Climate change impact assessment on mild and extreme drought events using copulas over Ankara, Turkey

Afshar, Mahdi; Şorman, A. Ünal; Tosunoğlu, Fatih; Bulut, Burak; Yılmaz, M. Tuğrul; Mehr, Ali Danandeh

doi:10.1007/s00704-020-03257-6

Cited by 42 publications

(19 citation statements)

References 34 publications

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“…The length of the precipitation time series and the nature of the probabilistic distributions play an important role in the calculation of SPI [48]. The ability to calculate the SPI drought index at different time scales (e.g., 1, 6, 12, and 24) can be considered as one of the advantages of this index [49]. In this study, among different SPI time scales, the SPI-12 is selected as the meteorological drought indicator due to its capability in accurate detection of drought durations [50].…”

Section: Study Areamentioning

confidence: 99%

Comparative Evaluation of Microwave L-Band VOD and Optical NDVI for Agriculture Drought Detection over Central Europe

2021

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Agricultural droughts impose many economic and social losses on various communities. Most of the effective tools developed for agricultural drought assessment are based on vegetation indices (VIs). The aim of this study is to compare the response of two commonly used VIs to meteorological droughts—Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and Soil Moisture and Ocean Salinity (SMOS) vegetation optical depth (VOD). For this purpose, meteorological droughts are calculated by using a standardized precipitation index over more than 24,000 pixels at 0.25° × 0.25° spatial resolution located in central Europe. Then, to evaluate the capability of VIs in the detection of agricultural droughts, the average values of VIs anomalies during dry and wet periods obtained from meteorological droughts are statistically compared to each other. Additionally, to assess the response time of VIs to meteorological droughts, a time lag of one to six months is applied to the anomaly time series of VIs during their comparison. Results show that over 35% of the considered pixels NDVI, over 22% of VOD, and over 8% of both VIs anomalies have a significant response to drought events, while the significance level of these differences and the response time of VIs vary with different land use and climate conditions.

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Section: Study Areamentioning

confidence: 99%

Comparative Evaluation of Microwave L-Band VOD and Optical NDVI for Agriculture Drought Detection over Central Europe

2021

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“…where 𝐸(𝐷𝐼𝑇) is the expected value of DIT and 𝑇 𝑈>𝑢 is the return period of drought, which is determined by 𝑢. E(DIT) was calculated as the ratio of the total duration to the total number of droughts. It is also possible to extend the return period to the bivariate case by characterizing events with a coincidence or conditional probability [27], [28], i.e…”

Section: Joint Return Periodmentioning

confidence: 99%

Copula in Wildfire Analysis: A Systematic Literature Review

Najib¹,

Nurdiati²,

Sopaheluwakan

2021

InPrime:Ind.Jour.Pure.Applied.Math

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Copula model is a method that can be implemented in various study fields, including analyzing wildfires. The copula distribution function gives a simple way to define joint distribution between two or more random variables. This study aims to review the application of copula in the analysis of wildfires using a Systematic Literature Review (SLR) and provide insight into research opportunities related to the application in Indonesia. The results show there are very few articles using the copula model in the analysis of wildfires. However, the increasing number of article citations each year shows the importance of such article research and has contributed to wildfire analysis development. In that article, 50% of studies applied the copula model to direct wildfire analysis (using fire data) in Canada, Portugal, and the US. Meanwhile, the other 50% use the copula model for indirect wildfire analysis (not using fire data) in Canada and the European region. The outcome of the presented review will provide the latest research positions and future research opportunities on the application of copula in the analysis of wildfires in Indonesia.Keywords: copula; wildfire; systematic literature review. AbstrakModel copula merupakan metode yang dapat diimplementasikan pada berbagai bidang penelitian, salah satunya pada analisis kebakaran hutan. Fungsi sebaran copula memberikan cara yang mudah untuk mendefinisikan sebaran peluang bersama antara dua peubah acak atau lebih. Tujuan penelitian ini mengulas penerapan model copula tersebut pada analisis kebakaran hutan dalam studi literatur menggunakan Systematic Literature Review (SLR) serta memberikan peluang riset ke depan terkait implementasinya pada analisis kebakaran hutan di Indonesia. Hasil penelitian menunjukkan bahwa model copula pada analisis kebakaran hutan masih sangat sedikit. Namun, peningkatan jumlah sitasi artikel tiap tahun menunjukkan pentingnya penelitian tersebut dan memiliki kontribusi pada perkembangan analisis kebakaran hutan. Pada artikel tersebut, sebanyak 50% penelitian menerapkan model copula pada analisis kebakaran secara langsung (menggunakan data kebakaran) di Kanada, Portugal, dan Amerika. Sementara, sebanyak 50% lainnya menerapkan model copula pada analisis kebakaran secara tak langsung (tidak menggunakan data kebakaran), yaitu di Kanada dan kawasan Eropa. Hasil tinjauan memberikan posisi riset terkini serta usulan riset ke depan mengenai penerapan model copula untuk analisis kebakaran hutan dan lahan di Indonesia.Kata kunci: copula; kebakaran hutan; studi literatur sistematik.

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“…Agriculture plays a critical role in supporting livelihoods and food security for rural households across the developing world [1]. Designing strategies to protect farmers against crop losses caused by adverse weather conditions, such as droughts or floods, has become a key priority for governments and donors, particularly given expected increases in the frequency or intensity of extreme weather events in the coming decades due to climate change [2,3]. One of these strategies is to provide smallholder farmers with agricultural insurance, which offers financial protection from losses associated with extreme weather.…”

Section: Introductionmentioning

confidence: 99%

Improving the Performance of Index Insurance Using Crop Models and Phenological Monitoring

et al. 2021

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Extreme weather events cause considerable damage to the livelihoods of smallholder farmers globally. Whilst index insurance can help farmers cope with the financial consequences of extreme weather, a major challenge for index insurance is basis risk, where insurance payouts correlate poorly with actual crop losses. We analyse to what extent the use of crop simulation models and crop phenology monitoring can reduce basis risk in index insurance. Using a biophysical process-based crop model (Agricultural Production System sIMulator (APSIM)) applied for rice producers in Odisha, India, we simulate a synthetic yield dataset to train non-parametric statistical models to predict rice yields as a function of meteorological and phenological conditions. We find that the performance of statistical yield models depends on whether meteorological or phenological conditions are used as predictors and whether one aggregates these predictors by season or crop growth stage. Validating the preferred statistical model with observed yield data, we find that the model explains around 54% of the variance in rice yields at the village cluster (Gram Panchayat) level, outperforming vegetation index-based models that were trained directly on the observed yield data. Our methods and findings can guide efforts to design smart phenology-based index insurance and target yield monitoring resources in smallholder farming environments.

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Climate change impact assessment on mild and extreme drought events using copulas over Ankara, Turkey

Cited by 42 publications

References 34 publications

Comparative Evaluation of Microwave L-Band VOD and Optical NDVI for Agriculture Drought Detection over Central Europe

Comparative Evaluation of Microwave L-Band VOD and Optical NDVI for Agriculture Drought Detection over Central Europe

Copula in Wildfire Analysis: A Systematic Literature Review

Improving the Performance of Index Insurance Using Crop Models and Phenological Monitoring

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