Measurement Science Review

<p>This paper examined and compared the reliability of two popular unit hydrograph methods for flood assessment in a dryland, poorly gauged basin: the Soil Conservation Service (NRCS-UH) method and the geomorphologic instantaneous unit hydrograph (GIUH) model. In addition, two different estimates of the basin's time of concentration were compared, along with varying values of the runoff curve number, to compute the watershed lag. Simulations were performed for the upper Napostá Grande (SW Buenos Aires, Argentina), using eight historic rainfall-runoff events to validate the resulting hydrograph at the basin outlet. Validation used runoff volume, peak flow, and recession time as an alternative to time to peak, for which only mean daily data were available. Results revealed great discrepancies in unit hydrograph parameters for varying determination methods, time of concentration estimates, and basin lag factors, as well as lower-than-standard peak rate factors for GIUH hydrographs. The comparison of simulated with observed hydrographs suggested a better agreement of GIUH for the highest retardance factor, as it produced the smaller peaks with the longer recession. This study informs on the complex relationships involved in unit hydrograph (UH) determination for the studied basin and warns about the variability of obtained results depending on the applied methodology, the caution needed in the systematic use of standard parameters, and the importance of verifying the accuracy of results. This provides a valuable framework for flood assessment within regional, ungauged basins with similar characteristics, which may exhibit comparable total runoff volumes for the same rainfall event but not necessarily equivalent flood hydrographs.</p>

<p>The cultural landscape of traditional villages is a valuable cultural heritage. Using the example of the Huangdu Dong Village, this study collected data on the perceptions of 209 tourists regarding the cultural landscape of traditional villages using a questionnaire survey. The perceptions and satisfaction rates of tourists were analyzed, and key factors influencing their satisfaction with the cultural landscape were identified. The results show that tourists generally hold a positive perception of traditional village cultural landscapes, with the highest levels of perceptions belonging to folk activity cultural landscapes and clothing cultural landscapes. Additionally, this study identified four key factors that have a significant positive impact on tourist satisfaction with the cultural landscape, namely architectural, water, vegetation, and service facility cultural landscapes. The research also found that tourists residing in rural areas reported significantly higher satisfaction with the cultural landscape than those living in urban areas; moreover, tourists with an income above 10,000 yuan exhibited significantly higher satisfaction compared to other income groups. Finally, based on its findings, this study provides recommendations for optimizing the protection, planning, and design of traditional village cultural landscapes to enhance overall tourist satisfaction.</p>

<p>This special issue, through various contributions from distinguished scholars in the field, attempts if not to provide exhaustive answers then at least to delineate the perimeter of the issues and scientifically circumscribe the contours of the questions that still exist regarding smart cities. Specifically, the ambition of this special issue is to fuel a multidisciplinary debate on the role of cities—especially innovative ones—in the ongoing (sustainable digital energy) transition processes. The contributions in this special issue will certainly stimulate an exchange of ideas and perspectives on this topic.</p>

Under the influence of global climate change, the climatic conditions of China's major agricultural regions have changed significantly over the last half-century, affecting regional grain production levels. With its favorable conditions for agricultural activities, China's central region has been a strategic location for grain production since ancient times and has assumed an essential responsibility for maintaining national grain security. However, the key concerns of this study are whether the national grain security pattern is stable and whether it might be affected by global climate change (especially climate instability and increased risks in recent years). Therefore, the present study collected grain production data and used descriptive statistical and geospatial analyses to reveal the trend and spatiotemporal pattern of grain production in China's central region from 2010 to 2020. Then, a further analysis was conducted by combining meteorological data with a geographically weighted regression (GWR) model to investigate the relationship between spatial differences in the output per unit of the grain sown area (OPUGSA). The findings were as follows: (1) The overall development trend of grain production in China's central region from 2010 to 2020 revealed a positive overall trend in grain production, with notable differences in growth rates between northern and southern provinces. (2) Most regions in the southern part of the central region from 2015 to 2020 showed varying degrees of total output of grain (TOG) and OPUGSA reduction, possibly affected by the effects of the anomalies for global climate change and a strong El Niño effect in 2015. (3) Low-low (L-L) clusters of TOG and OPUGSA indicators were consistently in the northwest part (Shanxi) of the central region, and high-high (H-H) clusters of TOG were consistently in the central part (Henan and Anhui) of the central region, but H-H clusters of OPUGSA were not stably distributed. (4) The fitting results of the GWR model showed a better fit compared to the ordinary least squares (OLS) model; it was found that the annual average temperature (AAT) had the greatest impact on OPUGSA, followed by annual sunshine hours (ASH) and annual precipitation (AP) last. The spatiotemporal analysis identified distinct clusters of productivity indicators. It suggested an expanding range of climate impact possibilities, particularly in exploring climate-resilient models of grain production, emphasizing the need for targeted adaptation strategies to bolster resilience and ensure agricultural security.

<abstract> <p>This is a data-based analysis of how Native American interpretations of their distant past are being considered reflecting new science findings. A key science understanding developed over the past 75 years has been that Native people did not occupy North America (or any place in the so-called New World) longer than 12,000 years before present (BP), thus they could neither have experienced nor understood any event in the late Pleistocene interglacial period (128,000 BP to 11,700 BP). As called in this analysis, the <italic>Clovis glass ceiling</italic> references the popular use of Clovis spear points to represent the earliest signs of humans in North America with dates generally later than 12,000 BP. This analysis engaged with recent science findings that Native people were present in North America up to 40,000 years ago. Opening the science limits of Native presence affords a reinterpretation of the past using extant Native interpretations. As an example, Salt Spring near Death Valley is a component of an ancient Pleistocene heritage landscape that can be reconstructed using geology and Native American interpretations. Native American perspectives were derived from 404 ethnographic interviews with Numic speaking peoples, focused on 24 ancient springs near Death Valley, California, and Las Vegas, Nevada.</p> </abstract>

<abstract> <p>This paper aimed to demonstrate the correlation, a hidden, intricate, interplay, between the conception of risk and the fluid nature of society during the eras of migratory relocations as portrayed in Salman Rushdie's literary masterpiece, <italic>The Satanic Verses</italic>. The general premise found in this paper was that risk is based on the following logical axiom: Risk is mathematically unpredictable, something that goes beyond the human capability of discernment or probabilistic prevision. This blank space that separates reality from its potentiality is the risk. Thus, in migratory relocation, the risk consists of the unknowability of what could happen the second after having passed a line. It is the border of what is known. Rushdie's work offers profound insights into the ways in which individuals navigate the turbulent waters of a rapidly changing world, where cultural, social, and political paradigms constantly shift. In the first part of this work, we will present the main topics related to risk. Rushdie's work underlines the central role that storytelling and narrative play in navigating the complexities of a fluid society. The characters in Rushdie's novel employ storytelling as a means of understanding and asserting their own identities, thereby confronting the inherent risk of being silenced or marginalized in a world dominated by shifting power dynamics. In conclusion, Salman Rushdie's <italic>The Satanic Verses</italic> provides a rich tapestry of narratives that not only explore the conception of risk in a fluid society but also challenge readers to contemplate the intricate interplay of identity, culture, and faith in an ever-changing world. This works serve as a testament to the power of literature to engage with contemporary issues, transcending boundaries, and sparking critical conversations. Through his vivid characters and daring narratives, Rushdie invites readers to grapple with the aims and main issues of our time: the quest for self-identity, the inevitability of risk, and the enduring need for storytelling as a means of understanding and shaping our rapidly evolving society.</p> </abstract>

<abstract> <p>Landslides represent a growing threat among the various morphological processes that cause damage to territories. To address this problem and prevent the associated risks, it is essential to quickly find adequate methodologies capable of predicting these phenomena in advance. The following study focuses on the implementation of an experimental WebGIS infrastructure designed and built to predict the susceptibility index of a specific presumably at-risk area in real time (using specific input data) and in response to extreme weather events (such as heavy rain). The climate data values are calculated through an innovative and experimental atmospheric simulator developed by the authors, which is capable of providing data on meteorological variables with high spatial precision. To this end, the terrain is represented through cellular automata, implementing a suitable neural network useful for producing the desired output. The effectiveness of this methodology was tested on two debris flow events that occurred in the Calabria region, specifically in the province of Reggio Calabria, in 2001 and 2005, which caused extensive damage. The (forecast) results obtained with the proposed methodology were compared with the (known) historical data, confirming the effectiveness of the method in predicting (and therefore signaling the possibility of an imminent landslide event) a higher susceptibility index than the known one and one provided (to date) by the Higher Institute for Environmental Protection and Research (ISPRA), validating the result obtained through the actual subsequent occurrence of a landslide event in the area under investigation. Therefore, the method proposed today is not aimed at predicting the local movement of a small landslide area, but is primarily aimed at predicting the change or improving the variation of the landslide susceptibility index to compare the predicted value with the current one provided by the relevant bodies (ISPRA), thus signaling an alert for the entire area under investigation.</p> </abstract>

<abstract> <p>In the rapidly evolving landscape of the digital age, the call for intelligent governance has become paramount. This study offers a nuanced exploration of global sustainable governance, integrating the Seven Pillars of Sustainability (7PS) framework and innovation culture. Utilizing structural equation modeling and data from diverse government organizations, this research empirically established the 7PS framework's pivotal role in enhancing organizational sustainability, supported by a robust 95% confidence level. Notably, it unveiled the transformative influence of innovation culture in amplifying the 7PS's impact. The methodological innovation lies in strategically applying the fuzzy analytic hierarchy process (AHP), assigning priority weights to 7PS criteria, and identifying culture as the linchpin. This approach provided a robust framework for dissecting the complex interplay of emerging technologies, sustainable engineering, and cybersecurity. The study delves into the X.0 wave/age (X.0 = 5.0) theory, offering insights into the intricate dynamics of innovation, sustainability, and governance. Beyond academic discourse, this research informs practical strategies globally, particularly for small and medium-sized enterprises (SMEs) transitioning to SME 5.0/hybrid SMEs. Emphasizing inclusivity and diversity as catalysts for innovation, it scrutinizes contemporary challenges amid technological evolution and cybersecurity threats. Functioning as a visionary compass, the study elucidates the path to a 7PS sustainable future. It signifies a paradigm shift, transcending boundaries between knowledge domains. The fusion of the 7PS framework, X.0 wave theory, and fuzzy AHP navigates global governance, digital resilience, and cybersecurity, offering a transformative roadmap. This research contributes by substantiating the pivotal role of culture in emerging technologies, augmenting global tech-sustainable governance, fortifying digital resilience, and safeguarding cybersecurity.</p> </abstract>

<abstract> <p>With the rapid development of aeromagnetic (primarily uncrewed) methods for measuring the magnetic field, the possibility of detailed magnetic research in hard-to-reach mountainous areas, forested areas, swamp areas, desert areas, and water areas has emerged. The conditions for interpreting the magnetic field are most difficult due to the vector nature of the magnetic properties of rocks, the wide range of their properties, and the presence of residual magnetization. The physical and geological conditions of the territory of Azerbaijan are characterized by rugged terrain relief, inclined magnetization (~58°), and complex geological environments. Along with using a probabilistic approach, deterministic methods for solving inverse and direct problems of geophysics become of great importance since it is possible to identify relatively extended reference boundaries and analyze magnetic anomalies from separate bodies of relatively simple shape. The article briefly outlines the main stages of processing and interpreting magnetic data under complex environments. The theoretical examples discussed include a block diagram of various disturbances, interpretive models of thin and thick beds, an intermediate model, a thin horizontal plate, and a horizontal circular cylinder on the flat and inclined surfaces under inclined magnetization conditions. The process of assessing magnetization on sloping terrain relief is shown. The presented field examples for the Caucasus Mountains show the quantitative interpretation of aeromagnetic data at the Big Somalit and Guton sites (southern Greater Caucasus, Azerbaijan), a deep regional profile through the Lesser and Greater Caucasus, magnetic field studies in the area around the Saatly superdeep borehole (Middle Kur depression between the Greater and Lesser Caucasus), and 3D magnetic field modeling at the Gyzylbulag gold deposit (the Azerbaijani part of the Lesser Caucasus). In the Caspian Sea, we demonstrated the use of an information parameter to identify faults in the Bulla hydrocarbon field (Gulf of Baku) and, for the first time, obtained the relationship between the generalized aeromagnetic data (2.5 kilometers over the mean sea level) and the central area of the mud volcanoes distribution in Azerbaijan.</p> </abstract>

<abstract> <p>In the past century, water demand increased extensively due to the rapid growth of the human population. Ground observations can reveal hydrological dynamics but are expensive in the long term. Alternatively, hydrological models could be utilized for assessing streamflow with historical observations as the control point. Despite the advancements in hydrological modeling systems, watershed modeling over mountainous regions with complex terrain remains challenging. This study utilized the multi-physical Weather Research and Forecasting Hydrological enhancement model (WRF-Hydro), fully distributed over the Amu River Basin (ARB) in Afghanistan. The calibration process focused on land surface model (LSM) physics options and hydrological parameters within the model. The findings emphasize the importance of LSM for accurate simulation of snowmelt–runoff processes over mountainous regions. Correlation coefficient (R), coefficient of determination (R<sup>2</sup>), Nash-Sutcliff efficiency (NSE), and Kling-Gupta efficiency (KGE) were adopted for accuracy assessment over five discharge observation stations at a daily time scale; overall performance results were as follows: R was 0.85–0.42, R<sup>2</sup> was 0.73–0.17, NSE was 0.52 to −8.64, and KGE was 0.74 to −0.56. The findings of the current study can support snowmelt process simulation within the WRF-Hydro model.</p> </abstract>

<abstract> <p>Diamer Basha Dam is an under-construction, 272-meter-high, roller compacted concrete (RCC) dam on the Indus River in Pakistan. Once constructed, it will be the world's highest RCC gravity dam with a 105-kilometer-long reservoir. Most of the reservoir lies in unstable moraine deposits with steep slopes. Events like saturation during reservoir filling, alternate wetting, drawdown during reservoir operation, or a seismic event could trigger a large mass movement of these slopes into the reservoir to disrupt the dam functionality. This work identified the 15 most vulnerable slide areas using digital slope maps, elevation maps, and satellite imagery. Deterministic slope stability analysis was carried out on the identified sections under various stages of reservoir operation for static and seismic loading, using pseudo-static and dynamic analysis approaches. Probabilistic analysis was then performed using Monte Carlo simulation. The findings showed that most moraine deposits would collapse under reservoir filling, rapid drawdown, or seismic activity. Following the assessments, landslide susceptibility maps were generated, and an assessment of potential impacts, including the generation of dynamic waves, reservoir blockage, increased sediment loads, and reduced reservoir storage capacity, was also performed.</p> </abstract>

<abstract> <p>The lateral earth pressure at rest is typically considered in situations where lateral wall movements are negligible. Determining the coefficient of lateral earth pressure at rest (referred to as <italic>K</italic><sub>0</sub>) often relies on established classical equations. However, these equations often overlook the influence of the width of the backfill soil on lateral earth pressure. While this omission is generally acceptable when the backfill soil is wide enough, there are instances where a retaining wall supports backfill soils of limited width, such as basement walls between adjacent buildings. Yet, there is limited research addressing the impact of narrow backfill in such scenarios. We aimed to address this gap by investigating variations in <italic>K</italic><sub>0</sub> values under different conditions, including backfill width and soil properties. Using ABAQUS for numerical simulations, we refined and validated our model using relevant laboratory experimental data. Subsequently, the validated model was applied to various simulation scenarios. For narrow backfill widths (ranging from 0.1 to 0.7 times the retaining wall height), our findings indicated a general decrease in <italic>K</italic><sub>0</sub> values with decreasing backfill widths, often smaller than those estimated using classical equations. Additionally, along the depth of the wall, <italic>K</italic><sub>0</sub> values tended to decrease with increasing depth for narrow backfill widths. These findings contribute to our understanding of the impact of narrow backfill on <italic>K</italic><sub>0</sub>.</p> </abstract>

<abstract> <p>This paper analyzes the emergence of micro-cultural material worlds in marginal rural areas of Spain from the viewpoint of postmodern rural cultural geography. The methodology is qualitative and geo-ethnographic, based on the study of three cases that suggest a renewed relevance of place as cultural capital in the production and consumption pattern of new or renovated rural materialities. The main conclusions suggest that two sides characterized the renovated houses: externally linked with traditional spirit and style of the area and internal with an individual and cosmopolitan design These represent a new dialectic similarity/difference.</p> </abstract>

<abstract><p>Assessing the capacity of groundwater is essential for efficient water management. Regrettably, evaluating the potential of groundwater in regions with limited data accessibility, particularly in mountainous regions, presents significant challenges. In the Nan basin of Thailand, where there is a scarcity of groundwater well data, we utilized remote sensing and geographic information system (GIS) techniques for evaluating and determining the potential of groundwater resources. The analysis included seven hydrological factors, including elevation, drainage density, lineament density, land use and land cover, slope, soil moisture, and geology. The quantification of groundwater potential was conducted by the utilization of linear combination overlays, employing weights derived from two distinct methodologies: the analytical hierarchy process (AHP) and the frequency ratio (FR). Interestingly, it is noteworthy that both the FR and AHP approaches demonstrated a very comparable range of accuracy levels (0.89–1.00) when subjected to cross-validation using field data pertaining to groundwater levels. Although the FR technique has shown efficacy in situations when data is well-distributed, it displayed constraints in regions with less data, which could potentially result in misinterpretations. On the other hand, the AHP provided a more accurate assessment of the potential of groundwater by taking into account the relative importance of the criteria throughout the full geographical scope of the study. Moreover, the AHP has demonstrated its significance in the prioritization of parameters within the context of water resource management. This research contributes to the development of sustainable strategies for managing groundwater resources.</p></abstract>

<abstract> <p>Terrain surface roughness, often described abstractly, poses challenges in quantitative characterization with various descriptors found in the literature. In this study, we compared five commonly used roughness descriptors, exploring correlations among their quantified terrain surface roughness maps across three terrains with distinct spatial variations. Additionally, we investigated the impacts of spatial scales and interpolation methods on these correlations. Dense point cloud data obtained through Light Detection and Ranging technique were used in this study. The findings highlighted both global pattern similarities and local pattern distinctions in the derived roughness maps, emphasizing the significance of incorporating multiple descriptors in studies where local roughness values play a crucial role in subsequent analyses. The spatial scales were found to have a smaller impact on rougher terrain, while interpolation methods had minimal influence on roughness maps derived from different descriptors.</p> </abstract>