Meteorological Drought Monitoring Based on Satellite CHIRPS Product over Gamo Zone, Southern Ethiopia

Abstract

Drought is a frequent occurrence in semidesert areas of southern Ethiopia that significantly affect regional, social, economic, and environmental conditions. Lack of rainfall monitoring network, instrument measurement, and failure are major bottlenecks for agro-and hydroclimate research in developing countries. The objectives of this study were to evaluate the performance of CHIRPS rainfall product and to assess meteorological drought using SPI for the period 2000 to 2020 over Gamo Zone, southern Ethiopia. The performance of CHIRPS v2 was assessed and compared to station observations (2000–2020) in the study domain to derive SPI on a three-month timescale. The Pearson correlation coefficient (R), bias, probability of bias (PBias), mean error (ME), mean absolute error (MAE), root mean square error (RMSE), and Nash simulation efficiency (NSE) values across the zone for CHIRPS v2 were found to be 0.88, 1.02, 2.56, 0.25, 22.41, 33.14, and 0.77, respectively. The results indicate that CHIRPS performed good ability to analyze the drought characteristics in the Gamo Zone. The spatial and temporal distribution method of meteorological drought has been evaluated using the Climate Data Tool (CDT). The Standardized Precipitation Index (SPI) was computed using the gamma distribution method. The magnitude of (SPI-3) of monthly and seasonal (MAM) meteorological drought in the zone from 2000 to 2020. The result shows that the known historic drought years (2014, 2015, 2010, 2009, and 2008) were indicated very well. Furthermore, sever and extreme droughts were observed in 2008 and 2009 with drought duration of 6.7 and 6.3, respectively, in most areas of the zone. Hence, this study revealed that CHIRPS can be a useful supplement for measuring rainfall data to estimate rainfall and drought monitoring in this region.

Drought monitoring performance of global precipitation products in three wet seasons in Ethiopia: Part I—Quasi‐objective examination

“…Similar discrepancies were reported by other studies conducted in Ethiopia (e.g., Bayissa et al, 2017; Lemma et al, 2022; Shalishe et al, 2022; Tesfamariam et al, 2019) and in the other part of the world (e.g., Golian et al, 2019; Katiraie‐Boroujerdy et al, 2016). It is also important to note that all these studies have identified CHIRPS as the relatively best precipitation data in representing the spatiotemporal characteristics of precipitation and drought conditions over their respective study regions.…”

“…Many precipitation data evaluation studies were also conducted in Ethiopia during the last two decades (e.g., Ayehu et al, 2018; Bayissa et al, 2017; Belay et al, 2019; Dinku et al, 2008, 2011, 2018; Diro et al, 2009; Dubache et al, 2021; Hirpa et al, 2010; Hordofa et al, 2021; Lemma et al, 2019; Romilly & Gebremichael, 2011; Sahlu et al, 2017; Shalishe et al, 2022; Worqlul et al, 2014; Young et al, 2014). The focus of all these studies was to see the performance of precipitating products in representing the spatial and temporal patterns of precipitation at different spatial scales.…”

“…Results generated from these studies demonstrated that precipitation products have a different level of performance in representing the spatiotemporal characteristics of precipitation over Ethiopia, and most of the recent studies (e.g., Bayissa et al, 2017; Belay et al, 2019; Dubache et al, 2021; Lemma et al, 2019) have identified the CHIRPS as a relatively best precipitation data over Ethiopia. There are also very few studies that evaluated global precipitation products for their drought monitoring performance in Ethiopia (Bayissa et al, 2017; Degefu et al, 2022; Lemma et al, 2022; Reda et al, 2021; Shalishe et al, 2022; Tesfamariam et al, 2019). Except for Degefu et al (2022), all the other studies were conducted at the river basin scale and evaluated a few precipitation products.…”

Evaluation of SPI and Rainfall Departure Based on Multi-Satellite Precipitation Products for Meteorological Drought Monitoring in Tamil Nadu

“…Among the HRPPs evaluated, CHIRPS data were found to have very good agreement with that of the AWS data, indicating the ability to accurately locate the spatial centres and accumulation of precipitation [77]. Such strong agreement between the identified drought and historical drought implies that CHIRPSv2 is a promising rainfall dataset that might be utilised to construct a drought monitoring and early warning system in Ethiopia [51,78]. The highest performance of CHIRPS over other products may be attributed to the development of the products derived from merging IR-derived precipitation with the climate hazards group precipitation climatology and blending with the ground station observation using the inverse distance weighted (IDW) method [27].…”

Performance variations of global precipitation products in detecting drought episodes in three wet seasons in Ethiopia: Part II—statistical analysis

“…There are also very few studies that evaluated the capability of global precipitation datasets in detecting drought occurrences in Ethiopia (Bayissa et al, 2017; Degefu et al, 2022; Lemma et al, 2022; Reda et al, 2021; Shalishe et al, 2022; Tesfamariam et al, 2019). Almost all local studies, except Degefu et al (2022), only looked at a few precipitation products and assessed their performance at river basin and regional scales.…”