Hostname: page-component-55f67697df-twqc4 Total loading time: 0 Render date: 2025-05-11T11:52:21.777Z Has data issue: false hasContentIssue false
  • English
  • Français

Cropping pattern effects on water supply-demand balance in a traditional irrigation network of a semi-arid region of Iran

Published online by Cambridge University Press:  19 March 2025

Sina Mallah Open the ORCID record for Sina Mallah [Opens in a new window] ,
Manouchehr Gorji Anari ,
Mohammad Reza Balali ,
Hossein Asadi ,
Naser Davatgar ,
Hojjat Varmazyari ,
Anna Maria Stellacci  and
Mirko Castellini
Sina Mallah
Affiliation:
Department of Soil Science Engineering, University of Tehran, Karaj, Iran Department of Soil Physics and Irrigation, Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
Manouchehr Gorji Anari*
Affiliation:
Department of Soil Science Engineering, University of Tehran, Karaj, Iran
Mohammad Reza Balali
Affiliation:
Department of Soil Chemistry, Fertility and Plant Nutrition, Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
Hossein Asadi
Affiliation:
Department of Soil Science Engineering, University of Tehran, Karaj, Iran
Naser Davatgar
Affiliation:
Department of Soil Physics and Irrigation, Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
Hojjat Varmazyari
Affiliation:
Department of Agricultural Management and Development, University of Tehran, Karaj, Iran
Anna Maria Stellacci
Affiliation:
Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, Bari, Italy
Mirko Castellini
Affiliation:
Council for Agricultural Research and Economics-Research Center for Agriculture and Environment (CREA-AA), Bari, Italy
*
Corresponding author: Manouchehr Gorji Anari; Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Agriculture, as the largest consumer of freshwater, plays a crucial role in managing limited water resources. However, uncertainties in water supply, particularly in water-scarce regions, hinder further agricultural development. Balancing agricultural development with environmental sustainability is especially demanding in the Karkheh River Basin (KRB), western Iran. Traditional irrigation networks in the upper KRB are inefficient, exacerbated by unregulated water use and over-extraction. This study explores the Water Supply-Demand Balance (WSDB) dynamics under current cropping patterns in the semi-arid Honam sub-basin of the upper KRB. Time-series Landsat imagery and Machine Learning (ML) algorithms classified crop types and estimated major crop cultivation areas during 2019–2021. Regional Crop Water Requirement (ETcreg) and Regional Net Irrigation Requirement (INETreg) estimated the Regional Gross Irrigation Water Demand (GIWDreg), while inflow-outflow analyses determined Surface Irrigation Water Supply (SIWS). The study achieved high crop classification accuracy, facilitating precise water demand estimation across large-scale traditional irrigation networks. Results indicated the highest GIWDreg in 2020 (11.3 × 106 m3/year), driven by increased forage cultivation with crop water requirements (ETc) exceeding 1000 mm. That year also recorded the maximum SIWS (14.8 × 106 m3/year). The Water Scarcity Index (WSI) classified shortages as severe to extreme, indicating WSDB instability due to drought and cropping pattern shifts. This study highlights the necessity for government initiatives promoting water-efficient cropping to align agriculture with water availability. The proposed approach offers practical insights for policymakers seeking to optimize food security while ensuring sustainable water management in traditional irrigation networks, where cropping patterns are difficult to assess.

Keywords

agricultural watercrop water requirementirrigation managementwater scarcitywater supply-demand balance
Type
Climate Change and Agriculture Research Paper
Information
The Journal of Agricultural Science , First View , pp. 1 - 17
Check for updates
Copyright
© The Author(s), 2025. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Ahmad, M-D and Giordano, M (2010) The Karkheh River basin: the food basket of Iran under pressure. Water International 35, 522–544.CrossRefGoogle Scholar
Ahmadi, H, Rostami, N and Dadashi-roudbari, A (2020) Projected climate change in the Karkheh Basin, Iran, based on CORDEX models. Theoretical and Applied Climatology 142, 661–673.CrossRefGoogle Scholar
Akbari, F, Shourian, M and Moridi, A (2022) Assessment of the climate change impacts on the watershed-scale optimal crop pattern using a surface-groundwater interaction hydro-agronomic model. Agricultural Water Management 265, 107508.CrossRefGoogle Scholar
Alizadeh, A and Kamali, GA (2007) Crop Water Requirement in Iran. Mashhad: Astan Ghods Razavi Press.Google Scholar
Allen, RG, Pereira, LS, Raes, D and Smith, M (1998) Crop evapotranspiration guidelines for computing crop requirements. FAO Irrig. Drain. Report modeling and application. Journal of Hydrology 285, 19–40.Google Scholar
Allen, RG, Pereira, LS, Smith, M, Raes, D and Wright, JL (2005) FAO-56 dual crop coefficient method for estimating evaporation from soil and application extensions. Journal of Irrigation and Drainage Engineering 131, 2–13.CrossRefGoogle Scholar
Alsenjar, O, Cetin, M, Aksu, H, Akgul, MA and Golpinar, MS. (2022) Cropping pattern classification using artificial neural networks and evapotranspiration estimation in the Eastern Mediterranean region of Turkey. Tarım Bilimleri Dergisi 29, 677–689.Google Scholar
Amanat, A (2016) Environment and culture: an introduction. Iranian Studies 49, 925–941.CrossRefGoogle Scholar
An, M, Fan, L, Huang, J, Yang, W, Wu, H, Wang, X and Khanal, R (2021) The gap of water supply—demand and its driving factors: from water footprint view in Huaihe River Basin Ed A. Hussain. PloS One 16, e0247604.CrossRefGoogle Scholar
Bai, T, Ji, H, Yang, W, Huang, Q and Liu, X (2022) Study on multi-objective optimal operation of Xiaolangdi Reservoir based on NNIA algorithm. Physics and Chemistry of the Earth, Parts A/B/C 126, 103142.CrossRefGoogle Scholar
Barati, K, Abedi Koupaie, J, Darvishi, E, Azari, A and Yousefi, A (2019) Estimation of net irrigation requirement of the crop pattern in Kermanshah Plain and comparison with the data in the national water document. Journal of Water Research in Agriculture 32, 543–554.Google Scholar
Bazzani, GM (2005) A decision support for an integrated multi-scale analysis of irrigation: DSIRR. Journal of Environmental Management 77, 301–314.CrossRefGoogle ScholarPubMed
Becker, WR, Ló, TB, Johann, JA and Mercante, E (2021a) Statistical features for land use and land cover classification in Google Earth Engine. Remote Sensing Applications: Society and Environment, 21, 100459.CrossRefGoogle Scholar
Becker, WR, Ló, TB, Johann, JA and Mercante, E (2021b) Statistical features for land use and land cover classification in Google Earth Engine. Remote Sensing Applications: Society and Environment 21, 100459.CrossRefGoogle Scholar
Bhagat, V (2014) Agriculture water balance of micro-watershed using GIS techniques. Journal of Earth Science Research 2, 1–12.CrossRefGoogle Scholar
Boithias, L, Acuña, V, Vergoñós, L, Ziv, G, Marcé, R and Sabater, S (2014) Assessment of the water supply:demand ratios in a Mediterranean basin under different global change scenarios and mitigation alternatives. Science of The Total Environment 470–471, 567–577.CrossRefGoogle Scholar
Cetin, M, Alsenjar, O, Aksu, H, Golpinar, MS and Akgul, MA (2023a) Estimation of crop water stress index and leaf area index based on remote sensing data. Water Supply 23, 1390–1404.CrossRefGoogle Scholar
Cetin, M, Alsenjar, O, Aksu, H, Golpinar, MS and Akgul, MA (2023b) Comparing actual evapotranspiration estimations by METRIC to in-situ water balance measurements over an irrigated field in Turkey. Hydrological Sciences Journal 68, 1162–1183.CrossRefGoogle Scholar
Chen, D, Li, J, Yang, X, Zhou, Z, Pan, Y and Li, M (2020b) Quantifying water provision service supply, demand and spatial flow for land use optimization: a case study in the YanHe watershed. Ecosystem Services 43, 101117.CrossRefGoogle Scholar
Chen, X, Li, F, Li, X, Hu, Y and Hu, P (2020a) Evaluating and mapping water supply and demand for sustainable urban ecosystem management in Shenzhen, China. Journal of Cleaner Production 251, 119754.CrossRefGoogle Scholar
Congalton, RG (1991) A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment 37, 35–46.CrossRefGoogle Scholar
Congalton, RG and Green, K (2008) Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, 2nd Edn. Boca Raton, FL: CRC Press.CrossRefGoogle Scholar
Conrad, C, Lamers, JPA, Ibragimov, N, Löw, F and Martius, C (2016) Analysing irrigated crop rotation patterns in arid Uzbekistan by the means of remote sensing: a case study on post-Soviet agricultural land use. Journal of Arid Environments 124, 150–159.CrossRefGoogle Scholar
Dastane, NG (1974) Effective rainfall in irrigated agriculture.Google Scholar
De Pauw, E, Mirghasemi, S, Ghaffari, A and Nseir, B (2008) Agro·ecological Zones of Karkheh River Basin: A Reconnaissance Assessment of Climatic and Edaphic Patterns and Their Similarity to Areas inside and Outside the Basin. Aleppo, Syria: International Center for Agricultural Research in the Dry Areas (ICARDA).Google Scholar
Deng, L, Guo, S, Yin, J, Zeng, Y and Chen, K (2022) Multi-objective optimization of water resources allocation in Han River basin (China) integrating efficiency, equity and sustainability. Scientific Reports 12, 798.CrossRefGoogle Scholar
Dong, J, Fu, Y, Wang, J, Tian, H, Fu, S, Niu, Z, Han, W, Zheng, Y, Huang, J and Yuan, W (2020) Early-season mapping of winter wheat in China based on Landsat and Sentinel images. Earth System Science Data 12, 3081–3095.CrossRefGoogle Scholar
Doungmanee, P (2016) The nexus of agricultural water use and economic development level. Kasetsart Journal of Social Sciences 37, 38–45.CrossRefGoogle Scholar
Dutta, SK, Laing, AM, Kumar, S, Gathala, MK, Singh, AK, Gaydon, DS and Poulton, P (2020) Improved water management practices improve cropping system profitability and smallholder farmers’ incomes. Agricultural Water Management 242, 106411.CrossRefGoogle Scholar
Ebrahimipak, N and Ghalebi, S (2014) Determination of evapotranspiration and crop coefficient (kc) of sugar beet using lysimeter and comparing it with experimental methods in Shahrekord. Journal of Sugar Beet 30, 41–58.Google Scholar
Elsgaard, L, Børgesen, CD, Olesen, JE, Siebert, S, Ewert, F, Peltonen-Sainio, P, Rötter, RP, Skjelvåg, AO (2012) Shifts in comparative advantages for maize, oat and wheat cropping under climate change in Europe. Food Addit Contam Part A Chem Anal Control Expo Risk Assess 29(10), 1514-1526. doi: 10.1080/19440049.2012.700953. Epub 2012 Jul 24. PMID: 22827234.CrossRefGoogle ScholarPubMed
Emami, F and Koch, M (2018) Agricultural water productivity-based hydro-economic modeling for optimal crop pattern and water resources planning in the Zarrine River Basin, Iran, in the wake of climate change. Sustainability 10, 3953.CrossRefGoogle Scholar
European Commission. (2012) Report on the Review of the European Water Scarcity and Droughts Policy. Luxembourg City: European Commission.Google Scholar
FAO. (1992) CROPWAT: A Computer Program for Irrigation Planning and Management. Rome: FAO.Google Scholar
FAO. (2009) CropWat 8.0. Rome: FAO.Google Scholar
Farshi, A, Shariati, M, JaroLlahi, R, Ghaemi, M, Shahabifar, M and Tavallaei, M (1997) An Estimate of Water Requirement of Main Field Crops and Orchards in Iran. Karaj, Iran: Ministry of Agriculture, Agricultural and Natural Resource Organization, Water and Soil Research Institute Press.Google Scholar
Fernando, WAM and Senanayake, IP (2023) Developing a two-decadal time-record of rice field maps using Landsat-derived multi-index image collections with a random forest classifier: a Google Earth Engine based approach. Information Processing in Agriculture 11, 260–275.CrossRefGoogle Scholar
Ghafouri, M, Siadat, H and Oweis, T (2012) Integrated Watershed Management in the Upper Catchments of Karkheh River Basin of Iran. Aleppo, Syrian Arab Republic: Agricultural Research, Education and Extension Organization (AREEO).Google Scholar
Gong, X, Zhang, H, Ren, C, Sun, D and Yang, J (2020) Optimization allocation of irrigation water resources based on crop water requirement under considering effective precipitation and uncertainty. Agricultural Water Management 239, 106264.CrossRefGoogle Scholar
Gorelick, N, Hancher, M, Dixon, M, Ilyushchenko, S, Thau, D and Moore, R (2017) Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sensing of Environment 202, 18–27.CrossRefGoogle Scholar
Gu, Z, Qi, Z, Burghate, R, Yuan, S, Jiao, X and Xu, J (2020) Irrigation scheduling approaches and applications: a review. Journal of Irrigation and Drainage Engineering 146, 04020007.CrossRefGoogle Scholar
Guo, Y and Shen, Y (2016) Agricultural water supply/demand changes under projected future climate change in the arid region of northwestern China. Journal of Hydrology 540, 257–273.CrossRefGoogle Scholar
Hanasaki, N, Yoshikawa, S, Pokhrel, Y and Kanae, S (2018) A quantitative investigation of the thresholds for two conventional water scarcity indicators using a state-of-the-art global hydrological model with human activities. Water Resources Research 54, 8279–8294.CrossRefGoogle Scholar
Hatamkhani, A and Moridi, A (2021) Optimal development of agricultural sectors in the basin based on economic efficiency and social equality. Water Resources Management 35, 917–932.CrossRefGoogle Scholar
Hoekstra, AY (2014) Water scarcity challenges to business. Nature Climate Change 4, 318–320.CrossRefGoogle Scholar
Huang, J, Li, Y, Fu, C, Chen, F, Fu, Q, Dai, A, Shinoda, M, Ma, Z, Guo, W, Li, Z, Zhang, L, Liu, Y, Yu, H, He, Y, Xie, Y, Guan, X, Ji, M, Lin, L, Wang, S, Yan, H and Wang, G (2017) Dryland climate change: recent progress and challenges. Reviews of Geophysics 55, 719–778.CrossRefGoogle Scholar
Iman, RL (2008) Latin Hypercube Sampling. Hoboken, NJ: John Wiley & Sons, Ltd.CrossRefGoogle Scholar
Jadczyszyn, J, Niedźwiecki, J and Debaene, G (2017) Analysis of agronomic categories in different soil texture classification systems. Polish Journal of Soil Science 49, 61.CrossRefGoogle Scholar
Jin, Y, Liu, X, Chen, Y and Liang, X (2018) Land-cover mapping using random forest classification and incorporating NDVI time-series and texture: a case study of central Shandong. International Journal of Remote Sensing 39, 8703–8723.CrossRefGoogle Scholar
Kelley, LC, Pitcher, L and Bacon, C (2018) Using google earth engine to map complex shade-grown coffee landscapes in Northern Nicaragua. Remote Sensing 10, 952.CrossRefGoogle Scholar
Khaydar, D, Chen, X, Huang, Y, Ilkhom, M, Liu, T, Friday, O, Farkhod, A, Khusen, G and Gulkaiyr, O (2021) Investigation of crop evapotranspiration and irrigation water requirement in the lower Amu Darya River Basin, Central Asia. Journal of Arid Land 13, 23–39.CrossRefGoogle Scholar
KhazaiPoul, A, Moridi, A and Yazdi, J (2019) Multi-objective optimization for interactive reservoir-irrigation planning considering environmental issues by using parallel processes technique. Water Resources Management 33, 5137–5151.CrossRefGoogle Scholar
Landis, JR and Koch, GG (1977) The measurement of observer agreement for categorical data. Biometrics 33, 159–174.CrossRefGoogle ScholarPubMed
Lashkari, H, Keikhosravi, G and Rezaei, A (2009) The Analysis of the CROPWAT model efficiecy estimating water requirement of wheat in the west of Kermanshah, townships of the Islamabad Gharb, Sarpol Zahab and Ravansar. The Journal of Spatial Planning 13, 247–270.Google Scholar
Lehecka, GV and Lehecka, GV (2014) The value of USDA crop progress and condition information: Reactions of corn and soybean futures markets. Journal of Agricultural and Resource Economics 39, 88–105.Google Scholar
Li, T, Yang, S and Tan, M (2019) Simulation and optimization of water supply and demand balance in Shenzhen: a system dynamics approach. Journal of Cleaner Production 207, 882–893.CrossRefGoogle Scholar
Liu, H, Gong, P, Wang, J, Clinton, N, Bai, Y and Liang, S (2020) Annual dynamics of global land cover and its long-term changes from 1982 to 2015. Earth System Science Data 12, 1217–1243.CrossRefGoogle Scholar
Liu, W, Liu, X, Yang, H, Ciais, P and Wada, Y (2022b) Global water scarcity assessment incorporating green water in crop production. Water Resources Research 58, e2020WR028570.CrossRefGoogle Scholar
Liu, X, Liu, W, Tang, Q, Liu, B, Wada, Y and Yang, H (2022a) Global agricultural water scarcity assessment incorporating blue and green water availability under future climate change. Earth’s Future 10, e2021EF002567.CrossRefGoogle Scholar
Magidi, J, Nhamo, L, Mpandeli, S and Mabhaudhi, T (2021) Application of the random forest classifier to map irrigated areas using google earth engine. Remote Sensing 13, 876.CrossRefGoogle ScholarPubMed
Mallah, S, Gorji, M, Balali, MR, Asadi, H, Davatgar, N, Varmazyari, H, Stellacci, AM and Castellini, M (2023) Deep insight on land use/land cover geospatial assessment through internet-based validation tool in Upper Karkheh River Basin (KRB), West, Iran. Land 12, 979.CrossRefGoogle Scholar
Maxwell, AE, Strager, MP, Warner, TA, Ramezan, CA, Morgan, AN and Pauley, CE (2019) Large-area, high spatial resolution land cover mapping using random forests, GEOBIA, and NAIP orthophotography: findings and recommendations. Remote Sensing 11, 1409.CrossRefGoogle Scholar
Mohammadian, R (2019) Management package to reduce irrigation water and increase water use productivity in sugar beet cultivation. Journal of Water Management in Agriculture 6, 103–114.Google Scholar
Monsef, H, Naghashzadegan, M, Jamali, A and Farmani, R (2019) Comparison of evolutionary multi objective optimization algorithms in optimum design of water distribution network. Ain Shams Engineering Journal 10, 103–111.CrossRefGoogle Scholar
Nath, R, Luo, Y, Chen, W and Cui, X (2018) On the contribution of internal variability and external forcing factors to the cooling trend over the humid subtropical Indo-Gangetic Plain in India. Scientific Reports 8, 18047.CrossRefGoogle Scholar
Nikoo, MR, Karimi, A, Kerachian, R and Gavahi, K (2019) Optimum operation of reservoirs in the Karkheh Basin in Iran considering impacts of non-integrated development and climate change. Iranian Journal of Science and Technology, Transactions of Civil Engineering 43, 37–47.CrossRefGoogle Scholar
Nouri, M (2023) Drought assessment using gridded data sources in data-poor areas with different aridity conditions. Water Resources Management 37, 4327–4343.CrossRefGoogle Scholar
Parraguez-Vergara, E, Contreras, B, Clavijo, N, Villegas, V, Paucar, N and Ther, F (2018) Does indigenous and campesino traditional agriculture have anything to contribute to food sovereignty in Latin America? Evidence from Chile, Peru, Ecuador, Colombia, Guatemala and Mexico. International Journal of Agricultural Sustainability 16, 326–341.CrossRefGoogle Scholar
Pedro-Monzonís, M, Solera, A, Ferrer, J, Estrela, T and Paredes-Arquiola, J (2015) A review of water scarcity and drought indexes in water resources planning and management. Journal of Hydrology 527, 482–493.CrossRefGoogle Scholar
Phan, TN, Kuch, V and Lehnert, LW (2020) Land cover classification using google earth engine and random forest classifier—the role of image composition. Remote Sensing 12, 2411.CrossRefGoogle Scholar
Qiu, B, Luo, Y, Tang, Z, Chen, C, Lu, D, Huang, H, Chen, Y, Chen, N and Xu, W (2017) Winter wheat mapping combining variations before and after estimated heading dates. Journal of Photogrammetry and Remote Sensing 123, 35–46.CrossRefGoogle Scholar
Rahimi, J, Khalili, A and Bazrafshan, J (2014) Estimation of effective precipitation for winter wheat in different regions of Iran using an extended soil-water balance model. Desert 19, 91–98.Google Scholar
Ren, T, Xu, H, Cai, X, Yu, S and Qi, J (2022) Smallholder crop type mapping and rotation monitoring in mountainous areas with Sentinel-1/2 imagery. Remote Sensing 14, 566.CrossRefGoogle Scholar
Saatsaz, M (2020) A historical investigation on water resources management in Iran. Environment, Development and Sustainability 22, 1749–1785.CrossRefGoogle Scholar
Schewe, J, Heinke, J, Gerten, D, Haddeland, I, Arnell, NW, Clark, DB, Dankers, R, Eisner, S, Fekete, BM, Colón-González, FJ, Gosling, SN, Kim, H, Liu, X, Masaki, Y, Portmann, FT, Satoh, Y, Stacke, T, Tang, Q, Wada, Y, Wisser, D, Albrecht, T, Frieler, K, Piontek, F, Warszawski, L and Kabat, P (2014) Multimodel assessment of water scarcity under climate change. Proceedings of the National Academy of Sciences 111, 3245–3250.CrossRefGoogle ScholarPubMed
Schieder, T-M (2011) Analysis of Water Use and Crop Allocation for the Khorezm Region in Uzbekistan using an Integrated Hydrologic-Economic Model. Bonn: University of Bonn.Google Scholar
Sun, G, McNulty, SG, Moore Myers, JA and Cohen, EC (2008) Impacts of multiple stresses on water demand and supply across the Southeastern United States. JAWRA Journal of the American Water Resources Association 44, 1441–1457.CrossRefGoogle Scholar
Sun, SK, Wu, PT, Wang, YB and Zhao, XN (2015) Impact of changing cropping pattern on the regional agricultural water productivity. The Journal of Agricultural Science 153, 767–778.CrossRefGoogle Scholar
Syrbe, R-U and Walz, U (2012) Spatial indicators for the assessment of ecosystem services: providing, benefiting and connecting areas and landscape metrics. Ecological Indicators 21, 80–88.CrossRefGoogle Scholar
Tabari, MMR, Eilbeigi, M and Chitsazan, M (2022) Multi-objective optimal model for sustainable management of groundwater resources in an arid and semiarid area using a coupled optimization-simulation modeling. Environmental Science and Pollution Research 29, 22179–22202.CrossRefGoogle Scholar
Teluguntla, P, Thenkabail, PS, Oliphant, A, Xiong, J, Gumma, MK, Congalton, RG, Yadav, K and Huete, A (2018) A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform. ISPRS Journal of Photogrammetry and Remote Sensing 144, 325–340.CrossRefGoogle Scholar
Thomlinson, JR, Bolstad, PV and Cohen, WB (1999) Coordinating methodologies for scaling landcover classifications from site-specific to global. Remote Sensing of Environment 70, 16–28.CrossRefGoogle Scholar
Tian, H, Huang, N, Niu, Z, Qin, Y, Pei, J and Wang, J (2019) Mapping winter crops in China with multi-source satellite imagery and phenology-based algorithm. Remote Sensing 11, 820.CrossRefGoogle Scholar
Topcu, S (2011) Water for agriculture: a major and inefficient consumer. In Turkey’s Water Policy. Berlin, Heidelberg: Springer, pp. 93–115.CrossRefGoogle Scholar
Trigo, RM, Gouveia, CM and Barriopedro, D (2010) The intense 2007–2009 drought in the fertile crescent: impacts and associated atmospheric circulation. Agricultural and Forest Meteorology 150, 1245–1257.CrossRefGoogle Scholar
Tsendbazar, N, Li, L, Koopman, M, Carter, S, Herold, M, Georgieva, I and Lesiv, M (2021) World Cover Product Validation Report. V1.1. Paris, France: European Space Agency.Google Scholar
USDA (1970) Irrigation water requirements. In United States Department of Agriculture, Soil Conservation Service, Technical Release. Washington DC: USDA.Google Scholar
Veysi, S, Galehban, E, Nouri, M, Mallah, S and Nouri, H (2024) Comprehensive framework for interpretation of WaPOR water productivity. Heliyon 10, e36350.CrossRefGoogle ScholarPubMed
Wang, Z, Huang, Y, Liu, T, Zan, C, Ling, Y and Guo, C (2022) Analysis of the water demand-supply gap and scarcity index in Lower Amu Darya River Basin, Central Asia. International Journal of Environmental Research and Public Health 19, 743.CrossRefGoogle ScholarPubMed
Wu, Z and Suo, L (2004) Advance about study of water resources optimal distribution. Journal of Irrigation and Drainage Engineering 23, 1–5.Google Scholar
Yao, H, Dong, Z, Li, D, Ni, X, Chen, T, Chen, M, Jia, W and Huang, X (2022) Long-term optimal reservoir operation with tuning on large-scale multi-objective optimization: case study of cascade reservoirs in the Upper Yellow River Basin. Journal of Hydrology: Regional Studies 40, 101000.Google Scholar
Yin, Z, Wu, J, Song, J, Yang, Y, Zhu, X and Wu, J (2022) Multi-objective optimization-based reactive nitrogen transport modeling for the water-environment-agriculture nexus in a basin-scale coastal aquifer. Water Research 212, 118111.CrossRefGoogle Scholar
Yoosefdoost, I, Basirifard, M, Álvarez-García, J and del Río-Rama, MC (2022) Increasing agricultural resilience through combined supply and demand management (Case Study: Karaj Reservoir Dam, Iran). Agronomy 12, 1997.CrossRefGoogle Scholar
You, N, Dong, J, Huang, J, Du, G, Zhang, G, He, Y, Yang, T, Di, Y and Xiao, X (2021) The 10-m crop type maps in Northeast China during 2017–2019. Scientific Data 8, 41.CrossRefGoogle ScholarPubMed
Yousaf, W, Awan, WK, Kamran, M, Ahmad, SR, Bodla, HU, Riaz, M, Umar, M and Chohan, K (2021) A paradigm of GIS and remote sensing for crop water deficit assessment in near real time to improve irrigation distribution plan. Agricultural Water Management 243, 106443.CrossRefGoogle Scholar
Yousefi, H and Moridi, A (2022) Multiobjective optimization of agricultural planning considering climate change impacts: Minab reservoir upstream watershed in Iran. Journal of Irrigation and Drainage Engineering 148, 04022007.CrossRefGoogle Scholar
Zanaga, D, Van De Kerchove, R, De Keersmaecker, W, Souverijns, N, Brockmann, C, Quast, R, Wevers, J, Grosu, A, Paccini, A, Vergnaud, S, Cartus, O, Santoro, M, Fritz, S, Georgieva, I, Lesiv, M, Carter, S, Herold, M, Linlin, L, Tsendbazar, N, Raimoino, F and Arino, O (2021) ESA WorldCover 10 m 2020 v100, https://zenodo.org/record/5571936#.YrV38HZByUk.Google Scholar
Zaredar, N, Jozi, SA, Khorssani, N and Shariat, SM (2021) Climate-induced changing environment in semidry lands: a statistical-based simulation approach in Qarasou Sub-basin of Karkheh River Basin. Environment, Development and Sustainability 23, 10416–10431.CrossRefGoogle Scholar
Zarepour Moshizi, M, Yousefi, A, Amini, AM and Shojaei, P (2022) Rural vulnerability to water scarcity in Iran: an integrative methodology for evaluating exposure, sensitivity and adaptive capacity. GeoJournal 88, 2121–2136.CrossRefGoogle ScholarPubMed
Zhang, H, Du, H, Zhang, C and Zhang, L (2021) An automated early-season method to map winter wheat using time-series Sentinel-2 data: a case study of Shandong, China. Computers and Electronics in Agriculture 182, 105962.CrossRefGoogle Scholar
Zhang, K, Zhang, Y, Xi, S, Liu, J, Li, J, Hou, S and Chen, B (2022) Multi-objective optimization of energy-water nexus from spatial resource reallocation perspective in China. Applied Energy 314, 118919.CrossRefGoogle Scholar
Zhao, Z, Islam, F, Waseem, LA, Tariq, A, Nawaz, M, Islam, IU, Bibi, T, Rehman, NU, Ahmad, W, Aslam, RW, Raza, D and Hatamleh, WA (2024) Comparison of three machine learning algorithms using google earth engine for land use land cover classification. Rangeland Ecology & Management 92, 129–137.CrossRefGoogle Scholar
Zhou, L, Sun, D and Xu, J (2015) Zoning assessment of water environmental supporting capacity for socioeconomic development in the Huaihe River Basin, China. Journal of Geographical Sciences 25, 1199–1217.CrossRefGoogle Scholar
Zuo, Q, Zhao, H and Ma, J (2014) Study on harmony equilibrium between water resources and economic society development. Journal of Hydraulic Engineering 45, 785–792.Google Scholar
Supplementary material: File

Mallah et al. supplementary material 1

Mallah et al. supplementary material
Download Mallah et al. supplementary material 1(File)
File 18.9 MB
Supplementary material: File

Mallah et al. supplementary material 2

Mallah et al. supplementary material
Download Mallah et al. supplementary material 2(File)
File 14.9 KB