Abstract
This study aims to assess, compare, and attribute the effects due to separate and combined land use/land cover (LULC) and climate changes on hydrological processes in a tropical catchment. The Soil and Water Assessment Tool (SWAT) model is set up and calibrated for a small contributing sub-basin of the Tana River Basin (TRB) in Kenya. The model is then applied to simulate the hydrological components (i.e., streamflow (FLOW), evapotranspiration (ET), soil water (SW), and water yield (WYLD)) for different combinations of LULC and climate scenarios. Land use data generated from Land Satellite 5 Thematic Mapper (Landsat 5TM) images for two different periods (1987 and 2011) and satellite-based precipitation data from the African Rainfall Climatology version 2 (ARC2) dataset are utilized as inputs to the SWAT model. The Nash–Sutcliffe model efficiency (NSE), coefficient of determination (R2), percent bias (PBIAS), and the ratio of root mean square error to the standard deviation (RSR) for daily streamflow were 0.73, 0.76, 3.16%, and 0.51 in calibration period, respectively, and 0.45, 0.54, 12.53%, and 0.79 in validation period, respectively, suggesting that the model performed relatively good. An analysis of the LULC data for the catchment showed that there was an increase in agricultural, grassland, and forested land with a concomitant decrease in woodland and shrubland. Simulation results revealed that change in climate had a more significant effect on the simulated parameters than the change in LULC. It is shown that changes in LULC only had very minor effects in the simulated parameters. The monthly mean FLOW and WYLD decreased by 0.02% and 0.11%, respectively, while ET and SW increased by a monthly mean of 0.2% and 2.2%. Varying the catchment climate and holding the land use constant reduced FLOW, ET, SW, and WYLD by an average monthly mean of 43.2%, 21%, 13%, and 70%, respectively, indicating that climate changes have more significant effects on the catchment hydrological processes than changes in LULC. Thus, it is necessary to evaluate and identify the isolated and combined effects of LULC and climatic changes when assessing impacts on the TRB’s hydrological processes.
Similar content being viewed by others
Data availability
The data that support the findings of this study are available from Quoc Bao Pham, phambaoquoc@tdmu.edu.vn, upon reasonable request.
Code availability
Code is available from Quoc Bao Pham, phambaoquoc@tdmu.edu.vn, upon reasonable request.
References
Abbaspour KC, Yang J, Maximov I, Siber R, Bogner K, Mieleitner J, Zobrist J (2007) Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. J Hydrol 333(2007):413–430. https://doi.org/10.1016/j.jhydrol.2006.09.014
Abbaspour KC, Rouholahnejad E, Vaghefi S, Srinivasan R, Yang H, Kløve B (2015) A continental-scale hydrology and water quality model for Europe: calibration and uncertainty of a high-resolution large-scale SWAT model. J Hydrol 524:733–752. https://doi.org/10.1016/j.jhydrol.2015.03.027
Abbaspour Karim C (2015) SWAT - CUP SWAT calibration and uncertainty programs - a user manual. Eawag: Swiss Federal Institute of Aquatic Science and Technology
Anaba LA, Banadda N, Kiggundu N, Wanyama J, Engel B, Moriasi D (2017) Application of SWAT to assess the effects of land use change in the Murchison Bay catchment in Uganda. Comput Water, Energy, Environ Eng 6:24–40. https://doi.org/10.4236/cweee.2017.61003
Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment part I : model development. J Am Water Resour Assoc 34(1):73–89
Arnold JG, Kiniry JR, Srinivasan R, Williams JR, Haney EB, Neitsch SL (2012) Soil & water assessment tool. Input/Output Documentation Version 2012. Texas Water Resources Institute TR-439
Batjes NH (2011) Soil property estimates for the Upper Tana river catchment , Kenya , derived from SOTER and WISE (ver. 1.1). Report 2010/07b, ISRIC - World Soil Information, Wageningen (vi + 37 p. with data set)
Camara M, Jamil NR, and Abdullah AFB (2019) Impact of land uses on water quality in Malaysia: a review. Ecol Proc 8(1). https://doi.org/10.1186/s13717-019-0164-x
D’Agostino DR, Trisorio LG, Lamaddalena N, Ragab R (2010) Assessing the results of scenarios of climate and land use changes on the hydrology of an Italian catchment : modelling study. Hydro Nepal 24(2010):2693–2704. https://doi.org/10.1002/hyp.7765
De Niel J, Willems P (2018) Climate or land cover variations: what is driving observed changes in river peak flows? A data-based attribution study. Hydrol Earth Syst Sci Discuss 23:1–19. https://doi.org/10.5194/hess-2018-385
DeFries R, Eshleman K (2004) Land-use change and hydrologic processes : a major focus for the future. Hydrol Process 18(2004):2183–2186. https://doi.org/10.1002/hyp.5584
Droogers P, Torabi M, Akbari M, Pazira E (2001) Field-scale modeling to explore salinity problems in irrigated agriculture. Irrig Drain 50(2001):77–90
Fang N, Shi Z, Li L, Guo Z, Liu Q, Ai L (2012) The effects of rainfall regimes and land use changes on runoff and soil loss in a small mountainous watershed. CATENA 99:1–8. https://doi.org/10.1016/j.catena.2012.07.004
FAO (2012) FAO/IIASA/ISRIC/ISS-CAS/JRC, 2012. Harmonized World Soil Database (version 1.2). FAO, Rome, Italy and IIASA, Laxenburg, Austria. Retrieved from https://esdac.jrc.ec.europa.eu/ESDB_Archive/Soil_Data/Docs_GlobalData/Harmonized_World_Soi_Database_v1.2.pdf
Franczyk J, Chang H (2009) The effects of climate change and urbanization on the runoff of the Rock Creek basin in the Portland metropolitan area, Oregon, USA. Hydrol Process 23(2009):805–815. https://doi.org/10.1002/hyp
Gassman PPW, Reyes MMR, Green CCH, Arnold JJG (2007) The soil and water assessment tool : historical development, applications, and future research directions. Trans ASAE 50(4):1211–1250. https://doi.org/10.13031/2013.23637
Ghaffari G, Keesstra S, Ghodousi J, Ahmadi H (2010) SWAT-simulated hydrological impact of land-use change in the Zanjanrood Basin, Northwest Iran. Hydrol Process 24(2010):892–903. https://doi.org/10.1002/hyp.7530
Gupta HV, Sorooshian S, Yapo PO (1999) Status of automatic calibration for hydrologic models : comparison with multilevel expert calibration. J Hydrol Eng. https://doi.org/10.1061/(ASCE)1084-0699(1999)4
Gyamfi C, Ndambuki JM, Salim RW (2016) Hydrological responses to land use/cover changes in the Olifants Basin, South Africa. Water 8(588):2–16. https://doi.org/10.3390/w8120588
Haghighi AT, Darabi H, Shahedi K, Solaimani K, Kløve B (2020) A scenario-based approach for assessing the hydrological impacts of land use and climate change in the Marboreh Watershed, Iran. Environ Model Assess 25(1):41–57. https://doi.org/10.1007/s10666-019-09665-x
Hu Q, Willson GD, Chen X, Akyuz A (2005) Effects of climate and landcover change on stream discharge in the Ozark Highlands, USA ∗. Environ Model Assess 2005(10):9–19. https://doi.org/10.1007/s10666-004-4266-0
Huo W, Li Z, Wang J et al (2019) Multiple hydrological models comparison and an improved Bayesian model averaging approach for ensemble prediction over semi-humid regions. Stoch Environ Res Risk Assess 33:217–238
Hunink JE, Immerzeel WW, Droogers P, and Kauffman S (2010) Green water credits target areas for the Upper Tana Catchment, Kenya. Phase II - pilot operations: biophysical assessment using SWAT. Green Water Credits Report 10/ ISRIC Report 2010/04, ISRIC World Soil Information, Wageningen
Im S, Kim ÆH, Kim ÆC, Jang C (2009) Assessing the impacts of land use changes on watershed hydrology using MIKE SHE. Environ Geol 57:231–239. https://doi.org/10.1007/s00254-008-1303-3
Jabro JD (1992) Estimation of saturated hydraulic conductivity of soils from particle size distribution and bulk density data. Trans ASAE 35(2):557–560. https://doi.org/10.13031/2013.28633
Jacobs JH, Angerer J, Vitale J, Srinivasan R, Kaitho R (2007) Mitigating economic damage in Kenya’s Upper Tana River Basin: an application of Arc-View SWAT. J Spat Hydrol 7(1):23–46. https://doi.org/10.1017/CBO9780511806049
Kavetski D, Kuczera G, Franks SW (2006) Bayesian analysis of input uncertainty in hydrological modeling: 1. Theory. Water Resour 42(W03407):1–9. https://doi.org/10.1029/2005WR004368
Kerandi NM, Laux P, Arnault J, and Kunstmann H (2016) Performance of the WRF model to simulate the seasonal and interannual variability of hydrometeorological variables in East Africa: a case study for the Tana River basin in Kenya. Theor Appl Climatol 1–18.https://doi.org/10.1007/s00704-016-1890-y
KSS, and ISRIC (2007) Kenya Soil and Terrain database - version 2. Kenya Soil Survey and ISRIC
Lahmer W, Pfiitzner B, Becker A (2001) Assessment of land use and climate change impacts on the mesoscale. Phys Chem Earth 26(7–8):565–575
Li Z, Zhang K (2008) Comparison of Three GIS-Based Hydrological Models. J Hydrol Eng 13(5):364–370
Li Z, Liu W, Zhang X, Zheng F (2009) Impacts of land use change and climate variability on hydrology in an agricultural catchment on the Loess Plateau of China. J Hydrol 377(2009):35–42. https://doi.org/10.1016/j.jhydrol.2009.08.007
Li Z, Deng X, Wu F, and Hasan SS (2015) Scenario analysis for water resources in response to land use change in the middle and upper reaches of the Heihe River Basin. Sustainability 3086–3108.https://doi.org/10.3390/su7033086
Liu D, Chen X, Lian Y, Lou Z (2010) Impacts of climate change and human activities on surface runoff in the Dongjiang River basin of China. Hydrol Process 24(2010):1487–1495. https://doi.org/10.1002/hyp.7609
Liu Y, Zhang K, Li Z, Liu Z, Wang J, ... Huang P (2020) A hybrid runoff generation modelling framework based on spatial combination of three runoff generation schemes for semi-humid and semi-arid watersheds. J Hydrol (Amsterdam) 590:125440. https://doi.org/10.1016/j.jhydrol.2020.125440
Lu Z, Zou S, Qin Z, Yang Y, Xiao H, Wei Y, … Xie J (2015) Hydrologic responses to land use change in the Loess Plateau : case study in the Upper Fenhe River Watershed. AdvMeteorol 2015(2013):1–10
Mango LM, Melesse AM, McClain ME, Gann D, Setegn SG (2011) Land use and climate change impacts on the hydrology of the upper Mara River Basin, Kenya: results of a modeling study to support better resource management. Hydrol Earth Syst Sci 15(7):2245–2258. https://doi.org/10.5194/hess-15-2245-2011
Marhaento H, Booij MJ, Hoekstra AY (2018) Hydrological response to future land-use change and climate change in a tropical catchment. Hydrol Sci J 63(9):1368–1385. https://doi.org/10.1080/02626667.2018.1511054
Miller SN, Kepner WG, Mehaffey MH, Hernandez M, Miller RC, Goodrich DC, … Miller WP (2002) Integrating landscape assessment and hydrologic modeling for land cover change analysis 1. J Am Water Resour Assoc 38(4):915–929
Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50(3):885–900
NASA JPL (2013) NASA Shuttle Radar Topography Mission Global 1 arc second. NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/MEaSUREs/SRTM/SRTMGL1.003
Ndomba P, Mtalo F, Killingtveit A (2008) SWAT model application in a data scarce tropical complex catchment in Tanzania. Phys Chem Earth 33(2008):626–632. https://doi.org/10.1016/j.pce.2008.06.013
Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2005) Soil and w ater assessment tool theoretical documentation
Novella NS, Thiaw WM (2013) African rainfall climatology version 2 for famine early warning systems. J Appl Meteorol Climatol 52(3):588–606. https://doi.org/10.1175/JAMC-D-11-0238.1
Palamuleni LG, Ndomba M, Annegarn HJ (2011) Evaluating land cover change and its impact on hydrological regime in Upper Shire river catchment, Malawi. Reg Environ Chang 11(2011):845–855. https://doi.org/10.1007/s10113-011-0220-2
Polong F, Chen H, Sun S, Ongoma V (2019) Temporal and spatial evolution of the standard precipitation evapotranspiration index (SPEI) in the Tana River Basin. Theoretical and Applied Climatology, Kenya. https://doi.org/10.1007/s00704-019-02858-0
Qi S, Sun G, Wang Y, Mcnulty SG, Myers JAM (2009) Streamflow response to climate and landuse changes in a coastal watershed in North Carolina. Am Soc Agric Biol Eng 52(3):739–749
Qiu L, Zheng F, Yin R (2012) SWAT-based runoff and sediment simulation in a small watershed, the loessial hilly-gullied region of China: capabilities and challenges. Int J Sedim Res 27(2):226–234. https://doi.org/10.1016/S1001-6279(12)60030-4
Rockstrӧm J, Barron J, Fox P (2002) Rainwater management for increased productivity among small-holder farmers in drought prone environments. Phys Chem Earth 27(2002):949–959
Ryberg KR, Vecchia AV (2017) waterData—An R package for retrieval, analysis, and anomaly calculation of daily hydrologic time series data
Shooshtari SJ, Shayesteh K, Gholamalifard M, Azari M, Serrano-notivoli R, López-moreno JI (2017) Impacts of future land cover and climate change on the water balance in northern Iran. Hydrol Sci J 62(16):2655–2673. https://doi.org/10.1080/02626667.2017.1403028
Stehr A, Debels P, Romero F, Alcayaga H (2008) Hydrological modelling with SWAT under conditions of limited data availability : evaluation of results from a Chilean case study. Hydrol Sci J 53(3):37–41. https://doi.org/10.1623/hysj.53.3.588
Stonestrom DA, Scanlon BR, Zhang L (2009) Introduction to special section on impacts of land use change on water resources. Water Resour Res 45:2–4. https://doi.org/10.1029/2009WR007937
Talib A, Randhir TO (2017) Climate change and land use impacts on hydrologic processes of watershed systems. J Water Clim Chang 1–12.https://doi.org/10.2166/wcc.2017.064
Uniyal B, Jha MK, Campus M (2015) Assessing climate change impact on water balance components of Upper Baitarni River Basin using SWAT model. Water Resour Manage 29(2015):4767–4785. https://doi.org/10.1007/s11269-015-1089-5
Van Liew MW, Bosch DD, Arnold J (2007) Suitability of SWAT for the conservation effects assessment project: comparison on USDA agricultural research service watersheds. J Hydrol Eng 12(2):173–189. https://doi.org/10.1061/(ASCE)1084-0699(2007)12
Verburg PH, Neumann K, Nol L (2011) Challenges in using land use and land cover data for global change studies. Glob Change Biol 17(2011):974–989. https://doi.org/10.1111/j.1365-2486.2010.02307.x
Vӧrӧsmarty CJ, Green P, Salisbury J, Lammers RB (2000) Global water resources: vulnerability from climate change and population growth. SCIENCE (Vol. 289). Retrieved from www.sciencemag.org
Wagner PD, Kumar S, Schneider K (2013) An assessment of land use change impacts on the water resources of the Mula and Mutha Rivers catchment upstream of Pune, India. Hydrol Earth Syst Sci 17:2233–2246. https://doi.org/10.5194/hess-17-2233-2013
Wang R, Kalin L, Kuang W, Tian H (2014) Individual and combined effects of land use / cover and climate change on Wolf Bay watershed stream fl ow in southern Alabama. Hydrol Process 28(2014):5530–5546. https://doi.org/10.1002/hyp.10057
Welde K, Gebremariam B (2017) Effect of Land Use Cover Dynamics on Hydrological Response of Watershed: Case Study of Tekeze Dam Watershed, Northern Ethiopia. Int Soil Water Conserv Res. https://doi.org/10.1016/j.iswcr.2017.03.002
Xu L, Liu X, Tong D, Liu Z, Yin L, ... Zheng W (2022) Forecasting Urban Land Use Change Based on Cellular Automata and the PLUS Model. Land (Basel) 11(5):652
Yin J, He F, Xiong YJ, Qiu GY (2017) Effects of land use/land cover and climate changes on surface runoff in a semi-humid and semi-arid transition zone in northwest China. Hydrol Earth Syst Sci 21:183–196. https://doi.org/10.5194/hess-21-183-2017
Zheng J, Sun G, Li W, Yu X, Zhang C, Gong Y, … Ii V (2016) Impacts of land use change and climate variations on annual inflow into the Miyun Reservoir, Beijing, China. Hydrol Earth Syst Sci 20:1561–1572.https://doi.org/10.5194/hess-20-1561-2016
Zuo D, Xu Z, Yao W, Jin S, Xiao P, Ran D (2016) Assessing the effects of changes in land use and climate on runoff and sediment yields from a watershed in the Loess Plateau of China. Sci Total Environ 544:238–250. https://doi.org/10.1016/j.scitotenv.2015.11.060, https://doi.org/10.1016/j.scitotenv.2015.11.060
Acknowledgements
The authors extend their thanks to anonymous reviewers.
Author information
Authors and Affiliations
Contributions
Francis Polong: project administration, conceptualization, writing—original draft, software, formal analysis, visualization. Khidir Deng, Quoc Bao Pham, Nguyen Thi Thuy Linh, S.I. Abba, Ali Najah Ahmed: formal analysis; writing—original draft, visualization. Khaled Mohamed Khedher: data curation, writing, review and editing. Duong Tran Anh, Ahmed El-Shafie: supervision, writing, review, editing.
Corresponding author
Ethics declarations
Ethics approval
Not applicable.
Consent to participate
Not applicable.
Consent for publication
Not applicable.
Conflict of interest
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Polong, F., Deng, K., Pham, Q.B. et al. Separation and attribution of impacts of changes in land use and climate on hydrological processes. Theor Appl Climatol 151, 1337–1353 (2023). https://doi.org/10.1007/s00704-022-04351-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00704-022-04351-7