Thiessen Polygon Method Research Articles

SPATIAL ANALYSIS OF PHYSICAL ACCESSIBILITY TO PUBLIC PRIMARY HEALTHCARE CENTERS IN KADUNA STATE, NIGERIA

The rising call for spatial justice in the distribution and access to public facilities especially health necessitated this study. The study sets out to assess the spatial patterns of physical accessibility to PPHCs in Kaduna State. Four physical accessibility parameters were used in this study: travel time, travel distance to the nearest Public Primary Healthcare Centers (PPHCs), mean distances between and within PPHCs, and effective geographic catchment area coverage of PPHCs. Both travel time and distance to the nearest PPHC were evaluated using a questionnaire. The mean distance between and within PPHCs for LGAs was estimated from the Nearest Neighbor Analysis. The effective geographic catchment area of a PPHC was determined using the geospatial Thiessen polygon method. Findings showed that 42% of the respondents, live close (< 2 km) to a PPHC facility. The proximity of the respondents from Igabi (52%), Zaria (49%), and Zangon-Kataf (51%) is closer than the other LGAs. Thiessen catchment area showed a wide range of variations with some PPHCs with very large areas (426 -615 km2) mostly found in the central senatorial zone, especially in Birnin Gwari and Chikun LGAs. The most widespread are PPHCs with relatively moderate catchment sizes of (187–339 km2) found across parts of northern, central, and southern senatorial and LGAs. The study concludes that areal and topographic factors as revealed by the polygon-derived catchment areas should also guide the decision for the siting of PPHCs in the state. Hence, additional PPHCs are recommended especially LGAs with extensive land masses.

Assessment of area at risk of flood and drought in the SeThamok Sub-basin

The problem of floods and drought is a serious problem and has affected many areas in many areas of the world including Lao PDR. SeThaMok sub-basin is a sub-basin that suffers from disasters as mentioned almost every year, especially in Phin district, which has caused enormous damage. Because of such a problem, it is necessary to assess the risk areas for floods and droughts in order to manage floods and droughts that are suitable for the area in order to move forward in planning to deal with floods and droughts in the future. Therefore, this study aims to study flood and drought risk areas as well as create flood maps in (2014, 2018, 2019) and drought maps in (2006, 2012, 2015) using ArcGIS 10.5. This study uses rainfall data from 4 stations using the Thiessen Polygon Method to calculate the average rainfall and using data from the survey, collecting actual data from the field together with the data collected by the Department of Natural Resources and Environment. The results of the study found that: in 2014, there was a flood area covering 11.93% of the total catchment area and the maximum flood level was about 26 meters compared to the lowest level of the catchment area. Among them, the flood event covered 20 villages; In 2018, there is a flood area covering 16.06% of the total catchment area and the maximum flood level is about 32 meters. Among them, the flood event covered 27 villages; In 2019, there is a flood area covering 20.91% and the maximum flood level is about 34 meters. Among them, the flood event covered 39 villages and the results of the evaluation of areas at risk of drought showed that: in 2007, there were areas at risk of drought covering 39.18% of the area of the SeThaMok sub-watershed which covered the number of villages around 32 villages; In 2012, there is a drought-prone area covering 43.29% of the SeThaMok sub-watershed area, which covers about 38 villages; In 2015, there is a drought-prone area covering 36.73% of the SeThaMok sub-basin area, which covers about 30 villages.

Evaluation and Division Methods of Coupled Spatial Units between Parks and Living Circles: A Case Study of Four National-Level New Areas

This study, based on the perspective of supply and demand coupling between parks and living circles, divides spatial units by introducing the Thiessen polygon method with urban parks as the core. Simultaneously, the coefficient of variation (CV) was used to evaluate the distribution characteristics of these spatial units. The suitability of the spatial units was comprehensively evaluated through the three indicators of park service support, functional concentration of living circle, and management and development level. The Node–Place (NP) model was used to quantify the coupling relationship between the park and the living circle, and the characteristics of the coupling units were deeply analyzed from the aspects of supply and demand services, coupling configuration relationship, development management, etc. The results are empirically applied to four national-level new areas, thereby providing a new evaluation method and perspective for urban planning and management.

Koreksi Bias Data Hujan Satelit Persiann Sebagai Alternatif Pos Stasiun Hujan dengan Pendekatan Quantile Mapping di Sub Das Brantas Hulu

The rainfall data is usually obtained from meteorological stations, which many sill observed manually in Indonesia and can lead to an observation error. Remote sensing rainfall data observed by satellite offer interesting alternatives to overcome the limitation of existing meteorological stations in Indonesia. It offers accuracy, spatial coverage, timeliness and cost effectiveness. However it contains bias if compared to land based station. This research will evaluate rainfall data observed in PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) in Brantas Hulu Watershed. The rainfall data of 13 years from 12 stations is evaluated to obtain area averaged rainfall using Thiessen Polygon method. Three datasets from PERSIANN, PERSIANN CCS and PERSIANN CDR are compared statistically with the area averaged area for daily, monthly and yearly rainfall. Bias correction is performed using Quantile Mapping to match the cumulative distribution curve from the area averaged rainfall. Verification of bias correction is performed using 2 years data from 2019 to 2020. Finally, the extreme rainfall analysis is performed to test the corrected data for design rainfall calculations. The correlation of daily data shows poor agreement for all three datasets with correlation coefficient below 0,40. The monthly and yearly data gives better correlation with coefficient above 0,80. It shows that for time series event, the satellite data gives poor correlation with the area averaged rainfall. However, quantile mapping correction gives consistent cumulative distribution agreement for correction and model verification. The verification analysis shows an increase in coefficient correlation from 0.387 to 0.43 (daily) and 0.887 to 0.915 (monthly). In addition, there is a decrease in normalized root mean square error (NRMSE) from 31.03% to 16.91% (daily) and 46.03% to 14.03% (monthly). A decrease in normalized mean absolute error (NMAE) occurred from 16.12% to 9.74% (daily) and 31.67% to 10.07% (monthly). Beside that, the results of extreme rainfall analysis produce values that are very close to the rain station. So it is found that the PERSIANN CCS quantile mapping regression model is the best in improving data quality.

Analysis of Micro Hydro Potential as A New Renewable Energy Source

Electricity demand in Indonesia is currently increasing along with population growth, economic growth, and development. This increase can lead to an energy crisis if it is not accompanied by the provision of additional power plants. This study aims to analyze the micro-hydro potential located at Bangkong Waterfall, Kuningan Regency. The research uses a quantitative approach that begins with field surveys and data collection from relevant agencies. Next, the dependable discharge analysis uses the Thiessen polygon method based on rainfall data and watershed area, as well as flow discharge analysis using the rational method. The results of calculations using the Thiessen polygon method and the rational method yield Q80 with a minimum discharge of 0.009 m³/d and a maximum discharge of 1.160 m³/d. For direct discharge analysis, the Float method is used to calibrate the calculation results with field conditions. The direct discharge analysis using the Float method yields 0.32 m³/d. Based on the efficiency considerations of the micro-hydro power plant (MHPP) components such as a head of 20 meters, turbine type efficiency, water density, gravity factor, and flow discharge in the pipe of 0.109 m³/d, the potential power that can be generated at the Bangkong Waterfall micro-hydro power plant is 16,097.23 Watts or 16.097 Kilowatts.

Exploration of the Impact of Built Environment Factors on Morning and Evening Peak Ridership at Urban Rail Transit Stations: A Case Study of Changsha, China

<div>To identify the influences of various built environment factors on ridership at urban rail transit stations, a case study was conducted on the Changsha Metro. First, spatial and temporal distributions of the station-level AM peak and PM peak boarding ridership are analyzed. The Moran’s I test indicates that both of them show significant spatial correlations. Then, the pedestrian catchment area of each metro station is delineated using the Thiessen polygon method with an 800-m radius. The built environment factors within each pedestrian catchment area, involving population and employment, land use, accessibility, and station attributes, are collected. Finally, the mixed geographically weighted regression models are constructed to quantitatively identify the effects of these built environment factors on the AM and PM peak ridership, respectively. The estimation results indicate that population density and employment density have significant but opposite influences on the AM and PM peak ridership, which can be attributed to the opposite travel directions of commuters in the AM and PM peak. The recreational facility density, road density, and 10-min walking accessibility could significantly positively affect the PM peak ridership, and their influences vary greatly over space. Besides, the operating time of stations significantly positively affects both the AM and PM peak ridership, transfer stations have significantly larger PM peak ridership and terminal stations have significantly larger AM peak ridership. The findings are expected to provide new insights for agencies to formulate appropriate measures to improve the ridership of urban rail transit.</div>

Maritime Boundary Delimitation using Different Methods of GIS - A Case Study of the France-United Kingdom (Jersey Island) Boundaries

Abstract Maritime and territorial zone disputes have created tensions and conflicts between countries with contiguous or adjacent maritime zones. France escalated its fishing rights dispute with the UK by announcing that it had seized an unlicensed British vessel operating in French waters. This paper examines the incident by reviewing the geographical condition and creating a maritime boundary map between the France-United Kingdom (Jersey) that complies with the UNCLOS 1982 convention. This research uses GIS software and bathymetry data to create maritime boundaries according to the UNCLOS 1982 convention. GIS methods used include Buffer, Thiessen Polygon and Geocap Maritime Delimitation toolbox. According to the “geocap maritime delimitation” toolbox, the total water area measures 509 square miles, with an even division between the two areas. However, when utilizing the buffer and Thiessen polygon methods, there is a notable variation of 56 square miles between the water areas of Jersey and France. The delimitation method from the Geocap Maritime Delimitation toolbox was chosen as the best method because this tool can generate critical points and baselines from the closest point between two baselines that follow UNCLOS convention and produce a solution with the equidistance division between the two countries.

A genetic algorithm's novel rainfall distribution method for optimized hydrological modeling at basin scales

ABSTRACT Rainfall has a dominant role in rainfall-runoff models, with the rendering of these models depending both on the accuracy of the data and on the way that rainfall is spatially allocated. The research proposes a methodological framework where a genetic algorithm (GA)-based method responsible for the spatial distribution of gauge observations at the basin scale is coupled with the HEC-HMS hydrological model to produce simulated discharges of high accuracy. The custom-developed GA is used to divide a 2D space, adhering to specific criteria, into polygonal geometries that represent gauge zones of influences, similar to the Thiessen polygon method concept. Consequently, a collection of vectorial polygonal areas, equivalent in number to the employed monitoring stations, is produced with the areal weights to be used for distributing the rainfall across the case study basin and subsequently to force the hydrological simulations. The generated gauge weights are validated for a different temporal precipitation event. The final outputs expressed through a series of statistical measures, clearly demonstrate the effectiveness of the specific methodology (e.g. R2 and Nash–Sutcliffe are larger than 0.83 and 0.73). The methodology can foster accurate hydrological simulations, especially in cases where there is a limited number of rainfall stations and corresponding observations.

Temporal Dynamics and Trend Analysis of Areal Rainfall in Muger Subwatershed, Upper Blue Nile, Ethiopia

This study was employed to investigate the temporal variability and trend analysis of areal rainfall in the Muger subwatershed, Upper Blue Nile, Ethiopia. The study was run over the following procedures to handle the main objective: (1) determining the areal rainfall from gauged point rainfall using the Thiessen polygon method, (2) grouping the months in the season according to the study area, (3) evaluating the temporal dynamics of annual and seasonal areal rainfall using the coefficient of variation (CV), standard anomaly index (SAI), and precipitation concentration index (PCI), and (4) analyzing the trend of annual and seasonal areal rainfall using modified Mann–Kendall’s (modifiedmk) test in RStudio. Based on the temporal variability analysis, CV results depict that annual and summer areal rainfall had low variability with values of 13.43% and 13.7%, respectively. Winter and spring areal rainfall shows high variation with a CV value of 50.5% and 36%, respectively. According to the SAI output, around 70% of the considered year was in the normal condition of wetness. On the other hand, the seasonal (winter, spring, and summer) rainfall distribution of the study area shows strong irregularity distribution throughout the considered years as a result of PCI with a value of 57.5%. The trend of the areal rainfall was shown to be both increasing and decreasing. However, the trend was insignificant with a 10% confidence level.

Prediction of the Hydrological Drought Index (HDI) based on Rain Simulation Data using an Artificial Neural Network (ANN) in the Randugunting Watershed, Rembang Regency

Randugunting Watershed, with the main river Randugunting River, originates from the North Limestone Mountains of Rembang Regency. Because of its cyclical nature, the river flow discharge is continually subject to change. The discharge rises during rainy weather and falls during dry weather. Due to this issue, Rembang will likely experience drought throughout the dry season. The objectives of this study are to: (1) determine the drought index and its sharpness based on the Hydrological Drought Index Method (HDI) and (2) make drought predictions using the HDI based on discharge for the years 2023–2026 using simulated rain data with Artificial Neural Networks (ANN). Calculation of regional rainfall using the Thiessen Polygon Method. To find simulated rain and drought prediction based on the ANN with Backpropagation algorithm using Mathlab software. From the analysis indicate that the number of months that would experience wet conditions are decreasing from 7 months in 2023 and 2024 to 6 months in 2025 and only 3 months in 2026. In the anticipated drought from 2023 to 2026, there will be 14 dry months, 8 very dry months, and 3 extremely dry months. The examination of the hydrological drought’s duration revealed that the typical drought period fell between May and November.

Precipitation Study in Flood Zones: San Mateo Atenco, State of Mexico, Mexico Case Study

This work is focused on analyzing the causes of flooding in the sub-basin belonging to the municipality of San Mateo Atenco: Almoloya-Otzolotepec, because the municipal territory is constantly threatened by hydrometeorological phenomena, such as hailstorms, frost and torrential rains. The maximum precipitation was analyzed in neighboring climatological stations and the precipitation at different return periods (2 to 1000) was determined through the Gumbel distribution, and its impact according to the Thiessen polygon method. With the information of the 24-hour intensities, the Intensity Duration Frequency (IDF) curves and the hietogram of the study area were plotted using the alternating block method. The above procedure was applied to the precipitation data from the 9 stations that affect the basin. The approach proposed in this work considers all the precipitation variables for the best approximation of the phenomena that may occur in the basin; it is an innovative model because it considers the weighted averages of precipitation for each area of influence and its surroundings; this information is useful for the implementation of flood protection projects, adequate design of drainage and sewage systems, and a rational use of the resource to guarantee better living conditions for the inhabitants. According to the results obtained, there is a slow hydrological response and the areas with the greatest runoff potential (8383<CN<100) are located towards the central part of the basin where there is a significant concentration of bare soil.

Improving flood forecasting in Narmada river basin using hierarchical clustering and hydrological modelling

The purpose of the study was to use hierarchical clustering and Thiessen polygon algorithms to identify the significant rain gauge stations for flood forecasting at Sardar Sarovar Dam. Rainfall data from 2010 to 2018 was utilized to analyze the catchment region between Omkareshwar Dam and Sardar Sarovar Dam. The study identified two clusters of rain gauge stations with similar rainfall patterns and divided the study area into seventeen regions using Thiessen polygons. The land use map showed that the study area was mostly covered by crop lands, and the soil map divided the area into three types of sedimentary claystone soil. A hydrological model, Hydrologic Engineering Center – Hydrologic Modelling System (HEC-HMS), was used for rainfall-runoff modeling, and the computed runoff was compared with observed gauge discharge and inflow of Sardar Sarovar Dam. Regression analysis was performed to assess the performance of the model, and the results showed a good correlation between observed rainfall and estimated runoff values for 2012 and 2016. The study concludes that the existing rain gauge network is sufficient for flood forecasting, and the developed model along with the Thiessen polygon method can provide more accurate predictions of flow. The study highlights the importance of selecting suitable rain gauge stations for reliable flood forecasting in flood-prone basins. The study findings can be useful for future runoff prediction and flood forecasting in the study area.

Prediction of global potential growth areas for Panax ginseng based on GMPGIS system and MaxEnt model

The suitable habitat for the endangered and valuable medicinal herb Panax ginseng is gradually decreasing. It is crucial to investigate its suitable growing areas in China for global protection and sustainable utilization of P. ginseng. In this study, 371 distribution points of P. ginseng were collected, and 21 environmental factors were used as ecological indicators. The geographic information system for global medicinal plants(GMPGIS) system, MaxEnt model, and Thiessen polygon method were used to analyze the potential suitable areas for P. ginseng globally. The results showed that the key environmental variables affecting P. ginseng were precipitation in the hottest quarter(Bio18) and the coefficient of temperature seasonality(Bio4). The suitable habitats for P. ginseng were mostly located in the "One Belt, One Road" countries such as China, Japan, South Korea, North Korea, and Russia. The highly suitable habitats were mainly distributed along mountain ranges in southeastern Shandong, southern Shanxi and Shaanxi, northern Jiangsu, and northwestern Henan of China. Data analysis indicated that the current P. ginseng planting sites were all in high suitability zones, and the Thiessen polygon results showed that the geographic locations of P. ginseng production companies were unbalanced and urgently needed optimization. This study provides data support for P. ginseng planting site selection, scientific introduction, production layout, and long-term development planning.

A novel regional drought monitoring method using GNSS-derived ZTD and precipitation

The drought monitoring indexes, such as SPEI and SPCI, have been proposed previously. However, these indexes are established at specific station and unsuitable to evaluate the regional drought, which becomes the focus of this study. A novel drought monitoring method using the zenith troposphere delay (ZTD) derived from global navigation satellite system (GNSS) and precipitation is proposed, and a new index, which is named regional precipitation and ZTD index (RPZI), is established. The station-based precipitation and ZTD index (PZI) is first proposed by considering the data selection, expression, multi-time scale and standardization. The RPZI is then calculated by using the Thiessen Polygon method to determine the weighting of each station in the located area. The proposed PZI is first validated in 8 climatic regions of China over the period of 2006–2018 at 801 metrological stations. The RPZI is further evaluated in arid, semiarid, humid, and semi humid areas of China over the period of 2006–2018 and Townsville, Queensland in Australia over the period of 1998–2018, respectively. Comparison results show that the proposed RPZI has a good consistency with the regional precipitation smoothing index (RPSI) when compared with station-based SPEI, station-based PZI, and regional SPEI (RSPEI), and the correlation coefficient is the highest between the RPZI and RPSI with values of 0.81, 0.90, 0.93, and 0.85 in four areas of China, and the corresponding value reaches 0.964 in Queensland, Australia. Such results show the good capacity of the proposed RPZI for regional drought monitoring, which is of great importance for global drought disaster prevention.

PERENCANAAN BENDUNG TETAP UNTUK JARINGAN IRIGASI BANDA MUSAJIK D.I GUMARANG KECAMATAN PELEMBAYAN KABUPATEN AGAM

Banda Musajik, which is located in Jorong Alahan Anggang, Nagari Tigo Koto Silungkang, Agam Regency, West Sumatra Province, is one of the irrigation networks in D.I Gumarang, under the authority of the UPTD Balai SDA and BK North Sumatra Province. The service area is 30 ha, the water source comes from Batang alahan anggang. Weir planning is based on the design flood discharge with a return period of 100 years. The discharge plan uses 10 years of rainfall data. Rainfall stations that affect the Alahan Anggang watershed are Gumarang Station and Kampuang IV Station. The area's average rainfall was determined by the Thiessen Polygon method, the planned rain by the log normal method and the frequency analysis test using the chi square test. Maximum flood discharge (Q100) 13.54 m3/s. The effective width of the dam is 11.42 m, one flush door is 0.80 m wide, one pillar is 0.50 m thick. The type of lighthouse is round with a radius of 0.80 m and a height of 1.52 m. The stilling pool is planned for the Vlugter type with the height of the weir, the length of the pool floor and the radius of the weir of 3.74 m. The length of the flood embankment from the weir to the upstream is 19 m with a height of 0.50 m from the flood water level. From the analysis of the forces acting on the body of the weir, the number of vertical forces (ΣRV) is 5,916 T, the number of horizontal forces (ΣRH) is 8,397 T, the number of holding moments (ΣMT) is 352,678 T.m, the number of overturning moments (ΣMG) is 344,87 T.m. stability of the weir body against overturning 1.31 1.3 , against shear 1.42 1.3, Eccentricity ( e ) 5.05 78.74 Maximum stress 1.90 78.74, minimum stress -0.36 78.7, the design of the weir body is safe against shearing, overturning, and the bearing capacity of the ground.Key words : Hydrological analysis, Hydraulic design of weir, Weir stability.

Status of primary healthcare services in a geographically disadvantageous area: a study of Alipurduar district, West Bengal, India

PurposeThe locational disadvantage of a health-care centre often restricts adequate delivery of health-care services in an area. The purpose of this study is to examine the status of primary health-care services in such a geographically disadvantageous area which is confined by forests, tea gardens and undulating topography.Design/methodology/approachNecessary secondary data of 13 primary health centres and 236 sub-centres has been collected from the Office of the Chief Medical Officer of Health. Based on obtained data, Health-care Infrastructure Index has been prepared which has been validated by an expert panel, and subsequently, the Thiessen Polygon method has been applied through Arc GIS software to show spatial variation of health-care services delivered by different health-care centres.FindingsIn the study area, there is wide variation found in the case of physical facilities, caregivers and connectivity of road networks, which altogether affect the overall status of health-care services. Among all the indicators, some health-care centres experience staff shortages for prolonged non-recruitment, inaccessibility and inconsistent patient load in different health centres.Originality/valueIn spite of the unfavourable geographical landscape, health-care centres have to be set up wherever possible. There is a need to make new roads and simultaneously the existing road connectivity should be improved so that patients and caregivers can move quickly whenever required. Existing physical facilities need to be renewed or redeveloped along with increasing the number of doctors and other health-care providers as per the need of people with an adequate and optimum level of services.

Assessing the changeability of precipitation patterns using multiple remote sensing data and an efficient uncertainty method over different climate regions of Iran

While the rain gauge measurements are unevenly distributed in many world regions, it is necessary to use remote sensing-based precipitation data at high spatial and temporal resolutions. On the other hand, quantifying the uncertainty of precipitation is a vital issue for hydrometeorological applications globally. For this purpose, applying a new fusion framework using high-resolution remote sensing datasets can provide accurate precipitation evaluation against local observations with low uncertainty. This study examines three weighted fusion-based models containing the Ordered-Weighted-Averaged (OWA) family approach based on the ORLIKE method (OWA-ORLIKE) and ORNESS method (OWA-ORNESS) as well as the Entropy-weight (EW) method to combine different remote sensing precipitation products over different climate zones of Iran. In this case, multiple monthly remotely sensed datasets, including ERA5, ERA5-Land, TerraClimate, GPM, PERSIANN-CDR, TRMM, and CHIRPS, are utilized to assess precipitation patterns versus local measurements, which were gathered by Google Earth Engine (GEE) platform. Furthermore, the K-means algorithm is employed to cluster ground-based precipitation stations based on the climate zones category across Iran. Additionally, the Genetic Optimization Algorithm (GOA) is applied to specify optimal values of weights in weighting-based models. The performance of single and combination datasets are evaluated using statistical error metrics, including Pearson correlation coefficient (PCC), root mean square error (RMSE), Kling Gupta efficiency (KGE), and bias. The Thiessen polygon method has been applied to calculate each cluster's mean precipitation to obtain the optimal weights of stations. Finally, as an efficient uncertainty approach, Cross Wavelet Transform (XWT) method has been used for uncertainty assessment of monthly and seasonal precipitation series. Results indicated that the OWA family as the best fusion model had almost the lowest uncertainty values and best statistical error indices compared to the EW model and all single products in different clusters of Iran. As a motivation part of this study, unlike the single sources of remotely sensed data, multiple datasets can apply together in different climate conditions with various features using combination models, which mentioned uncertainty method has clearly revealed this claim.

A Method for Assessing the Thickness of Cobalt-Rich Crust on Seamounts and Its Application on the Il’ichev Guyot

Seamount cobalt-rich crusts are rich in cobalt resources and are sought after worldwide. Among different affecting parameters, crust thickness is the most important in evaluating cobalt-rich crust resources in seamounts. Generally, there are two challenges to crust thickness evaluation: firstly, due to high operating costs, most geological stations for seamount exploration have sparse sampling distributions so there are insufficient data to estimate the crust thickness distribution; secondly, a single evaluation method has advantages and disadvantages, and it is not feasible to benefit from the advantages only. These methods cannot simultaneously make full use of the sampling data in local areas, providing a more appropriate evaluation of the whole area. As a result, the estimated results cannot fully reflect the thickness distribution. Based on the thickness data of the station survey and topographic data, geostatistical units are divided, and a comprehensive crust thickness assessment scheme is established on the ArcGIS platform. To this end, the adjacent area method is applied to calculate the crust thickness within the influence range of the station. Combined with the station buffer radius and Thiessen polygon method, the crust thickness within 1.5 km of the survey station was estimated. Then the “slope–distance” Kriging interpolation method was used to calculate the crust thickness in the study area, and the crust thickness in the optimal effective radius area was given to compensate for the missing part in the first step. Finally, the geological blocks were divided using the topographic classification method, and the crust thickness of the remaining unassigned regions was estimated using the mathematical expectation method. The proposed method was applied to evaluate the Il’ichev Guyot’s crust thickness and reasonable results were achieved. It was found that the thickness estimation of the area near the station is consistent with the measured values. Since finer topographic data are used in the calculation, the thickness estimation result is more detailed. In this regard, a simple and effective calculation method was established on the ArcMap platform. The mathematical expectation estimation method of the crust thickness, based on the topographic and geomorphological classification from the perspective of the mineralization mechanism, compensates for the drawbacks of the first two methods originating from the lack of data points. The results show that the proposed method is an appropriate scheme to evaluate seamount crust thickness without comprehensive investigation.

Acquisition of rainfall in ungauged basins: a study of rainfall distribution heterogeneity based on a new method

High-density rainfall data is always desired to capture the heterogeneity of precipitation to accurately describe the components of the hydrological cycle. However, equipping and maintaining a high-density rain gauge network involve high costs, and the existing rain gauges are often unable to meet the density requirements. The objective of this study is to provide a new method to analyze the spatiotemporal variability of the precipitation field and to solve the problem of insufficient site density. To this end, the proper orthogonal decomposition (POD) method is proposed, which can analyze the spatial distribution characteristics of rainfall fields to solve data shortages. To demonstrate the feasibility and advantages of the proposed methodology, four districts and counties (Hongshan District, Jianli County, Sui County, and Xuanen County) in Hubei province in China were selected as case studies. The principal results are as follows. (1) The proposed method is effective in analyzing the spatiotemporal variability of the rainfall field to reconstruct rainfall processes in ungauged basins. (2) Compared with the commonly used Thiessen polygon method, the inverse distance weighting method, and the Kriging method, POD is more accurate and convenient, and the root mean squared error is reduced from 3.22, 1.83, 2.19 to 2.09; the correlation coefficients are improved from 0.60, 0.85, 0.79 to 0.89, respectively. (3) The POD method performs particularly well in simulating the peak value and the peak time and can offer a meaningful reference for analyzing the spatial distribution of rainfall.

Assessing the effective spatial characteristics of input features through physics-informed machine learning models in inundation forecasting during typhoons

This study aimed to assess the effective spatial characteristics of input features by using physics-informed, machine learning (ML)-based inundation forecasting models. To achieve this aim, inundation depth data were simulated using a numerical hydrodynamic model to obtain training and testing data for these ML-based models. Effective spatial information was identified using a back-propagation neural network, an adaptive neuro-fuzzy inference system, support vector machine, and a hybrid model combining support vector machine and a multi-objective genetic algorithm. The conventional average rainfall determined using the Thiessen polygon method, rain gauge observations, radar-based rainfall data, and typhoon characteristics were used as the inputs of the aforementioned ML models. These models were applied in inundation forecasting for Yilan County, Taiwan, and the hybrid model had the best forecasting performance. The results show that the hybrid model with crucial features and appropriate lag lengths has the best performance.