Utilization Management Research Articles

Integrating carbon reduction and ecological resilience strategies in the silk road economic corridor

The Silk Road Economic Belt has become a pivotal region for China's sustainable development, focusing on the balance between carbon emissions and ecological resilience. Understanding the coordination between these factors is crucial for advancing China's westward economic shift and optimizing urban and demographic structures. This study investigates the coupling and coordination dynamics between carbon emissions and ecological resilience across 15 key cities in the Silk Road Economic Belt, using data from 2008 to 2018. By applying a "pressure-state-response" framework, the ecological resilience of the region is quantitatively assessed. Spatial disparities and the dynamic evolution of coupling coordination are analyzed through the Gini coefficient and kernel density estimation. The findings reveal significant regional variations in ecological resilience and a decline in coupling coordination over time. Shifts in the patterns of coordination indicate opportunities for enhancing resource utilization and environmental management. This research provides theoretical insights for policymakers to improve green development strategies, optimize industrial structures, and plan urban green spaces more effectively within the Silk Road Economic Belt.

52 The bag is not always bad: Implementing a two-step method for urine testing on the inpatient paediatric units

Abstract Background Urinary tract infections (UTIs) are a common source of infection in children. Best practice for diagnosis includes interpreting a urinalysis (UA) and urine culture. Urine cultures obtained through bladder catheterization are invasive and time consuming. A two-step approach with noninvasive UA screen, followed by urine culture if positive has previously demonstrated a reduction in unnecessary catheterizations and urine cultures in children 6-24 months with suspected UTIs. Pre-intervention, there was inconsistent use of screening point-of-care urinalysis prior to bladder catheterization for culture. Objectives To decrease the number of bladder catheterizations in children 6-24 months with a negative screen on Point of Care Test (POCT) urinalysis by 25% over 1 year on paediatrics wards at a paediatric tertiary care centre. Outcome measures: 1. Proportion of bladder catheterizations with negative or no UA screen prior 2. Proportion of UA completed as POCT rather than lab sample Process measures: 1. Number of urinary catheterizations performed for UTI screen 2. Number of times pathway is followed Balancing measure: 1. Missed UTIs Design/Methods Baseline data was collected from the paediatric inpatient units at a tertiary paediatric hospital from April 2020 – April 2021. A two-step pathway for collecting urine samples was adopted, including POCT UA screen on a bag sample, followed by bladder catheterization for culture if positive. The pathway was implemented using the Model for Improvement and multiple PDSA cycles. Intervention focused on education, interdisciplinary collaboration, and process standardization. Results Baseline data demonstrated a high rate of urinary catheter cultures despite a negative UA or no UA prior (69%). After pathway implementation, this rate decreased to 23%, with a reduction in initial UA collected by catheter from 14% to 5% (figure 1). The number of POCT UA performed has increased from a median of 64% pre-intervention to 80% post-intervention, resulting in fewer samples processed in the lab (figure 2). Conclusion Variability in practice for specimen choice for collection and investigation contributed to unnecessary catheterizations. Process standardization successfully improved patient-centered care and efficiency. Next steps include broadening pathway inclusion criteria to the 3–6-month age group. Potential competing interests This work was partially supported by the UMC (Utilization Management Committee) Resource Stewardship Grant. The authors declare no additional sources of funding or conflicts of interest.

Sustainable Development in Rural Underserved Communities through Improved Responsible Management of Decentralized Wastewater Infrastructure: A Focus on the Alabama Black Belt.

Despite global efforts on meeting sustainable development goals by 2030, persistent and widespread sanitation deficits in rural, underserved communities in high-income countries─including the United States (US)─challenge achieving this target. The recent US federal infrastructure funding, coupled with research efforts to explore innovative, alternative decentralized wastewater systems, are unprecedented opportunities for addressing basic sanitation gaps in these communities. Yet, understanding how to best manage these systems for sustainable operations and maintenance (O&M) is still a national need. Here, we develop an integrated management approach for achieving such sustainable systems, taking into account the utility structure, operational aspects, and possible barriers impeding effective management of decentralized wastewater infrastructure. We demonstrate this approach through a binomial logistic regression of survey responses from 114 public and private management entities (e.g., water and sewer utilities) operating in 27 states in the US, targeting the rural Alabama Black Belt wastewater issues. Our assessment introduces policy areas that support sustainable decentralized wastewater systems management and operations, including privatizing water-wastewater infrastructure systems, incentivizing/mandating the consolidation of utility management of these systems, federally funding the O&M, and developing and retaining water-wastewater workforce in rural, underserved communities. Our discussions give rise to a holistic empirical understanding of effective management of decentralized wastewater infrastructure for rural, underserved communities in the US, thereby contributing to global conversations on sustainable development.

GIS and Bhuvan Data as Tools for Agricultural Development and Economic Empowerment in Pune District

This paper examines the use of Geographic Information Systems (GIS) and Bhuvan data to enhance agricultural development and drive economic empowerment in Pune District, Maharashtra, India. GIS technology has been instrumental in optimizing water management, land utilization, and crop management. Likewise, Bhuvan data plays a critical role in monitoring crop growth, identifying diseases, and evaluating land use patterns. These advancements contribute to improved crop yields and increased profits for farmers. The paper highlights the significant impact of GIS and Bhuvan data in promoting agricultural progress in Pune district and suggests that these tools could be effectively implemented in other regions to achieve similar benefits.

Elucidating Heterogeneous Li Insertion Using Single-Crystalline and Freestanding Layered Oxide Thin Film.

The kinetics of interfacial ion insertion govern the uniformity of electrochemical reactions, playing a crucial role in lithium-ion battery performance. In two-dimensional lithium-conducting layered-oxide battery particles, variation in insertion rates across insertion channels remains unclear due to poorly defined crystal orientation at the solid-liquid interface and solid-state-lithium-diffusion length. This ambiguity complicates understanding inhomogeneous lithium-insertion channels activation. A systematic study requires crystallographically predefined interfaces and in situ lithium-concentration mapping. Here, we fabricated a freestanding, (104)-oriented-LiNi1/3Mn1/3Co1/3O2 single-crystal thin film using dissolution-induced release and performed in situ scanning-transmission-X-ray-microscopy to spatially resolve lithium-insertion at well-defined-interfaces. We observed heterogeneous lithium-concentration evolution due to channel-by-channel insertion rate variation, despite the potential for homogeneous lithium distribution via a solid-solution-phase at equilibrium in NMC111. Increasing current density exacerbates this heterogeneity, highlighting channel-by-channel variation. Our findings provide critical insights into battery electrode utilization and lifetime management, potentially guiding the design of more efficient and durable lithium-ion batteries.

The Effects of Different Grazing Periods on the Functional Traits of Leymus chinensis (Trin.) Tzvelev in a Typical Inner Mongolia Steppe

Plant functional traits are effective indicators and predictors of environmental change, revealing plants’ ecological countermeasures and adaptability through phenotypic plasticity. We conducted a 6-year grazing experiment on typical temperate grassland to assess the impact of different grazing periods on the plasticity and variability of the functional traits of Leymus chinensis and the relationship between traits and individual plant biomass. Our study included four treatments: CK (enclosure), T1 (grazing in May and July), T2 (grazing in June and August), and T3 (grazing in July and September). The results for 13 functional traits indicated that the T3 treatment showed the smallest reduction in individual plant biomass, plant height, leaf area, stem length, and leaf length, making it the most effective type of grassland management and optimal for the maintenance and restoration of L. chinensis traits. Under T1, T2, and T3, the plasticity of stem weight, total leaf weight, total leaf area, and stem length was higher and crucial for regulating individual plant biomass. The results underscore that the changes and plasticity of dominant species under grazing treatments are key to understanding the relationship between ecosystem function and grassland management. This study provides a theoretical basis and data support for the adaptive utilization and restoration management of typical grassland resources.

The study on the Internet of Things implication in improving the punctuality of air transportation in bad weather

Air travel is a popular choice for people who seek to travel outside in the present. It greatly promotes communication and economic development. However, flight delays can have seriously disappointing effects on various aspects. For passengers, they not only need a long time to wait and additional expenses, but they also experience more psychological stress. And airlines face economic losses, reduced customer satisfaction, and disruptions in flight scheduling, which further affect operational efficiency. Therefore, this paper aims to explore potential methods that are combined with the Internet of Things to improve the punctuality of air transportation in order to ease the hard situation of flight delays caused by bad weather. And based on the previous related papers, the author of this paper thinks a kind of meteorological monitoring and early warning system can be built based on the Internet of Things to improve real-time weather monitoring and flight scheduling, as well as ground service optimization. Hence, people can improve the punctuality of air transportation by optimizing resource utilization and cost management so that the whole industry can bring significant economic benefits to airline companies and improved travel experiences to passengers.

Medicaid managed care restrictions on medications for the treatment of opioid use disorder.

To examine whether Medicaid managed care plan (MCP) utilization management policies for buprenorphine-naloxone and injectable naltrexone are related to key state Medicaid program policy decisions. We abstracted data on state Medicaid regulatory and policy information from publicly available sources and publicly available insurance benefit documentation from all 241 Medicaid MCPs operating in 2021. In this cross-sectional study, we used bivariate and multivariate analyses to examine whether Medicaid MCP prior authorization and quantity limits on receipt of buprenorphine and injectable naltrexone were associated with key state Medicaid choices to leverage federal funds to expand coverage and eligibility (Medicaid expansion, 1115 waivers) and to regulate Medicaid MCPs (uniform preferred drug lists, medical loss ratio remittance). Models were adjusted for MCP characteristics, including profit status, behavioral health contracting arrangement, National Committee for Quality Assurance accreditation, size, market share, and state opioid overdose death rates. Average marginal effects (AME) were reported. Utilization management was common among MCPs, and restrictions were more commonly applied to buprenorphine than injectable naltrexone, despite its higher cost. States that required MCPs to comply with utilization management policies stipulated in a uniform preferred drug list were more likely to require prior authorization for buprenorphine (AME: 0.29, 95% CI: 0.15-0.42) and injectable naltrexone (AME: 0.25, 95% CI: 0.12-0.38). MCPs in states that required plans to pay back earnings above a certain threshold were less likely to require prior authorization for buprenorphine (AME: -0.30, 95% CI: -0.43 to -0.18). Restrictions on medications for opioid use disorder are widespread among MCPs and vary by medication. State Medicaid regulatory and policy characteristics were strongly linked to MCPs' utilization management approaches. State Medicaid policy and contracting approaches may be levers to eliminate utilization management restrictions on medications for opioid use disorder.

A deep reinforcement learning approach towards distributed Function as a Service (FaaS) based edge application orchestration in cloud-edge continuum

Serverless computing has emerged as a new cloud computing model which in contrast to IoT offers unlimited and scalable access to resources. This paradigm improves resource utilization, cost, scalability and resource management specifically in terms of irregular incoming traffic. While cloud computing has been known as a reliable computing and storage solution to host IoT applications, it is not suitable for bandwidth limited, real time and secure applications. Therefore, shifting the resources of the cloud-edge continuum towards the edge can mitigate these limitations. In serverless architecture, applications implemented as Function as a Service (FaaS), include a set of chained event-driven microservices which have to be assigned to available instances. IoT microservices orchestration is still a challenging issue in serverless computing architecture due to IoT dynamic, heterogeneous and large-scale environment with limited resources. The integration of FaaS and distributed Deep Reinforcement Learning (DRL) can transform serverless computing by improving microservice execution effectiveness and optimizing real-time application orchestration. This combination improves scalability and adaptability across the edge-cloud continuum. In this paper, we present a novel Deep Reinforcement Learning (DRL) based microservice orchestration approach for the serverless edge-cloud continuum to minimize resource utilization and delay. This approach, unlike existing methods, is distributed and requires a minimum subset of realistic data in each interval to find optimal compositions in the proposed edge serverless architecture and is thus suitable for IoT environment. Experiments conducted using a number of real-world scenarios demonstrate improvement of the number of successfully composed applications by 18%, respectively, compared to state-of-the art methods including Load Balance, Shortest Path algorithms.

B-013 Improving the Workflow of Blood and Coagulation Tests in clinical laboratory through the Utilization of Laboratory Automation Track Systems

Abstract Background The Laboratory Automation Track System (TLA) is an automated system designed for executing highly repetitive tasks within a laboratory, commonly applied in biochemical and immunological testing systems. It aims to reduce human errors in specimen handling, enhance the overall process quality, and provide better Turnaround Time (TAT) from specimen collection to result reporting. For the first time in our laboratory, we have integrated the blood and coagulation systems with TLA. Consequently, we seek to evaluate the differences in the testing workflow and reporting efficiency of the blood and coagulation systems after being connected to TLA. Methods Abbott GLP systems Track was the TLA system for connecting with blood and coagulation systems. Two Sysmex XN-9100 fully automatic hematology systems and two Sysmex CS-5100 fully automatic coagulation analyzers were developed for blood and coagulation system, respectively. TUNYEN Laboratory Information System was established for Laboratory information system (LIS). Results Through the analysis of quality indicators and integration with intelligent information systems, improvements have been made, including the reduction of blood collection tube usage, efficient manpower utilization management, tracking of specimen progress and achievement of timely reporting rates.(1)Approximately 2,915 blood collection test tubes are saved every month, with a converted cost of 0.15 USD per tube, and a total saving of 437 USD. And reduce the carbon emissions of 32 kgCO2e, comply with the spirit of ESG sustainable development.(2)The TLA no longer requires staff to collect and deliver specimens as in the past,reducing staff and enhancing work efficiency.One of manpower was saved and new inspection items were developed.(3)Tracking of specimen progress:The laboratory has set up a specimen tracking system to monitor the specimen delivery location and provide timely response to the clinical status.The one-hour TAT for blood and coagulation increased from 82.0% and 76.9% before improvement to 91.8% and 93.3% after improvement respectively. Conclusions The implementation of Laboratory Automation Track Systems (TLA) leads to a reduction in medical errors and specimen sample volume, while also enhancing accuracy and precision, thereby improving the safety of laboratory staff. Although the introduction of TLA may require an initial investment, it brings the benefits of automation, offering ease and efficiency to laboratory processes.

A Survey on the Utilization and Quality Management of Handy Tests or Point-of-Care In Vitro Diagnostic Tests in Korea

A Survey on the Utilization and Quality Management of Handy Tests or Point-of-Care <i>In Vitro</i> Diagnostic Tests in Korea

Visualization Method for Mesoscale Eddies Characteristics in Ocean Flow Fields Based on Variable Particle Systems

Visualization of ocean flow fields is a major area of interest in marine science. Existing visualization methods based on randomly generated particles tend to exhibit a uniform distribution. While this approach effectively represents ocean flow fields, it inadequately conveys the characteristic structures within the flow in an intuitive manner. Ocean eddies, as crucial components of ocean dynamics (Patrizio &amp; Thompson, 2021), are key features in visualizing ocean flow fields. Mesoscale eddies, which contain 90% of the ocean's kinetic energy, play a vital role in transporting this energy. These eddies significantly influence local marine environments and are instrumental in understanding the kinetic energy of ocean flow fields, providing valuable insights for fields such as oceanography, meteorology, and climate research. The aim of this study is to establish a method based on variable particle systems. Initially, a feature set for mesoscale eddies and a parameter set for variable particles are defined. By mapping the feature set to the parameter set, we express the characteristic structure of mesoscale eddies dynamically. Using ocean flow field data, we demonstrate the method's ability to effectively highlight the characteristic structures of mesoscale eddies within the flow field through qualitative and quantitative evaluation metrics. By analyzing and visualizing ocean flow fields, we can gain a deeper understanding of their spatiotemporal evolution, thereby uncovering the patterns and regularities of their movement. This research approach not only facilitates the effective development, utilization, and sustainable management of marine resources but also aligns with the demands of digital ocean technology for visualizing marine spatial information.

Prediction and spatial–temporal changes of soil organic matter in the Huanghuaihai Plain by combining legacy and recent data

Soil organic matter (SOM) is critical for soil fertility, crop growth, and plays an important role in the global carbon cycle and climate change. Therefore, spatial prediction of SOM is important to rational soil resource utilization, agricultural production, and ecological environment management. However, large-area SOM mapping research heavily relies on legacy soil data, and large-scale recent SOM mapping may not be possible or have lower accuracy due to limited or less recent data availability. In this study, we aimed to improve SOM prediction and mapping accuracy by combining legacy data with limited recent data. Three models, namely, partial least squares regression (PLSR), random forest (RF), and one-dimensional convolutional neural network (1D-CNN), were applied and compared. The results showed that combining legacy and recent data effectively improved SOM prediction accuracy compared to using only recent data. Among the three modeling methods, 1D-CNN exhibited superior performance, with an averaged determination coefficient of the prediction (R2) of 0.58, a root mean square error (RMSE) of 4.56 g/kg, and a ratio of performance to interquartile distance (RPIQ) of 2.05. The predicted SOM content for both legacy (1980 s) and recent (2010 s) periods showed similar spatial distribution patterns throughout the Huanghuaihai Plain. Generally, there was a noticeable trend of increasing SOM content from northwest to southeast, with higher values observed in Jiangsu and lower values concentrated in Henan, Hebei, and Shandong regions within the study area. Over time, SOM contents in the Huanghuaihai Plain showed an increasing trend, with an average increase of 5.90 g/kg from legacy to recent period. This study provides a promising approach for improving SOM prediction and mapping accuracy at large scales, particularly when recent data availability is limited.

A Study on Food waste, Religious guidance and its impact on Environment in Central Kashmir: A Sample Survey

In economy of any state food waste plays a significant role and its wastage has direct impact on environment and on economy. The decreasing of food waste clearly would lead to improved land utilization and water resources management of that area. In the present study carried out in Central Kashmir, a survey of the study area was carried out and discussions were held with the people of the study area i.e., district Srinagar, Budgam and Ganderbal of Kashmir. The study based on surveying methodology was conducted by designing a suitable questionnaire to bring out the current methods practiced for food waste disposal in central Kashmir, J&amp;K. The data collected from survey was statistically analysed using standard statistical tools. The study revealed that food waste is directly or indirectly responsible for in environment pollution. It was suggested that responsible persons of area and government should come forward and play their role in controlling food waste and proper disposal of food wastage. We know plastic pollution is the aggregation of plastic objects and particles in the Earth's environment that adversely affects humans, wildlife and their habitat. The elders of study area revealed that a number of water bodies vanished in last 3-4 decades because of overpopulation, poor drainage system, deviation from Islamic teaching and climate change. Finally, it was suggested that everyone should play his/her role in reducing food waste as it is a social, environmental as well as a religious crime

An Attribution Analysis of Runoff Alterations in the Danjiang River Watershed for Sustainable Water Resource Management by Different Methods

Determining the relative roles of climatic versus anthropogenic factors in runoff alterations is important for sustainable water resource utilization and basin management. The Danjiang River watershed is a crucial water resource area of the middle route of the South-to-North Water Transfer Project. In this study, four widely used quantitative methods, including the simple linear regression, the double mass curve, the paired year with similar climate conditions, and an elasticity method based on the Budyko framework were applied to detect the relative contribution of climatic and anthropogenic factors to runoff variation in the Danjiang River watershed. The calculation processes of each method were systematically explained, and their characteristics and applications were summarized. The results showed that runoff decreased significantly (p &lt; 0.05) with an average change rate of −3.88 mm year−1 during the period of 1960–2017, and a significant change year was detected in 1989 (p &lt; 0.05). Generally, consistent estimates could be derived from different methods that human activity was the dominant driving force of significant runoff reduction. Although the impacts of human activity estimated by the paired year with similar climate conditions method varied among paired years, the other three methods demonstrated that human activity accounted for 80.22–92.88% (mean 86.33%) of the total reduction in the annual runoff, whereas climate change only contributed 7.12–19.78% (mean 13.67%). The results of this study provide a good reference for estimating the effects of climate change and human activities on runoff variation via different methods.

Enhancing renewable energy utilization and energy management strategies for new energy yachts

Hydrogen energy, due to its clean and efficient nature, has shown great potential during the current transition period in the shipbuilding industry. However, the application of hydrogen energy in ship energy systems is influenced by variations in operational load and the integration of new energy sources during actual navigation. To address these issues, this paper focuses on optimizing and scheduling the operation of ships under various navigation conditions, considering the distributed nature of hydrogen energy. System simulations were conducted to model the photovoltaic (PV), proton exchange membrane fuel cells (PEMFCs), lithium batteries (LIBs), electrolytic cells (ECs), and energy storage modules of yacht energy systems. Component boundaries and objective functions were set, and two cases (excess photovoltaic state and constant power state) were designed to optimize and regulate the energy balance of hydrogen-powered yachts, enhancing their comprehensive utilization of renewable energy. By comparing the changes in ship energy under the two cases, it was concluded that case 1 ensures the maximum utilization of renewable energy. When photovoltaic power generation is insufficient, the PEMFC and LIB in the system provide the required power to achieve a supply-demand balance. Moreover, when PV power generation is sufficient, hydrogen energy is used to store renewable energy. The optimization method designed in this study can, to some extent, maximize the application of renewable energy in new energy yachts, ensuring the efficiency of the comprehensive energy system of new energy yachts, reducing emissions, and improving the sustainability and economic efficiency of the ships.

Managing Injuries and Utilizing Protein: A Literature Review on Strategies for Enhancing Athletic Performance in Modern Sports Health

This study aims to assess the impact of protein utilization and injury management on enhancing athletic performance and recovery in modern sports. Utilizing a qualitative descriptive research model, the study involves a comprehensive review of literature from reputable scientific databases such as Scopus, ScienceDirect, and Google Scholar. Keywords such as "Injury Management," "Protein Utilization," and "Athletic Performance" guided the search for relevant studies. The analysis reveals that adequate protein intake and balanced nutrition are vital for muscle repair, reducing muscle damage, and accelerating recovery following injury or intense exercise. The findings emphasize that effective nutritional strategies not only support recovery but also contribute to injury prevention and overall performance improvement. Personalized nutrition plans tailored to individual needs and specific conditions, including those of athletes with spinal cord injuries or from various sports disciplines, are crucial for optimizing outcomes. The study highlights that integrating protein and nutritional strategies into training and recovery programs can significantly enhance athletic performance and reduce the risk of injuries. Effective injury management, coupled with appropriate protein utilization, plays a pivotal role in achieving better recovery rates and improving overall health. By adopting these evidence-based strategies, athletes can better meet their performance goals and enhance their overall well-being. This research underscores the importance of a comprehensive and personalized approach to nutrition and injury management in sports health, offering valuable insights for optimizing athletic training and recovery practices

Medical Device Database: Scoping Lifecycle Review

Objectives: This study examines the utilization and lifecycle management of medical device databases in multiple regions including the United States, Europe, Japan, and Canada, and evaluates their public health impact. The objective is to identify best practices, gaps, and challenges in the current systems to inform future improvements and standardization efforts on a global scale.Methods: A comprehensive comparative analysis was conducted on databases in these regions. The analysis focused on the structure, operation, and application of these databases in lifecycle management. Key factors include data collection, integration, utilization throughout the product lifecycle, data accessibility, user interfaces, integration with other healthcare data, regulatory compliance, and public health impacts. Data were collected through literature reviews, policy documents, and expert interviews to provide a robust understanding of each system.Results: Results show reveal significant variations in how regions utilize medical device databases to enhance device safety and efficacy. While all regions aim to improve device safety and public health outcomes, there are notable differences in data accessibility, usage, and management practices. Comprehensive coverage of the medical device lifecycle from pre-market approval to post-market surveillance varies significantly. Integration with regulatory processes and support for public health interventions through detailed tracking and reporting mechanisms also differ widely. Data accessibility and integration with national databases remain challenging. Inconsistent data formats, varying levels of data granularity, and differences in regulatory requirements hinder effective global monitoring and comparison. Despite these challenges, the study highlights the potential for medical device databases to significantly enhance healthcare quality and patient safety.Conclusions: National medical device databases are crucial for improving healthcare quality and safety. They serve as vital tools for identifying issues and informing policy-making. Korea should consider developing a comprehensive database focused on user health protection and safety enhancement, aligned with global standards.

Scalability of CASCADE2001: Gis-Based Flood Risk Screening Tool to Support Watershed Master Planning

Flood risk analysis is the instrument by which floodplain and stormwater utility managers create a sound strategy and adaptation plans to reduce flood potential in their communities. As a result, there is a need to develop a flood risk screening tool to analyze watersheds and find vulnerable areas by leveraging the scientific and technological developments of the last decade to prioritize improvements. Because local municipalities are continuously challenged by the impacts of changes in precipitation and other climatic events, the screening tool needs to be scalable, while providing similar results of spatial inundation extent regardless of the scale. Likewise, the ability to perform this analysis without overwhelming limited modeling budgets is a goal for local governments who may spend large amounts of money on capital in the future to retrofit their stormwater management systems. The present study investigates the scalability of a GIS-based hydrologic-hydraulic model, CASCADE2001, to support development of watershed-based flood protection plans. The comparative analysis of the predicted flood response at three nested levels of scale were applied in south Florida to a 8-digit hydrologic unit code (HUC) level (the Caloosahatchee Watershed), a 12-digit HUC level (the Ninemile Canal Subwatershed within the Caloosahatchee Watershed), and a local municipal level (City of Clewiston, Florida within the Ninemile Canal subwatershed). The findings were that the model was scalable and the infrastructure that mattered with respect to results was driven by the scale.

Strategies of water resource utilization and agricultural water management in the coastal saline zone of Bangladesh

Strategies of water resource utilization and agricultural water management in the coastal saline zone of Bangladesh