the main extreme meteorological, and hydrological phenomena, which influence both the functioning of ecosystems, and many important sectors of human economic activity. Throughout the world, various direct changes in meteorological, and climatic conditions, such as: air temperature, humidity, and evapotranspiration can be observed. They have a significant influence upon the shaping of the phenomenon of drought. Land cover and land use can also be indirect factors influencing evapotranspiration, and, by the same token, the water balance in the water catchment area. They can also influence the course of the process of the drought. The observed climate change, manifested mainly by increases in temperature, in turn, influencing evapotranspiration, may cause intensification in terms of both the degree and frequency of droughts. Droughts related to changes in the hydrological regime, and to the decrease in water resources. Its results can be observed in various sectors, related, among others, to a demand for water for people, agriculture and the Industry. It can also prove problematic for water ecosystems. To reflect the aforementioned information, a reasonable drought risk management is indispensable in order to ease the water demand related problems in various sectors of human activity. This book presents original research on various drought indicators, modern measurement techniques used, among others, for monitoring and predicting droughts, drought indicator trends, the impact of insufficient precipitation on human activity in the context of climate change, and examples of modern solutions devised to prevent water shortages

Climate Change, Security Risks, and Violent Conflicts

Research on security-related aspects of climate change is an important element of climate change impact assessments. Hamburg has become a globally recognized center of pertinent analysis of the climate-conflict-nexus. The essays in this collection present a sample of the research conducted from 2009 to 2018 within an interdisciplinary cooperation of experts from Universität Hamburg and other institutions in Hamburg related to the research group “Climate Change and Security” (CLISEC). This collection of critical assessments covers a broad understanding of security, ranging from the question of climate change as a cause of violent conflict to conditions of human security in the Anthropocene. The in-depth analyses utilize a wide array of methodological approaches, from agent-based modeling to discourse analysis

2005 Florida Bay and Adjacent Marine Systems Science Conference; Hawk’s Cay Resort Duck Key, Florida; December 11-14, 2005: program and abstract book

Conference themes addressed: Applications and Restoration Targets, the Mangrove-Estuarine Transition Zone, Benthic Habitats, Water Quality, Physical Processes, Higher Trophic Levels, and Adjacent Systems

Advances in Sustainable River Management

The main objective of this Special Issue is to contribute in understanding and provide science-based knowledge, new ideas/approaches and solutions in sustainable river management, to improve water management policies and practices following different environmental requirements aspects