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This study hybridizes the background error covariance (BEC) of the hourly atmospheric three-dimensional variational data assimilation (3DVar) in Local Analysis (LA) operated at Japan Meteorological Agency using the flow-dependent BEC derived from the singular vector-based Mesoscale Ensemble Prediction System (MEPS) and the static BEC. The impact of introducing the hybrid BEC into the 3DVar is examined, along with its sensitivities to various factors like the ensemble size that is augmented by using lagged ensemble forecasts, the weight given to the ensemble-based component of BEC, the localization scales, and the use (or not) of the cross-variable correlation. This hybrid 3DVar system can be operated with small additional computational cost because it has no coupling with another ensemble data assimilation system. In sensitivity experiments, this hybrid 3DVar is shown to yield smaller forecast root mean square errors than the pure 3DVar, especially for surface variables. Moreover, the hybrid 3DVar shows a better equitable threat score for strong precipitation. These improvements were greater in the experiments with larger ensemble sizes that were increased by using lagged ensemble forecasts because of the reduced sampling errors in the ensemble-based BEC. These results were sensitive to the weight given to the ensemble-based BEC and the horizontal localization scale, whose optimal values were found to be approximately 0.5 and 100 km, respectively. The longer vertical correlation scale and the cross-variable correlation were also found important to create dynamically-balanced analysis, which is especially true for heavy rain cases. [ABSTRACT FROM AUTHOR]

The research conducted was aimed at developing a comprehensive method to evaluate the technical performance of an operator-centered Operation. The study was conducted under different water supply shortage conditions. The NekooAbad irrigation District was selected for simulation purposes using the Integral-Delay model to simulate flow distribution in the canals. The boundary conditions were based on historical statistics of surface water supply at the source. Seven scenarios were created, ranging from normal to severe water shortage. The technical assessment was based on two aspects: temporal analysis of the daily average water distribution adequacy in 13 main and 149 secondary off-takes. The second aspect included spatial analysis of the distribution of the mentioned index throughout the district. The study classified water distribution adequacy under each scenario. The results showed a pattern of reduced water distribution adequacy from the source to the downstream in all 13 secondary and the main canal. The daily average of the surface water distribution adequacy index ranged from over 10% in the normal scenario to less than 40% in the water scarcity scenarios. The percentage changes ranged from -95% to 64%, 90% to 56%, 89% to 54%, 89% to 50%, 86% to 49%, 86% to 46%, and 33% to 77%. The study also revealed a clear pattern of the operational system's inefficiency in the adequate distribution of surface water under water scarcity scenarios. Furthermore, it identified the vulnerable areas of the district through spatial regionalization maps of water distribution adequacy. [ABSTRACT FROM AUTHOR]

Geographical indication (GI) represents the specific good quality and reputation of the regional characteristics of agricultural products, which is a positive approach for stabilising the export of agricultural products, realising high quality and high prices for agricultural products and rural revitalisation. Based on the China-EU Geographical Indications Agreement, this paper discusses the differences between China and the European Union (EU) in terms of GI protection from three aspects: the institutional framework, the operational system, and the operational status of GIs. The purpose of the study is to identify the differences between China and the EU in the protection of GIs, China's shortcomings, and gaps, and to propose policy recommendations for China to protect GI products better, exploit the economic impact of GIs and enhance the competitiveness of China's exports.

The need for Sharia insurance products in the Muslim community continues to significantly increase. Sharia insurance offers sustainability in overcoming the risk of economic loss based on the principles of Islamic law. In addition, Sharia insurance can be a sustainable solution in providing risk management funds. This study aimed to analyze the development and sustainability of Islamic insurance as an alternative form of risk management, as well as its sustainability in the future. The general review is still in the form of the products offered and operational system models in the Sharia insurance industry. The systematic literature review method was used to obtain a visualization and general description of Islamic insurance, employing 774 data articles from 2010 to 2022. From the results of the analysis, it was found that research discussing Islamic insurance has demonstrated significant developments every year. Mitigating risks by offering the principles of Islamic law represents added value for the Islamic insurance industry. In addition, five models of Sharia insurance systems have been introduced and used; namely, the Mudharabah model, the modified Mudharabah model, the Wakalah model, the hybrid model, and the Waqf model. However, the products offered in Sharia insurance are not too numerous and are still focused on individual risk. Based on these results, Sharia insurance will undergo development in the future in terms of both the products offered and risk management. Of course, it can also lead to a transition to the development of sustainable Sharia insurance. [ABSTRACT FROM AUTHOR]

Comprehensive resilience management schemes are vital to urban risk governance and sustainable development. In this study, we decompose the urban physical system into the built environment subsystem (BES), information subsystem (IS), and metabolic flow subsystem (MFS), then construct a microscopic mechanism model of the urban system to quantify urban resilience, characterize the dynamics of urban resilience, and analyze the effect of network topology on urban resilience with the complex network method. The results provide several points: (1) There is a tipping point of the system, which crashes at 104.74% times the observed shock intensity in the case of Typhoon Morakot, taking the model parameters unchanged; (2) The topology of resource allocation network has a significant effect on urban resilience; (3) The externality of subsystem varies with the losses caused by negative shocks; and (4) The effects of network topology are contingent on the levels of urban resilience; therefore, for emergency management, city managers need to select resource allocation strategies based on urban resilience, by balancing the functional levels of operational and defensive parts. This study proposes a set of integrated management solutions based on resource deployment relationships among subsystems that can help urban systems better cope with shocks and increase resilience. • A new, multi-dimensional approach to urban resilience assessment was developed. • The topology of resource allocation network was validated as effective for urban resilience. • BES provides an important foundation and plays a stable role in the construction of urban resilience. • Resource allocation should adjust with resilience changes during shock periods. • A cross-system emergency management solution was constructed to cope with shocks. [ABSTRACT FROM AUTHOR]

Sea ice information has traditionally been associated with Manual Ice Charts, however the demand for accurate forecasts is increasing. This study presents an improved operational forecast system for the Arctic sea ice focusing on the Greenlandic waters. In addition, we present different observational sea ice products and conduct inter-comparisons. First, a re-analysis forced by ERA5 from 2000 to 2021 is evaluated to ensure that the forecast system is stable over time and to provide statistics for the users. The output is similar to the initial conditions for a forecast. Secondly, the sea ice forecast system is tested and evaluated based on two re-forecasts forced by the high resolution ECMWF-HRES forecast for the period from January 2019 to September 2021. Both the re-analysis and the re-forecasts include assimilation of sea surface temperatures and sea ice concentrations. We validate the re-analysis and the re-forecast systems for sea ice concentration against different remotely sensed observational products by computing the Integrated Ice Edge Error metric at the initial conditions of each system. The results reveal that the re-analysis and the re-forecast perform well. However, the summertime retreat of sea ice near the western Greenlandic coast seems to be delayed a few days compared with the observations. Importantly, part of the bias associated with the model representation of the sea ice edge is associated with the observational errors due to limitations in the passive microwave product in summertime and also near the coast. An inter-comparison of the observational sea ice products suggests that the model performance could be improved by assimilation of sea ice concentrations derived from a newly-developed automated sea ice product. In addition, analysis of persistence shows that the re-forecast has better skill than the persistence forecast for the vast majority of the time.

Combining optical and synthetic aperture radar (SAR) data for crop mapping has become a crucial way to improve classification accuracy, especially in cloudy and rainy areas. However, the acquisition of optical images is significantly unstable due to the influence of cloudy and rainy weather, which seriously restricts the application of this method in practice. To solve this problem, this study proposed an optical-SAR imagery-based rice mapping method which has the advantages of less dependence on optical images, easy operation and high classification accuracy. To account for the trait of sparse availability of optical images, this method only needs one clear sky optical image in the rice growth period and combined it with multi-temporal SAR images to achieve a high accuracy rice mapping result. Meanwhile, this paper also proposed a comprehensively multi-scale segmentation parameter optimization algorithm, which considers the area consistency, shape error and location difference between the segmented object and reference object, and adopts an orthogonal experiment approach. Based on the optical image, the boundaries of the parcel objects can be segmented, which were subsequently used to perform the object-oriented classification. The results show that the overall accuracy of the proposed method in Yangzhou City is 94.64%. Moreover, according to a random pick test, it is encouraging that the proposed method has strong robustness in response to the instability of the acquisition time of SAR images. A relatively high overall accuracy of 90.09% suggested that the proposed method can provide a reliable rice mapping result in cloudy and rainy areas. [ABSTRACT FROM AUTHOR]

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This paper aims to demonstrate the research-to-application and operational use of numerical hydrologic and hydraulic modeling to (a) quantify potential flash flood risks in small urban communities with high spatial resolution; (b) assess the effectiveness of possible flood mitigation measures appropriate for such communities; and (c) construct an effective operational urban flash flood warning system. The analysis is exemplified through case studies pertaining to a small community with dense housing and steep terrain in Tegucigalpa, Honduras, through numerical simulations with a customized self-contained hydrologic and hydraulic modeling software. Issues associated with limited data and the corresponding modeling are discussed. In order to simulate the extreme scenarios, 24-h design storms with return periods from 1 to 100 years with distinctive temporal and spatial distributions were constructed using both daily and hourly precipitation for each month of the rainy season (May–October). Four flood mitigation plans were examined based on natural channel revegetation and the installation of gabion dams with detention basins. Due to limitations arising from the housing layout and budgets, a feasible plan to implement both measures in selected regions, instead of all regions, is recommended as one of the top candidates from a cost-to-performance ratio perspective. Numerical modeling, customized for the conditions of the case study, is proven to be an effective and robust tool to evaluate urban flood risks and to assess the performance of mitigation measures. The transition from hydrologic and hydraulic modeling to an effective urban flash warning operational system is demonstrated by the regional Urban Flash Flood Warning System (UFFWS) implemented in Istanbul, Turkey. With quality-controlled remotely sensed precipitation observations and forecast data, the system generates forcing in the hydrologic and hydraulic modeling network to generate both historical and forecast flow to assist forecasters in evaluating urban flash flood risks. [ABSTRACT FROM AUTHOR]

Combining optical and synthetic aperture radar (SAR) data for crop mapping has become a crucial way to improve classification accuracy, especially in cloudy and rainy areas. However, the acquisition of optical images is significantly unstable due to the influence of cloudy and rainy weather, which seriously restricts the application of this method in practice. To solve this problem, this study proposed an optical-SAR imagery-based rice mapping method which has the advantages of less dependence on optical images, easy operation and high classification accuracy. To account for the trait of sparse availability of optical images, this method only needs one clear sky optical image in the rice growth period and combined it with multi-temporal SAR images to achieve a high accuracy rice mapping result. Meanwhile, this paper also proposed a comprehensively multi-scale segmentation parameter optimization algorithm, which considers the area consistency, shape error and location difference between the segmented object and reference object, and adopts an orthogonal experiment approach. Based on the optical image, the boundaries of the parcel objects can be segmented, which were subsequently used to perform the object-oriented classification. The results show that the overall accuracy of the proposed method in Yangzhou City is 94.64%. Moreover, according to a random pick test, it is encouraging that the proposed method has strong robustness in response to the instability of the acquisition time of SAR images. A relatively high overall accuracy of 90.09% suggested that the proposed method can provide a reliable rice mapping result in cloudy and rainy areas.

• Presented an unique HSR typology based on operational characteristics more independently of infrastructure models. • HSR operational system introduces a strongly differentiate connectivity between HSR European countries. • Not only economic attributes generate strong connection by international services; also cultural ones. • Infrastructural HSR spatial pattern is still designed for national services in Europe. [ABSTRACT FROM AUTHOR]

• DHI-GHM provides valuable hydrological information for data scarce areas. • DHI-GHM allows for hourly simulations, as often as new forecasts are available. • Physical based parameter estimation gives informed start for calibration activities. • DHI-GHM produces comparable results in world's main basins to other GHMs. • DHI-GHM is an operational system ideal to support decision-making. An operational global hydrological model (DHI-GHM) has been developed that provides historical, real-time, 10-day and seasonal forecast simulations at the global scale. DHI-GHM is comprised of a distributed gridded rainfall-runoff model with a spatial resolution of 0.1° and an agile kinematic routing model that moves water between model grid cells and sub-catchments and in the river system. Model output includes gridded hydrological variables, such as soil moisture content and different runoff components, and discharge at more than 1 million river points globally. DHI-GHM uses a novel parameterization scheme, where global data products of land surface physical characteristics are used to establish relations with model parameters, and thus DHI-GHM does not rely on local discharge data for model calibration. Multiple forcing datasets were tested, and the combination of ERA5 precipitation and Priestley-Taylor potential evaporation yielded the overall best results with a median KGE of 0.51 and average water balance error of 0.78% based on data from 1667 discharge stations worldwide. The model results and the operational system are particularly relevant for organizations with national, regional, or global scope who need information on large areas at once and for data scarce areas or projects without resources for local scale models. [ABSTRACT FROM AUTHOR]