Resource Assessment Research Articles

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.

Empowering public health: building advanced molecular surveillance in resource-limited settings through collaboration and capacity-building.

The rapid detection and continuous surveillance of infectious diseases are important components of an effective public health response. However, establishing advanced molecular surveillance systems, crucial for monitoring and mitigating pandemics, poses significant challenges in resource-limited developing countries. In a collaborative effort, research institutions from Benin joined forces with Mali's National Institute of Public Health to implement a state-of-the-art molecular surveillance system in Mali. This approach was characterized by collaboration, multidisciplinarity, and tutoring. Key activities included a comprehensive assessment of infrastructure and human resources through document reviews, interviews, and laboratory visits; the development and validation of Standard Operating Procedures (SOPs) for advanced molecular surveillance following an inclusive approach; capacity-building initiatives for 25 biologists in Mali on sequencing techniques; and international tutoring sessions for eight Malian professionals held in Benin. These collective efforts enabled Mali to establish an advanced molecular surveillance system aligned with the WHO's global strategy for genomic surveillance. This manuscript aims to share experiences, insights, and outcomes from this initiative, with the hope of contributing to the broader discussion on strengthening global health security through collaborative approaches and capacity-building efforts, particularly in developing countries.

Record of a pioneering geothermal borehole in London

This paper records the results of a pioneering exploration borehole drilled in 1984 to a depth of 403.84 m in the London Basin and underlying London–Brabant basement high. The key objectives of the project were to measure the equilibrium temperature in the Paleozoic basement, estimate the temperature gradient after climate impact corrections and assess the heat flow in the area. From this, estimates of temperature at depths of 2000 m could be made with a view to evaluating potential geothermal resources. From the downhole measurements, a temperature gradient of 16°C km −1 was estimated with a temperature range between 46°C and 51°C at a depth of 2000 m, considered to be consistent with other UK sites where there is no contribution from high heat production granites. The results of the Thamesmead exploration borehole suggested that the geothermal potential of the Devonian and the Paleozoic basement below London is poor, and no further work was carried out. The work has remained unpublished until now but in view of the current renewed interest in geothermal resources it is appropriate to make the work public. Although the results were not encouraging, they do remain as a contribution to the revitalized assessment of geothermal resources in the London area and the UK in general.

Modern approaches to land resources valuation (on the example of Western Kazakhstan)

Western Kazakhstan is characterized by a large territory, extremely heterogeneous in terms of soil formation conditions and a complex soil cover structure. Its formation is also influenced by negative anthropogenic factors against the background of desertification. A soil map has been compiled. A methodology for an integrated approach to land resource assessment based on a genetic approach, taking into account the degree of soil degradation, has been substantiated.

Resource and environmental risk assessment of groundwater well fields in the Beijing-Tianjin-Hebei region

Groundwater in the Beijing-Tianjin-Hebei (BTH) region has been overdrawn for a long time, and groundwater pollution is severe. Groundwater well fields (GWFs) face resource- and environment-related pressures, and their safety is a key issue restricting regional social and economic development. We evaluated the groundwater quality and drinking suitability via the entropy-weighted water quality index and the overall health risks to adults and children with an improved model. Furthermore, the risks to GWF resources were determined based on the groundwater level and its variation. The higher Na+ and NO3− concentrations were mainly due to agricultural and industrial activities. Forty-seven GWFs approached the Class Ⅳ water standard, and 25 and 4 GWFs posed high health risks to adults and children, respectively, suggesting environmental risks. Moreover, the average annual groundwater level in the groundwater depression cone of 2 shallow and 6 deep GWFs decreased by 0.25 and 3.2 m, respectively. These GWFs were substantially threatened by groundwater resource attenuation. The groundwater level of 4 GWFs slowly declined, but a deep groundwater depression cone was not formed. However, the risk to groundwater resources remained high. The resource-related and environmental risks of GWFs in the BTH region were synchronous, but the resource-related risk was higher.

An Aeromagnetic Compensation Strategy for Large UAVs

Aeromagnetic surveys are widely used in geological exploration, mineral resource assessment, environmental monitoring, military reconnaissance, and other areas. It is necessary to perform magnetic compensation for interference in these fields. In recent years, large unmanned aerial vehicles (UAVs) have been more suitable for magnetic detection missions because of the greater loads they can carry. This article proposes some methods for the magnetic compensation of large multiload UAVs. Because of the interference of the large platform and instrument noise, the standard deviations (stds) of the compensation data used in this paper are larger. At the beginning of this article, using the traditional T-L model, we avoid the shortcomings of the anti-magnetic interference ability of triaxial magnetic gate magnetometers. The direction cosine information is obtained by using an inertial navigation system, the global positioning system, and a triaxial magnetic gate magnetometer. Then, we increase the amplitude of the maneuvers in the compensation process; this reduces the multicollinearity problems in the compensation matrix to a certain extent, but it also results in greater magnetic field interference. Lastly, we employ the method of Lasso regularization Newton iteration (LRNM). Compared to the traditional methods of least squares (LS) and singular value decomposition (SVD), LRNM provides improvements of 34% and 27%, respectively. In summary, this series of schemes can be used to perform effective compensation for large multi-load UAVs and improve the actual use of large UAVs, making them more accurate in the measurement of aeromagnetic survey data.

Adaptive density guided network with CNN and Transformer for underwater fish counting

Accurate assessment of high-density underwater fish resources is vital to the aquaculture industry. It is directly related to the formulation of fishery insurance strategies and the implementation of breeding plans. However, accurately counting fish in high-density environments becomes challenging due to the uneven distribution of fish density and individual fish’s different sizes and postures. To break through this technical bottleneck, we developed an advanced adaptive density-guided high-density fish counting network. In detail, first of all, the network adopts a multi-layer feature fusion structure similar to UNet, which significantly enhances the matching between fish targets of different scales and feature pyramid levels, effectively alleviating the problems caused by scale changes and morphological deformations. Secondly, the network also introduces a density-guided adaptive selection module, which can intelligently judge the applicability of Convolutional Neural Network and Transformer blocks in different density areas, thereby achieving robust information transfer and interaction between blocks. Finally, to verify the effectiveness of this method, we also specially constructed two high-density data sets: a simulated high-density underwater fish image data set (SHUFD) and a real high-density underwater fish image data set (RHUFD). The proposed method has significant improvements over the state-of-the-art method (CUT) on SHUFD and RHUFD datasets, with the mean absolute error, mean square error, background region bias, foreground region bias and density map bias indicators improving by 3.44% and 6.47%, 11.43% and 4.41%, 23.91% and 29.48%, 4.43% and 10.33%, 8.3% and 13.14%, respectively.

A revised weight of evidence model for potential assessments of geothermal resources: a case study at western Sichuan Plateau, China

Efficient exploration of geothermal resources is the basis of exploitation and utilization of geothermal resources. In recent years, Geographic Information System (GIS) has been increasingly used for the exploration owing to its power ability to integrate and analyze multiple sources of data related to the formation of geothermal resources, such as geology, geophysics, and geochemistry. Correctly understanding the control effect of evidence factors on geothermal resources is the premise and basis of whether the prediction results of evidence weight model are accurate. Traditionally, the conventional weight of evidence model assume that each evidence factor exerts a uniform controlling effect on the formation and distribution of geothermal resources. However, recent research indicates significant variations in the controlling ability of factors such as faults and granites, influenced by factors like activity levels and crystalline ages. Yet, studies addressing this differential control are lacking. To address this gap, we propose a series of weight of evidence models using abundant geological, geophysical, and geothermal data from the western Sichuan plateau, a high-temperature geothermal hotspot in China. This study aims to investigate the impact of varying controlling abilities of evidence factors on the evaluation model, with faults and granites as a case. Performance metrics include prediction rate, success rate index, receiver operating characteristic curve (ROC) and prediction rate of geothermal well. The findings of this research reveal that the weight of evidence model developed through the methodology outlined in this study exhibits superior performance compared to the conventional weight of evidence model. This superiority is evidenced by higher prediction rates, success indices, prediction rate of geothermal wells, and larger AUC values of ROC. Among these models, the weight of evidence model considering both fault and granite classification have the best performance in model evaluation indicators, with a prediction rate of 22.528 and a success index of 0.015408 in the very high potential area. The prediction rate and success index of the high potential area are 3.656 and 0.0025, respectively, and the prediction rate and success index of the middle potential area are 1.649 and 0.001128, respectively, and the AUC value is 0.808, indicating that the model has good accuracy. In terms of geothermal well prediction, the total prediction rate of geothermal favorable areas based on fault and granite classification evidence weight model is as high as 47.0526. Therefore, when constructing the weight of evidence model, the influence of the difference control of evidence factors on the formation of geothermal resources should be fully considered. These results underscore the effectiveness of the proposed methodology in enhancing the predictive accuracy and reliability of geothermal resource assessment in this study. Based on the prediction results of the weight of evidence model considering both fault and granite classification, four favorable geothermal areas with abundant surface heat display are identified in this paper, namely Kangding, Litang, Batang and Ganzi-Dege. In addition, the relatively weak surface heat display areas such as Jiulong, Daofu, Luhuo and Derong also show high geothermal potential. Some attention should be paid to geothermal exploration in the future.