scholarly journals A new GA-IDW approach for interpolating the precipitation

2021 ◽  
Vol 958 (1) ◽  
pp. 012006
Author(s):  
C Șerban ◽  
A Bărbulescu ◽  
C Ș Dumitriu
Keyword(s):  
Inverse Distance Weighting ◽  
Annual Precipitation ◽  
Precipitation Series ◽  
Distance Weighting ◽  
Evolutionary Technique ◽  
Inverse Distance

Abstract This article presents a new algorithm for detecting the Inverse Distance Weighting Algorithm parameter (IDW) using an evolutionary technique. The algorithm was applied to interpolate 51 series of maximum annual precipitation series. Comparisons of its results with those of IDW and the optimized OIDW (a version of IDW optimized with PSO) are provided. The best performances are those of the actual approach.

scholarly journals A Multimethod Analysis for Average Annual Precipitation Mapping in the Khorasan Razavi Province (Northeastern Iran)

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 592
Author(s):  
Mehdi Aalijahan ◽  
Azra Khosravichenar
Keyword(s):  
Regional Planning ◽  
Interpolation Method ◽  
Absolute Error ◽  
Rain Gauge ◽  
Annual Precipitation ◽  
Coefficient Of Determination ◽  
Distance Weighting ◽  
Average Annual Precipitation ◽  
Inverse Distance

The spatial distribution of precipitation is one of the most important climatic variables used in geographic and environmental studies. However, when there is a lack of full coverage of meteorological stations, precipitation estimations are necessary to interpolate precipitation for larger areas. The purpose of this research was to find the best interpolation method for precipitation mapping in the partly densely populated Khorasan Razavi province of northeastern Iran. To achieve this, we compared five methods by applying average precipitation data from 97 rain gauge stations in that province for a period of 20 years (1994–2014): Inverse Distance Weighting, Radial Basis Functions (Completely Regularized Spline, Spline with Tension, Multiquadric, Inverse Multiquadric, Thin Plate Spline), Kriging (Simple, Ordinary, Universal), Co-Kriging (Simple, Ordinary, Universal) with an auxiliary elevation parameter, and non-linear Regression. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and the Coefficient of Determination (R2) were used to determine the best-performing method of precipitation interpolation. Our study shows that Ordinary Co-Kriging with an auxiliary elevation parameter was the best method for determining the distribution of annual precipitation for this region, showing the highest coefficient of determination of 0.46% between estimated and observed values. Therefore, the application of this method of precipitation mapping would form a mandatory base for regional planning and policy making in the arid to semi-arid Khorasan Razavi province during the future.

scholarly journals Evaluation of an inverse distance weighting method for patching daily and dekadal rainfall over the Free State Province, South Africa

Water SA ◽  
2016 ◽  
Vol 42 (3) ◽  
pp. 466 ◽  
Author(s):  
Mokhele Edmond Moeletsi ◽  
Zakhele Phumlani Shabalala ◽  
Gert De Nysschen ◽  
Sue Walker
Keyword(s):  
South Africa ◽  
Inverse Distance Weighting ◽  
Free State ◽  
Weighting Method ◽  
Free State Province ◽  
Distance Weighting ◽  
Inverse Distance

ÁP DỤNG PHƯƠNG PHÁP NỘI SUY NGHỊCH ĐẢO KHOẢNG CÁCH CÓ TRỌNG SỐ ĐÁNH GIÁ PHÂN BỐ KHÔNG GIAN TÀI SẢN SINH KẾ TẠI TỈNH ĐỒNG THÁP

2020 ◽  
Vol 17 (12) ◽  
pp. 2229
Author(s):  
Huỳnh Song Nhựt ◽  
Nguyễn An Bình ◽  
Nguyễn Ngọc Ẩn ◽  
Trần Anh Phương ◽  
Phạm Việt Hòa ◽  
...  
Keyword(s):  
Inverse Distance Weighting ◽  
Asset Index ◽  
Distance Weighting ◽  
Inverse Distance

  Việc tính toán các chỉ số sinh kế góp phần nắm bắt sự khác biệt về sinh kế của các hộ nông dân trên một khu vực nghiên cứu nhất định. Tuy nhiên, công tác điều tra sinh kế sẽ bị giới hạn bởi nhiều yếu tố như chi phí, nhân công, khoảng cách khiến cho các điểm điều tra không thể bao trọn cả vùng nghiên cứu. Các phương pháp thống kê không gian mà cụ thể là phương pháp nội suy cho phép tính toán giá trị tại một vị trí thông qua các giá trị tại những vị trí đã biết bao quanh nó. Nghiên cứu áp dụng phương pháp IDW (Inverse Distance Weighting) để tính toán chỉ số tài sản sinh kế LAI (Livelihood Asset Index) cho toàn bộ khu vực gồm 3 huyện Tam Nông, Tháp Mười và Tân Hồng. Kết quả cho thấy, có sự phân bố không đồng đều về các nguồn vốn và chỉ số tài sản sinh kế giữa các xã cũng như các huyện trong khu vực nghiên cứul; đồng thời, còn chứng minh rằng, phương pháp IDW là một công cụ hữu hiệu trong thống kê không gian với độ chính xác cao. Hơn nữa, kết quả của nghiên cứu có thể được dùng để đánh giá hiện trạng sinh kế, góp phần tạo sự liên kết giữa các vùng trong khu vực nghiên cứu và hướng đến phát triển bền vững.

Static Reservoir Modeling Comparing Inverse Distance Weighting to Kriging Interpolation Algorithm in Volumetric Estimation. Case Study: Gullfaks Field

2021 ◽  
Author(s):  
Daniel Asante Otchere ◽  
David Hodgetts ◽  
Tarek Arbi Omar Ganat ◽  
Najeeb Ullah ◽  
Alidu Rashid
Keyword(s):  
Power Index ◽  
Inverse Distance Weighting ◽  
Kriging Interpolation ◽  
Reservoir Modeling ◽  
Interpolation Algorithm ◽  
Significant Difference ◽  
Distance Weighting ◽  
Porosity And Permeability ◽  
Well Data ◽  
Inverse Distance

Abstract Understanding and characterizing the behaviour of the subsurface by combining it with a suitable statistical method gives a higher level of confidence in the reservoir model produced. Interpolation of porosity and permeability data with minimum error and high accuracy is, therefore, essential in reservoir modeling. The most widely used interpolation algorithm, kriging, with enough well data is the best linear unbiased estimator. This research sought to compare the applicability and competitiveness of inverse distance weighting (IDW) method using power index of 1, 2 and 4 to kriging when there is sparse data, due to time and budget constraints, to calculate hydrocarbon volumes in a fluvial-deltaic reservoir. Interpolation results, estimated from descriptive statistics, were insignificant and showed similar prediction accuracy and consistency but IDW with power index of 1 indicated the least error estimation and higher accuracy. The assessment of hydrocarbon volume calculations also showed a marginal difference below 0.08 between IDW power index of 1 and kriging in the reservoir zones. Reservoir segments cross-validation and correlation analysis results indicate IDW to have no significant difference to kriging with absolute errors of 3% for recoverable oil and 0.7% for recoverable gas. Grid upscaling, which usually causes a loss of geological features and extreme porosity values, did not impact the results but rather complemented the robustness of IDW in both fine and coarse grid upscale. With IDW exhibiting least errors and higher accuracy, the volumetric and statistical results confirm that when there are fewer well data in a fluvial-deltaic reservoir, the suitable spatial interpolation choice should be IDW method with a power index of 1.

scholarly journals Inverse distance weighting interpolated soil properties and their related landslide occurrences

2018 ◽  
Vol 195 ◽  
pp. 03013 ◽  
Author(s):  
Purwanto B. Santoso ◽  
Yanto ◽  
Arwan Apriyono ◽  
Rani Suryani
Keyword(s):  
Internal Friction ◽  
Slope Stability ◽  
Soil Properties ◽  
Hard Rock ◽  
Friction Angle ◽  
Inverse Distance Weighting ◽  
Central Java ◽  
Soil Cohesion ◽  
Distance Weighting ◽  
Inverse Distance

The causes of landslides can be categorized into three factors: climate, topographic, and soil properties. In many cases, thematic maps of landslide hazards do not involve slope stability analyses to predict the region of potential landslide risks. Slope stability calculation is required to determine the safety factor of a slope. The calculation of slope stability requires the soil properties, such as soil cohesion, the internal friction angle and the depth of hard-rock. The soil properties obtained from the field and laboratory investigation from the western part of Central Java were interpolated using Inverse Distance Weighting (IDW) to estimate the unknown soil properties in the gridded area. In this research, the IDW optimum parameter was determined by validation toward the percent bias. It was found that the IDW interpolation using higher weighting factor corresponds with a higher percent bias in case of the depth of hard-rock and soil cohesion, while the opposite was found for the internal friction angle. Validation to landslide incidents in western parts of Central Java shows that the majority of landslide incidents occur at depths of hard rock of 6 m-8 m, at soil cohesions of 0.0 kg/cm2-0.2 kg/cm2, and at internal friction angles of 30°-40°.

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