Resource Assessment Research Articles

Drought risk in the Mahanadi River basin: a multi-dimensional approach for integrated urban-rural drought management strategies

ABSTRACT Droughts are one of the most spatially complex geohazards, having a significant impact on the economic status of any region. To mitigate drought risks, a comprehensive drought management plan is required, and the first step towards that goal is to assess the various aspects of drought risks in the preparation of a drought risk map. To produce an integrated drought risk map for Mahanadi River basin, India, the current study combines geospatial methodologies with the Analytical Hierarchy Process (AHP) technique to assess various dimensions, viz. hydrological, meteorological, agricultural and socio-economic drought risk in the region in view of integrated rural-urban management strategies. A total of 17 criteria from different aspects were taken into consideration in different groups. The results showed that districts like Raipur, Bilaspur, Durg and Ragnandgaon faced extreme drought conditions combining assessments of agriculture, water resources, socioeconomic factors and weather patterns, reveals varying levels of risk across the region. According to the findings, 22.01% of the region is vulnerable to extreme drought and 31.64% of the area is suffering from severe drought. The results indicate that the technique used for identifying the region's susceptibility to drought is effective, which will help planners develop strategies for mitigating drought.

A Review of Integration Techniques of Multi-Geoscience Data-Sets in Mineral Prospectivity Mapping

In every sphere and utility aspects of human life, there is need of metals and construction materials. Minerals which are below the near subsurface is almost explored on the basis of direct geospatial evidences. There is high demand of metals and other materials which are mined below the surface of earth In the current landscape, there's a demand for faster and more precise exploration strategies, particularly emphasizing Greenfield exploration and deep-seated mineralization. This paper conducts a comprehensive review of existing methodologies for integrating multi-geoscience datasets aimed at mineral prognostication, with a focus on identifying the most precise and authentic Artificial Intelligence (AI) - based data integration techniques. Additionally, it offers insights into the current status of mineral exploration in India and the global evolution of data integration practices. Several types of geoscientific datasets i.e. geological, geophysical, geochemical and geospectral data have to be organized in geospatial domain for meaningful mineral exploration outcome. These datasets have been processed to extract exploratory indicator layers for data integration are called Mineral Prospectivity Mapping (MPM). Indeed, MPM is a multiple criterion decision making (MCDM) task which provide a predictive model for categorizing of sought areas in terms of ore mineralization. There after based upon Geological factors i.e. lithology, structure, shear & fault zones, alteration zones etc. of sought mineralized area, selection of drilling parameters (depth, angle, level, type, rpm, feed) is done for resource assessment. Literature survey suggests that minerals exploration by integrated approach on the basis of these datasets is still poorly performed. It has been gathered that knowledge-driven data integration using Fuzzy Gamma Operator and Multiclass Index Overlay method is best suited for mineral exploration. In past, few researchers of other countries have exploited data integration approach with encouraging results. Despite the abundance of data available in India, this approach has not been utilized very successfully and no standard protocols exist even for decision making for drilling operation. Thus, it's evident that employing the Fuzzy Inference System (FIS) algorithm, particularly utilizing the Fuzzy Gamma Operator and Multiclass Index Overlay integration method, remains underutilized in designing standardized operating procedures (SOP) for mineral exploration in India and decision-making for drilling operations. This approach holds promise for minimizing time lag and optimizing resources such as manpower, instruments, and finances.

Remote Sensing Assessment of Water Resources, Vegetation, and Land Surface Temperature in Eastern Saudi Arabia: Identification, Variability, and Trends

Saudi Arabia has one of the biggest water shortages and the least vegetation in the world, which is presumed to provoke this problem further due to climate change. Therefore, the present study investigates the water, vegetation, and temperature over Al-Asfar Lake region, Al Ahsa, Eastern province of Saudi Arabia using the Normalized Difference Water Index (NDWI), Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST: °C) from Landsat-8 based operational land imager (OLI) measurements for the period 2013 to 2023. This study presented annual and seasonal (dry months: June–September and wet months: December–April) spatiotemporal distribution and variations, calculated their absolute change and trends, and examined their relationship. Results showed positive NDWI values over Al-Asfar Lake, indicating waterbodies; while positive NDVI values on the lake's bank, signifying vegetation. Notably, there were significant temporal variations in water and vegetation observed on annual, seasonal, and monthly scales. The study also found an overall decrease in vegetation areas of 5.36 km2 in 2023 compared to 2013, while waterbodies increased by 8.83 km2. The trend analysis using area-averaged data demonstrated that NDWI increased on annual (0.0075/year) and seasonal (dry: 0.0083/year and wet: 0.0049/year) scales, while NDVI decreased (annual: 0.0066/year, dry: 0.0083/year, and wet: 0.0009/year). Moreover, LST was recorded least amount over waterbodies (28.23 °C) and vegetation (32.45 °C) covered areas compared to the entire lake region (38.43 °C), respectively. Remark, LST displayed decreasing trends over waterbodies (−0.05/year), followed by vegetation (−0.17/year), and the entire lake region (−0.0001/year), signifying that water and vegetation are vital components to controlling land surface temperature in this region. Finally, the LST showed a positive correlation with NDVI and negative correlation with NDWI. There may be a direct and indirect impact of climate change upon NDVI, LST, and NDWI as shown by the decreases in NDVI and LST and an increase in NDWI. This study can be considered as a base document to monitor waterbodies, vegetation cover, and temperature changes using remote sensing measurements of NDWI, NDVI, and LST, which will assist policymakers in developing water resource management, irrigation planning, and environmental monitoring strategies.

Indicators for suitability and feasibility assessment of flexible energy resources

Recommender systems play a critical role in optimizing building energy consumption by providing personalized advice based on data analytics and user preferences. However, the literature highlights the need for systems that can justify their recommendations, as many of these systems use non-transparent machine-learning techniques. This research introduces two distinct types of indicators with three main goals: to identify patterns of flexible consumption behavior using transparent and straightforward methods suitable for remote decision support systems, thereby eliminating the need for extensive databases; to evaluate the feasibility of installing solar panels on building facades, rooftops, and structures using high-resolution 3D models; and to enhance understanding through a quantitative assessment of the feasibility and suitability of integrating renewable energy sources, particularly photovoltaic systems. Flexible prosumers are scored by assessing their energy consumption level, consistency, and variability through the Flexible Consumption Indicators. Topology Indicators perform a quantitative assessment of the feasibility of support surfaces for installing photovoltaic panels, taking into account rooftop pitch angles, orientations, and surrounding and internal structures, identifying those areas exposed to sufficient levels of irradiation. This study, which uses actual consumption profiles and similar households' buildings 3D models, demonstrates how the proposed indicators can aid identifying users with flexible consumption profiles that reside in buildings compatible with renewable energy sources, aiding in decision-making process within the energy transition.

Comprehensive impact assessment on resource and environment of emerging recycling technologies for waste materials: Evidence from waste rare earth phosphors recycling

The recycling of waste materials has dual attributes of resource and environment, and current technical evaluation methods are difficult to balance the comprehensive impact of resource and environment, failing to meet the selection requirements of emerging recycling technologies. Focusing on the emerging recycling technology for rare earth phosphors, we developed a resource and environment composite assessment model, employing emergy accounting principles to uniformly quantify resource inputs and environmental impacts. The results indicated that the composite emergy of resource and environment of the recycling technologies is reduced by over 89.05 % compared to that of natural ores development technology. Moreover, the synergistic recycling of zinc (Zn) along with yttrium oxide (Y2O3) achieves an additional emergy reduction by 88.37 %. The resource emergy of natural ores development technology accounts for 95.15 %, indicating its heavy reliance on resource depletion. Due to the utilization of various chemicals, the recycling technologies exhibit stronger environment attribute.

Security assessment and diagnosis for industrial water resources using TODIMSort considering Best–Worst Method with double hierarchy hesitant fuzzy linguistic term set

Motivated by the driving force to address global water scarcity, industrial water resources, as the second largest consumption of water resources, its security assessment plays a crucial role in improving the current situation. Hence, this paper proposes a novel methodology to conduct the industrial water resources security (IWRS) assessment. Firstly, a more targeted assessment system based on the framework of the Pressure–State–Response (P–S–R) on IWRS is established. Then, enhanced with a double hierarchy hesitant fuzzy linguistic term set (DHHFLTS), the Best–Worst Method (BWM) now determines subjective weights through DHHFLTS-BWM (DF-BWM). By introducing the Criteria Importance Through Intercriteria Correlation (CRITIC) method, which considers the indicator interactions, objective weights are obtained to modify the subjective weights. Furthermore, the global dominance of all alternatives is calculated by a TODIMSort method and grading them. Moreover, 16 cities in Anhui Province are taken as examples to assess IWRS in the decade from 2011 to 2020. Comparative analysis with original BWM, time series analysis, sensitivity analysis on loss attenuation coefficient, coupling and coordination analysis and obstacle analysis on all indicators are conducted to verify the rationality, effectiveness, and stability of the proposed assessment methodology. Simultaneously, explore the existing issues within IWRS. It can be seen from the results that the performance of Lu’an and Huainan cities is relatively better, while Ma’anshan city shows relatively poorer performance. In addition, per capita water resources and wastewater treatment facilities have a significant impact on the IWRS. Finally, some management suggestions are proposed to enhance the scientific and effective management of industrial water resources and ensure their sustainable utilization.

Human Resource Assessment and Sustainability : Investigating the Measurability of Human Activity

Sustainability, as a complex set of goals, has many possible interpretations and approaches the 17 Sustainable Development Goals (SDGs) set out in the document have 169 sub-goals, of which Goal 10 is "reduced inequalities". There are 10 sub-goals linked to this goal, the first of which is aimed at reducing income inequality. Employers have direct responsibility and considerable leeway to develop fair wage systems. For HR professionals, the practical implementation of this is a major task, and their knowledge can therefore be a key factor in achieving SDG 10. In our research, we sought to answer the question of what future HR professionals know about the accounting measurability of human performance and how they assess its monetary valuation. In our view, HR professionals who are aware of the issues of human performance measurement and recognize the fundamental problems can play a significant role in meeting SDG 10. In our primary research, we surveyed 448 undergraduate human resources students from early December 2022 to the end of January 2023 using an online questionnaire. The questionnaire contains closed and open questions in addition to demographic data. Our research shows that the value of human activity is not well expressed in monetary terms, which implies that wages and the value of work are not closely related.

Statistical Analysis of Wind Resource Assessment for Different Locations in South-Western Thailand

Weibull parameters have been widely used to evaluate wind energy potential. In this work presents wind resource assessment by statistical analysis with a Weibull distribution model for Krabi, Phuket, and Ranong weather stations in south-western Thailand. Ten-minute intervals include wind speed and wind direction of 10m from four-year records obtained by the Thai meteorological department. Four numerical methods, namely empirical method, graphical method, energy pattern factor method and maximum likelihood method are examined to estimate the Weibull parameters. The Weibull distribution obtained from each method is compared with the observed wind speed distribution by the performance tests using root mean square error, mean percentage error, and chi-square error to select a suitable method for the station area. The results revealed that the maximum likelihood method was the most accurate for Krabi and Phuket stations, and the energy pattern factor method was the most accurate for Ranong station. At a hub height of 80m, the highest mean wind speed and mean wind power density found in Krabi station were 3.25 m/s and 44.84 W/m2. The most probable wind speed value in three stations had a range from 1.80 to 2.50 m/s. The maximum wind speed carrying maximum energy found in Krabi station was 5.53 m/s. The operating probability of a wind turbine in Krabi station was 49.61%, followed by Phuket station was 46.80%, and Ranong station was 37.84%, respectively. In conclusion, all three stations had wind power potential classified as wind class 1 and can be sorted as follows: Krabi, Phuket, and Ranong stations.

Technical and economic challenges for floating offshore wind deployment in Italy and in the Mediterranean Sea

AbstractOffshore wind is nowadays already well developed in the North European countries. Ninety‐nine percent of the offshore wind turbines are installed on fixed foundations in shallow waters. For areas with water depth greater than 50–60 m, the floating wind is the cheapest and mostly used technology. This technology is going to reach the commercial phase in a few years, thus disclosing the potential of all marine areas with deep waters close to the coast, including the Mediterranean basin. One of the main challenges for floating offshore wind deployment in this area is the achievement of its economic feasibility. The offshore wind resource in the Mediterranean is generally lower than the one in the North Sea and in Oceans and the cost of offshore wind farms, especially with floating technology, is higher than the present offshore wind farm installations also because this industrial sector has not yet started in this area. However, in the Mediterranean area, the potential of offshore wind to contribute to the decarbonization pathway and reduce the dependence on imported fuel supply is substantial. Numerous studies, examined in this article, have already performed a technical‐economic assessment of offshore wind farms in different countries and geographical areas within the basin. A significant number of offshore wind projects are already in different stages of development, confirming the industrial interest and readiness of the Mediterranean offshore wind energy sector. The article provides a comprehensive review of various factors influencing the future deployment of offshore wind in the Mediterranean. It covers a range of topics including technology advancements, resource assessment, wind energy potential, ongoing projects, costs, and economic aspects. Additionally, it discusses environmental sustainability, regulatory frameworks, supply chain logistics, and system integration. The updated review presented in this article could assist decision‐makers and stakeholders in gaining a better understanding of the characteristics of this promising sector and accelerating its development.This article is categorized under: Sustainable Energy > Wind Energy

Integrated hydrological modeling and water resource assessment in the Mayurakshi River Basin: A comprehensive study from historical data to future predictions

This study employs the SWAT hydrologic model to integrate climatological and hydrological processes for an in-depth analysis of the Mayurakshi River Basin. Utilizing the Markov Chain Model, the study evaluates water availability, flow patterns, and the basin's response to various climatic and land-use scenarios. Over 30 years of daily observed river discharge data were rigorously calibrated, validated, and analyzed for uncertainty, with critical data from the Massanjore Dam and Tilpara Barrage gauge stations characterizing the river's hydrological behavior. The result suggests the watershed received an average annual precipitation of 1432.4 mm, with evapotranspiration accounting for 40% of total water loss (578.4 mm). Surface runoff constituted over 90% of the total discharge, highlighting its importance for agricultural practices, particularly during the dry season. However future projections (2021-2031) indicate a significant decrease in mean annual precipitation (1404.7 mm) and a drop in evapotranspiration (542.1 mm or 38% of mean precipitation), attributed to reduced vegetation cover and increased settlement, leading to enhanced surface runoff. By quantifying internal renewable blue water, evapotranspiration, and soil water, this research provides crucial data for long-term water resource planning and assessment. The findings are valuable for national, regional, and transboundary water management agencies, offering insights into sustainable water resource management under changing climatic and different land-use conditions.

Rekrutmen dan Penilaian Kinerja SDM di Koperasi ISM Karya Sinar Bahari, Desa Tanggul Jaya, Kelurahan Banten, Kecamatan Kasemen, Kota Serang, Provinsi Banten

This service is entitled Recruitment and HR performance assessment at the ISM Karya Sinar Bahari Cooperative, Tangul Jaya Village, Banten Subdistrict, Kasemen District, Serang City, Banten Province. This service was carried out on Saturday, August 3 2024, which was attended by 22 students and 1 supervisor at Pamulang University. This Community Service aims to analyze the recruitment process and performance assessment of human resources (HR) at the ISM Karya Sinar Bahari Cooperative, Tanggul Jaya Village, Banten Village, Kasemen District, Serang City, Banten Province. The ISM Karya Sinar Bahari Cooperative is an economic institution that plays an important role in improving the welfare of its members and the surrounding community. However, the main challenge faced is how to recruit quality human resources and carry out performance assessments effectively to ensure the achievement of cooperative goals. This Community Service uses survey methods and direct material delivery as well as simulations and discussions regarding management, financial management and product marketing via WhatsApp Business. This Community Service activity succeeded in providing understanding to ISM Karya Sinar Bahari Cooperative Members regarding Recruitment and performance assessment, Financial Management and Product marketing via business WhatsApp social media. In this way, it is hoped that this cooperative can improve the quality of its human resources and, in turn, strengthen its competitiveness and contribution to the welfare of its members and society.

A bee's-eye view of landscape change: differences in diet of 2 Andrena species (Hymenoptera: Andrenidae) between 1943 and 2021.

Declines in pollinating insects have been linked to changes in land cover, affecting the availability of nesting sites and floral resources. Our study is the first analysis of changes in pollen load composition of 2 mining bees, Andrena barbilabris (Kirby) and Andrena flavipes (Panzer) (Hymenoptera: Andrenidae), at the same sites in central England, over 75 years. This provides a unique opportunity to remove spatial variation and review temporal changes in pollen diet within the context of landscape change. We analyzed modern-day pollen load composition for these species and compared it with historical data from the same sites. We then examined potential links between land-use change and the bees' diets. Both bees showed dietary flexibility and lower diet breadth for A. barbilabris, and the bees' foraging strategies appear to have changed. Andrena flavipes collected more pollen taxa in a single load, while A. barbilabris appeared to source pollen from greater distances. Landscape changes at the studied sites have affected the nutritional environment for these bees. Our findings are supported by an existing assessment of floral resources, which found floral diversity has decreased overall in both the habitats used by these bees. However, more research is needed on the nutritional content of pollens used by these bees, both now and historically, to estimate how pollen diversity has changed. The bee's-eye view underlines the importance of understanding how species respond to local changes so that effective conservation strategies can be developed.

Comparison of bulk snow density measurements using different methods

Snow density is one of the basic properties used to describe snow cover characteristics, and it is critical for remote sensing retrieval, water resources assessment and modeling inputs. There are many instruments available to measure snow density in situ. However, there are measurement errors of snow density for bulk and layers or gravimetric and electronic instruments, which may affect the accuracy of remote sensing retrieval and model simulation. Especially in China, due to the noticeable heterogeneity of snowpacks, it is necessary to evaluate in detail the performance and applicability of snow density instruments in different snowpack conditions. This study evaluated the performance of different snow density instruments: the Federal Sampler, the model VS–43 snow density cylinder (VS–43), the wedge snow density cutter (WC1000 and WC250), and the Snow Fork. The average bulk snow density of all instrument measurements was set as the reference value for evaluation. The results showed that as compared with the reference, the VS–43 cylinder presented the best performance for bulk snow density measurement in the measured range with the lowest RMSE (11 kg m−3), BIAS (3 kg m−3), and MRE (1.6%). For layer observation, bulk snow density was overestimated by 8.1% with WC1000 and underestimated by 11.4% with Snow Fork which was the worst performance compared with the reference value, and there were greater measurement errors of snow density in the depth hoar than other snow layers. Compared with grassland, the uncertainty of snow density measurements was slightly lower in forests. Overall, the Federal Sampler and VS–43 cylinder are more suitable for bulk snow density measurement in deep snowpack regions across China, and it is recommended to use WC1000, WC250 and Snow Fork to measure the snow density of snow layers in the snow stratigraphy.

Wind resource assessment for turbine class identification in Bayanzhaganxiang, China

Abstract The wind resource assessment has been used effectively to identify the classification of wind turbines at a particular wind farm site. The current study used WAsP software and various statistical methods such as graphical, energy pattern factor, standard deviation, and Rayleigh distribution methods to find the Weibull parameters by evaluating the raw data collected from August 2005 until July 2006 at four (4) different heights of the meteorological mast station in Bayanzhaganxiang, China. The Weibull parameters were utilized to find the annual mean wind speed, probability density, and cumulative distribution functions of wind conditions at the reference heights of 70 m, 50 m, 30 m, and 10 m. The wind shear coefficient was 0.130 with an overall roughness factor of 0.0385 m, suggesting the site vicinity is an open country with no significant structures and vegetation. The results also showed that the post-processed output from WAsP and standard deviation method at the sensor’s height of 70 m have a correlation coefficient and confidence level of 0.99977 and above 95%, respectively. Based on the turbine classification from GL Wind 2003 and IEC 61400-1 Ed.2, it was found that the turbine class ideal for the site is class III wind turbines with an annual mean wind speed of 7.439 m/s at a hub height of 99 m. The measured wind power density at hub height was calculated according to IEC 61400-12-1, which yields 464.36 W/m2. The characteristic wind turbulence at 70 m high is IEC subclass B. Among the selected wind turbines, the net annual energy production with efficiency is 8,059.57 MWh/year using Avantis AV1010, with the highest capacity factor of 40.05%. It has been found that the lowest energy generation cost is US$ 0.0292/kWh for a period of 20 years.

Molecular delimitation of cryptic Australian squid species of the genus Uroteuthis Rehder, 1945 (Cephalopoda: Loliginidae), provides a baseline of diversity to resolve classification challenges throughout the Indo-Pacific

ABSTRACT This study provides a comprehensive molecular phylogenetic analysis of Uroteuthis squid from the Indo-Pacific region. The main aim was to increase sample coverage from northern and eastern Australian waters to resolve the identity and distribution of Uroteuthis species taken by local fisheries. Two mitochondrial regions, cytochrome c oxidase subunit I (COI) and 16S ribosomal RNA (16S rRNA), were sequenced from 220 new specimens and analysed with a further 51 sequences from GenBank to create a combined phylogeny for the genus. Three nuclear regions, 18S ribosomal DNA (18S rDNA), 28S ribosomal DNA (28S rDNA) and rhodopsin, were also sequenced from representatives of each species. Based on the mitochondrial phylogeny plus distance and tree-based delimitation models, a COI species barcode gap of 4–5% is proposed for discriminating Uroteuthis species. Applying this gap partitioned many described species into species complexes; for example, U. duvaucelii, U. noctiluca and U. edulis resolved into 10 species. Although more conserved, mitochondrial 16S rRNA sequences differentiated all new species clades, whereas none of the nuclear markers resolved the closest species. Results confirm that neither U. chinensis nor U. edulis occurs in Australian waters. Five undescribed species are identified from northern and eastern Australia, of which four are consistent with earlier allozyme studies (and two align with existing DNA sequences). One is a new southeastern, deeper shelf species differentiated in this study, along with a sixth undescribed species from Indonesian waters. Results of the molecular analysis are now being used to inform complementary morphometric analyses for new species descriptions, and genetic stock structure assessments of these important fisheries resources.

Probabilistic assessment of deep geothermal resources in the Cornubian Batholith and their development in Cornwall and Devon, United Kingdom

Geothermal energy could play a pivotal role in decarbonisation as it can provide clean, constant base-load energy which is weather independent. With a growing demand for clean energy and improved energy security, geothermal resources must be quantified to reduce exploration risk. This study aims to quantify the untapped resource-potential of the Cornubian Batholith as a geothermal resource for power generation and direct heat use. Recent field work, laboratory measurements and petrophysical characterization provides a newly compiled dataset which is inclusive of subsurface samples taken from the production well of the United Downs Deep Geothermal Power Project. Deterministic and probabilistic calculations are undertaken to evaluate the: total heat in place, recoverable resource, technical potential and potential carbon savings. The Cornubian Batholith is considered a petrothermal system which may require stimulation as an enhanced geothermal system. This study shows the batholith has significant heat stored of 8988 EJ (P50), corresponding to 366 EJ recoverable and a technical potential of 556 GWth. When evaluating the potential for power generation (i.e., electricity) the P50 is 31 GWe. The total carbon savings when generating electricity (P50) equates to 106 Mt.

Resource assessment and techno-economic analysis of solar pv integrated hybrid off-grid power generation system: a case study of Krishnanagar, India

Resource assessment and techno-economic analysis of solar pv integrated hybrid off-grid power generation system: a case study of Krishnanagar, India

Analyses of LULC dynamics in a socio-ecological system of the Bale Mountains Eco Region of Southeast Ethiopia.

Analysis of land use and land cover (LULC) change and its drivers and impacts in the biodiversity hotspot of Bale Mountain's socio-ecological system is crucial for formulating plausible policies and strategies that can enhance sustainable development. The study aimed to analyze spatio-temporal LULC changes and their trends, extents, drives, and impacts over the last 48 years in the Bale Mountain social-ecological system. Landsat imagery data from the years 1973, 1986, 1996, 2014, and 2021 together with qualitative data were used. LULC classification scheme employed a supervised classification method with the application of the maximum likelihood algorithm technique. In the period between 1973 and 2021, agriculture, bare land, and settlement showed areal increment by 153.13%, 295.57%, and 49.03% with the corresponding increased annual rate of 1.93%, 2.86%, and 0.83%, respectively. On the contrary, forest, wood land, bushland, grass land, and water body decreased by 29.97%, 1.36%, 28.16%, 8.63%, and 84.36% during the study period, respectively. During the period, major LULC change dynamics were also observed; the majority of woodland was converted to agriculture (757.8 km2) and grassland (531.3 km2); and forests were converted to other LULC classes, namely woodland (766.5 km2), agriculture (706.1 km2), grassland (34.6 km2), bushland (31.9 km2), settlement (20.5 km2), and bare land (14.3 km2). LULC changes were caused by the expansion of agriculture, settlement, overgrazing, infrastructure development, and fire that were driven by population growth and climate change, and supplemented by inadequate policy and institutional factors. Social and environmental importance and values of land uses and land covers in the study area necessitate further assessment of potential natural resources' user groups and valuation of ecosystem services in the study area. Hence, we suggest the identification of potential natural resource-based user groups, and assessment of the influence of LULC changes on ecosystem services in Bale Mountains Eco Region (BMER) for the sustainable use and managements of land resources.

Frequency, duration, severity of energy drought and its propagation in hydro-wind-photovoltaic complementary systems

Analyzing low-renewable-output events, termed “energy droughts” is crucial for renewable energy systems. However, due to the challenges in hydropower regulation and complex spatiotemporal correlations among resources, the assessment and contributions of various resources to energy droughts in hydro-wind-photovoltaic (PV) energy systems (HWPSs) remain unexplored. To address these issues, this study evaluated energy droughts and compound resource droughts rather than single-resource in HWPSs, exploring the propagation. Assessments of frequency, duration, and severity relied on weather-to-resource conversion models and total power obtained through complementary operation. Estimating propagation probability from resource to energy droughts was achieved via the C-vine copula, quantifying resource contributions to drought propagation. Results of a case study in the Yalong River Basin indicated that (1) short-lived compound resource droughts have been increasingly frequent recently, peaking during winter or summer. After incorporating hydro energy resources, the severity and annual average occurrence of compound droughts decreased (from 18.56 to 5.24 events/year). (2) Complementary operation effectively reduced the probability of drought propagation. (3) Hydro and PV energy resources were pivotal contributors to drought propagation, contributing 49.1 % and 40.1 % when representing 53.4 % and 22.5 % of the total system capacity, respectively. Therefore, the study offers valuable insights into energy drought warnings and risk mitigation.

Recycling for a sustainable future: Advancing resource efficiency through life cycle assessment resource indicators

While Circular Economy (CE) is promoted as a resource-optimizing strategy, there is a need to ensure a clear and mutual understanding of the goals of CE and the indicators to measure progress. This requires access to assessment tools and methods based on a shared understanding of resources. Through life cycle assessment, the carbon-energy-material nexus of recycling a washing machine is investigated as a case study. We find that circularity efficiencies, such as recycling rates, do not always align with environmental impact, emphasizing the need to consider both aspects,and further elaborate on the disparities between carbon, energy, and material impact indicators. Results support the use of both energy and material impact indicators to avoid trade-offs, however, limitations to consistently operationalize CE require methodological advancements to expand beyond current natural resource stocks. Lastly, large sensitivity and uncertainties related to composition can hamper the comparability and accuracy of LCA resource assessments.