Skip to main content

Advertisement

SpringerLink
Log in

A modified regionalization weighting approach for climate change impact assessment at watershed scale

  • Original Paper
  • Published:
Theoretical and Applied Climatology Aims and scope Submit manuscript

Abstract

This study is conducted to investigate the regional effects of climate change on Zayandeh-Rud River Basin located in the central part of Iran for the both near and far future scenarios. A combination of various general circulation models (GCMs) is used through a weighting approach to generate different climate change patterns including the ideal, medium, and critical patterns. Each of the GCMs has different ability to simulate the baseline climatic parameters in various months and regions of the basin. A new method, namely “modified weighting method based on the actual values” (MWM-AV), also is applied to convert the local effects of climate change to the regional effects. The results showed that the annual temperature of Zayandeh-Rud River Basin would increase by 0.59–1.34 and 1.02–2.53 °C, respectively, in the near and far futures in which maximum increase in seasonal temperature is expected to happen in the summer. Annual precipitation would change by +1.78 to −20.78 % in the near future and −14.35 to −32.82 % in the far future. The maximum decrease in precipitation is observed to be in the winter. The results of temperature and precipitation regionalization showed that the applied method has a good precision in estimating temperature and precipitation in different regions of the desired basin. The eastern part of the basin would have the maximum increase in temperature, while the western part would experience the maximum decrease in precipitation. Overall, the results demonstrated that due to the centralization of the main water uses in the east and the water resources in the west, the Zayandeh-Rud River Basin will face an intensive water shortage under climate change.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  • Almaraz JJ, Mabood F, Zhou XM, Gregorich EG, Smith DL (2008) Climate change, weather variability and corn yield at a higher latitude locale: southwestern Quebec. Climate Change 88:187–197

    Article  Google Scholar 

  • Anwar MR, Liu DL, Macadam I, Kelly G (2013) Adapting agriculture to climate change: a review. Theor Appl Climatol 113:225–245

    Article  Google Scholar 

  • Arnell NW, Gosling SN (2014) The impacts of climate change on river flood risk at the global scale. Clim Chang. doi:10.1007/s10584-014-1084-5

    Google Scholar 

  • Arnell NW, Lloyd-Hughes B (2014) The global-scale impacts of climate change on water resources and flooding under new climate and socio-economic scenarios. Clim Chang 122:127–140

    Article  Google Scholar 

  • Buytaert W, Celleri R, Timbe L (2009). Predicting climate change impacts on water resources in the tropical Andes: effects of GCM uncertainty. Geophysical Research Letters 36

  • Chen FW, Liu CW (2012) Estimation of the spatial rainfall distribution using inverse distance weighting (IDW) in the middle of Taiwan. Paddy Water Environ 10:209–222

    Article  Google Scholar 

  • Cline WR (2007) Global warming and agriculture: impact estimates by country. Center for Global Development and Peterson Institute for International Economics, Washington, DC

    Google Scholar 

  • Collins WD, Bitz CM, Blackmon ML, Bonan GB, Bretherton CS, Carton JA et al (2006) The community climate system model: CCSM3. J Clim 19:2122–2143

    Article  Google Scholar 

  • Connolley WM, Bracegirdle TJ (2007) An antarctic assessment of IPCC AR4 coupled models. Geophys Res Lett. doi:10.1029/2007gl031648, 34

    Google Scholar 

  • Costa AC, Santos JA, Pinto JG (2012) Climate change scenarios for precipitation extremes in Portugal. Theor Appl Climatol 108:217–234

    Article  Google Scholar 

  • Cressie NAC (1993) Statistics for spatial data. Wiley, New York

    Google Scholar 

  • Delworth TL, Broccoli AJ, Rosati A, Stouffer RJ, Balaji V, Beesley JA (2006) GFDL’s CM2 global coupled climate models, part Ι: formulation and simulation characteristics. J Clim 19:643–674

    Article  Google Scholar 

  • Deque M, Dreveton C, Braun A, Cariolle D (1994) The ARPEGE/Ifs atmosphere model: a contribution to French community climate modeling. Clim Dyn 10:249–266

    Article  Google Scholar 

  • Diansky NA, Bagno AV, Zalensny VB (2002) Sigma model of global ocean circulation and its sensitivity to variations in wind stress. Izv Atmos Ocean Phys 38:477–494

    Google Scholar 

  • Dingman SL, Seely-Reynolds DM, Reynolds RC (1988) Application of kriging to estimating mean annual precipitation in a region of orographic influence. Water Resour Bull 24:329–339

    Article  Google Scholar 

  • Dong XH, Bo HJ, Deng X, Su J, Wang X (2009) Rainfall spatial interpolation methods and their applications to Qingjiang River Basin. J China Three Gorges Univ (Nat Sci) 31:6–10

    Google Scholar 

  • Dufresne J-L, Foujols M-A, Denvil S, Caubel A, Marti O, Aumont O, Balkanski Y et al (2013) Climate change projections using the IPSL-CM5 earth system model: from CMIP3 to CMIP5. Clim Dyn 40:2123–2165

    Article  Google Scholar 

  • Elmahdi A, El-Gafy I, Kheireldin K (2008) WBFS model: strategic water and food security planning on national wide level. IGU-2008 Water sustainability commission, Tunis

  • Elmahdi A, Shahkarami N, Morid S, Massah Bavani A (2009) Assessing the impact of AOGCMs uncertainty on the risk of agricultural water demand caused by climate change. In 18th World IMACS/MODSIM Congress, Cairns, Australia

  • Eslamian SS, Gilroy KL, McCuen RH (2011) Climate change detection and modeling in hydrology. Handbook of Climate change research and technology for adaptation and mitigation, InTech press, Rijeka, Croatia, p 87–100

  • Eslamian SS, Gohari SA, Zareian MJ, Firoozfar A (2012) Estimating Penman-Monteith reference evapotranspiration using artificial neural networks and genetic algorithm: a case study. Arab J Sci Eng 37:935–944

    Article  Google Scholar 

  • Frei C, Schar C (1998) A precipitation climatology of the Alps from high-resolution rain-gauge observations. Int J Climatol 18:873–900

    Article  Google Scholar 

  • Ganachaud AS, Sen Gupta A, Orr JC, Wijffels SE, Ridgway KR, Hemer MA, Maes C, Steinberg CR, Tribollet AD, Qiu B, Kruger JC (2011) Observed and expected changes to the tropical Pacific Ocean. In: Bell J, Johnson JE, Hobday AJ (eds) Vulnerability of tropical pacific fisheries and aquaculture to climate change. Secretariat of the Pacific Community, Noumea, pp 115–202

    Google Scholar 

  • Garcia M, Peters-Lidard CD, Goodrich DC (2008) Spatial interpolation of precipitation in a dense gauge network for monsoon storm events in the southwestern United States. Water Resour Res 44:W05S13(1–14)

  • Gohari A, Eslamian S, Abedi-Koupaei J, Massah Bavani A, Wang D, Madani K (2013a) Climate change impacts on crop production in Iran’s Zayandeh-Rud River Basin. Sci Total Environ 442:405–419

    Article  Google Scholar 

  • Gohari A, Eslamian S, Mirchi A, Abedi-Koupaei J, Massah Bavani A, Madani K (2013b) Water transfer as a solution to water shortage: a fix that can backfire. J Hydrol 491:23–39

    Article  Google Scholar 

  • Gohari A, Bozorgi A, Madani K, Elledge J, Berndtsson R (2014a) Adaptation of surface water supply to climate change in Central Iran. J Water Clim Chang. doi:10.2166/wcc.2013.189

    Google Scholar 

  • Gohari A, Madani K, Mirchi A, Massah Bavani A (2014b) System-dynamics approach to evaluate climate change adaptation strategies for Iran’s Zayandeh-Rud water system. World Environmental and Water Resources Congress, Portland, USA, pp 1598–1607

    Google Scholar 

  • Goldblum D (2009) Sensitivity of corn and soybean yield in Illinois to air temperature and precipitation: the potential of future climate change. Phys Geogr 30:27–42

    Article  Google Scholar 

  • Gordon C, Cooper C, Senior CA, Banks H, Gregory JM, Johns TC et al (2000) The simulation of SST, sea ice extents and ocean heat transports in a version of Hadley Center coupled model without flux adjustments. Clim Dyn 16:147–168

    Article  Google Scholar 

  • Gordon H, Rotstayn L, McGregor J, Dix M, Kowalczyk E, OFarrell S, Waterman L, Hirst A, Wilson S, Collier M, Watterson I, Elliott T (2002) The CSIRO MK3 climate system model. CSIRO Mar Atmos Res Tech Rep 60:130

    Google Scholar 

  • Greene AM, Goddard L, Lall L (2006) Probabilistic multi-model regional temperature change projections. J Clim 19:4326–4346

    Article  Google Scholar 

  • Guegan M, Uvo CB, Madani K (2012) Developing a module for estimating climate warming effects on hydropower pricing in California. Energy Policy 42:261–271

    Article  Google Scholar 

  • Guo R, Lin Z, Mo X, Yang C (2010) Responses of crop yield and water use efficiency to climate change in the North China Plain. Agric Water Manag 97:1185–1194

    Article  Google Scholar 

  • Hashmi MZ, Shamseldin AY, Melville BW (2011) Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed. Stoch Env Res Risk A 25:475–484

    Article  Google Scholar 

  • Hasumi H, Emori S (2004) K-1 coupled model (MIROC) description, K-1 technical report no. 1. Center for Climate System Research, University of Tokyo, Japan

  • Hawkins E, Sutton R (2009) The potential to narrow uncertainty in regional climate predictions. Bull Am Meteorol Soc 90:1095–1107

    Article  Google Scholar 

  • Hevesi JA, Istok JD, Flint AL (1992) Precipitation estimation in mountainous terrain using multivariate geostatistics. Part I: structural analysis. J Appl Meteorol 31:661–676

    Article  Google Scholar 

  • IPCC (2007) Climate change 2007: the physical science basis. Contribution of Working Group I to the IPCC Fourth Assessment Report. Cambridge University Press, Cambridge

    Google Scholar 

  • Jamab Consulting Engineering Co (1998) National comprehensive water survey; Zayandeh-Rud River Basin, Iran

  • Jeffrey SJ, Carter JO, Moodie KB, Beswick AR (2001) Using spatial interpolation to construct a comprehensive archive of Australian climate data. Environ Model Softw 16:309–330

    Article  Google Scholar 

  • Jerez S, Montavez JP, Gomez-Navarro JJ, Lorente-Plazas R, Garcia-Valero JA, Jimenez-Guerrero P (2013) A multi-physics ensemble of regional climate change projections over the Iberian Peninsula. Clim Dyn 41:1749–1768

    Article  Google Scholar 

  • Karl TR, Melillo JM, Peterson TC (2009) Global climate change impacts in the United States. Cambridge University Press, New York, 188 pp

    Google Scholar 

  • Kiehl JT, Hack JJ, Bonan GB, Boville BA, Williamson DL, Rasch PJ (1998) The National Center for Atmospheric Research Community Climate model: CCM3. J Clim 11:1131–1149

    Article  Google Scholar 

  • Kloster S, Dentener F, Feichter J, Raes F, Lohmann U, Roeckner E, Fischer-Bruns I (2010) A GCM study of future climate response to aerosol pollution reductions. Clim Dyn 34:1177–1194

    Article  Google Scholar 

  • Kucharik CJ, Serbin SP (2008) Impacts of recent climate change on Wisconsin corn and soybean yield trends. Environ Res Lett 3:034003. doi:10.1088/1748-9326/3/3/034003

    Article  Google Scholar 

  • Kunkel KE, Bromirski PD, Brooks HE et al. (2008) Observed changes in weather and climate extremes. In: Karl TR, Meehl GA, Miller CD, Hassol SJ, Waple AM, Murray WL (eds) Weather and climate extremes in a changing climate. Regions of focus: North America, Hawaii, Caribbean, and U.S. Pacific Islands. A report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. Washington, DC

  • Leclerc G, Schaake JC (1972) Derivation of hydrologic frequency curves, report 142. Massachusetts Institute of Technology, Cambridge

    Google Scholar 

  • Lee JY, Wang B (2014) Future change of global monsoon in the CMIP5. Clim Dyn 42:101–119

    Article  Google Scholar 

  • Lee J, Gryze SD, Six J (2011) Effect of climate change on field crop production in California’s Central Valley. Clim Chang 109:335–353

    Article  Google Scholar 

  • Lehodey P, Senina I, Calmettes B, Hampton J, Nicol S (2013) Modelling the impact of climate change on Pacific skipjack tuna population and fisheries. Clim Chang 119:95–109

    Article  Google Scholar 

  • Levinson DH, Fettig CJ (2014) Climate change: overview of data sources, observed and predicted temperature changes, and impacts on public and environmental health. Global climate change and public health. Springer, New York, pp 31–49

    Google Scholar 

  • Li J, Heap AD (2011) A review of comparative studies of spatial interpolation methods in environmental sciences: performance and impact factors. Ecol Inform 6:228–241

    Article  Google Scholar 

  • Liu J, Fritz S, van Wesenbeeck CFA, Fuchs M, You L, Obersteiner M, Yang H (2008) A spatially explicit assessment of current and future hotspots of hunger in Sub-Saharan Africa in the context of global change. Glob Planet Chang 64:222–235

    Article  Google Scholar 

  • Lizumi T, Yokozawa M, Nishimori M (2009) Parameter estimation and uncertainty analysis of a large-scale crop model for paddy rice: application of a Bayesian approach. Agric For Meteorol 149:333–348

    Article  Google Scholar 

  • Madani K (2005) Watershed management and sustainability—a system dynamics approach (case study: Zayandeh-Rud River Basin, Iran). Thesis (Master). Lund University, Sweden.

  • Madani K, Marino MA (2009) System dynamics analysis for managing Iran’s Zayandeh-Rud River Basin. Water Resour Manag 23:2163–2187

    Article  Google Scholar 

  • Marti O, Braconnot P, Bellier J, Benshila R et al (2005) The new IPSL climate system model: IPSL-CM4. Institut Pierre Simon Laplace, Paris, 84 pp

    Google Scholar 

  • Massah Bavani AR, Morid S (2005) The impacts of climate change on water resources and agricultural production. J Water Resour Res 1:40–47 (In Persian)

    Google Scholar 

  • Masutomi Y, Takahashi K, Matsuoka Y (2009) Impact assessment of climate change on rice production in Asia in comprehensive consideration of process/parameter uncertainty in general circulation models. Agric Ecosyst Environ 131:281–291

    Article  Google Scholar 

  • McFarlane NA, Boer GJ, Blanchet J-P, Lazare M (1992) The Canadian Climate Centre second-generation general circulation model and its equilibrium climate. J Clim 5:1013–1044

    Article  Google Scholar 

  • Moghaddasi M, Araghinejad S, Morid S (2013) Water management of irrigation dams considering climate variation: case study of Zayandeh-Rud reservoir, Iran. Water Resour Manag 27:1651–1660

    Article  Google Scholar 

  • Morid S, Massah Bavani AR (2010) Exploration of potential adaptation strategies to climate change in the Zayandeh Rud irrigation system, Iran. J Irrig Drain Eng-ASCE 59:226–238

    Google Scholar 

  • Osborne T, Rose G, Wheeler T (2013) Variation in the global-scale impacts of climate change on crop productivity due to climate model uncertainty and adaptation. Agric For Meteorol 170:183–194

    Article  Google Scholar 

  • Ozdogan M (2011) Modeling the impacts of climate change on wheat yields in northwestern Turkey. Agric Ecosyst Environ 141:1–12

    Article  Google Scholar 

  • Parry ML, Rosenzweig C, Iglesias A, Livermore M, Fischer G (2004) Effects of climate change on global food production under SRES emissions and socio-economic scenarios. Glob Environ Chang 14:53–67

    Article  Google Scholar 

  • Perdinan, Winkler JA (2014) Selection of climate information for regional climate change assessments using regionalization techniques: an example for the Upper Great Lakes Region. USA Int J Climatol. doi:10.1002/joc.4036

  • Pourmoghaddas H (2006) Water quality and health issues in the Zayandeh Rud basin. Research report presented to the International Water Management Institute, Iran

  • Rajagopalan B, Lall U (1998) Locally weighted polynomial estimation of spatial precipitation. J Geogr Inf Decis Anal 2:44–51

    Google Scholar 

  • Roeckner E, Oberhuber JM, Bacher A, Christoph M, Kirchner I (1996) ENSO variability and atmospheric response in a global coupled atmospheric-ocean GCM. Clim Dyn 12:737–574

    Article  Google Scholar 

  • Roudier P, Sultan B, Quirion P, Berg A (2011) The impact of future climate change on West African crop yields: what does the recent literature say? Global Environ Chang 21:1073–1083

    Article  Google Scholar 

  • Sabade SS, Kulkarni A, Kripalani RH (2011) Projected changes in South Asian summer monsoon by multi-model global warming experiments. Theor Appl Climatol 103:543–565

    Article  Google Scholar 

  • Safavi HR, Esfahani MK, Zamani AR (2014) Integrated index for assessment of vulnerability to drought, case study: Zayandehrood River Basin, Iran. Water Resour Manag 28:1671–1688

    Article  Google Scholar 

  • Salemi HR, Murray-Rust H (2004) An overview of the hydrology of the Zayandeh Rud Basin, Iran. Water Wastewater (Isfahan) 1:2–13

    Google Scholar 

  • Samanta S, Pal DK, Lohar D, Pal B (2012) Interpolation of climate variables and temperature modeling. Theor Appl Climatol 107:35–45

    Article  Google Scholar 

  • Schmidt GA, Ruedy R, Hansen JE, Aleinov I, Bell N, Bauer M et al (2006) Present day atmospheric simulations using GISS ModelE: comparison to in-situ, satellite and reanalysis data. J Clim 19:153–192

    Article  Google Scholar 

  • Segond ML, Neokleous N, Makropoulos C, Onof C, Maksimovic C (2007) Simulation and spatio-temporal disaggregation of multisite rainfall data for urban drainage applications. Hydrol Sci J 52:917–935

    Article  Google Scholar 

  • Semenov MA (2007) Development of high-resolution UKCIP02-based climate change scenarios in the UK. Agric For Meteorol 144:127–138

    Article  Google Scholar 

  • Semenov MA (2008) Simulation of extreme weather events by a stochastic weather generator. Clim Res 35:203–212

    Article  Google Scholar 

  • Semenov MA, Barrow EM (2002) LARS-WG: a stochastic weather generator for use in climate impact studies. Version 3.0 user manual

  • Shibata K, Yoshimura H, Oizumi M, Hosaka M, Sugi M (1999) A simulation of troposphere, stratosphere and mesosphere with an MRI/JMA98 GCM. Pap Meteorol Geophys 50:15–53

    Article  Google Scholar 

  • Strauss F, Formayer H, Schmid E (2013) High resolution climate data for Austria in the period 2008–2040 from a statistical climate change model. Int J Climatol 33:430–443

    Article  Google Scholar 

  • Tanaka HL, Ishizaki N, Nohara D (2005) Intercomparison of the intensities and trends of Hadley, Walker, and Monsoon circulations in the global warming projects. SOLA 1:77–80

    Article  Google Scholar 

  • Tao F, Zhang Z (2010) Adaptation of maize production to climate change in North China Plain: quantify the relative contributions of adaptation options. Eur J Agron 33:103–116

    Article  Google Scholar 

  • Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498

    Article  Google Scholar 

  • Thomson AM, Izaurralde RC, Rosenberg NJ, He X (2006) Climate change impacts on agriculture and soil carbon sequestration potential in the Huang-Hai Plain of China. Agric Ecosyst Environ 114:195–209

    Article  Google Scholar 

  • Tobin C, Nicotina L, Parlange MB, Berne A, Rinaldo A (2011) Improved interpolation of meteorological forcings for hydrologic applications in a Swiss alpine region. J Hydrol 401:77–89

    Article  Google Scholar 

  • Tomczak M (1998) Spatial interpolation and its uncertainty using automated anisotropic inverse distance weighting (IDW) cross-validation/jackknife approach. J Geogr Inf Decis Anal 2:18–30

    Google Scholar 

  • Ueda H, Iwai A, Kuwako K, Hori ME (2006) Impact of anthropogenic forcing on the Asian summer monsoon as simulated by eight GCMs. Geophys Res Lett 33, L06703. doi:10.1029/2005GL025336

    Google Scholar 

  • Vose RS, Easterling DR, Gleason B (2005) Maximum and minimum temperature trends for the globe: an update through 2004. Geophys Res Lett 32, L23822. doi:10.1029/2005GL024379

    Article  Google Scholar 

  • Wang B, Kim HJ, Kikuchi K, Kitoh A (2011) Diagnostic metrics for evaluation of annual and diurnal cycles. Clim Dyn 37:941–955

    Article  Google Scholar 

  • White JW, Hoogenboom G, Kimball BA, Wall GW (2011) Methodologies for simulating impacts of climate change on crop production. Field Crop Res 124:357–368

    Article  Google Scholar 

  • Wolff JO, Maier-Raimer E, Legutke S (1997) The Hamburg ocean primitive equation model. Deutches Klimarechenzentrum Tech. Rep. 13, Hamburg, Germany

  • Wratt D, Revell M, Sinclair M, Gray W, Henderson R, Chater A (2000) Relationships between air mass properties and mesoscale rainfall in New Zealand’s Southern Alps. Atmos Res 52:261–282

    Article  Google Scholar 

  • Xu C-Y, Gong L, Jiang T, Chen D, Singh VP (2006) Analysis of spatial distribution and temporal trend of reference evapotranspiration in Changjiang (Yangtze River) Catchment. J Hydrol 327:81–93

    Article  Google Scholar 

  • Yeh HC, Chen YC, Wei C, Chen RH (2011) Entropy and kriging approach to rainfall network design. Paddy Water Environ 9:343–355

    Article  Google Scholar 

  • You L, Rosegrant MW, Wood S, Sun D (2009) Impact of growing season temperature on wheat productivity in China. Agric For Meteorol 149:1009–1014

    Article  Google Scholar 

  • Yue TX, Zhao N, Ramsey RD, Wang CL, Fan ZM, Chen CF, Lu YM, Li BL (2013) Climate change trend in China, with improved accuracy. Climate Change 120:137–151

    Article  Google Scholar 

  • Zareian MJ, Eslamian S, Hosseinipour EZ (2014) Climate change impacts on reservoir inflow using various weighting approaches. World Environmental and Water Resources Congress, Portland

    Book  Google Scholar 

  • Zayandab Consulting Engineering Co. (2008) Determination of resources and consumptions of water in the Zayandeh-Rud River Basin, Iran

  • Zhang Q, Xu CY, Tao H, Jiang T, Chen YD (2010) Climate changes and their impacts on water resources in the arid regions: a case study of the Tarim River Basin, China. Stoch Env Res Risk A 24:349–358

    Article  Google Scholar 

  • Zhong JJ (2010) A comparative study of spatial interpolation precision of annual average precipitation based on GIS in Xinjiang. Desert Oasis Meteorol 4:51–54

    Google Scholar 

  • Zhu HY, Jia SF (2004) Uncertainty in the spatial interpolation of rainfall data. Prog Geogr 23:34–42

    Google Scholar 

Download references

Acknowledgments

The authors would like to thank Isfahan Regional Water Company for financial support and providing data for this study.

Author information

Authors and Affiliations

  1. Department of Water Engineering, College of Agriculture, Isfahan University of Technology, Isfahan, 84156-83111, Iran

    Mohammad Javad Zareian & Saeid Eslamian

  2. Department of Civil Engineering, Isfahan University of Technology, Isfahan, Iran

    Hamid Reza Safavi

Authors
  1. Mohammad Javad Zareian
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Saeid Eslamian
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hamid Reza Safavi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammad Javad Zareian.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zareian, M.J., Eslamian, S. & Safavi, H.R. A modified regionalization weighting approach for climate change impact assessment at watershed scale. Theor Appl Climatol 122, 497–516 (2015). https://doi.org/10.1007/s00704-014-1307-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-014-1307-8

Keywords

Search

Navigation