Hydroclimatic Drivers of Soil Moisture Decline in South-South Nigeria: Implications for Sustainable Agriculture
DOI:
https://doi.org/10.69930/fsst.v2i2.560Keywords:
Soil moisture dynamics, climate variability, precipitation patterns, climate-smart agriculture, ecosystem resilienceAbstract
This study investigates the hydroclimatic drivers of soil moisture decline in South-South Nigeria from 2000 to 2020, emphasizing implications for sustainable agriculture in rain-fed systems. Utilizing satellite-derived datasets including CHIRPS for precipitation, ERA5 for temperature, and SMAP/AMSR-E for soil moisture, integrated with GIS and statistical analyses (Mann-Kendall trends, Sen's slope, cross-wavelet coherence, and correlation), we reveal a consistent warming trend with maximum temperatures peaking at 28.38°C in 2020, erratic precipitation patterns with highs of 7.01 mm/day in 2015, and a ~6% soil moisture reduction (from 0.325 to 0.305 m³/m³). Correlations indicate a weak positive link between soil moisture and precipitation (r=0.124) and a strong inverse relationship with temperature (r=-0.614), highlighting a temperature-driven evapotranspiration as a primary deficit mechanism. Data limitations, such as satellite biases in vegetated tropics (RMSE 0.04–0.06 m³/m³ for SMAP), were addressed through literature-based validation and cross-referencing with regional benchmarks. These trends pose risks to staples like cassava and rice, projecting 10–25% yield losses. Actionable recommendations include adopting drought-resistant cultivars, conservation agriculture for enhanced retention (15–30%), community water harvesting, and satellite-based early-warning systems. This research informs climate-smart policies to bolster food security and ecosystem resilience amid escalating variability in tropical Africa.
References
Adeogun, B. K., Fulazzaky, M. A., Mohammed, B. S., Daud, O., & Ghazali, A. H. (2021). Hydropower potential assessment using spatial technology and hydrological modelling in Nigeria river basin. Renewable Energy, 178, 213-228.
Akinsanola, A. A., & Ogunjobi, K. O. (2014). Analysis of rainfall and temperature variability over Nigeria. Global Journal of Human-Social Science: B Geography, Geo-Sciences, Environmental Science & Disaster Management, 14(3), 1-17.
Akayeti, A., Liermann, S., & Vogel, M. (2024). Evaluation of satellite-based rainfall estimates against rain gauge observations in Nigeria. Remote Sensing, 16(10), 1755.
Anejionu, O. C., Ahiarammunnah, P. A. N., & Nri-ezedi, C. J. (2015). Hydrocarbon pollution in the Niger Delta: Geochemistries of soil organic matter indicate extent of pollution. Environmental Forensics, 16(1), 71-83.
Arnold, J. G., Moriasi, D. N., Gassman, P. W., Abbaspour, K. C., White, M. J., Srinivasan, R., & Jha, M. K. (2012). SWAT: Model use, calibration, and validation. Transactions of the ASABE, 55(4), 1491–1508.
Ayanlade, A., & Howard, M. T. (2019). Land surface temperature and heat fluxes over three cities in Niger Delta. Journal of African Earth Sciences, 151, 54–66.
Bouskill, N. J., Wood, T. E., Baran, R., Ye, Z., Bowen, B. P., Lim, H., Zhou, J., Van Nostrand, J. D., Nico, P., Northen, T. R., Silver, W. L., & Brodie, E. L. (2016). Belowground response to drought in a tropical forest soil. I. Changes in microbial functional potential and metabolism. Frontiers in Microbiology, 7, 525.
Colliander, A., Jackson, T. J., Bindlish, R., Chan, S., Das, N., Kim, S. B., … Yueh, S. H. (2017). Validation of SMAP surface soil moisture products with core validation sites. Remote Sensing of Environment, 191, 215–231.
Das, N. N., Entekhabi, D., Dunbar, R. S., Njoku, E. G., & Yueh, S. H. (2019). The SMAP mission combined active-passive soil moisture retrieval. IEEE Transactions on Geoscience and Remote Sensing, 57(5), 2884–2897.
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. Quarterly Journal of the Royal Meteorological Society, 144(S1), 292–312.
Dosio, A., Mentaschi, L., Fischer, E. M., & Wyser, K. (2018). Extreme heat waves under 1.5°C and 2°C global warming. Environmental Research Letters, 13(5), 054006.
Dunkerley, D. (2015). Percolation soil moisture under steady rainfall: Dynamic or steady state? Journal of Hydrology, 531, 156-162.
Entekhabi, D., Njoku, E. G., O’Neill, P. E., Kellogg, K. H., Crow, W. T., Edelstein, W. N., … Van Zyl, J. (2010). The Soil Moisture Active Passive (SMAP) mission. Proceedings of the IEEE, 98(5), 704–716.
Ford, J. D. (2015). Vulnerability of Inuit food systems to food insecurity as a consequence of climate change: A case study from Igloolik, Nunavut. Regional Environmental Change, 15(1), 83-100.
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., … Michaelsen, J. (2015). The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Scientific Data, 2, 150066.
Gebrechorkos, S. H., Hülsmann, S., & Bernhofer, C. (2018). Evaluation of multiple climate data sources for managing environmental resources in East Africa. Hydrology and Earth System Sciences, 22(9), 4547–4564.
Green, J. K., Seneviratne, S. I., Berg, A. M., Findell, K. L., Hagemann, S., Lawrence, D. M., & Gentine, P. (2019). Large influence of soil moisture on long-term terrestrial carbon uptake. Nature, 565(7738), 476-479.
Grinsted, A., Moore, J. C., & Jevrejeva, S. (2004). Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophysics, 11(5/6), 561–566.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., … Thépaut, J.-N. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), 1999–2049.
Kardol, P., Cornips, N. J., van Kempen, M. M., Bakx-Schotman, J. M., & van der Putten, W. H. (2010). Microbe-mediated plant-soil feedback causes historical contingency effects in plant community assembly. Ecological Monographs, 80(1), 147-162.
Li, H., & Si, B. (2018). Spatial patterns of soil moisture from distributed and self-organizing wireless sensor networks. Journal of Hydrology, 566, 852-860.
Li, Y., Huang, J., Ji, M., & Ran, L. (2015). Dryland vegetation pattern dynamics driven by the disturbance effects of human activities and climate change. Ecological Research, 30(4), 651-663.
Mallick, K., Bhattacharya, B. K., Rao, V., Reddy, D., Banerjee, S., Venkatesh, H., Pandey, L. M., Kar, G., Mukherjee, J., Vyas, S. P., Gadgil, A. S., & Patel, N. K. (2015). Latent heat flux estimation in clear sky days over Indian agro-climatic zones using no reference pixel values of thermal infrared imagery and high-resolution radiometric data. Agricultural and Forest Meteorology, 215-216, 176-191.
Mann, H. B. (1945). Nonparametric tests against trend. Econometrica, 13(3), 245–259.
Nduka, C. C., & Nduka, E. C. (2025). Climate smart agriculture in food insecurity mitigation in Nigeria. Asian Journal of Agricultural Extension, Economics & Sociology, 43(1), 1-10.
Njoku, E. G., Jackson, T. J., Lakshmi, V., Chan, T. K., & Nghiem, S. V. (2003). Soil moisture retrieval from AMSR-E. IEEE Transactions on Geoscience and Remote Sensing, 41(2), 215–229.
Ogwu, C., & Idisi, E. B. (2024). Characterization of the polycyclic aromatic hydrocarbons in the wetlands of Gbokoda and environs for pen aquaculture adoption as a recipe for achieving zero hunger in Nigeria. International Journal of Advanced Multidisciplinary Research Studies, 4(4), 1021–1026.
Ogunrinde, A. T., Oguntunde, P. G., Fasinmirin, J. T., Akinola, G. E., & Olaifa, O. P. (2024). Field-scale variability and dynamics of soil moisture in Southwestern Nigeria. Geoenvironmental Disasters, 11, 20.
R Core Team. (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
Schimel, J. P. (2018). Life in dry soils: Effects of drought on soil microbial communities and processes. Annual Review of Ecology, Evolution, and Systematics, 49, 409-432.
Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall’s tau. Journal of the American Statistical Association, 63(324), 1379–1389.
Smith, P., Cotrufo, M. F., Rumpel, C., Paustian, K., Kuikman, P. J., Elliott, J. A., ... & Lal, R. (2015). Biogeochemical cycles and biodiversity as key drivers of ecosystem services provided by soils. Soil, 1(2), 665-685.
Stackhouse, P. W., Jr. (2006). Prediction of worldwide energy resources (POWER): NASA’s applied science program for renewable energy and buildings. Solar Energy, 80(12), 1580-1593.
Torrence, C., & Compo, G. P. (1998). A practical guide to wavelet analysis. Bulletin of the American Meteorological Society, 79(1), 61–78.
Wang, T., Franz, T. E., Li, R., You, J., Shulski, M. D., & Ray, C. (2017). Evaluating climate and soil effects on regional soil moisture spatial variability using EOFs. Water Resources Research, 53(5), 4022-4035.
Wekpe, V. O., & Idisi, E. B. (2024). Long-term monitoring of oil spill impacted vegetation in the Niger Delta region of Nigeria: A Google Earth Engine derived vegetation indices approach. Journal of Geography, Environment and Earth Science International, 28(2), 27–40.
Zhang, Y., Chiew, F. H., Peña-Arancibia, J., Sun, F., Li, H., & Leuning, R. (2017). Global variation of transpiration and soil evaporation and the role of their major climate drivers. Journal of Geophysical Research: Atmospheres, 122(13), 6868-6881.













