Future Impacts of Climate Change on Actual Evapotranspiration and Soil Water in the Talar Watershed in Mazandran Province

Document Type : Full length article

Authors

1 Assistant Professor of Environmental Sciences and Engineering, Shomal University, Iran

2 Professor of Agriculture and natural Resources, Sari University, Iran

3 Assistant Professor of Agriculture and Natural Resources, Sari University, Iran

4 Associate Professor, Natural Recourses, Tarbiat Modarres University, Iran

5 Professor of Agriculture and Natural Resources, Sari University, Iran

Abstract

Introduction  
Climate change is recognized as a major environmental problem by a majority of the international scientific community. According to the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (IPCC, 2007), “global atmospheric concentrations of carbon dioxide, methane and nitrous oxide have increased markedly as a result of human activities since 1750 and now it exceeded pre-industrial values”. This report further suggests that most of the observed increase in global average temperatures since the mid-twentieth century is very likely resulted from rising anthropogenic greenhouse gas concentrations and that, if not controlled, climate effects such as rising sea level, disruption to weather patterns, and ocean acidification pose serious harms to human health, water supplies, agricultural systems, economic performance, and global security. Such projections have triggered calls for prompt and coordinated action to reduce greenhouse gas emissions and adapt to changes in the climate system. Paying attention to climate change event affecting all sections of hydrologic cycle, the goal of this research is to study these phenomena on actual evapotranspiration and soil humidity that play important role in this cycle, with available water for plant, decrease or increase in annual runoff. This can affect all sections of the environmental factors. 
Materials and methods  
Watershed models are essential for studying hydrologic processes and their responses to both natural and anthropogenic factors, but due to model limitations in representation of complex natural processes and conditions, these models usually must be calibrated prior to application to closely matching with SWAT (Soil and Water Assessment Tool). This is a comprehensive and semi-distributed river basin model that requires a large number of input parameters, which complicates model parameterization and calibration. Several calibration techniques have been developed for SWAT, including manual calibration procedures and automated procedures using the shuffled complex evolution method and other common methods. In SWAT, a basin is delineated into sub-basins, which are then further subdivided into Hydrologic Response Units (HRUs). HRUs consist of homogeneous land use and soil type (also, management characteristics) and based on two options in SWAT, they may either represent different parts of the sub-basin area or a dominant land use or soil type (also, management characteristics). With this semi-distributed (sub-basins) set-up, SWAT is attractive for its computational efficiency as it offers some compromise between the constraints imposed by other model types such as lumped, conceptual or fully distributed, and physically based models. For this goals in the boundary of Talar watersheds of Mazandaran province, we selected 8 stations for precipitation, 5 for temperature and discharge, with Shirgah-Talar station in output. After preparing maps and necessary weather data, we conducted output of SWAT model for this watershed. In this research, we used water year of 2003-2004 until 2006-2007 by a duration of 4 years for calibration and water year of 2008-2009 by duration of 2 years for validation. For calibration and validation of this model, we also used SWAT-CUP package software and SUFI2 program.  
Results and discussion
The entire Talar watershed is divided into 219 Hydrologic Response Unite in 23 sub-watersheds. For assessment of SWAT model from climate change on actual evapotranspiration and available soil water, the SWAT model, further run for this area with new condition. In this stage with definition of HRU for the model, only variated precipitation and temperature are entered into the model to study the influence of these effects on assessment factors in output of the model. To do so, we used variable precipitation and temperature, forecasted by LARS-WG model as one of the important model output for random data of weather condition. After change of daily temperature and precipitation for these stations, variation values enter into SWAT model for second run.
Conclusion
It can be concluded that the mean daily evapotranspiration (to year) in the time of calibration and validation, is increased for all duration and higher evaporation in majority of future   month. This can be compared with present time that is high index evaporation in May, June, July and August. Study about available water shows unregularly process in decrease or increase of this factor and at least available water in May, June, July and August in the future time that affected hydrologic regularity of the watershed. This can provide water for plant in any month where water is necessary as another environmental factor of area. 

Keywords

Main Subjects


آبابایی، ب. و سهرابی، ت. (1388). ارزیابی عملکرد مدل SWATدر حوضة آبریز زاینده‏رود، مجلة پژوهش‏‏‏های حفاظت آب و خاک، 16(3): 41ـ58.
اکبری مجدر، ح.؛ بهره‏مند، ع.؛ نجفی‏نژاد، ع. و احدبردی، ش. (1392). ‏شبیه‏سازی جریان روزانة رودخانة چهل‏چای استان گلستان با مدل SWAT، نشریةپژوهش‏‏‏های حفاظت آ ب و خاک، 20(3): 253ـ259.
ذهبیون، ب.؛ گودرزی، م. و مساح بوانی، ع. (1389) کاربرد مدل SWAT در تخمین رواناب حوضه در دوره‏‏‏های آتی تحت تأثیر تغییر اقلیم، نشریۀ پژوهش‏‏‏های اقلیم‏شناسی، 3: 43ـ58.
سادات آشفته، پ. و مساح بوانی، ع. (1389). تأثیر تغییر اقلیم بر دبی‏‏‏های حداکثر: مطالعة موردی، حوزۀ آیدوغموش، آذربایجان شرقی، مجلة علوم و فنون کشاورزی و منابع طبیعی، علوم آب و خاک، 14(53): 25ـ39.
سلمانی، ح.؛ رستمی خلج، م.؛ محسنی ساروی، م.؛ روحانی، ح. و سلاجقه، ع. (1391). بهینه‏سازی پارامتر‏های مؤثر بر بارش- رواناب در مدل نیمه‏توزیعی SWAT (مطالعة موردی: حوضة آبخیز قزاقلی استان گلستان)، فصل‏نامة علمی‏- پژوهشی اکوسیستم‏های طبیعی ایران، 3(2): 85ـ100.
عارفی اصل، ا.؛ نجفی‏نژاد، ع.؛ کیانی، ف. و سلمان ماهینی، ع. (1392). تعیین مناطق بحرانی تولید رسوب در آب‏خیز چهل‏چای استان گلستان با استفاده از مدل SWAT، نشریةپژوهش‏‏‏های حفاظت آب و خاک، 20(5): 193ـ205.
علیزاده، ا.؛ ایزدی، ع.؛ داوری، ک.؛ ضیایی، ع.ن.؛ اخوان، س. و حمیدی، ز. (1392). برآورد تبخیر- تعرق واقعی در مقیاس سال- حوضه با استفاده از SWAT، نشریةآبیاری و زهکشی ایران، 7(2): 243ـ258.
گزارش طرح تلفیق آبخیزداری حوضة تالار (1380). دفتر مطالعات و ارزیابی آبخیزها، معاونت آبخیزداری وزارت جهاد کشاورزی.
Ababei, B. and Sohrabi, T. (2009). Assessing the performance of SWAT model in Zayandeh Rud Watershed, J. of Water and Soil Conservation, 16(3): 41-58.
Abbaspour, K.C.; Rouholahnejad,B.; 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, Journal of Hydrology, 524: 733-752.
Abbaspour,K.; Faramarzi, M.; Ghasemi, S. and Yang, H. (2009). Assessing the impactof climate change on water resources in Iran, Water Resour. Res., 45(10).
Abbaspour, K.; Schulin, R.; Schlappi, E. and Fluhler, H. (1996). A Bayesian approach for incorporating uncertainty and data worth in environmental projects, Environ. Model. Assess, 1: 151-158.
Akbari Mejdar, H.; Bahremand, A.R.; Najafinejad, A. and Sheikh, V.B. (2013). Assessing the performance of SWAT model in Zayandeh Rud watershed, J. of Water and Soil Conservation ,20(3): 253-259.
Alizadeh, A.; Izady, A.; Davary, K.; Ziaei, A.N.; Akhavan, S. and Hamidi, Z. (2013). Estimation of Actual Evapotranspiration at Regional – Annual scale using SWAT, Iranian Journal of lrrigation and Drainage, 7(2): 243-258.
Andrade, M.A.; Mello, C.R. and Beskow, S. (2013). Hydrological simulation in a watershed with predominance of Oxisol in the Upper Grande river region, MG-Brazil, Rev. Bras. Eng. Agric. Ambient, 17: 69-76 (in Portuguese).
Aragão, R.; Cruz, M.A.S.; Amorim, J.R.A.; Mendonça, L.C.; Figueiredo, E.E. and Srinivasan, V.S. (2013). Sensitivity analysis of the parameters of the SWAT model and simulation of the hydrosedimentological processes in a watershed in the northeastern region of Brazil, Rev. Bras. Ciênc. Solo, 37: 1091-1102 (in Portuguese).
Arefi Asl, A.; Najafinejad, A.; Kiani, F. and Salmanmahiny, A. (2013). Identification of critical sediment production regions yield in Chehelchai watershed using SWAT model, J. of Water and Soil Conservation, 20(5): 193-205.
Arnold, J.G.; Srinivasan, R.; Muttiah, R.S. and Williams, J.R. (1998). Large area hydrologic modeling and assessment, Part I: Model development, J. Am. Water Resour. Assoc, 34(1): 73-89.
Bailey, Ian; Revell, Piers (2015) . Climate Change, International Encyclopedia of the Social & Behavioral Sciences, 2nd edition, Vol. 3, School of Geography, Earth and Environmental Sciences, Plymouth University, Plymouth, UK
Baker, T.J. ; Miller, S.N. (2013). Using the Soil and Water Assessment Tool (SWAT) to assess land use impact on water resources in an East African watershed, J. Hydrol, 486:100-111.
Bastiaanssen, W.G.M.; Pelgrum, H.; Wang, J.; Ma, Y.; Moreno, J.F.; Roerink, G.J. and Van der Val, T. (1998). A remote sensing surface energy balance algorithm for land (SEBAL): 2. Validation, Journal of Hydrology, 213-229.
Brown, L.C; T.O. Barnwell, Jr. (1987). The enhanced water quality models QUAL2E and QUAL2E-UNCAS documentation and user manual.EPA document EPA/600/3-87/007.USEPA. Athens.GA.
Brzozowski, J.; Miatkowski, Z.; Śliwiński, D.; Smarzyńska, K. and Śmietanka, M. (2011). Application of SWATmodel to small agricultural catchment in Poland, J. Water Land Dev, 15: 157-166.
Chen, Ji. and Yiping, Wua (2012). Advancing representation of hydrologic processes in the Soil and WaterAssessment Tool (SWAT) through integration of the Topographic Model (Topmodel) features, Journal of Hydrology, 420-421: 319-328.
Christensen, N.S.; Wood, A.W.; Voisin, N.; Lettenmaier, D.P. and Palmer, R.N. (2004). The effects of climate change on the hydrology and water resources of the Colorado River Basin, Climatic Change, 62(1): 337-363.
Davidson, E.A. and Janssens, I.A. (2006). Temperature sensitivity of soil carbon decomposition and feedbacks to climate change, Nature, 440(7081): 165-173.
Demirel, C.; Mehmet, A; Anabela Venancio, B and Ercan Kahya, C. (2009). Flow forecast by SWAT model and ANN in Pracana basin, Portugal, Advances in Engineering Software, 40: 467-473.
Diabat, M.; Haggerty, R. and Wondzell, S.M. (2013). Diurnal timing of warmer air under climate change affects magnitude, timing and duration of stream temperature change, Hydrol. Process, 27(16): 2367-2378.
Dobler, C.; Bürger, G. and Stötter, J. (2012). Assessment of climate change impacts on flood hazard potential in the Alpine Lech watershed, J. Hydrol, 460-461: 29-39.
Dubrovsky, M. (1996). Validation of the stochastic Weather Generator Met&ROLL, Meteorogickeo Zpravy, 49: 12q-1380.
Durães, F.; Mello, C.R. and Naghettini, M. (2011). Applicability of theSWATmodel for hydrologic simulation in Paraopeba river basin, MG. Cerne, 17: 481-488.
Eum, H. and Simonovic, S.P. (2012). Assessment on variability of extreme climate events for the Upper Thames River basin in Canada, Hydrol. Process, 26(4): 485-499.
Fukunaga D. C. ; Roberto A. C. ;Sidney S. Z, ;Laís T, O,; Marco A, C, C.(2015) Application of the SWAT hydrologic model to a tropical watershed at Brazil ,Catena 125: 206–213.
Wolock, D. and McCabe, G. (1999), Estimates of Runoff Using Water-Balance and Atmospheric
General Circulation Models. Journal of the American Water Resources Association, 35(6):1341-1350.
Hawkins, A; Enrique R.; Vivoni a,; Agustin R,; Giuseppe M, ; Erick ,R; Francina D. (2015) A climate change projection for summer hydrologic conditions in a Gretchen semiarid watershed of central Arizona, Journal of Arid Environments 118 , 9-20
Intergovernmental Panel on Climate Change (IPCC) (2012). Summary for policymakers. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, A Special Report of Working Groups I and II of theIntergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK, and New York, NY, USA, pp. 1-19.
Kite, G.W. and Droogers, P. (2000). Comparing evapotranspiration estimates from satellites hydrological models and field data, Journal of Hydrology, 229: 3-18.
Li , Lu,; Ismaïla D,;Chong ,X,;Frode S.(2015) Hydrological projections under climate change in the near future by RegCM4in Southern Africa using a large-scale hydrological model, Journal of Hydrology S0022,1649(15)00378-9
Milly, P.C.D. (1994). Climate, soil water storage, and the average annual water balance, Water Resources Research, 30: 2143- 2156.
Musaua, J.; Sanga, J.; Gathenyaa, J. and Luedeling, E. (2015). Hydrological responses to climate change inMt, Elgon watersheds, Journal of Hydrology: Regional Studies, Contents lists available at ScienceDirect, Journal of Hydrology: Regional Studies (In Press).
Neitsch, S.L.; Arnold, J.G.; Kiniry, J.R.; King, K.W. and Williams, J.R. (2005). Soil and Water Assessment Tool (SWAT) Theoretical Documentation, Blackland ResearchCenter, Texas Agricultural Experiment Station, Temple, Texas (BRC Report02-05).
Neitsch, S.L.; Arnold, J.G.; Kiniry, J.R.; Srinivasan, R. and Williams, J.R. (2000). Soil and water assessment tool user’s manual – version 2000, Soil and Water Research Laboratory, Agricultural Research Service, Grassland, 808 East Blackland Road, Temple, Texas.
Qiao, L.; Chris B.; Zou, R.; Elaine S.(2015) Calibration of SWAT model for woody plant encroachment using paired experimental watershed data, Journal of Hydrology 523 : 231–239
Sadat Ashofteh, P. and Massah Bovani, A. (2009). Uncertainty of Climate Change Impact on the Flood Regim, Case Study: Aidoghmoush Basin, East Azerbaijan, Iran, Iran-Water Resources Researc, 14(53): 25-39.
Safeeq, M. and Fares, A. (2012). Hydrologic response of a Hawaiian watershed to future climate change scenarios, Hydrol. Process, 26(18): 2745-2764.
Salmani, H.; Rostami Khalaj, M.; Mohseni Saravi, M.; Rohani, H. and Salajeghe, A. (2012). Optimmization of afecte parameter on runoff-precipitatuion in SWAT model(case study in ghazaghely watershed of golestan province), Quarterly Natural Ecosystems of Iran, 3(2): 85-100.
Semenov, M.A. and Brooks, R.J. (1999). Spatial interpolation of the LARSWG stochastic weather generator in great Britain, Climate Research, 11: 137-148.
Singh V.; Niteenkumar B.; Sagar S.; Apurba K.; Sharma,j.(2013) Hydrological stream flow modelling on Tungabhadra catchment: parameterization and uncertainty analysis using SWAT CUP, CURRENT SCIENCE, VOL. 104, NO. 9: 1187-1199.
Talar watershed combining project report (2001). Watershed assessment and study registry, Watershed assistant of Jihade-Agricultural Ministry of Iran.
Task Group on Data and Scenario Support for Impact and Climate Assessment (TGICA) Intergovernmental Panel on Climate Change.June (2007). General Guidelines On The Use Of Scenario Enario Data For Climate IMPACT And Adaptation Assessment Version 2, Prepared by T.R.
Thampi, S.G.; Raneesh, K.Y. and Surya, T.V. (2010). Influence of scale on SWAT model calibration for streamflow in a river basin in the humid tropics, Water Resour. Manag., 24: 4567-4578.
Tian, Y.; Xu, Y.P. and Zhang, X. (2013). Assessment of climate change impacts on river high flows through comparative use of GR4J, HBV and Xinanjiang models, Water Resour. Manage, 27 (8): 2871-2888. in Spain: Water resources, agriculture and land, Journal of Hydrology, 518: 243-249.
Wang, D.; Hejazi, M.; Cai, X. and Valocchi, A.J. (2011). Climate change impact on meteorological, agricultural, and hydrological drought in central Illinois, Water Resour. Res., 47(9).
Wellen C .;George B.;Tanya, L.;Duncan,B.;(2014) Quantifying the uncertainty of nonpoint source attribution in distributed water quality models: A Bayesian assessment of SWAT’s sediment export Predictions ,Journal of Hydrology 519 : 3353–3368
William, J.R. and Hann, R.W. (1972). HYMO, a problem oriented computer language for building computer models, Water Resour.Res., 8(1): 79-85.
Wolock, D. and McCabe, G. (1999). Estimates of Runoff Using Water-Balance and AtmosphericXu, Y.P.; Zhang, X. and Tian, Y. (2012). Impact of climate change on 24-h design rainfall depth estimation in Qiantang River Basin, East China, Hydrol. Process., 26(26): 4067-4077.
Xu, Y.P.; Zhang, X.; Ran, Q. and Tia, Y. (2013). Impact of climate change on hydrology of upper reaches of Qiantang River Basin, East China, Journal of Hydrology, 483: 51-60.
Yang, J.; Reichert, P.; Abbaspour, K.C. and Yang, H. (2007). Hydrological modelling of theChaohe Basin in China: Statistical model formulation and Bayesian inference, Journal of Hydrology, 340: 167-182.
Yeh, William. W.-G. (1986). Review of parameter identification procedures in ground water hydrology: The inverse problem, Water Resour. Res, 22: 95-108.
Yu, Pao-Shan; Tao-Chang, Y. and Chih-Kang, W. (2002). Mpact of climate change on water resources in southern Taiwan, J. Hydrol, 260: 161-175.
Zahbion, B.; Goodarzi, M. and  Massah Bouani, A.R. (2010). Using of SWAT model for assume of runoff in the future duration effecting of climate change, Journal of climate research, 3(4): 43-58.
Zhang ,X.;Yue, X.; Guangtao, F. (2014) Uncertainties in SWAT extreme flow simulation under climate change. Journal of Hydrology. 515, 205–222.