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Agricultural drought analysis and its association among land surface temperature, soil moisture and precipitation in Gamo Zone, Southern Ethiopia: a remote sensing approach

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Abstract

Drought is a multifaceted natural hazard that has an impact on various aspects like; agricultural, hydrological, ecological and socio-economic systems. Drought has been a predominant concern for farmers in Gamo Zone over the last decades; hence, monitoring drought is important for soil conservation, water planning and management to mitigate impacts on agriculture in the Zone. The vegetation indices normal difference vegetation index and vegetation condition index are popular since they are based only on satellite images. The present study attempts to monitoring spatiotemporal distribution of agricultural droughts and its association with land surface temperature, precipitation and soil moisture from the period 2000–2020 using remote sensing application method in Gamo Zone. The vegetation condition index (VCI) and Normal difference vegetation index (NDVI) were used to evaluate spatial and temporal distribution of agricultural drought in Gamo Zone. The Pearson correlation method was used to identify Normal difference vegetation index association with land surface temperature, soil moisture and precipitation. The results discovered that severe drought to very severe drought was identified in 2000, 2002, 2004, 2008, 2009 and 2015 with the area coverage 39.7%, 28.8%, 33.4%, 24.5%, 61.3% and 23.0%, respectively. Similarly, the findings show that slight to mild droughts have a great chance of occurrence in Gamo Zone. The data also demonstrate that normal difference vegetation index has a strong relationship with land surface temperature (R = − 0.95), precipitation (R = 0.65) and soil moisture (R = 0.85), indicating that normal difference vegetation index is more sensitive to land surface temperature than soil moisture and precipitation, although soil moisture has a positive relationship with precipitation (R = 0.60). Therefore, this study revealed that normal difference vegetation index and vegetation condition index indices are suitable for agricultural drought monitoring and they are strongly associated with precipitation, soil moisture and land surface temperature. This study shall be helpful for decision makers to take the necessary measures by considering the drought risk maps for early warning system and future drought management plans.

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References

  • Abera K (2022) Review of hydrological drought analysis status in Ethiopia. In: Admasu G, Murat E, Ahmed A, Mesut T, Ercan G (eds) IntechOpen, Ch. 3, Rijeka

  • Alahacoon N, Edirisinghe M (2022) A Comprehensive assessment of remote sensing and traditional based drought monitoring indices at global and regional scale. Geomat Nat Haz Risk 13(1):762–799

    Article  Google Scholar 

  • Bayable G, Gashaw T (2021) Spatiotemporal variability of agricultural drought and its association with climatic variables in the upper Awash Basin, Ethiopia. SN Appl Sci 3(4):1–20

    Article  Google Scholar 

  • Belay A et al (2021) Analysis of climate variability and trends in Southern Ethiopia. Climate 9(6):1–17

    Article  Google Scholar 

  • Chou CB et al (2022) Monitoring the spring 2021 drought event in Taiwan using multiple satellite-based vegetation and water indices. Atmosphere 13(9):1–15

    Article  Google Scholar 

  • Daba M (2016) Studies on temporal relationship between normalized difference vegetation index and rainfall in the southern part of Ethiopia. Studies 3216:93–97

    Google Scholar 

  • Dagnachew M, Asfaw K, Awdenegest M, Adane A (2020) Effects of climate variability on normalized difference vegetation index (NDVI) in the Gojeb River catchment, Omo-Gibe Basin Ethiopia. Adv Meteorol 2020:1

    Article  Google Scholar 

  • Deng Y et al (2018) Relationship among land surface temperature and LUCC, NDVI in Typical Karst Area. Sci Rep 2017:1–12

    Google Scholar 

  • Dutta D et al (2015) Assessment of agricultural drought in Rajasthan (India) using remote sensing derived vegetation condition index (VCI) and standardized precipitation index (SPI). Egypt J Remote Sens Space Sci 18(1):53–63

    Google Scholar 

  • Emana B et al (2015) Characterization and assessment of vegetable production and marketing systems in the humid tropics of Ethiopia. Quart J Int Agric 54(2):163–187

    Google Scholar 

  • Fahad S et al (2022) Spatiotemporal variation in land use land cover in the response to local climate change using multispectral remote sensing data. Land 11:595

    Article  Google Scholar 

  • FAO, Land and Water Division (2017). FAO water reports, food and agriculture organization of the United Nations Rome In: 2017 Drought Characteristics and Management in Central Asia and Turkey

  • Faridatul MI, Ahmed B (2020) Assessing agricultural vulnerability to drought in a heterogeneous environment: a remote sensing-based approach. Remote Sens 12(20):1–17

    Article  Google Scholar 

  • Food and Agriculture Organization of the United Nations (FAO) (2017). The impact of disasters and crises on agriculture and food security

  • Gao F et al (2018) Evaluation of CHIRPS and its application for drought monitoring over the Haihe River Basin, China. Nat Hazards 92(1):155–172

    Article  Google Scholar 

  • Gebru BM, Lee WK, Khamzina A, Wangyel S (2021) Spatiotemporal multi—index analysis of desertification in dry Afromontane forests of Northern Ethiopia. Environ Dev Sustain 23(1):423–450

    Article  Google Scholar 

  • Gidey E et al (2018) Analysis of the long-term agricultural drought onset, cessation, duration, frequency, severity and spatial extent using vegetation health index (VHI) in Raya and its environs, Northern Ethiopia. Environ Syst Res 7(1):13

    Article  Google Scholar 

  • Godde CM et al (2021) Impacts of climate change on the livestock food supply chain; a review of the evidence. Glob Food Sec 28:100488

    Article  Google Scholar 

  • Hao Z et al (2016) A theoretical drought classification method for the multivariate drought index based on distribution properties of standardized drought indices. Adv Water Resour 92:240–247

    Article  Google Scholar 

  • Hengsdijk H, Jansen H (2006) Agricultural development in the central Ethiopian rift valley: a desk-study on water-related issues and knowledge to supporta policy dialogue. Plant Res Int. 〈http://LibraryWur.Nl/WebQuery/Wurpubs/347623〉

  • Ji L, Albert JP (2018) Assessing vegetation response to drought in the northern great plains using vegetation and drought indices assessing vegetation response to drought in the northern great plains using vegetation and drought indices

  • Jiao W et al (2016) Evaluating an enhanced vegetation condition index (VCI) based on VIUPD for drought monitoring in the continental United States. Remote Sens 8:3

    Article  Google Scholar 

  • Karnieli A et al (2010) Use of NDVI and land surface temperature for drought assessment: merits and limitations. J Clim 23(3):618–633

    Article  Google Scholar 

  • Keys PW et al (2012) Analyzing precipitationsheds to understand the vulnerability of rainfall dependent regions. Biogeosciences 9(2):733–746

    Article  Google Scholar 

  • Kim J-S et al (2021) Integrated drought monitoring and evaluation through multi-sensor satellite-based statistical simulation. Remote Sens 13(2):272

    Article  Google Scholar 

  • Kourouma JM et al (2021a) Assessing the spatio-temporal variability of NDVI and VCI as indices of crops productivity in Ethiopia: a remote sensing approach assessing the spatio-temporal variability of NDVI and VCI as indices of crops productivity in Ethiopia: a remote sensing Ap. Geomat Nat Haz Risk 12(1):2880–2903

    Article  Google Scholar 

  • Kourouma M, Jean, et al (2021b) Assessing the spatio-temporal variability of NDVI and VCI as indices of crops productivity in Ethiopia: a remote sensing approach. Geomat Nat Haz Risk 12(1):2880–2903

    Article  Google Scholar 

  • Kuśmierek-Tomaszewska R, Żarski J (2021) Assessment of meteorological and agricultural drought occurrence in central Poland in 1961–2020 as an element of the climatic risk to crop production. Agriculture 11(9):855

    Article  Google Scholar 

  • Lee S-J, Kim N, Lee Y (2021) Development of integrated crop drought index by combining rainfall, land surface temperature, evapotranspiration, soil moisture, and vegetation index for agricultural drought monitoring. Remote Sens 13(9):1778

    Article  Google Scholar 

  • Legesse SA (2016) The outlook of Ethiopian long rain season from the global circulation model. Environ Syst Res 5(1):16

    Article  Google Scholar 

  • Liang L et al (2021) VCI-based analysis on spatiotemporal variations of spring drought in China. Int J Environ Res Public Health 18(15):7967

    Article  Google Scholar 

  • Liou Y-A, Mulualem GM (2019) Spatio–temporal assessment of drought in Ethiopia and the impact of recent intense droughts. Remote Sens 11(15):1828

    Article  Google Scholar 

  • Liu WT, Kogan FN (1996) Monitoring regional drought using the vegetation condition index. Int J Remote Sens 17(14):2761–2782

    Article  Google Scholar 

  • Mekonen AA, Berlie AB, Ferede MB (2020) Spatial and temporal drought incidence analysis in the northeastern highlands of Ethiopia. Geoenviron Disas 7(1):10

    Article  Google Scholar 

  • Mera GA (2018) Drought and its impacts in Ethiopia. Weather Clim Extremes 22:24–35

    Article  Google Scholar 

  • Młyński D, Wałęga A, Kuriqi A (2021) Influence of meteorological drought on environmental flows in mountain catchments. Ecol Ind 133:108460

    Article  Google Scholar 

  • Mo KC, Lettenmaier DP (2014) Objective drought classification using multiple land surface models. J Hydrometeorol 15(3):990–1010

    Article  Google Scholar 

  • Naga RA, Abinaya S, Purna Durga G, and Lakshmi KTV (2022) Long-term relationships of MODIS NDVI with rainfall, land surface temperature, surface soil moisture and groundwater storage over monsoon core region of India. Arid Land Res Manag 1–20.

  • Nakalembe C et al (2021) A review of satellite-based global agricultural monitoring systems available for Africa. Global Food Secur 29:100543

    Article  Google Scholar 

  • Nicolai-Shaw N et al (2017) A drought event composite analysis using satellite remote-sensing based soil moisture. Remote Sens Environ 203:216–225

    Article  Google Scholar 

  • Obiahu OH, Elias E (2020) Effect of land use land cover changes on the rate of soil erosion in the upper Eyiohia river catchment of Afikpo North Area, Nigeria. Environ Challeng 1:100002

    Article  Google Scholar 

  • Orimoloye IR et al (2022) Drought: a common environmental disaster. Atmosphere 13(1):111

    Article  Google Scholar 

  • Orke YA, Li M-H (2022) Impact of climate change on hydrometeorology and droughts in the Bilate Watershed, Ethiopia. Water 14(5):729

    Article  Google Scholar 

  • Patel NR et al (2009) Assessing potential of MODIS derived temperature/vegetation condition index (TVDI) to infer soil moisture status. Int J Remote Sens 30(1):23–39

    Article  Google Scholar 

  • Region S-A, Sergio MV-S (2014) Evaluating the impact of drought using remote sensing in a Mediterranean, evaluating the impact of drought using remote sensing in a Mediterranean, semi-arid region. 2007

  • Richman MB, Leslie LM, Segele ZT (2016) Classifying drought in Ethiopia using machine learning. Proc Comput Sci 95:229–236

    Article  Google Scholar 

  • Rodríguez MM, Benítez-Parejo B (2011) Simple linear and multivariate regression models. Allergol Immunopathol 39(3):159

    Article  Google Scholar 

  • Sánchez N, González-zamora Á, Piles M, Martínez-fernández J (2016) (SMADI) integrating MODIS and SMOS products : a case of study over the Iberian Peninsula. Remote Sens 8:287

    Article  Google Scholar 

  • Sandeep P, Obi Reddy GP, Jegankumar R, Arun Kumar KC (2021) Monitoring of agricultural drought in semi-arid ecosystem of Peninsular India through indices derived from time-series CHIRPS and MODIS datasets. Ecol Ind 121:107033

    Article  Google Scholar 

  • Scarnecchia, David L., and D. Layne Coppock. 1995. 48 Journal of Range Management the Borana Plateau of Southern Ethiopia. Synthesis of Pastoral Research, Development and Change.

  • Senamaw A, Addisu S, Suryabhagavan KV (2021a) Mapping the spatial and temporal variation of agricultural and meteorological drought using geospatial techniques, Ethiopia. Environ Syst Res 10(1):15. https://doi.org/10.1186/s40068-020-00204-2

    Article  Google Scholar 

  • Shan G, Hua Z, and Tao J (2020) Correlation coefficients for a study with repeated measures In: Rafik K (ed) Computational and mathematical methods in medicine. p 7398324

  • Sharma M, Bangotra P, Gautam AS, Gautam S (2021) Sensitivity of normalized difference vegetation index (NDVI) to land surface temperature, soil moisture and precipitation over district Gautam Buddh Nagar, UP, India. Stoch Environ Res Risk Assess 1:729

    Google Scholar 

  • Shiferaw B et al (2014) Managing vulnerability to drought and enhancing livelihood resilience in Sub-Saharan Africa: technological, institutional and policy options. Weather Clim Extremes 3:67–79

    Article  Google Scholar 

  • Shukla S et al (2021) Enhancing the application of earth observations for improved environmental decision-making using the early warning EXplorer (EWX). Front Clim 2:1–16

    Article  Google Scholar 

  • Singh P, and Ovais J (2021) NDVI based assessment of land cover changes using remote sensing and GIS—(a case study of Srinagar District, Kashmir) Evaluación Basada En El NDVI de Los Cambios En La Cubierta Terrestre Utilizando La Teledetección y El GIS (Estudio de Caso Del Distr 9(4): 491–504

  • Sruthi S, Mohammed Aslam MA (2015) Agricultural drought analysis using the NDVI and land surface temperature data; a case study of Raichur District. Aqu Proc 4:1258–1264

    Google Scholar 

  • Tadesse L, Suryabhagavan KV, Sridhar G, Legesse G (2017) Land use and land cover changes and soil erosion in Yezat Watershed, North Western Ethiopia. Int Soil Water Conser Res 5(2):85–94

    Article  Google Scholar 

  • Teyso T (2016) Spatio-temporal variability and trends of rainfall and temperature over Gamo Gofa Zone, Ethiopia. J Sci Res Rep 12:1–11

    Google Scholar 

  • Towers PC, Strever A, Poblete-echeverr C (2019) Comparison of vegetation indices for leaf area index estimation in vertical shoot positioned vine canopies with and without Grenbiule hail-protection netting. Remote Sens 11:1073

    Article  Google Scholar 

  • Vaani N, Porchelvan P (2018) Monitoring of agricultural drought using fortnightly variation of vegetation condition index (VCI) for the State of Tamil Nadu, India. Int Arch Photogramm Remote Sens Spatial Inf Sci ISPRS Arch 42(4):159–164

    Article  Google Scholar 

  • Wakjira MT et al (2021) Rainfall seasonality and timing: implications for cereal crop production in Ethiopia. Agric Meteorol 310:108633

    Article  Google Scholar 

  • Wang M, Jun F, Zhitao W, Pang Z (2020) Spatiotemporal variation of NDVI in the vegetation growing season in the source region of the yellow. IJGI 9:282

    Article  Google Scholar 

  • Wang S et al (2021) Relationship between drought and precipitation heterogeneity: an analysis across rain-fed agricultural regions in Eastern Gansu, China. Atmosphere 12(10):1274

    Article  Google Scholar 

  • Zambrano F, Lillo-Saavedra M, Verbist K, Lagos O (2016) Sixteen years of agricultural drought assessment of the Biobío region in Chile using a 250 m resolution vegetation condition index (VCI). Remote Sens 8(6):1–20

    Article  Google Scholar 

  • Zeng J et al (2022) Improving the drought monitoring capability of VHI at the global scale via ensemble indices for various vegetation types from 2001 to 2018. Weather Clim Extremes 35:100412

    Article  Google Scholar 

  • Zhao M et al (2019) Assessing socio-economic drought evolution characteristics and their possible meteorological driving force. Geomat Nat Haz Risk 10(1):1084–1101

    Article  Google Scholar 

  • Zhu J et al (2013) Modis Ndvi products and metrics

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Acknowledgements

We wish to thank the Arba Minch University, College of Natural and Computational Sciences. We are also grateful to the National Meteorological Agency of Ethiopia (NMA) and the Department of Water, Irrigation, and Electricity (MoWIE) for providing data

Funding

This study was supported by Arba Minch University, College of Natural and computational science.

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Authors and Affiliations

  1. Faculty of Meteorology and Hydrology, Arba Minch University, Arba Minch, Ethiopia

    Amba Shalishe, Anirudh Bhowmick & Kumneger Elias

  2. Research Center for Environment Change, Academia Sinica, Taipei, Taiwan

    Amba Shalishe

  3. Earth System Science, National Central University, Taoyüan, Taiwan

    Amba Shalishe

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  1. Amba Shalishe
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  2. Anirudh Bhowmick
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  3. Kumneger Elias
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Data collection and analysis, and first draft writing were prepared by ASS. AB and KE analyzed the results and modified the manuscript. All authors are read and commented the manuscript.

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Correspondence to Amba Shalishe.

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Shalishe, A., Bhowmick, A. & Elias, K. Agricultural drought analysis and its association among land surface temperature, soil moisture and precipitation in Gamo Zone, Southern Ethiopia: a remote sensing approach. Nat Hazards 117, 57–70 (2023). https://doi.org/10.1007/s11069-023-05849-7

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