Abstract
The use of models affords an understanding of hydrological processes under different environmental conditions, and aids action planning in the face of changes in land use, soil, and climate. Arid and semi-arid regions are the most vulnerable to climate change. To this effect, the SWAT model has been used in different locations around the world and in various applications. This work analysed recent studies published between 2009 and 2022, to understand the following: (1) how the SWAT model has been applied in arid and semi-arid regions of the world, (2) the criteria used in applying the model, and (3) what alternatives can be used to overcome the limitation of input data and improve SWAT performance in dry environments? A systematic search was conducted based on scientific articles. A total of 234 articles were identified where SWAT was used drylands. The largest and the smallest applications were implemented in Asia and Oceania respectively, in such segments as agriculture, water governance, environmental conservation, hydrological processes, and extreme events. The number of years of data used for calibration and validation was generally low (<20 years), with a median of 9 for calibration and 6 years for validation. The NSE (92%) was the most applied in analysing modelling efficiency, followed by the R2 (78%) and PBIAS (51%). The lack of observational data in the drylands is still a major challenge for studies que involving hydrologic modelling, and to improve the hydrological responses, researchers use strategies such as the use of data measured in the field, remote sensing, and even application of other models with or inside the SWAT.
Similar content being viewed by others
Data Availability
Not applicable
Code availability
Not applicable.
References
Abbas N, Wasimi SA, Al-Ansari N (2016) Assessment of climate change impacts on water resources of khabour in kurdistan, Iraq using swat model. J Environ Hydrol 24:716–732. https://doi.org/10.4236/eng.2016.810065
Abbaspour KC (2015) SWAT-CUP: SWAT calibration and uncertainty programs, Duebendorf
Abu-Allaban M, El-Naqa A, Jaber M, Hammouri N (2015) Water scarcity impact of climate change in semi-arid regions: a case study in Mujib basin, Jordan. Arab J Geosci 8:951–959. https://doi.org/10.1007/s12517-014-1266-5
Abunada Z, Kishawi Y, Alslaibi TM et al (2021) The application of SWAT-GIS tool to improve the recharge factor in the DRASTIC framework: case study. J Hydrol 592. https://doi.org/10.1016/j.jhydrol.2020.125613
Aghakhani Afshar A, Hassanzadeh Y, Pourreza-Bilondi M, Ahmadi A (2018) Analyzing long-term spatial variability of blue and green water footprints in a semi-arid mountainous basin with MIROC-ESM model (case study: Kashafrood River Basin, Iran). Theor Appl Climatol 134:885–899. https://doi.org/10.1007/s00704-017-2309-0
Ahn S, Abudu S, Sheng Z, Mirchi A (2018) Hydrologic impacts of drought-adaptive agricultural water management in a semi-arid river basin: case of Rincon Valley, New Mexico. Agric Water Manag 209:206–218. https://doi.org/10.1016/j.agwat.2018.07.040
Akbari F, Shourian M, Moridi A (2022) Assessment of the climate change impacts on the watershed-scale optimal crop pattern using a surface-groundwater interaction hydro-agronomic model. Agric Water Manag 265:107508. https://doi.org/10.1016/j.agwat.2022.107508
Alvares CA, Stape JL, Sentelhas PC et al (2013) Köppen’s climate classification map for Brazil. Meteorol Zeitschrift 22:711–728. https://doi.org/10.1127/0941-2948/2013/0507
de Amorim PB, Chaffe PLB (2019) Integrating climate models into hydrological modelling: what’s going on in Brazil? Rev Bras Recur Hidricos 24. https://doi.org/10.1590/2318-0331.241920180176
Anand J, Gosain AK, Khosa R (2018) Prediction of land use changes based on Land Change Modeler and attribution of changes in the water balance of Ganga basin to land use change using the SWAT model. Sci Total Environ 644:503–519. https://doi.org/10.1016/j.scitotenv.2018.07.017
Andaryani S, Nourani V, Trolle D et al (2019a) Assessment of land use and climate change effects on land subsidence using a hydrological model and radar technique. J Hydrol 578:124070. https://doi.org/10.1016/j.jhydrol.2019.124070
Andaryani S, Trolle D, Nikjoo MR et al (2019b) Forecasting near-future impacts of land use and climate change on the Zilbier river hydrological regime, northwestern Iran. Environ Earth Sci 78:1–14. https://doi.org/10.1007/s12665-019-8193-4
Anjum MN, Ding Y, Shangguan D (2019) Simulation of the projected climate change impacts on the river flow regimes under CMIP5 RCP scenarios in the westerlies dominated belt, northern Pakistan. Atmos Res 227:233–248. https://doi.org/10.1016/j.atmosres.2019.05.017
Arjomandi A, Mortazavi SA, Khalilian S, Garizi AZ (2021) Optimal land-use allocation using MCDM and SWAT for the Hablehroud Watershed, Iran. Land use policy 100:104930. https://doi.org/10.1016/j.landusepol.2020.104930
Ashraf Vaghefi S, Mousavi SJ, Abbaspour KC et al (2014) Analyses of the impact of climate change on water resources components, drought and wheat yield in semiarid regions: Karkheh River Basin in Iran. Hydrol Process 28:2018–2032. https://doi.org/10.1002/hyp.9747
Ashrafi S, Khoie MMM, Kerachian R, Shafiee-Jood M (2022) Managing basin-wide ecosystem services using the bankruptcy theory. Sci Total Environ 842. https://doi.org/10.1016/j.scitotenv.2022.156845
Azimi M, Heshmati GA, Farahpour M et al (2013) Modeling the impact of rangeland management on forage production of sagebrush species in arid and semi-arid regions of Iran. Ecol Modell 250:1–14. https://doi.org/10.1016/j.ecolmodel.2012.10.017
Bai J, Zhou Z, Li J et al (2022) Predicting soil conservation service in the **ghe River Basin under climate change. J Hydrol 615:128646. https://doi.org/10.1016/j.jhydrol.2022.128646
Bannwarth MA, Sangchan W, Hugenschmidt C et al (2014) Pesticide transport simulation in a tropical catchment by SWAT. Environ Pollut 191:70–79. https://doi.org/10.1016/j.envpol.2014.04.011
Bauwe A, Kahle P, Lennartz B (2019) Evaluating the SWAT model to predict streamflow, nitrate loadings and crop yields in a small agricultural catchment. Adv Geosci 48:1–9. https://doi.org/10.5194/adgeo-48-1-2019
Bhatta B, Shrestha S, Shrestha PK, Talchabhadel R (2019) Evaluation and application of a SWAT model to assess the climate change impact on the hydrology of the Himalayan River Basin. Catena 181:104082. https://doi.org/10.1016/j.catena.2019.104082
Bi W, Weng B, Yuan Z et al (2018) Evolution characteristics of surface water quality due to climate change and LUCC under scenario simulations: a case study in the Luanhe River Basin. Int J Environ Res Public Health 15:1724. https://doi.org/10.3390/ijerph15081724
Bressiani DD, Gasman P, Fernades JG et al (2015a) A review of soil and water assessment tool (SWAT) applications in Brazil: challenges and prospects. Int J Agric Biol Eng 8:1–27. https://doi.org/10.3965/j.ijabe.20150803.1765
Bressiani DA, Srinivasan R, Jones CA, Mendiondo EM (2015b) Effects of different spatial and temporal weather data resolutions on the stream flow modeling of a semi-arid basin, Northeast Brazil. Int J Agric Biol Eng 8:1–16. https://doi.org/10.3965/j.ijabe.20150803.970
Brighenti TM, Bonumá NB, Srinivasan R, Chaffe PLB (2019) Simulating sub-daily hydrological process with SWAT: a review. Hydrol Sci J 64:1415–1423. https://doi.org/10.1080/02626667.2019.1642477
Brouziyne Y, Abouabdillah A, Bouabid R, Benaabidate L (2018) SWAT streamflow modeling for hydrological components’ understanding within an agro-sylvo-pastoral watershed in Morocco. J Mater Environ Sci 9:128–138. https://doi.org/10.26872/jmes.2018.9.1.16
Cao Y, Fu C, Wang X et al (2021) Decoding the dramatic hundred-year water level variations of a typical great lake in semi-arid region of northeastern Asia. Sci Total Environ 770:145353. https://doi.org/10.1016/j.scitotenv.2021.145353
CARD (2020) SWAT literature database for peer-reviewed journal articles. https://www.card.iastate.edu/swat_articles/. Accessed 19 Aug 2020
Chanapathi T, Thatikonda S (2020) Investigating the impact of climate and land-use land cover changes on hydrological predictions over the Krishna river basin under present and future scenarios. Sci Total Environ 721:137736. https://doi.org/10.1016/j.scitotenv.2020.137736
Chen D, Li J, Yang X et al (2020a) Quantifying water provision service supply, demand and spatial flow for land use optimization: a case study in the YanHe watershed. Ecosyst Serv 43:101117. https://doi.org/10.1016/j.ecoser.2020.101117
Chen Y, Marek GW, Marek TH et al (2021) Modeling climate change impacts on blue, green, and grey water footprints and crop yields in the Texas High Plains, USA. Agric For Meteorol 310:108649. https://doi.org/10.1016/j.agrformet.2021.108649
Chen Y, Marek GW, Marek TH et al (2020b) Watershed scale evaluation of an improved SWAT auto-irrigation function. Environ Model Softw 131:104789. https://doi.org/10.1016/j.envsoft.2020.104789
Cheng L, Wan G, Yang M et al (2022) The runoff in the Upper Taohe River basin and its responses to climate change. Water (Switzerland) 14(13):2094. https://doi.org/10.3390/w14132094
Chun JA, Baik J, Kim D, Choi M (2018) A comparative assessment of SWAT-model-based evapotranspiration against regional-scale estimates. Ecol Eng 122:1–9. https://doi.org/10.1016/j.ecoleng.2018.07.015
Coppens J, Trolle D, Jeppesen E, Beklioğlu M (2020) The impact of climate change on a Mediterranean shallow lake: insights based on catchment and lake modelling. Reg Environ Chang 20. https://doi.org/10.1007/s10113-020-01641-6
Dadaser-celik F, Jouma N (2018) Simulation of irrigation and reservoir storage in the Develi Basin (Turkey) using Soil and Water Assessment Tool (SWAT). Süleyman Demirel Üniversitesi Ziraat Fakültesi Derg, pp 468–476
Daneshvar F, Frankenberger JR, Bowling LC et al (2021) Development of strategy for SWAT hydrologic modeling in data-scarce regions of Peru. J Hydrol Eng 26:1–13. https://doi.org/10.1061/(asce)he.1943-5584.0002086
de Andrade CW, Montenegro SM, de Sousa Lima JR, de Assunção Montenegro AA, Magalhães AG (2017a) Modelagem hidrológica sob mudanças na cobertura vegetal de uma bacia hidrográfica no Nordeste do Brasil. J Environ Anal Prog 2:239. https://doi.org/10.24221/jeap.2.3.2017.1446.239-248
de Andrade CW, Montenegro SM, de Sousa Lima JR, de Assunção Montenegro AA, Magalhães AG (2017b) Modelagem hidrológica sob mudanças na cobertura vegetal de uma bacia hidrográfica no Nordeste do Brasil. J Environ Anal Prog 2:239. https://doi.org/10.24221/jeap.2.3.2017.1446.239-248
Dechmi F, Burguete J, Skhiri A (2012) SWAT application in intensive irrigation systems: model modification, calibration and validation. J Hydrol 470–471:227–238. https://doi.org/10.1016/j.jhydrol.2012.08.055
Defersha MB, Melesse AM (2012) Field-scale investigation of the effect of land use on sediment yield and runoff using runoff plot data and models in the Mara River basin, Kenya. Catena 89:54–64. https://doi.org/10.1016/j.catena.2011.07.010
Degife A, Worku H, Gizaw S, Legesse A (2019) Land use land cover dynamics, its drivers and environmental implications in Lake Hawassa Watershed of Ethiopia. Remote Sens Appl Soc Environ 14:178–190. https://doi.org/10.1016/j.rsase.2019.03.005
Delavar M, Eini MR, Kuchak VS et al (2022) Model-based water accounting for integrated assessment of water resources systems at the basin scale. Sci Total Environ 830:154810. https://doi.org/10.1016/j.scitotenv.2022.154810
Dosdogru F, Kalin L, Wang R, Yen H (2020) Potential impacts of land use/cover and climate changes on ecologically relevant flows. J Hydrol 584:124654. https://doi.org/10.1016/j.jhydrol.2020.124654
Dowlatabadi S, Ali Zomorodian SM (2016) Conjunctive simulation of surface water and groundwater using SWAT and MODFLOW in Firoozabad watershed. KSCE J Civ Eng 20:485–496. https://doi.org/10.1007/s12205-015-0354-8
Du X, Shrestha NK, Wang J (2019) Assessing climate change impacts on stream temperature in the Athabasca River Basin using SWAT equilibrium temperature model and its potential impacts on stream ecosystem. Sci Total Environ 650:1872–1881. https://doi.org/10.1016/j.scitotenv.2018.09.344
Duan Y, Meng F, Liu T et al (2019) Sub-daily simulation of mountain flood processes based on the modified soil water assessment tool (Swat) model. Int J Environ Res Public Health 16:3118. https://doi.org/10.3390/ijerph16173118
Ehtiat M, Jamshid Mousavi S, Srinivasan R (2018) Groundwater modeling under variable operating conditions using SWAT, MODFLOW and MT3DMS: a catchment scale approach to water resources management. Water Resour Manag 32:1631–1649. https://doi.org/10.1007/s11269-017-1895-z
Eshtawi T, Evers M, Tischbein B (2016) Quantifying the impact of urban area expansion on groundwater recharge and surface runoff. Hydrol Sci J 61:826–843. https://doi.org/10.1080/02626667.2014.1000916
Fazeli Farsani I, Farzaneh MR, Besalatpour AA et al (2019) Assessment of the impact of climate change on spatiotemporal variability of blue and green water resources under CMIP3 and CMIP5 models in a highly mountainous watershed. Theor Appl Climatol 136:169–184. https://doi.org/10.1007/s00704-018-2474-9
Feng S, Fu Q (2013) Expansion of global drylands under a warming climate. Atmos Chem Phys 13:10081–10094. https://doi.org/10.5194/acp-13-10081-2013
Francesconi W, Srinivasan R, Pérez-Miñana E et al (2016) Using the Soil and Water Assessment Tool (SWAT) to model ecosystem services: a systematic review. J Hydrol 535:625–636
Freund ER, Abbaspour KC, Lehmann A (2017) Water resources of the Black Sea Catchment under future climate and landuse change projections. Water (Switzerland) 9:1–18. https://doi.org/10.3390/w9080598
Ghimire U, Shrestha NK, Biswas A et al (2020) A review of ongoing advancements in Soil and Water Assessment Tool (SWAT) for nitrous oxide (N2O) modeling. Atmosphere 11:450
Ghoraba SM (2015) Hydrological modeling of the Simly Dam watershed (Pakistan) using GIS and SWAT model. Alexandria Eng J 54:583–594. https://doi.org/10.1016/j.aej.2015.05.018
Girolamo AM, Lo Porto A (2012) Land use scenario development as a tool for watershed management within the Rio Mannu Basin. Land use policy 29:691–701. https://doi.org/10.1016/j.landusepol.2011.11.005
De Girolamo AM, Lo Porto A, Pappagallo G, Gallart F (2015) Assessing flow regime alterations in a temporary river - the River Celone case study. J Hydrol Hydromechanics 63:263–272. https://doi.org/10.1515/johh-2015-0027
Goldstein JC, Tarhule A (2015) Evaluating the impacts of climate change and switchgrass production on a semiarid basin. Hydrol Process 29:724–738. https://doi.org/10.1002/hyp.10159
Guo J, Su X, Singh VP, ** J (2016) Impacts of climate and land use/cover change on streamflow using SWAT and a separation method for the **ying river basin in northwestern China. Water (Switzerland) 8:9–13. https://doi.org/10.3390/w8050192
Hammouri N, Adamowski J, Freiwan M, Prasher S (2017) Climate change impacts on surface water resources in arid and semi-arid regions: a case study in northern Jordan. Acta Geod Geophys 52:141–156. https://doi.org/10.1007/s40328-016-0163-7
Himanshu SK, Pandey A, Shrestha P (2017) Application of SWAT in an Indian river basin for modeling runoff, sediment and water balance. Environ Earth Sci 76:1–8. https://doi.org/10.1007/s12665-016-6316-8
Hosseini P, Bailey RT (2022) Investigating the controlling factors on salinity in soil, groundwater, and river water in a semi-arid agricultural watershed using SWAT-Salt. Sci Total Environ 810:152293. https://doi.org/10.1016/j.scitotenv.2021.152293
Hu J, Wu Y, Wang L et al (2021) Impacts of land-use conversions on the water cycle in a typical watershed in the southern Chinese Loess Plateau. J Hydrol 593:125741. https://doi.org/10.1016/j.jhydrol.2020.125741
IPCC (2014a) Climate change 2014 part A: global and sectoral aspects
IPCC (2014b) Resumo para Decisores
IPCC (2019) Desertification. In: Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems, pp 249–344
Ji L, Duan K (2019) What is the main driving force of hydrological cycle variations in the semiarid and semi-humid Weihe River Basin, China? Sci Total Environ 684:254–264. https://doi.org/10.1016/j.scitotenv.2019.05.333
** X, He C, Zhang L, Zhang B (2018) A modified groundwater module in SWAT for improved streamflow simulation in a large, arid endorheic river watershed in Northwest China. Chinese Geogr Sci 28:47–60. https://doi.org/10.1007/s11769-018-0931-0
Jordan G, Goenster-Jordan S, Lamparter GJ et al (2018) Water use in agro-pastoral livelihood systems within the Bulgan River watershed of the Altay Mountains, Western Mongolia. Agric Ecosyst Environ 251:180–193. https://doi.org/10.1016/j.agee.2017.09.008
Jun X, Yongyong Z (2008) Water security in north China and countermeasure to climate change and human activity. Phys Chem Earth 33:359–363. https://doi.org/10.1016/j.pce.2008.02.009
Kamali B, Abbaspour KC, Yang H (2017a) Assessing the uncertainty of multiple input datasets in the prediction of water resource components. Water (Switzerland) 9(9):709. https://doi.org/10.3390/w9090709
Kamali B, Kouchi DH, Yang H, Abbaspour KC (2017b) Multilevel drought hazard assessment under climate change scenarios in semi-arid regions-a case study of the karkheh river basin in Iran. Water 9(4):241. https://doi.org/10.3390/w9040241
Kan G, He X, Ding L et al (2017) Study on applicability of conceptual hydrological models for flood forecasting in humid, semi-humid semi-arid and arid basins in China. Water (Switzerland) 9:1–25. https://doi.org/10.3390/w9100719
Karamouz M, Teymoori J, Olyaei MA (2021) A spatial non-stationary based site selection of artificial groundwater recharge: a case study for semi-arid regions. Water Resour Manag 35:963–978. https://doi.org/10.1007/s11269-020-02762-7
Kavian A, Mohammadi M, Gholami L, Rodrigo-Comino J (2018) Assessment of the spatiotemporal effects of land use changes on runoff and nitrate loads in the Talar River. Water (Switzerland) 10(4):445. https://doi.org/10.3390/w10040445
Khelifa WB, Hermassi T, Strohmeier S et al (2017) Parameterization of the effect of bench terraces on runoff and sediment yield by swat modeling in a small semi-arid watershed in Northern Tunisia. L Degrad Dev 28:1568–1578. https://doi.org/10.1002/ldr.2685
Kouchi DH, Esmaili K, Faridhosseini A et al (2017) Sensitivity of calibrated parameters and water resource estimates on different objective functions and optimization algorithms. Water (Switzerland) 9:1–16. https://doi.org/10.3390/w9060384
Kour R, Patel N, Krishna AP (2016) Climate and hydrological models to assess the impact of climate change on hydrological regime: a review. Arab J Geosci 9:1–31. https://doi.org/10.1007/s12517-016-2561-0
Kroeger T, Klemz C, Boucher T et al (2019) Returns on investment in watershed conservation: application of a best practices analytical framework to the Rio Camboriú Water Producer program, Santa Catarina, Brazil. Sci Total Environ 657:1368–1381. https://doi.org/10.1016/j.scitotenv.2018.12.116
Li E, Mu X, Zhao G et al (2017) Effects of check dams on runoff and sediment load in a semi-arid river basin of the Yellow River. Stoch Environ Res Risk Assess 31:1791–1803. https://doi.org/10.1007/s00477-016-1333-4
Li M, Di Z, Duan Q (2021a) Effect of sensitivity analysis on parameter optimization: case study based on streamflow simulations using the SWAT model in China. J Hydrol 603:126896. https://doi.org/10.1016/j.jhydrol.2021.126896
Li Q, Yu X, **n Z, Sun Y (2013) Modeling the effects of climate change and human activities on the hydrological processes in a semiarid watershed of Loess Plateau. J Hydrol Eng 18:401–412. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000629
Li X, Gao Q, Lei T, Yang X (2011) Application of an integrative hydro-ecological model to study water resources management in the upper and middle parts of the Yellow River basin. Front Earth Sci 5:45–55. https://doi.org/10.1007/s11707-011-0150-9
Li X, Tan L, Li Y et al (2022) Effects of global climate change on the hydrological cycle and crop growth under heavily irrigated management – a comparison between CMIP5 and CMIP6. Comput Electron Agric 202:107408. https://doi.org/10.1016/j.compag.2022.107408
Li X, Zhang Y, Ma N et al (2021b) Contrasting effects of climate and LULC change on blue water resources at varying temporal and spatial scales. Sci Total Environ 786:147488. https://doi.org/10.1016/j.scitotenv.2021.147488
Li Y, Luo L, Chang J et al (2020) Hydrological drought evolution with a nonlinear joint index in regions with significant changes in underlying surface. J Hydrol 585:124794. https://doi.org/10.1016/j.jhydrol.2020.124794
Li Z, Liu WZ, Zhang XC, Zheng FL (2010) Assessing and regulating the impacts of climate change on water resources in the Heihe watershed on the Loess Plateau of China. Sci China Earth Sci 53:710–720. https://doi.org/10.1007/s11430-009-0186-9
Lins FAC, Montenegro AADA, Farias CWLDA et al (2021) Analysis of the temporal dynamics of actual evapotranspiration in a semiarid river basin using hydrological modeling and remote sensing. Irriga 26:543–564. https://doi.org/10.15809/irriga.2021v26n3p543-564
Liu GH, Luan ZQ, Yan BX et al (2015a) Response of hydrological processes to land use change and climate variability in the upper Naoli River watershed, northeast China. Water Resour 42:438–447. https://doi.org/10.1134/S0097807815040077
Liu J, Zhang C, Kou L, Zhou Q (2017) Effects of climate and land use changes on water resources in the Taoer River. Adv Meteorol 2017. https://doi.org/10.1155/2017/1031854
Liu X, Wang S, Xue H et al (2015b) Simulating crop evapotranspiration response under different planting scenarios by modified SWAT model in an irrigation District, Northwest China. PLoS One 10:1–21. https://doi.org/10.1371/journal.pone.0139839
Lu Z, Zou S, Qin Z et al (2015) Hydrologic responses to land use change in the Loess Plateau: case study in the upper Fenhe River watershed. Adv Meteorol 2015. https://doi.org/10.1155/2015/676030
Luan XB, Te WP, Sun SK et al (2018a) Impact of land use change on hydrologic processes in a large plain irrigation district. Water Resour Manag 32:3203–3217. https://doi.org/10.1007/s11269-018-1986-5
Luan XB, Yin YL, Te WP et al (2018b) An improved method for calculating the regional crop water footprint based on a hydrological process analysis. Hydrol Earth Syst Sci 22:5111–5123. https://doi.org/10.5194/hess-22-5111-2018
Lubini A, Adamowski J (2013) Assessing the potential impacts of four climate change scenarios on the discharge of the Simiyu River, Tanzania using the SWAT model. Int J Water Sci 2:1. https://doi.org/10.5772/56453
Magalhães AG, Montenegro AA, Andrade CW, Montenegro SM, Fontes Júnior RV (2018) Hydrological modeling of an experimental basin in the semiarid region of the Brazilian State of Pernambuco. Rev Ambient e Agua 13:1–19. https://doi.org/10.4136/1980-993X
Maleki Tirabadi MS, Banihabib ME, Randhir TO (2021) SWAT-S: a SWAT-salinity module for watershed-scale modeling of natural salinity. Environ Model Softw 135:104906. https://doi.org/10.1016/j.envsoft.2020.104906
Marek GW, Gowda PH, Evett SR et al (2016) Estimating evapotranspiration for dryland crop** systems in the semiarid Texas High Plains using SWAT. J Am Water Resour Assoc 52:298–314. https://doi.org/10.1111/1752-1688.12383
Martínez-Salvador A, Conesa-García C (2020) Suitability of the SWAT model for simulating water discharge and sediment load in a karst watershed of the semiarid Mediterranean basin. Water Resour Manag 34:785–802. https://doi.org/10.1007/s11269-019-02477-4
Masih I, Maskey S, Uhlenbrook S, Smakhtin V (2011) Assessing the impact of areal precipitation input on streamflow simulations using the SWAT model. J Am Water Resour Assoc 47:179–195. https://doi.org/10.1111/j.1752-1688.2010.00502.x
Mehan S, Kannan N, Neupane R et al (2016) Climate change impacts on the hydrological processes of a small agricultural watershed. Climate 4:56. https://doi.org/10.3390/cli4040056
Mengistu AG, Van Rensburg LD, Woyessa YE (2019) Techniques for calibration and validation of SWAT model in data scarce arid and semi-arid catchments in South Africa. J Hydrol Reg Stud 25:100621. https://doi.org/10.1016/j.ejrh.2019.100621
Mengistu AG, Woyessa YE, van Rensburg LD, Tesfuhuney WA (2021) Analysis of the spatio-temporal variability of soil water dynamics in an arid catchment in South Africa. Geoderma Reg 25:e00395. https://doi.org/10.1016/j.geodrs.2021.e00395
Mimich K, Essahlaoui A, El Ouali A, El Hmaidi A (2018) Using SWAT to simulate a Moroccan watershed, including an assessment of the most sensitive modelling parameters with SUFI2. 50–63. https://doi.org/10.9790/1813-0710035063
Mohammed R, Scholz M (2017) Adaptation strategy to mitigate the impact of climate change on water resources in arid and semi-arid regions: a case study. Water Resour Manag 31:3557–3573. https://doi.org/10.1007/s11269-017-1685-7
Molina-Navarro E, Hallack-Alegría M, Martínez-Pérez S et al (2016) Hydrological modeling and climate change impacts in an agricultural semiarid region. Case study: Guadalupe River basin, Mexico. Agric Water Manag 175:29–42. https://doi.org/10.1016/j.agwat.2015.10.029
Nascimento JM, Frade TG, Silva RM (2018) Modelagem da resposta do escoamento em uma bacia do semiárido da Paraíba utilizando o modelo SWAT. Rev Bras Geogr Física 11:1137–1150
Ndambuki JM, Gyamfi C, Salim RW (2017) Modelling groundwater recharge in a semi-arid river basin: a retrospective assessment. Int J Res Chem Metall. Civ Eng 4. https://doi.org/10.15242/ijrcmce.ae0317111
Nerantzaki SD, Giannakis GV, Efstathiou D et al (2015) Modeling suspended sediment transport and assessing the impacts of climate change in a karstic Mediterranean watershed. Sci Total Environ 538:288–297. https://doi.org/10.1016/j.scitotenv.2015.07.092
Nie W, Yuan Y, Kepner W et al (2012) Hydrological impacts of mesquite encroachment in the upper San Pedro watershed. J Arid Environ 82:147–155. https://doi.org/10.1016/j.jaridenv.2012.02.008
Niraula R, Norman LM, Meixner T, Callegary JB (2012) Multi-gauge calibration for modeling the semi-arid Santa Cruz watershed in Arizona-Mexico border area using SWAT. Air, Soil Water Res 5:41–57. https://doi.org/10.4137/ASWR.S9410
Noor H, Vafakhah M, Taheriyoun M, Moghadasi M (2014) Hydrology modelling in Taleghan mountainous watershed using SWAT. J Water L Dev 20:11–18. https://doi.org/10.2478/jwld-2014-0003
Nunes FMS, Srinivasan VS, de Aragão R, de Brito YMA (2022) Applicability of the swat model for hydrosedimentologicaland parameter sensitivity assessment in the sucuru river basin. 15:1220–1239
Ouyang W, Xu X, Hao Z, Gao X (2017) Effects of soil moisture content on upland nitrogen loss. J Hydrol 546:71–80. https://doi.org/10.1016/j.jhydrol.2016.12.053
Paul M, Rajib A, Negahban-Azar M et al (2021) Improved agricultural water management in data-scarce semi-arid watersheds: value of integrating remotely sensed leaf area index in hydrological modeling. Sci Total Environ 791:148177. https://doi.org/10.1016/j.scitotenv.2021.148177
Peng J, Huo A, Cheng Y et al (2017) Submersion simulation in a typical debris flow watershed of Jianzhuangchuan catchment, Loess Plateau. Environ Earth Sci 76. https://doi.org/10.1007/s12665-017-6797-0
Perra E, Piras M, Deidda R et al (2018) Multimodel assessment of climate change-induced hydrologic impacts for a Mediterranean catchment. Hydrol Earth Syst Sci 22:4125–4143. https://doi.org/10.5194/hess-22-4125-2018
Prăvălie R (2016) Drylands extent and environmental issues. A global approach. Earth-Science Rev 161:259–278. https://doi.org/10.1016/j.earscirev.2016.08.003
Prăvălie R, Piticar A, Roșca B et al (2019) Spatio-temporal changes of the climatic water balance in Romania as a response to precipitation and reference evapotranspiration trends during 1961–2013. Catena 172:295–312. https://doi.org/10.1016/j.catena.2018.08.028
Pulido-Velazquez M, Peña-Haro S, García-Prats A et al (2015) Integrated assessment of the impact of climate and land use changes on groundwater quantity and quality in the Mancha Oriental system (Spain). Hydrol Earth Syst Sci 19:1677–1693. https://doi.org/10.5194/hess-19-1677-2015
Qiu J, Shen Z, Chen L, Hou X (2019) Quantifying effects of conservation practices on non-point source pollution in the Miyun Reservoir Watershed, China. Environ Monit Assess 191:1–21. https://doi.org/10.1007/s10661-019-7747-y
Rabelo UP, Costa AC, Dietrich J et al (2022) Impact of dense networks of reservoirs on streamflows at dryland catchments. Sustainability 14:14117. https://doi.org/10.3390/su142114117
Ramos MC, Martínez-Casasnovas JA (2015) Soil water content, runoff and soil loss prediction in a small ungauged agricultural basin in the Mediterranean region using the Soil and Water Assessment Tool. J Agric Sci 153:481–496. https://doi.org/10.1017/S0021859614000422
Ribeiro EP (2016) Mudanças ambientais e desertificação na bacia hidrográfica do rio Pajeú. Universidade Federal de Pernambuco
Rivas-Tabares D, Tarquis AM, De Miguel Á et al (2022) Enhancing LULC scenarios impact assessment in hydrological dynamics using participatory map** protocols in semiarid regions. Sci Total Environ 803:149906. https://doi.org/10.1016/j.scitotenv.2021.149906
Saath KC, Fachinello AL (2018) Crescimento da Demanda Mundial de Alimentos e Restrições do Fator Terra no Brasil. Rev Econ e Sociol Rural 56:195–212. https://doi.org/10.1590/1234-56781806-94790560201
Saha PP, Zeleke K, Hafeez M (2014) Streamflow modeling in a fluctuant climate using SWAT: Yass River catchment in south eastern Australia. Environ Earth Sci 71:5241–5254. https://doi.org/10.1007/s12665-013-2926-6
Santos CAS, Almeida C, Ramos TB et al (2018) Using a hierarchical approach to calibrate SWAT and predict the semi-arid hydrologic regime of northeastern Brazil. Water (Switzerland) 10(9):1137. https://doi.org/10.3390/w10091137
Santos CAS, Rocha FA, Ramos TB et al (2019) Using a hydrologic model to assess the performance of regional climate models in a semi-arid watershed in Brazil. Water (Switzerland) 11(1):170. https://doi.org/10.3390/w11010170
Santos YG, Silva RM, Montenegro SMGL, Santos CAG (2014) Aplicação do modelo SWAT na estimativa da produção de sedimentos na bacia do rio Tapacurá, Pernambuco. In: XI Encontro Nacional de Engenharia de Sedimentos. Associação Brasileira de Recursos Hídricos, João Pessoa, pp 1–19
Sayyad G, Vasel L, Besalatpour AA et al (2015) Modeling blue and green water resources availability in an Iranian data scarce watershed using SWAT. J Water Manag Model. https://doi.org/10.14796/jwmm.c391
Senent-Aparicio J, Pérez-Sánchez J, Carrillo-García J, Soto J (2017) Using SWAT and fuzzy TOPSIS to assess the impact of climate change in the headwaters of the Segura River Basin (SE Spain). Water (Switzerland) 9(2):149. https://doi.org/10.3390/w9020149
Sharma A, Patel PL, Sharma PJ (2022) Influence of climate and land-use changes on the sensitivity of SWAT model parameters and water availability in a semi-arid river basin. Catena 215:106298. https://doi.org/10.1016/j.catena.2022.106298
Shrestha MK, Recknagel F, Frizenschaf J, Meyer W (2016) Assessing SWAT models based on single and multi-site calibration for the simulation of flow and nutrient loads in the semi-arid Onkaparinga catchment in South Australia. Agric Water Manag 175:61–71. https://doi.org/10.1016/j.agwat.2016.02.009
Silva JF, da Silva RM, Santos CA, Silva AM, Vianna PC (2021) Analysis of the response of the Epitácio Pessoa reservoir (Brazilian semiarid region) to potential future drought, water transfer and LULC scenarios. Nat Hazards 108:1347–1371. https://doi.org/10.1007/s11069-021-04736-3
Silva L, dos Santos Cota SD (2019) Derivação de parâmetros para o uso do modelo SWAT na estimativa de recarga subterrânea em um aquifero cárstico- fissural do semiárido brasileiro. Águas Subterrâneas 33:22–33. https://doi.org/10.14295/ras.v33i1.29160
Silva M, de Azevedo PV, da Silva VR, da Nóbrega Silva BK, Mariano EB, Amorim MR (2017) Estimativa da produção de sedimentos na bacia hidrográfica do submédio Rio São Francisco. J Environ Anal Prog 01:1–27. https://doi.org/10.3109/03014460.2014.968618
da Silva VPR, Silva MT, Singh VP et al (2018) Simulation of stream flow and hydrological response to land-cover changes in a tropical river basin. Catena 162:166–176. https://doi.org/10.1016/j.catena.2017.11.024
Silva VDPR, Silva MT, De Souza EP (2016) Influence of land use change on sediment yield: a case study of the sub-middle of the são francisco river basin. Eng Agric 36:1005–1015. https://doi.org/10.1590/1809-4430-Eng.Agric.v36n6p1005-1015/2016
Singh VV, Sharma A, Joshi PC (2015) Modelling of runoff response in a semi-arid coastal watershed using SWAT. Int J Eng Res Appl 5:50–57
Solaymani HR, Gosain AK (2015) Assessment of climate change impacts in a semi-arid watershed in Iran using regional climate models. J Water Clim Chang 6:161–180. https://doi.org/10.2166/wcc.2014.076
Sönmez AY, Kale S (2020) Climate change effects on annual streamflow of filyos river (Turkey). J Water Clim Chang 11:420–433. https://doi.org/10.2166/wcc.2018.060
Sridhar V, Nayak A (2010) Implications of climate-driven variability and trends for the hydrologic assessment of the Reynolds Creek Experimental Watershed, Idaho. J Hydrol 385:183–202. https://doi.org/10.1016/j.jhydrol.2010.02.020
Stratton BT, Sridhar V, Gribb MM et al (2009) Modeling the spatially varying water balance processes in a semiarid mountainous watershed of Idaho. J Am Water Resour Assoc 45:1390–1408. https://doi.org/10.1111/j.1752-1688.2009.00371.x
Stringer LC, Mirzabaev A, Benjaminsen TA et al (2021) Climate change impacts on water security in global drylands. One Earth 4:851–864. https://doi.org/10.1016/j.oneear.2021.05.010
Suliman AHA, Jajarmizadeh M, Harun S, Mat Darus IZ (2015) Comparison of semi-distributed, GIS-based hydrological models for the prediction of streamflow in a large catchment. Water Resour Manag 29:3095–3110. https://doi.org/10.1007/s11269-015-0984-0
Sun L, Yang L, Hao L et al (2017) Hydrological effects of vegetation cover degradation and environmental implications in a semiarid temperate Steppe, China. Sustain 9. https://doi.org/10.3390/su9020281
Taie Semiromi M, Koch M (2020) How do gaining and losing streams react to the combined effects of climate change and pum** in the Gharehsoo River Basin, Iran? Water Resour Res 56:e2019WR025388. https://doi.org/10.1029/2019WR025388
Taie Semiromi M, Koch M (2019) Analysis of spatio-temporal variability of surface–groundwater interactions in the Gharehsoo river basin, Iran, using a coupled SWAT-MODFLOW model. Environ Earth Sci 78:1–21. https://doi.org/10.1007/s12665-019-8206-3
Tan ML, Gassman PW, Srinivasan R et al (2019) A review of SWAT studies in Southeast Asia: applications, challenges and future directions. Water 11:914. https://doi.org/10.3390/w11050914
Tan ML, Gassman PW, Yang X, Haywood J (2020) A review of SWAT applications, performance and future needs for simulation of hydro-climatic extremes, 103f662. Adv Water Resour 143
Tarawneh E, Bridge J, Macdonald N (2016) A pre-calibration approach to select optimum inputs for hydrological models in data-scarce regions. Hydrol Earth Syst Sci 20:4391–4407. https://doi.org/10.5194/hess-20-4391-2016
Uniyal B, Dietrich J (2019) Modifying automatic irrigation in SWAT for plant water stress scheduling. Agric Water Manag 223:105714. https://doi.org/10.1016/j.agwat.2019.105714
Wang H, Sun F, **a J, Liu W (2017) Impact of LUCC on streamflow based on the SWAT model over the Wei River basin on the Loess Plateau in China. Hydrol Earth Syst Sci 21:1929–1945. https://doi.org/10.5194/hess-21-1929-2017
Wang Q, Xu Y, Wang Y et al (2020) Individual and combined impacts of future land-use and climate conditions on extreme hydrological events in a representative basin of the Yangtze River Delta, China. Atmos Res 236:104805. https://doi.org/10.1016/j.atmosres.2019.104805
Wang R, Yuan Y, Yen H et al (2019) A review of pesticide fate and transport simulation at watershed level using SWAT: current status and research concerns. Sci Total Environ 669:512–526
Wang YJ, Meng XY, Liu ZH, Ji XN (2016) Snowmelt runoff analysis under generated climate change scenarios for the Juntanghu River Basin, in **njiang, China. Tecnol y Ciencias del Agua 7:41–54
Wei X, Bailey RT, Tasdighi A (2018) Using the SWAT model in intensively managed irrigated watersheds: model modification and application. J Hydrol Eng 23(10):04018044. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001696
Woldesenbet TA, Elagib NA, Ribbe L, Heinrich J (2018) Catchment response to climate and land use changes in the Upper Blue Nile sub-basins, Ethiopia. Sci Total Environ 644:193–206. https://doi.org/10.1016/j.scitotenv.2018.06.198
Wu F, Zhan J, Su H et al (2015) Scenario-based impact assessment of land use/cover and climate changes on watershed hydrology in Heihe River basin of Northwest China. Adv Meteorol 2015. https://doi.org/10.1155/2015/410198
Wu Y, Liu S, Gallant AL (2012) Predicting impacts of increased CO 2 and climate change on the water cycle and water quality in the semiarid James River Basin of the Midwestern USA. Sci Total Environ 430:150–160. https://doi.org/10.1016/j.scitotenv.2012.04.058
Xu C, Zhao J, Deng H et al (2016) Scenario-based runoff prediction for the Kaidu River basin of the Tianshan Mountains, Northwest China. Environ Earth Sci 75. https://doi.org/10.1007/s12665-016-5930-9
Xu H, Taylor RG, Xu Y (2011) Quantifying uncertainty in the impacts of climate change on river discharge in sub-catchments of the Yangtze and Yellow River Basins, China. Hydrol Earth Syst Sci 15:333–344. https://doi.org/10.5194/hess-15-333-2011
Xu ZP, Li YP, Huang GH et al (2021) A multi-scenario ensemble streamflow forecast method for Amu Darya River Basin under considering climate and land-use changes. J Hydrol 598:126276. https://doi.org/10.1016/j.jhydrol.2021.126276
Xu ZX, Pang JP, Liu CM, Li JY (2009) Assessment of runoff and sediment yield in the Miyun Reservoir catchment by using SWAT model. Hydrol Process 23:3619–3630. https://doi.org/10.1002/hyp.7475
Yang X, Sun W, Li P et al (2019) Integrating agricultural land, water yield and soil conservation trade-offs into spatial land use planning. Ecol Indic 104:219–228. https://doi.org/10.1016/j.ecolind.2019.04.082
Yao X, Cui X, Yu J, Sun W (2015) Response of hydrological processes to climate change in the middle reaches of the Yellow River, China. IAHS-AISH Proc Reports 368:293–298. https://doi.org/10.5194/piahs-368-293-2015
Yimam YT, Ochsner TE, Fox GA (2017) Hydrologic cost-effectiveness ratio favors switchgrass production on marginal croplands over existing grasslands. PLoS One 12:1–19. https://doi.org/10.1371/journal.pone.0181924
Yin Z, Feng Q, Zou S, Yang L (2016) Assessing variation in water balance components in mountainous Inland River Basin experiencing climate change. Water (Switzerland) 8. https://doi.org/10.3390/w8100472
Yonaba R, Biaou AC, Koïta M et al (2021) A dynamic land use/land cover input helps in picturing the Sahelian paradox: assessing variability and attribution of changes in surface runoff in a Sahelian watershed. Sci Total Environ 757:143792. https://doi.org/10.1016/j.scitotenv.2020.143792
Yu D, **e P, Dong X et al (2018) Improvement of the SWAT model for event-based flood simulation on a sub-daily timescale. Hydrol Earth Syst Sci 22:5001–5019. https://doi.org/10.5194/hess-22-5001-2018
Zettam A, Taleb A, Sauvage S et al (2017) Modelling hydrology and sediment transport in a semi-arid and anthropized catchment using the swat model: the case of the Tafna River (Northwest Algeria). Water (Switzerland) 9(3):216. https://doi.org/10.3390/w9030216
Zhang A, Liu W, Yin Z et al (2016) How will climate change affect the water availability in the Heihe River Basin, Northwest China? J Hydrometeorol 17:1517–1542. https://doi.org/10.1175/JHM-D-15-0058.1
Zhang G, Wu Y, Li H et al (2022a) Assessment of water retention variation and risk warning under climate change in an inner headwater basin in the 21st century. J Hydrol 615:128717. https://doi.org/10.1016/j.jhydrol.2022.128717
Zhang L, Karthikeyan R, Zhang H, Tang Y (2017) Estimation of sediment yield change in a loess Plateau basin, China. Water (Switzerland) 9. https://doi.org/10.3390/w9090683
Zhang L, Nan Z, Yu W, Ge Y (2015a) Modeling land-use and land-cover change and hydrological responses under consistent climate change scenarios in the Heihe River Basin, China. Water Resour Manag 29:4701–4717. https://doi.org/10.1007/s11269-015-1085-9
Zhang L, **n Z, Zhang C et al (2022b) Exploring the potential of satellite precipitation after bias correction in streamflow simulation in a semi-arid watershed in northeastern China. J Hydrol Reg Stud 43:101192. https://doi.org/10.1016/j.ejrh.2022.101192
Zhang Y, Qi J, Pan D et al (2022c) Development and testing of a dynamic CO2 input method in SWAT for simulating long-term climate change impacts across various climatic locations. J Hydrol 614:128544. https://doi.org/10.1016/j.jhydrol.2022.128544
Zhang Y, Su F, Hao Z et al (2015b) Impact of projected climate change on the hydrology in the headwaters of the Yellow River basin. Hydrol Process 29:4379–4397. https://doi.org/10.1002/hyp.10497
Zhao Y, Nearing MA, Guertin DP (2022) Modeling hydrologic responses using multi-site and single-site rainfall generators in a semi-arid watershed. Int Soil Water Conserv Res 10:177–187. https://doi.org/10.1016/j.iswcr.2021.09.003
Zuo D, Xu Z, Peng D et al (2015) Simulating spatiotemporal variability of blue and green water resources availability with uncertainty analysis. Hydrol Process 29:1942–1955. https://doi.org/10.1002/hyp.10307
Funding
The authors would like to thank the Fundação de Amparo à Ciência e Tecnologia de Pernambuco [APQ-0215-5.01/10 (TGFS), APQ-1159-1.07/14 (TGFS), APQ-0639-5.01/21 (LSBS) and Project ‘Universitas’ APQ-0300-5.03/17 (AAAM)], the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior [CAPES - Finance Code 001 (AKPR)] and the Conselho Nacional de Desenvolvimento Científico e Tecnológico [309421/2018-7 (TGFS), 152251/2018-9 (TGFS), 402622/2021-9 (TGFS), 309558/2021-2 (TGFS), 308.890/2018-3 (AAAM), and 420.488/2018-9 (AAAM)] for their financial support.
Author information
Authors and Affiliations
Contributions
AKPR: data collection, data interpretation, manuscript preparation, and literature search. LSBS: study design, data collection, statistical analysis, data interpretation, and review. AAAM: review. WMS: review. TGFS: study design, statistical analysis, data interpretation, manuscript preparation, and review.
Corresponding author
Ethics declarations
Ethics approval
Not applicable
Consent to participate
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
Rocha, A.K.P., de Souza, L.S.B., de Assunção Montenegro, A.A. et al. Revisiting the application of the SWAT model in arid and semi-arid regions: a selection from 2009 to 2022. Theor Appl Climatol 154, 7–27 (2023). https://doi.org/10.1007/s00704-023-04546-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00704-023-04546-6