Spatio-temporal interpolation of rainfall data in western Mexico

Vargas, Zaira Carolina Martinez; Valdez, S. Ivvan; Paredes-Tavares, Jorge

doi:10.1109/enc53357.2021.9534803

Cited by 3 publications

(3 citation statements)

References 17 publications

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“…An interpolation method based on inverse distance weighting (IDW) was used for this analysis (Wang et al, 2022). This IDW technique is appropriate when there is a need to quantify values in areas where data are not available, as it correlates them with stations that do have complete values, much wider ranges of the meteorological variable under study can be obtained (Arriola et al, 2022;Tan et al, 2021;Vargas et al, 2021). In addition, the application of IDW in the La Leche basin is justified because it is a simple and accurate methodology for determining the required flows and also, additional information is not needed beyond that available at each hydrometric station.…”

Section: Resultsmentioning

confidence: 99%

Generation of Flows Applying a Simple Method of Flood Routing to Monthly Level in La Leche Basin, Peru

Máximo,

Villegas,

Guillermo

et al. 2024

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Section: Resultsmentioning

confidence: 99%

Generation of Flows Applying a Simple Method of Flood Routing to Monthly Level in La Leche Basin, Peru

Máximo,

Villegas,

Guillermo

et al. 2024

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“…This holistic consideration of both spatial and temporal aspects of rainfall ensures that the simulations more faithfully mirror real-world hydrological processes, ultimately advancing our ability to manage and predict water resources in CZ effectively. Some scholars have studied rainfall spatiotemporal interpolation methods (Hussain et al, 2010;Vargas et al, 2021). Militino et al (2015) proposed two natural and simple extensions to kriging and thin-plate splines to incorporate time dependence into the statistical model.…”

Section: Introductionmentioning

confidence: 99%

Enhancing runoff simulation precision in the critical zone through spatiotemporal interpolation of areal rainfall with matrix decomposition

Sheng,

Chen,

Lin

et al. 2023

Hydrological Processes

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Modelling hydrological process in the critical zone not only contributes to a better understanding of interactions across different Earth surface spheres but also holds significant practical implications for water resource management and disaster prevention. Rainfall‐runoff simulation in critical zones is particularly challenging due to the amalgamation of temporal and spatial complexity, rainfall variability, and data limitations. As a pivotal input variable of hydrological models, accurate estimation of areal rainfall is critical to successful runoff simulation. However, most estimation methods ignore temporal information, thereby increasing uncertainty in rainfall estimation and constraining the precision of rainfall‐runoff simulation. In this study, the matrix decomposition‐based estimation method (F‐SVD), which considers the spatial and temporal correlation of the rainfall process is employed to estimate areal rainfall. The superiority of the method in producing two‐dimensional rainfall information is evaluated through its application in runoff simulation with the Xin'anjiang model. The simulation results of selected flood events in the Jianxi basin in southeast China, spanning from 2009 to 2019, are compared with those of two widely used rainfall estimation methods, namely Arithmetical Mean (AM) and Thiessen Polygons (TP). The results show that (1) F‐SVD not only produces the highest Pearson correlation coefficient between rainfall and runoff series but also reduces the number of flood events with abnormal rainfall‐runoff relationships; (2) the Xin'anjiang model based on F‐SVD achieves the highest Nash‐Sutcliffe efficiency and lowest Relative Error, and performs best in simulating peak flow and its occurrence time as compared to AM and TP. This study contributes to a finer characterization of watershed rainfall distribution, enhancing the accuracy and sharpness of runoff simulation. It provides reliable data support for critical zone research and offers a scientific foundation for rationally allocating and managing water resources.

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“…The precision of the results hinges on two key factors: the spatial interpolation methodologies applied to meteorological data and the thickness of each individual atmospheric layer, uniformly referred to as the 'integration step size' herein. Presently, the majority of research endeavors are concentrated on refining high-precision spatial interpolation techniques, encompassing methods such as mobile surface fitting and bilinear (or trilinear) interpolation [11,12] . However, comprehensive discourse on the subject of integration step size has been scarce.…”

Section: Introductionmentioning

confidence: 99%

Research on ray tracing integration step size in satellite laser ranging and its impact on atmospheric delay calculation results

Mai,

Feng,

et al. 2023

6th Optics Young Scientist Summit (OYSS 2023)

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Atmospheric delay induced by refraction is a significant factor influencing the accuracy of satellite laser ranging (SLR). While ray tracing technique is recognized for its precision in estimating atmospheric delay, there's a gap in the research concerning the computation of integration step size and its impact on results. Therefore, various calculation methods for integration step size were compared and ray tracing with different step sizes were employed to calculate atmospheric delay at Zhuhai Tianqin Station (referred to as "TQ station"). Under different elevation angles, a comparative analysis was conducted to assess the differences in the results and these results were further compared with those from the Mendes-Pavlis model and VMF3o model. The exploration of the relationship between the calculation errors and meteorological factors as well as integration step size indicate that it is essential to select an appropriate integration step size and parameter combination before conducting ray tracing. To achieve millimeter-level accuracy in results, the initial integration step size should be below 50 m. Nevertheless, to avoid data errors, excessively small initial integration step sizes should be avoided. This study highlights the importance of choosing an optimal integration step size and provides valuable insights for improving the precision of atmospheric delay estimation in SLR.

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Spatio-temporal interpolation of rainfall data in western Mexico

Cited by 3 publications

References 17 publications

Generation of Flows Applying a Simple Method of Flood Routing to Monthly Level in La Leche Basin, Peru

Generation of Flows Applying a Simple Method of Flood Routing to Monthly Level in La Leche Basin, Peru

Enhancing runoff simulation precision in the critical zone through spatiotemporal interpolation of areal rainfall with matrix decomposition

Research on ray tracing integration step size in satellite laser ranging and its impact on atmospheric delay calculation results

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