Comparison of the Relevance and the Performance of Filling in Gaps Methods in Climate Datasets

Kasri, Jada El; Lahmili, Abdelaziz; Ouadif, Latifa; Bahi, Lahcen; Soussi, Halima

doi:10.1007/978-3-030-11881-5_2

Cited by 6 publications

(8 citation statements)

References 11 publications

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“…This method assumes that the influence of the tracer variable decreases with distance from the sampled location [11] [12]. Inverse distance interpolation (IDW) is a good imputation method because it takes into consideration the weight of the stations [13]. The equation would be as: (6) P 0 is the estimated value of the missing data.…”

Section: The Inverse Distance Weighting (Idw)mentioning

confidence: 99%

Research of suitability area of agriculture in Coastal CHAOUIA by integration the AHP, IDW, and MCDA to GIS

et al. 2020

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Agricultural expansion in developing countries requires a strategy to develop the agricultural sector in a sustainable and rational manner, despite its complexity to be achieved. The objective of this work is to develop an agricultural Suitability map, based on a flexible and interactive model between several methods, which are the analytical hierarchy process (AHP), the Inverse Distance Weighting (IDW), and the multi-criteria decision analysis (MCDA),integrated into the GIS. The factors selected in this study are slope, elevation, land use, minimum and maximum temperature,also rainfall for both the dry and rainy periods. The analysis of the suitability map revealed the effectiveness of this model, which allowed the detection of areas unsuitable for agricultural development. the Comparison of the suitability map with the 2019 classified map shows that agricultural expansion is highly developed and covers almost the total area, which has had negative consequences on the groundwater quality of the Coastal CHAOUIA aquifer.

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Section: The Inverse Distance Weighting (Idw)mentioning

confidence: 99%

Research of suitability area of agriculture in Coastal CHAOUIA by integration the AHP, IDW, and MCDA to GIS

et al. 2020

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“…Three stations were taken into account for the analysis. Before the trend analysis the data were subjected to missing data treatment in previous studies [11,12].…”

Section: Introductionmentioning

confidence: 99%

Trend Analysis of Meteorological Variables: Rainfall and Temperature

et al. 2021

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The Souss-Massa region in southwestern Morocco is characterized by a semi-arid climate with high variability in rainfall. Frequent droughts and flash flood events combined with overexploitation of water resources in recent decades have had a significant impact on the human security and the economy which is mainly based on agriculture, tourism and fishery. For better management of extreme events and water resources under changing climatic conditions, a study was carried out to quantify the seasonal and annual variability and trends in rainfall and temperature over the past three decades with data from three stations. Climatological representative of the Souss-Massa region. The Mann-Kendall (MK) non-parametric test and the Sen’s slope are used to estimate the monotonic trend and magnitude of the trend of the variables, respectively. Statistical analysis of the rainfall series data set highlights that the occurrence of rainfall is unpredictable and irregular and the both the seasonal and annual rainfall trend appears negative (downward) for all the three climatological stations. The minimum temperature shows a remarkable increasing trend both on annual and seasonal scale while the maximum temperature registers a slightly increasing trend. The study presents some new insights on rainfall and temperature trends that will have significant impacts on the surface and groundwater resources of the region under changing climatic conditions. The results can help to prioritize new strategies to mitigate the risk of droughts, of floods and to manage water resources to sustain the dependence of agriculture tourism and fishery sectors in the region. Doi: 10.28991/cej-2021-03091765 Full Text: PDF

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“…But, [19,20] prioritized inverse distance weighting (IDW) over other spatial interpolation techniques. Outperformance was also reported for the normal ratio method (NRM) [16,21,22], correlation coefficient weighing (CCW) [23], and multiple linear regression (MLR) [24]. Nevertheless, Longman et al [25] specified no statistical differences (similar performance) between five spatial interpolation techniques (normal ratio method, linear regression, inverse distance weighting, quantile mapping, and single best estimator) for large gaps.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Seven Gap-Filling Techniques for Daily Station-Based Rainfall Datasets in South Ethiopia

Chinasho

Bedadi

Lemma

et al. 2021

Advances in Meteorology

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Meteorological stations, mainly located in developing countries, have gigantic missing values in the climate dataset (rainfall and temperature). Ignoring the missing values from analyses has been used as a technique to manage it. However, it leads to partial and biased results in data analyses. Instead, filling the data gaps using the reference datasets is a better and widely used approach. Thus, this study was initiated to evaluate the seven gap-filling techniques in daily rainfall datasets in five meteorological stations of Wolaita Zone and the surroundings in South Ethiopia. The considered gap-filling techniques in this study were simple arithmetic means (SAM), normal ratio method (NRM), correlation coefficient weighing (CCW), inverse distance weighting (IDW), multiple linear regression (MLR), empirical quantile mapping (EQM), and empirical quantile mapping plus (EQM+). The techniques were preferred because of their computational simplicity and appreciable accuracies. Their performance was evaluated against mean absolute error (MAE), root mean square error (RMSE), skill scores (SS), and Pearson’s correlation coefficients (R). The results indicated that MLR outperformed other techniques in all of the five meteorological stations. It showed the lowest RMSE and the highest SS and R in all stations. Four techniques (SAM, NRM, CCW, and IDW) showed similar performance and were second-ranked in all of the stations with little exceptions in time series. EQM+ improved (not substantial) the performance levels of gap-filling techniques in some stations. In general, MLR is suggested to fill in the missing values of the daily rainfall time series. However, the second-ranked techniques could also be used depending on the required time series (period) of each station. The techniques have better performance in stations located in higher altitudes. The authors expect a substantial contribution of this paper to the achievement of sustainable development goal thirteen (climate action) through the provision of gap-filling techniques with better accuracy.

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Comparison of the Relevance and the Performance of Filling in Gaps Methods in Climate Datasets

Cited by 6 publications

References 11 publications

Research of suitability area of agriculture in Coastal CHAOUIA by integration the AHP, IDW, and MCDA to GIS

Research of suitability area of agriculture in Coastal CHAOUIA by integration the AHP, IDW, and MCDA to GIS

Trend Analysis of Meteorological Variables: Rainfall and Temperature

Evaluation of Seven Gap-Filling Techniques for Daily Station-Based Rainfall Datasets in South Ethiopia

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