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Abstract
The increasing global population necessitates increased agricultural production, driving the expansion of agricultural lands and advancement of irrigation farming to supplement the inconsistent and insufficient rainfall patterns prevalent in many regions. This study aimed to evaluate the potential impacts of the expansion of agricultural lands on the streamflow regime of the Thiba River and its impact on the downstream users. The study involved comparing the 2004 and 2014 land uses and using the Hydrologic Engineering Centre’s Hydrologic Modelling Systems (HEC-GeoHMS and HEC-HMS) for long-term impact simulations. The results showed a considerable decline in the streamflow in the dry months compared to the wet months, with increasing water abstraction trends from 2007 to 2014. The long-term impact assessment showed an average decline in streamflow in the near (2030) and far (2060) future due to land use and population changes with minimal impact from the increasing precipitation. Based on these findings, there is a need for proper water management and adaptation mechanisms to be put in place to maintain the future water supply from the Thiba River. This study’s findings could assist policy and decision-makers in making informed water resource management decisions.
References
Acharya, A. K., & Nangia, P. (2004). Population growth and changing land-use pattern in Mumbai metropolitan region of India. Caminhos de Geografia, 5(11), 168–185. https://doi.org/10.14393/rcg51115332
Aeschbacher, J., Liniger, H., & Weingartner, R. (2005). River water shortage in a highland-lowland system: A case study of the impacts of water abstraction in the Mount Kenya region. Mountain Research and Development, 25(2), 155–162.
Akoko, G., Kato, T., & Tu, L. H. (2020). Evaluation of irrigation water resources availability and climate change impacts-a case study of Mwea irrigation scheme, Kenya. Water (Switzerland), 12(9), 1–22. https://doi.org/10.3390/W12092330
Batjes, N. H. (2011). Soil property estimates for the Upper Tana, Kenya, derived from SOTER and WISE (Ver. 1.1).. https://www.isric.org/sites/default/files/isric_report_2010_07b.pdf
Bentsen, M., Bethke, I., Debernard, J. B., Iversen, T., Kirkevåg, A., Seland, Ø., Drange, H., Roelandt, C., Seierstad, I. A., Hoose, C., & Kristjánsson, J. E. (2013). The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate. Geoscientific Model Development, 6, 687–720. https://doi.org/10.5194/gmd-6-687-2013
Chow, V. Te, Maidment, D. R., & Mays, L. W. (1988). Applied hydrology. McGraw-Hill Series in Water Resources and Environmental Engineering. McGraw-Hill Book Company. https://ponce.sdsu.edu/Applied_Hydrology_Chow_1988.pdf
Di Gregorio, A., & Latham, J. (2003). Africover land cover classification and mapping project. https://www.eolss.net/sample-chapters/c19/E1-05-01-09.pdf
Dijkshoorn, J. A., Macharia, P. N., Huting, J. R. M., Maingi, P. M., & Njoroge, C. R. K. (2011). Soil and terrain conditions for the Upper Tana River catchment, Kenya (Version 1.1). https://www.isric.org/sites/default/files/isric_gwc_report_k11.pdf
Dunne, J. P., John, J. G., Adcroft, A. J., Griffies, S. M., Hallberg, R. W., Shevliakova, E., Stouffer, R. J., Cooke, W., Dunne, K. A., Harrison, M. J., Krasting, J. P., Malyshev, S. L., Milly, P. C. D., Phillipps, P. J., Sentman, L. T., Samuels, B. L., Spelman, M. J., Winton, M., Wittenberg, A. T., & Zadeh, N. (2012). GFDL’s ESM2 global coupled climate-carbon earth system models. Part I: Physical formulation and baseline simulation characteristics. Journal of Climate, 25(19), 6646–6665. https://doi.org/10.1175/JCLI-D-11-00560.1
Food and Agriculture Organization of the United Nations. (2015). Climwat 2.0. for cropwat. Water Development and Management Unit and the climate Change and Bioenergy Unit of FAO (2.0; Issue September). Land and Water Development Division of FAO. https://www.fao.org/land-water/databases-and-software/climwat-for-cropwat/en/
Food and Agriculture Organization of the United Nations. (2017a). Spatially aggregated multipurpose landcover database for Kenya - AFRICOVER. Africover. https://data.apps.fao.org/map/catalog/srv/api/records/7b07bb4c-bf31-4487-8615-3a6a32643b1f
Food and Agriculture Organization of the United Nations. (2017b). Water for sustainable food and agriculture: A report produced for the G20 Presidency of Germany. Food and Agriculture Organization of the United Nations. https://www.fao.org/3/i7959e/i7959e.pdf
Food and Agriculture Organization of the United Nations, International Institute for Applied Systems Analysis, International Soil Reference and Information Centre, Institute of Soil Science, Chinese Academy of Sciences, &Joint Research Centre. (2012). Harmonized world soil database (version 1.2). http://webarchive.iiasa.ac.at/Research/LUC/External-World-soil-database/HTML/index.html?sb=1
Fernández-Cirelli, A., Arumí, J. L., Rivera, D., & Boochs, P. W. (2009). Environmental effects of irrigation in arid and semi-arid regions. Chilean Journal of Agricultural Research 69(Suppl. 1), 27–40. https://doi.org/10.4067/s0718-58392009000500004
Fowler, H. J., Blenkinsop, S., & Tebaldi, C. (2007). Linking climate change modelling to impacts studies: Recent advances in downscaling techniques for hydrological modelling. International Journal of Climatology, 27(12), 1547–1578. https://doi.org/10.1002/joc.1556
Githui, F., Gitau, W., Mutua, F., & Bauwens, W. (2009). Climate change impact on SWAT simulated streamflow in western Kenya. International Journal of Climatology, 29(12), 1823–1834. https://doi.org/10.1002/joc.1828
Hoblit, B. C., & Curtis, D. C. (2003). Integrating radar rainfall estimates with digital elevation models and land use data to create an accurate hydrologic model. (Working Paper). https://onerain.com/wp-content/uploads/2020/10/2001-radar-rainfall-accurate-hydologic-model.pdf
Jansen, L. J. M., & Di Gregorio, A. (2003). Land-use data collection using the “land cover classification system”: Results from a case study in Kenya. Land Use Policy, 20(2), 131–148. https://doi.org/10.1016/S0264-8377(02)00081-9
Jones, C. D., Hughes, J. K., Bellouin, N., Hardiman, S. C., Jones, G. S., Knight, J., Liddicoat, S., O’Connor, F. M., Andres, R. J., Bell, C., Boo, K. O., Bozzo, A., Butchart, N., Cadule, P., Corbin, K. D., Doutriaux-Boucher, M., Friedlingstein, P., Gornall, J., Gray, L., … Zerroukat, M. (2011). The HadGEM2-ES implementation of CMIP5 centennial simulations. Geoscientific Model Development, 4, 543–570. https://doi.org/10.5194/gmd-4-543-2011
Kawasaki, A., Takamatsu, M., He, J., Rogers, P., & Herath, S. (2010). An integrated approach to evaluate potential impact of precipitation and land-use change on streamflow in Srepok River Basin. Theory and Applications of GIS, 18(2), 9–20. https://doi.org/10.5638/thagis.18.117
Kenya National Bureau of Statistics (2010). Kenya population and housing census, volume 1, population by administrative units. https://www.knbs.or.ke/2009-kenya-population-and-housing-census-volume-1a-population-distribution-by-administrative-units/
Kiem, A. S., Ishidaira, H., Hapuarachchi, H. P., Zhou, M. C., Hirabayashi, Y., & Takeuchi, K. (2008). Future hydroclimatology of the Mekong River basin simulated using the high-resolution Japan Meteorological Agency (JMA) AGCM. Hydrological Processes, 22(9), 1382–1394. https://doi.org/10.1002/hyp.6947
Kirui, W. K. (2008). Analysis of catchment hydrologic response under changing land use: The case of upper molo river catchment, Kenya [Egerton University]. http://hdl.handle.net/1834/6858
Kitheka, J. U., & Ongwenyi, G. S. (2002). The Tana River Basin and the opportunity for research on the land-ocean interaction in the Tana Delta. University of Nairobi. http://hdl.handle.net/1834/7842
Mateo-Sagasta, J., Zadeh, S. M., & Turral, H. (2018). More people, more food, worse water? A global review on water pollution from agriculture. Food and Agricultural Organization and International Water Management Institute. http://www.fao.org/3/ca0146en/ca0146en.pdf
Meaurio, M., Zabaleta, A., Uriarte, J. A., Srinivasan, R., & Antigüedad, I. (2015). Evaluation of SWAT model’s performance to simulate streamflow spatial origin. The case of a small forested watershed. Journal of Hydrology, 525, 326–334. https://doi.org/10.1016/j.jhydrol.2015.03.050
Meehl, G. A., Stocker, T. F., Collins, W. D., Friedlingstein, P., Gaye, A. T., Gregory, J. M., Kitoh, A., Knutti, R., Murphy, J. M., Noda, A., Raper, S. C. B., Watterson, I. G., Weaver, A. J., & Zhao, Z.-C. (2007). Global climate projections: Climate change 2007: The physical science basis. Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Cambridge University Press.
Mishra, S. K., Pandey, A., & Singh, V. P. (2012). Special issue on Soil Conservation Service Curve Number (SCS-CN) methodology. Journal of Hydrologic Engineering, 17(11), 1157. https://doi.org/10.1061/(asce)he.1943-5584.0000694
Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D., & Veith, T. L. (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50(3), 885–900. https://doi.org/10.13031/2013.23153
Muema, F. M., Home, P. G., & Raude, J. M. (2018). Application of benchmarking and principal component analysis in measuring performance of public irrigation schemes in Kenya. Agriculture (Switzerland), 8(10), 162. https://doi.org/10.3390/agriculture8100162
Musau, J., Sang, J., Gathenya, J., & Luedeling, E. (2015). Hydrological responses to climate change in Mt. Elgon watersheds. Journal of Hydrology: Regional Studies, 3, 233–246. https://doi.org/10.1016/j.ejrh.2014.12.001
National Irrigation Authority. (2023). Mwea irrigation scheme. https://irrigation.go.ke/projects/mwea-irrigation-scheme/
Ngigi, S. N., Savenije, H. H. G., & Gichuki, F. N. (2007). Land use changes and hydrological impacts related to up-scaling of rainwater harvesting and management in upper Ewaso Ng’iro river basin, Kenya. Land Use Policy, 24(1), 129–140. https://doi.org/10.1016/j.landusepol.2005.10.002
Notter, B., MacMillan, L., Viviroli, D., Weingartner, R., & Liniger, H. P. (2007). Impacts of environmental change on water resources in the Mt. Kenya region. Journal of Hydrology, 343, 266–278. https://doi.org/10.1016/j.jhydrol.2007.06.022
Nyamai, M., Mati, B. M., Home, P. G., Odongo, B., Wanjogu, R., & Thuranira, E. G. (2012). Improving land and water productivity in basin rice cultivation in Kenya through system of rice intensification (SRI). Agricultural Engineering International: CIGR Journal, 14(2), 1–9.
Oduor, B. O., Campo-Bescós, M. Á., Lana-Renault, N., & Casalí, J. (2023). Effects of climate change on streamflow and nitrate pollution in an agricultural Mediterranean watershed in Northern Spain. Agricultural Water Management, 285, 1–12. https://doi.org/10.1016/J.AGWAT.2023.108378
Pulighe, G., Lupia, F., Chen, H., & Yin, H. (2021). Modeling climate change impacts on water balance of a Mediterranean watershed using SWAT+. Hydrology, 8(4), 1–14. https://doi.org/10.3390/hydrology8040157
Rallison, R. E., & Miller, N. (1982). Past, present, and future SCS runoff procedure. In V. P. Singh (Ed.), International symposium on rainfall-runoff modeling, 353–364. Mississippi State University.
Rodrigues, D., Fonseca, A., Stolarski, O., Freitas, T. R., Guimarães, N., Santos, J. A., & Fraga, H. (2023). Climate change impacts on the Côa Basin (Portugal) and potential impacts on agricultural irrigation. Water (Switzerland), 15(15), 1–17. https://doi.org/10.3390/w15152739
Rostamian, R., Jaleh, A., Afyuni, M., Mousavi, S. F., Heidarpour, M., Jalalian, A., & Abbaspour, K. C. (2008). Application of a SWAT model for estimating runoff and sediment in two mountainous basins in central Iran. Hydrological Sciences Journal, 53(5), 977–988. https://doi.org/10.1623/hysj.53.5.977
Siebert, S., Burke, J., Faures, J. M., Frenken, K., Hoogeveen, J., Döll, P., & Portmann, F. T. (2010). Groundwater use for irrigation – A global inventory. Hydrology and Earth System Sciences, 14(10), 1863–1880. https://doi.org/10.5194/hess-14-1863-2010
Tolson, B. A., & Shoemaker, C. A. (2007). Cannonsville reservoir watershed SWAT2000 model development, calibration and validation. Journal of Hydrology, 337(1–2), 68–86. https://doi.org/10.1016/j.jhydrol.2007.01.017
United States Army Corps of Engineers. (2010). Hydrologic modeling system, HEC-HMS user’s manual, version 3.5. https://www.hec.usace.army.mil/software/hec-hms/documentation/HEC-HMS_Users_Manual_3.5.pdf
United States Army Corps of Engineers. (2013). HEC-GeoHMS: Geospatial hydrologic modeling system, version 10.1, user’s manual. https://www.hec.usace.army.mil/software/hec-geohms/documentation/HEC-GeoHMS_Users_Manual_10.1.pdf
United States Department of Agriculture. (2016). Natural resources conservation service: Conservation practice standard-filter strip code 393. In United States Department of Agriculture (USDA) - Natural Resources Conservation Service (NRCS) (Issue September, pp. 1–4). United States Department of Agriculture (USDA) - Natural Resources Conservation Service (NRCS). https://www.nrcs.usda.gov/sites/default/files/2022-09/Filter_Strip_393_CPS.pdf
United States Geological Survey. (2017). USGS EROS Archive - Digital Elevation - Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global. Earth Resources Observation and Science (EROS) Center. https://doi.org/10.5066/F7PR7TFT
Yasin, Z., Nabi, G., & Randhawa, S. M. (2015). Modeling of hill torrent using HEC Geo-HMS and HEC-HMS models: A case study of mithawan watershed. Pakistan Journal of Meteorology, 11(22), 1–11. http://www.pmd.gov.pk/rnd/rndweb/rnd_new/journal/vol11_issue22_files/1.pdf
Zar, J. H. (1972). Significance testing of the Spearman Rank correlation coefficient. Journal of the American Statistical Association, 67(339), 578–580. https://doi.org/10.2307/2284441
Zeng, R., & Cai, X. (2014). Analyzing streamflow changes: Irrigation-enhanced interaction between aquifer and streamflow in the Republican River basin. Hydrology and Earth System Sciences, 18(2), 493–502. https://doi.org/10.5194/hess-18-493-2014
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