Geospatial monitoring and analysis of agricultural drought to identify hotspots and risk assessment for Senegal

Gurjeet Singh , Narendra N. Das , P.V. Vara Prasad

Geography and Sustainability ›› 2025, Vol. 6 ›› Issue (1) : 100248

PDF
Geography and Sustainability ›› 2025, Vol. 6 ›› Issue (1) :100248 DOI: 10.1016/j.geosus.2024.10.004
Research Article
review-article

Geospatial monitoring and analysis of agricultural drought to identify hotspots and risk assessment for Senegal

Author information +
History +
PDF

Abstract

Agricultural drought, characterized by insufficient soil moisture crucial for crop growth, poses significant challenges to food security and economic sustainability, particularly in water-scarce regions like Senegal. This study addresses this issue by developing a comprehensive geospatial monitoring system for agricultural drought using the Regional Hydrologic Extremes Assessment System (RHEAS). This system, with a high-resolution of 0.05°, effectively simulates daily soil moisture and generates the Soil Moisture Deficit Index (SMDI)-based agricultural drought monitoring. The SMDI derived from the RHEAS has effectively captured historical droughts in Senegal over the recent 30 years period from 1993 to 2022. The SMDI, also provides a comprehensive understanding of regional variations in drought severity (S), duration (D), and frequency (F), through S-D-F analysis to identify key drought hotspots across Senegal. Findings reveal a distinct north-south gradient in drought conditions, with the northern and central Senegal experiencing more frequent and severe droughts. The study highlights that Senegal experiences frequent short-duration droughts with high severity, resulting in extensive spatial impact. Additionally, increasing trends in drought severity and duration suggest evolving climate change effects. These findings emphasize the urgent need for sustainable interventions to mitigate drought impacts on agricultural productivity. Specifically, the study identifies recurrent and intense drought hotspots affecting yields of staple crops like maize and rice, as well as cash crops like peanuts. The developed high-resolution drought monitoring system for Senegal not only identifies hotspots but also enables prioritizing sustainable approaches and adaptive strategies, ultimately sustaining agricultural productivity and resilience in Senegal’s drought-prone regions.

Keywords

Agricultural resilience / Drought severity / Geospatial monitoring / S-D-F analysis / RHEAS / SMDI

Cite this article

Download citation ▾
Gurjeet Singh, Narendra N. Das, P.V. Vara Prasad. Geospatial monitoring and analysis of agricultural drought to identify hotspots and risk assessment for Senegal. Geography and Sustainability, 2025, 6(1): 100248 DOI:10.1016/j.geosus.2024.10.004

登录浏览全文

4963

注册一个新账户 忘记密码

CRediT authorship contribution statement

Gurjeet Singh: Writing – original draft, Validation, Resources, Methodology, Investigation, Formal analysis, Data curation, Conceptualization, Visualization, Writing – review & editing. Narendra N. Das: Writing – review & editing, Software, Project administration, Methodology, Investigation, Funding acquisition, Conceptualization. P.V. Vara Prasad: Writing – review & editing, Resources, Funding acquisition.

Declaration of competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This research was supported by the NASA (Grant No. 80NSSC21K0403) and USAID Kansas State University subcontract KSU-A20–0163-S035 with Michigan State University.

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.geosus.2024.10.004.

References

[1]

Abhishek, A, Das, N. N., Ines, A. V. M., Andreadis, K. M., Jayasinghe, S, Granger, S, Ellenburg, W. L., Dutta, R, Hanh Quyen, N, Markert, A. M., Mishra, V, Phanikumar, M. S., 2021. Evaluating the impacts of drought on rice productivity over Cambodia in the Lower Mekong Basin. J. Hydrol., 599 , Article 126291. doi: 10.1016/j.jhydrol.2021.126291.

[2]

Abhishek, A, Phanikumar, M. S., Sendrowski, A, Andreadis, K. M., Hashemi, M. G. Z., Jayasinghe, S, Vara Prasad, P. V., Brent, R. J., Das, N. N., 2023. Dryspells and minimum air temperatures influence rice yields and their forecast uncertainties in rainfed systems. Agric. For. Meteorol., 341 , Article 109683. doi: 10.1016/j.agrformet.2023.109683.

[3]

Al-Saeedi, A. H., 2022. Using a pedotransfer (PTF) model to establish GIS-based maps for the main physical and hydraulic soil properties in the eastern region of the Saudi Arabia. PLoS. One, 17 , Article e0276259. doi: 10.1371/journal.pone.0276259.

[4]

Anderson, W. B., Zaitchik, B. F., Hain, C. R., Anderson, M. C., Yilmaz, M. T., Mecikalski, J, Schultz, L., 2012. Towards an integrated soil moisture drought monitor for East Africa. Hydrol. Earth Syst. Sci., 16 , pp. 2893-2913. doi: 10.5194/hess-16-2893-2012.

[5]

Andreadis, K. M., Das, N, Stampoulis, D, Ines, A, Fisher, J. B., Granger, S, Kawata, J, Han, E, Behrangi, A., 2017. The regional hydrologic extremes assessment system: a software framework for hydrologic modeling and data assimilation. PLoS. One, 12 , Article e0176506. doi: 10.1371/journal.pone.0176506.

[6]

Ariom, T. O., Dimon, E, Nambeye, E, Diouf, N. S., Adelusi, O. O., Boudalia, S., 2022. Climate-smart agriculture in African countries: a review of strategies and impacts on smallholder farmers. Sustainability, 14 , p. 11370. doi: 10.3390/su141811370.

[7]

Barbier, B, Yacouba, H, Karambiri, H, Zoromé, M, Somé, B., 2009. Human vulnerability to climate variability in the Sahel: farmers’ adaptation strategies in northern Burkina Faso. Environ. Manage., 43 , pp. 790-803. doi: 10.1007/s00267-008-9237-9.

[8]

Baum, M. E., Archontoulis, S. V., Licht, M. A., 2019. Planting date, hybrid maturity, and weather effects on maize yield and crop stage. Agron. J., 111 , pp. 303-313. doi: 10.2134/agronj2018.04.0297.

[9]

Bazrafshan, J, Cheraghalizadeh, M, Shahgholian, K., 2022. 36 , pp. 3523-3543. doi: 10.1007/s11269-022-03209-x.

[10]

Bergman, K. H., Sabol, P, Miskus, D. 1988. Experimental indices for monitoring global drought conditions. Proceedings 13th Annual Climate Diagnostics Workshop, US Dept. of Commerce, Cambridge, MA, pp.190-197.

[11]

Bisht, D. S., Sridhar, V, Mishra, A, Chatterjee, C, Raghuwanshi, N. S., 2019. Drought characterization over India under projected climate scenario. Int. J. Climatol., 39 , pp. 1889-1911. doi: 10.1002/joc.5922.

[12]

Chan, S. K., Bindlish, R, O'Neill, P, Jackson, T, Njoku, E, Dunbar, S, Chaubell, J, Piepmeier, J, Yueh, S, Entekhabi, D, Colliander, A, Chen, F, Cosh, M. H., Caldwell, T, Walker, J, Berg, A, McNairn, H, Thibeault, M, Martínez-Fernández, J, Uldall, F, Seyfried, M, Bosch, D, Starks, P, Holifield Collins, C, Prueger, J, van der Velde, R, Asanuma, J, Palecki, M, Small, E. E., Zreda, M, Calvet, J, Crow, W. T., Kerr, Y., 2018. Development and assessment of the SMAP enhanced passive soil moisture product. Remote Sens. Environ., 204 , pp. 931-941. doi: 10.1016/j.rse.2017.08.025.

[13]

Cherubini, U., Luciano, E., Vecchiato, W., 2004. Copula Methods in Finance. The Wiley Finance Series. John Wiley & Sons Ltd, Chichester.

[14]

Clarke, C., Shackleton, S., Powell, M., 2012. Climate change perceptions, drought responses and views on carbon farming amongst commercial livestock and game farmers in the semiarid Great Fish River Valley, Eastern Cape province, South Africa. Afr. J. Range Forage Sci. 29, 13–23. doi: 10.2989/10220119.2012.687041.

[15]

Climate, Change, Knowledgeortal, P., 2023. Senegal key natural hazard statistics for 1980–2020. https://climateknowledgeportal.worldbank.org/(accessed 23 March 2024).

[16]

Conway, D, Schipper, E. L. F., 2011. Adaptation to climate change in Africa: challenges and opportunities identified from Ethiopia. Glob. Environ. Change, 21 , pp. 227-237. doi: 10.1016/j.gloenvcha.2010.07.013.

[17]

Cornforth, R., 2013. Weathering the drought in Africa. Planet Earth (Spring) 30–31.

[18]

Dai, A., 2011. Drought under global warming: a review. WIREs Clim. Change, 2 , pp. 45-65. doi: 10.1002/wcc.81.

[19]

Dai, A., 2013. Increasing drought under global warming in observations and models. Nat. Clim. Chang., 3 , pp. 52-58. doi: 10.1038/nclimate1633.

[20]

Deng, M, Di, L, Han, W, Yagci, A, Peng, C, Heo, G., 2013. Web-service-based monitoring and analysis of global agricultural drought. Photogramm. Eng. Remote Sens., 79(10), 929-943.

[21]

Dhage, P. M., Raghuwanshi, N. S., Singh, R, Mishra, A., 2017. Development of daily temperature scenarios and their impact on paddy crop evapotranspiration in Kangsabati command area. Theor. Appl. Climatol., 128 , pp. 983-997. doi: 10.1007/s00704-016-1743-8.

[22]

Dinku, T, Funk, C, Peterson, P, Maidment, R, Tadesse, T, Gadain, H, Ceccato, P., 2018. Validation of the CHIRPS satellite rainfall estimates over eastern Africa. Q. J. R. Meteorol. Soc., 144 , pp. 292-312. doi: 10.1002/qj.3244.

[23]

Diouf, A, Lambin, E. F., 2001. Monitoring land-cover changes in semi-arid regions: remote sensing data and field observations in the Ferlo. Senegal. J. Arid Environ., 48 , pp. 129-148. doi: 10.1006/jare.2000.0744.

[24]

Dutra, E, Magnusson, L, Wetterhall, F, Cloke, H. L., Balsamo, G, Boussetta, S, Pappenberger, F., 2013. The 2010–2011 drought in the Horn of Africa in ECMWF reanalysis and seasonal forecast products. Int. J. Climatol., 33 , pp. 1720-1729. doi: 10.1002/joc.3545.

[25]

EM-DAT, 2023. The international disaster database. Emergency Events Database (EMDAT). https://www.emdat.be/ . (accessed 13 October 2023).

[26]

Entekhabi, D., Reichle, R.H., Koster, R.D., Crow, W.T., 2010. Performance metrics for soil moisture retrievals and application requirements. J. Hydrometeorol. 11, 832–840. doi: 10.1175/2010JHM1223.1.

[27]

Fahad, S, Bajwa, A. A., Nazir, U, Anjum, S. A., Farooq, A, Zohaib, A, Sadia, S, Nasim, W, Adkins, S, Saud, S, Ihsan, M. Z., Alharby, H, Wu, C, Wang, D, Huang, J., 2017. Crop production under drought and heat stress: plant responses and management options. Front. Plant Sci., 8 , p. 1147. doi: 10.3389/fpls.2017.01147.

[28]

Fall, S, Semazzi, F. H. M., Niyogi, D. D. S., Anyah, R. O., Bowden, J., 2006. The spatiotemporal climate variability over Senegal and its relationship to global climate. Int. J. Climatol., 26 , pp. 2057-2076. doi: 10.1002/joc.1355.

[29]

FAO, 2008. Climate Change and Food Security in the Pacific Island Countries. Food and Agriculture Organization of the United Nations Rome, Itlay (accessed 8 January 2024).

[30]

Faye, C., 2017. Variability and trends in observed average monthly, seasonal and annual flows in the Falémé basin. Senegal. Hydrol. Sci. J., 62 , pp. 259-269. doi: 10.1080/02626667.2014.990967.

[31]

Friedl, M. A., Sulla-Menashe, D, Tan, B, Schneider, A, Ramankutty, N, Sibley, A, Huang, X., 2010. MODIS collection 5 global land cover: algorithm refinements and characterization of new datasets. Remote Sens. Environ., 114 , pp. 168-182. doi: 10.1016/j.rse.2009.08.016.

[32]

Funk, C, Peterson, P, Landsfeld, M, Pedreros, D, Verdin, J, Shukla, S, Husak, G, Rowland, J, Harrison, L, Hoell, A, Michaelsen, J., 2015. The climate hazards infrared precipitation with stations–a new environmental record for monitoring extremes. Sci. Data, 2 , Article 150066. doi: 10.1038/sdata.2015.66.

[33]

Genest, C, A-Favre, C., 2007. Everything you always wanted to know about Copula modeling but were afraid to ask. J. Hydrol. Eng., 12(4), 347-368.

[34]

Giannini, A, Biasutti, M, Verstraete, M. M., 2008. A climate model-based review of drought in the Sahel: desertification, the re-greening and climate change. Glob. Planet. Change, 64 , pp. 119-128. doi: 10.1016/j.gloplacha.2008.05.004.

[35]

Gonzalez, P., 2001. Desertification and a shift of forest species in the West African Sahel. Clim. Res., 17 , pp. 217-228. doi: 10.3354/cr017217.

[36]

Gupta, V, Jain, M. K., 2018. Investigation of multi-model spatiotemporal mesoscale drought projections over India under climate change scenario. J. Hydrol., 567 , pp. 489-509. doi: 10.1016/j.jhydrol.2018.10.012.

[37]

Hamed, K. H., Ramachandra Rao, A., 1998. A modified Mann-Kendall trend test for autocorrelated data. J. Hydrol., 204 , pp. 182-196. doi: 10.1016/S0022-1694(97)00125-X.

[38]

Hao, Z, AghaKouchak, A., 2013. Multivariate standardized drought index: a parametric multi-index model. Adv. Water Resour., 57 , pp. 12-18. doi: 10.1016/j.advwatres.2013.03.009.

[39]

Hao, Z, AghaKouchak, A., 2014. A nonparametric multivariate multi-Index drought monitoring framework. J. Hydrometeorol., 15 , pp. 89-101. doi: 10.1175/JHM-D-12-0160.1.

[40]

Hao, C., Zhang, J., Yao, F., 2015. Combination of multi-sensor remote sensing data for drought monitoring over Southwest China. Int. J. Appl. Earth Obs. Geoinf. 35, 270– 283. doi: 10.1016/j.jag.2014.09.011.

[41]

Hayes, M, Svoboda, M, Wall, N, Widhalm, M., 2011. The Lincoln declaration on drought indices: universal meteorological drought index recommended. Bull. Am. Meteorol. Soc., 92 , pp. 485-488. doi: 10.1175/2010BAMS3103.1.

[42]

Hengl, T, Mendes de Jesus, J, Heuvelink, G. B. M., Kilibarda, M, Blagotić, A, Shangguan, W, Wright, M. N., Geng, X, Bauer-Marschallinger, B, Guevara, M. A., Vargas, R, MacMillan, R. A., Batjes, N. H., Leenaars, J. G. B., Ribeiro, E, Wheeler, I, Mantel, S, Kempen, B., 2017. SoilGrids250m: global gridded soil information based on machine learning. PLoS One, 12 (2) , Article e0169748. doi: 10.1371/journal.pone.0169748.

[43]

Herrmann, S. M., Anyamba, A, Tucker, C. J., 2005. Recent trends in vegetation dynamics in the African Sahel and their relationship to climate. Glob. Environ. Change, 15 , pp. 394-404. doi: 10.1016/j.gloenvcha.2005.08.004.

[44]

Hollinger, S. E., Isard, S. A., Welford, M. R. 1993. A new soil moisture drought index for predicting crop yields. Eighth Conference on Applied Climatology, American Meteorological Society, Anaheim (CA), 17–22 January 1993, AMS, pp.187-190.

[45]

Huete, A, Didan, K, Miura, T, Rodriguez, E. P., Gao, X, Ferreira, L. G., 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens. Environ., 83 , pp. 195-213. doi: 10.1016/S0034-4257(02)00096-2.

[46]

Jones, J. W., Hoogenboom, G, Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., Wilkens, P. W., Singh, U, Gijsman, A. J., Ritchie, J. T., 2003. The DSSAT cropping system model. Eur. J. Agron., 18 , pp. 235-265. doi: 10.1016/S1161-0301(02)00107-7.

[47]

Jones, P. W., 1999. First- and second-order conservative remapping schemes for grids in spherical coordinates. Mon. Weather Rev., 127 , pp. 2204-2210. doi: 10.1175/1520-0493(1999)127<2204:FASOCR>2.0.CO;2.

[48]

Kalnay, E, Kanamitsu, M, Kistler, R, Collins, W, Deaven, D, Gandin, L, Iredell, M, Saha, S, White, G, Woollen, J, Zhu, Y, Chelliah, M, Ebisuzaki, W, Higgins, W, Janowiak, J, Mo, K. C., Ropelewski, C, Wang, J, Leetmaa, A, Reynolds, R, Jenne, R, Joseph, D., 1996. The NCEP/NCAR 40-year reanalysis project. Bull. Am. Meteorol. Soc., 77 , pp. 437-472. doi: 10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

[49]

Kao, S-C, Govindaraju, R. S., 2010. Kao, R.S. Govindaraju. A copula-based joint deficit index for droughts. J. Hydrol., 380 , pp. 121-134. doi: 10.1016/j.jhydrol.2009.10.029.

[50]

Kasei, R., Diekkrüger, B., Leemhuis, C., 2010. Drought frequency in the Volta Basin of West Africa. Sustain. Sci. 5, 89–97. doi: 10.1007/s11625-009-0101-5.

[51]

Katsanos, D., Retalis, A., Michaelides, S., 2016. Validation of a high-resolution precipitation database (CHIRPS) over Cyprus for a 30-year period. Atmos. Res. 169, 459–464. doi: 10.1016/j.atmosres.2015.05.015.

[52]

Kim, K-H, B-Lee, M., 2023. Effects of climate change and drought tolerance on maize growth. Plants, 12 , p. 3548. doi: 10.3390/plants12203548.

[53]

Kimutai, J., Barnes, C., Zachariah, M., Philip, S., Kew, S., Pinto, I., Wolski, P., Koren, G., Vecchi, G., Yang, W., Li, S., Vahlberg, M., Singh, R., Heinrich, D., Pereira, C., Arrighi, J., Thalheimer, L., Kane, C., Otto, F., 2023. Human-induced climate change increased drought severity in Horn of Africa. Preprint-archives. doi: 10.2139/ssrn.4701486

[54]

Klisch, A, Atzberger, C., 2016. Operational drought monitoring in Kenya using MODIS NDVI time series. Remote Sens., 8 , p. 267. doi: 10.3390/rs8040267.

[55]

Kogan, F. N., 2002. World droughts in the new millennium from AVHRR-based vegetation health indices. Eos Trans. Amer. Geophys. Union, 83 (48) , pp. 557-563. doi: 10.1029/2002EO000382.

[56]

Kottek, M, Grieser, J, Beck, C, Rudolf, B, Rubel, F., 2006. World map of the Köppen-Geiger climate classification updated. Meteorol. Z., 15 , pp. 259-263. doi: 10.1127/0941-2948/2006/0130.

[57]

Lebel, T, Cappelaere, B, Galle, S, Hanan, N, Kergoat, L, Levis, S, Vieux, B, Descroix, L, Gosset, M, Mougin, E, Peugeot, C, Seguis, L., 2009. AMMA-CATCH studies in the Sahelian region of West-Africa: an overview. J. Hydrol., 375 , pp. 3-13. doi: 10.1016/j.jhydrol.2009.03.020.

[58]

Liang, X, Lettenmaier, D. P., Wood, E. F., Burges, S. J., 1994. A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J. Geophys. Res., 99 , pp. 14415-14428. doi: 10.1029/94JD00483.

[59]

Liu, W. T., Kogan, F., 1996. Monitoring regional drought using the vegetation condition index. Int. J. Remote Sens., 17 , pp. 2761-2782. doi: 10.1080/01431169608949106.

[60]

Liu, Z, Wang, Y, Shao, M, Jia, X, Li, X., 2016. Spatiotemporal analysis of multiscalar drought characteristics across the Loess Plateau of China. J. Hydrol., 534 , pp. 281-299. doi: 10.1016/j.jhydrol.2016.01.003.

[61]

Lodoun, T, Giannini, A, Traoré, P. S., Somé, L, Sanon, M, Vaksmann, M, Rasolodimby, J. M., 2013. Changes in seasonal descriptors of precipitation in Burkina Faso associated with late 20th century drought and recovery in West Africa. Environ. Dev., 5 , pp. 96-108. doi: 10.1016/j.envdev.2012.11.010.

[62]

Lodoun, T., Giannini, A., Traoré, P.S., Somé, L., Sanon, M., Vaksmann, M., Rasolodimby, J.M., 2013. Changes in seasonal descriptors of precipitation in Burkina Faso associated with late 20th century drought and recovery in West Africa. Environ. Dev. 5, 96–108. doi: 10.1016/j.envdev.2012.11.010.

[63]

Maity, R, Sharma, A, Nagesh Kumar, D, Chanda, K., 2012. Characterizing drought using the reliability-resilience-vulnerability concept. J. Hydrol. Eng., 18 , pp. 859-869. doi: 10.1061/(ASCE)HE.1943-5584.0000639.

[64]

Masih, I, Maskey, S, Mussá, F. E. F., Trambauer, P., 2014. A review of droughts on the African continent: a geospatial and long-term perspective. Hydrol. Earth Syst. Sci., 18 , pp. 3635-3649. doi: 10.5194/hess-18-3635-2014.

[65]

McKee, T. B., Doesken, N. J., Kleist, J. 1995. Drought monitoring with multiple time scales. Preprints, 9th Conference on Applied Climatology, pp.233-236.

[66]

McKee, T. B., Doesken, N. J., Kleist, J. 1993. The relationship of drought frequency and duration to time scales. Preprints, 8th Conference on Applied Climatology, pp.179-184.

[67]

McSweeney, C, New, M, Lizcano, G, Lu, X., 2010. The UNDP climate change country profiles: improving the accessibility of observed and projected climate information for studies of climate change in developing countries. Bull. Amer. Meteorol. Soc., 91 , pp. 157-166. doi: 10.1175/2009BAMS2826.1.

[68]

Mekonnen, K, Velpuri, N. M., Leh, M, Akpoti, K, Owusu, A, Tinonetsana, P, Hamouda, T, Ghansah, B, Paranamana, T. P., Munzimi, Y., 2023. Accuracy of satellite and reanalysis rainfall estimates over Africa: a multi-scale assessment of eight products for continental applications. J. Hydrol. Reg. Stud., 49 , Article 101514. doi: 10.1016/j.ejrh.2023.101514.

[69]

Mishra, A. K., Ines, A. V., Das, N. N., Khedun, C. P., Singh, V. P., Sivakumar, B, Hansen, J. W., 2015. Anatomy of a local scale drought: application of assimilated remote sensing products, crop model, and statistical methods to an agricultural drought study. J. Hydrol., 526 , pp. 15-29. doi: 10.1016/j.jhydrol.2014.10.038.

[70]

Mishra, A. K., Singh, V. P., 2010. A review of drought concepts. J. Hydrol., 391 , pp. 202-216. doi: 10.1016/j.jhydrol.2010.07.012.

[71]

Mizukami, N, Clark, M. P., Slater, A. G., Brekke, L. D., Elsner, M. M., Arnold, J. R., Gangopadhyay, S., 2014. Hydrologic implications of different large-scale meteorological model forcing datasets in mountainous regions. J. Hydrometeorol., 15 , pp. 474-488. doi: 10.1175/JHM-D-13-036.1.

[72]

Barbosa, P, Naumann, G, Valentini, L, Vogt, J, Dutra, E, Magni, D, Jager, A. D., 2013. A Pan-African map viewer for drought monitoring and forecast. 14th WaterNet Symposium . doi: 10.13140/2.1.1275.2163.

[73]

Narasimhan, B, Srinivasan, R., 2005. Development and evaluation of Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) for agricultural drought monitoring. Agric. For. Meteorol., 133 , pp. 69-88. doi: 10.1016/j.agrformet.2005.07.012.

[74]

Naresh Kumar, M, Murthy, C. S., Sesha Sai, M. V. R., Roy, P. S., 2012. Spatiotemporal analysis of meteorological drought variability in the Indian region using standardized precipitation index. Meteorol. Appl., 19 , pp. 256-264. doi: 10.1002/met.277.

[75]

Nayak, A. K., Biswal, B, Sudheer, K. P., 2022. Drought hotspot maps and regional drought characteristics curves: development of a novel framework and its application to an Indian River basin undergoing climatic changes. Sci. Total Environ., 807 , Article 151083. doi: 10.1016/j.scitotenv.2021.151083.

[76]

Nelsen, R. B., 2007. An Introduction to Copulas (Springer Series in Statistics). Springer-Verlag, Berlin, Heidelberg

[77]

Nicholson, S. E., 2001. Climatic and environmental change in Africa during the last two centuries. Clim. Res., 17, 123-144.

[78]

Pandey, S, Bhandari, H, Ding, S, Prapertchob, P, Sharan, R, Naik, D, Taunk, S. K., Sastri, A., 2007. Coping with drought in rice farming in Asia: insights from a cross-country comparative study. Agric. Econ., 37 , pp. 213-224. doi: 10.1111/j.1574-0862.2007.00246.x.

[79]

Pozzi, W, Sheffield, J, Stefanski, R, Cripe, D, Pulwarty, R, Vogt, J. V., Heim, R. R., Brewer, M. J., Svoboda, M, Westerhoff, R, Van Dijk, A. I. J. M., Lloyd-Hughes, B, Pappenberger, F, Werner, M, Dutra, E, Wetterhall, F, Wagner, W, Schubert, S, Mo, K, Nicholson, M, Bettio, L, Nunez, L, Van Beek, R, Bierkens, M, De Goncalves, L. G. G., De Mattos, J. G. Z., Lawford, R., 2013. Toward global drought early warning capability: expanding international cooperation for the development of a framework for monitoring and forecasting. Bull. Amer. Meteorol. Soc., 94 , pp. 776-785. doi: 10.1175/BAMS-D-11-00176.1.

[80]

Rojas, O., Vrieling, A., Rembold, F., 2011. Assessing drought probability for agricultural areas in Africa with coarse resolution remote sensing imagery. Remote Sens. Environ. 115, 343–352. doi: 10.1016/j.rse.2010.09.006.

[81]

Sahana, V, Sreekumar, P, Mondal, A, Rajsekhar, D., 2020. On the rarity of the 2015 drought in India: a country-wide drought atlas using the multivariate standardized drought index and copula-based severity-duration-frequency curves. J. Hydrol. Reg. Stud., 31 , Article 100727. doi: 10.1016/j.ejrh.2020.100727.

[82]

Sall, M., Ba, B., Kane, L., des Parcs Nationaux, D., de Hann, P.F., 2013. Drought conditions and management strategies in Senegal. UN-Water Activity Information System. https://www.ais.unwater.org/ais/pluginfile.php/629/mod_page/content/6/Senegal_ EN.pdf (assessed 13 August 2024)

[83]

Samantaray, A. K., Singh, G, Ramadas, M, Panda, R. K., 2019. Drought hotspot analysis and risk assessment using probabilistic drought monitoring and severity–duration–frequency analysis. Hydrol. Process., 33 , pp. 432-449. doi: 10.1002/hyp.13337.

[84]

Saxton, K. E., Rawls, W. J., 2006. Soil water characteristic estimates by texture and organic matter for hydrologic solutions. Soil Sci. Soc. Am. J., 70 , pp. 1569-1578. doi: 10.2136/sssaj2005.0117.

[85]

Sheffield, J, Wood, E. F., Roderick, M. L., 2012. Wood, M.L. Roderick. Little change in global drought over the past 60 years. Nature, 491 , pp. 435-438. doi: 10.1038/nature11575.

[86]

Shiau, J. T., Shen, H. W., 2001. Recurrence analysis of hydrologic droughts of differing severity. J. Water Resour. Plan. Manage., 127 , pp. 30-40. doi: 10.1061/(ASCE)0733-9496(2001)127:1(30).

[87]

Shiau, J. T., 2006. Fitting drought duration and severity with two-dimensional copulas. Water Resour. Manag., 20 , pp. 795-815. doi: 10.1007/s11269-005-9008-9.

[88]

Shiau, J. T., Modarres, R., 2009. Copula-based drought severity-duration-frequency analysis in Iran. Meteorol. Appl., 16 , pp. 481-489. doi: 10.1002/met.145.

[89]

Singh, G, Bisht, D. S., 2023. Kumar (Eds.), Integrated Drought Management, Volume 2: Forecasting, Monitoring, and Managing Risk (1st ed.), CRC Press, Boca Raton . doi: 10.1201/9781003276548.

[90]

Singh, G, Das, N. N., Panda, R. K., Colliander, A, Jackson, T. J., Mohanty, B. P., Entekhabi, D, Yueh, S. H., 2019. Validation of SMAP soil moisture products using ground-based observations for the paddy dominated tropical region of India. IEEE Trans. Geosci. Remote Sens., 57 , pp. 8479-8491. doi: 10.1109/TGRS.2019.2921333.

[91]

Sklar, M. 1959. Fonctions de répartition àn dimensions et leurs marges. Annales de l'ISUP, pp.229-231.

[92]

Smith, A. B., Katz, R. W., 2013. US billion-dollar weather and climate disasters: data sources, trends, accuracy and biases. Nat. Hazards, 67 , pp. 387-410. doi: 10.1007/s11069-013-0566-5.

[93]

Song, Z, Xia, J, She, D, Zhang, L, Hu, C, Zhao, L., 2020. The development of a Nonstationary Standardized Precipitation Index using climate covariates: a case study in the middle and lower reaches of Yangtze River Basin, China. J. Hydrol., 588 , Article 125115. doi: 10.1016/j.jhydrol.2020.125115.

[94]

Svoboda, M, LeComte, D, Hayes, M, Heim, R, Gleason, K, Angel, J, Rippey, B, Tinker, R, Palecki, M, Stooksbury, D, Miskus, D, Stephens, S., 2002. The drought monitor. Bull. Amer. Meteor. Soc., 83, 1181-1190.

[95]

Szabó, B, Szatmári, G, Takács, K, Laborczi, A, Makó, A, Rajkai, K, Pásztor, L., 2019. Mapping soil hydraulic properties using random-forest-based pedotransfer functions and geostatistics. Hydrol. Earth Syst. Sci., 23 , pp. 2615-2635. doi: 10.5194/hess-23-2615-2019.

[96]

Thilakarathne, M, Sridhar, V., 2017. Characterization of future drought conditions in the Lower Mekong River Basin. Weather Clim. Extremes, 17 , pp. 47-58. doi: 10.1016/j.wace.2017.07.004.

[97]

Toté, C, Patricio, D, Boogaard, H, Van Der Wijngaart, R, Tarnavsky, E, Funk, C., 2015. Evaluation of satellite rainfall estimates for drought and flood monitoring in mozambique. Remote Sens., 7 , pp. 1758-1776. doi: 10.3390/rs70201758.

[98]

Tóth, B, Weynants, M, Nemes, A, Makó, A, Bilas, G, Tóth, G., 2015. New generation of hydraulic pedotransfer functions for Europe. Eur. J. Soil Sci., 66 , pp. 226-238. doi: 10.1111/ejss.12192.

[99]

Touchan, R, Anchukaitis, K. J., Meko, D. M., Attalah, S, Baisan, C, Aloui, A., 2008. Long term context for recent drought in northwestern Africa. Geophys. Res. Lett., 35 . doi: 10.1029/2008GL034264.

[100]

Touchan, R, Anchukaitis, K. J., Meko, D. M., Sabir, M, Attalah, S, Aloui, A., 2011. Spatiotemporal drought variability in northwestern Africa over the last nine centuries. Clim. Dyn., 37 , pp. 237-252. doi: 10.1007/s00382-010-0804-4.

[101]

Ugbaje, S. U., Reuter, H. I., 2013. Functional digital soil mapping for the prediction of available water capacity in Nigeria using legacy data. Vadose Zone J., 12 (4) . doi: 10.2136/vzj2013.07.0140.

[102]

UN-DESA, 2010. World Population Prospects: The 2010 Revision. United Nations Department of Economic and Social Affairs (UN-DESA), New York.

[103]

United Nation, 1996. Report of the World Food summit. Food and Agriculture Organization of the United Nations.

[104]

Vicente-Serrano, S. M., Beguería, S, López-Moreno, J. I., 2010. A multi scalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J. Clim., 23 (7) , pp. 1696-1718. doi: 10.1175/2009JCLI2909.1.

[105]

Vicente-Serrano, S. M., Camarero, J. J., Olano, J. M., Martín-Hernández, N, Peña-Gallardo, M, Tomás-Burguera, M, Gazol, A, Azorin-Molina, C, Bhuyan, U, El Kenawy, A., 2016. Diverse relationships between forest growth and the normalized difference vegetation index at a global scale. Remote Sens. Environ., 187 , pp. 14-29. doi: 10.1016/j.rse.2016.10.001.

[106]

Vogel, C., Koch, I., Van Zyl, K., 2010. “A persistent truth ”–reflections on drought risk management in southern Africa. Weather Clim. Soc. 2 (1), 9–22. doi: 10.1175/2009WCAS1017.1.

[107]

World Bank Group, 2021. Senegal, climate change overview, country summary. Climate Change Knowledge Portal (accessed 14 August 2024).

[108]

World, Food, Programme (WF), P., 2014. The 2014 rainfall season: west and East Africa. https://reliefweb.int/attachments/0c396d8d-1874-36d4-9199-dc241221ae52/wfp267946.pdf. (accessed 23 May 2024)

[109]

World Food Programme (WFP), 2012. Climate risk and food security in Senegal: analysis of climate impacts on food security and livelihood. WFP’s Office for Climate Change, Environment and Disaster Risk Reduction (accessed 10 August 2024).

[110]

Yang, Y., Yuan, H., Yu, W., 2018. Uncertainties of 3D soil hydraulic parameters in streamflow simulations using a distributed hydrological model system. J. Hydrol. 567, 12– 14. doi: 10.1016/j.jhydrol.2018.09.042.

[111]

Yevjevich, V. M., 1967. An Objective Approach to Definitions and Investigations of Continental Hydrologic Droughts. Colorado State University,

[112]

Zargar, A, Sadiq, R, Naser, B, Khan, F. I., 2011. A review of drought indices. Environ. Rev., 19 , pp. 333-349. doi: 10.1139/a11-013.

PDF

178

Accesses

0

Citation

Detail

Sections
Recommended

/