Groundwater Management in an Uncommon and Artificial Aquifer Based on Kc Approach and MODIS ET Products for Irrigation Assessment in a Subtropical Island
Abstract
:1. Introduction
2. Methods and Materials
2.1. Site Description
2.2. Meteorological and Remote Sensing Dataset
2.3. Future Climate Change Data
2.4. Flow Chart of the Methodology
2.5. FAO56-Based Sugarcane Evapotranspiration
2.6. Conversion from MOD16A2 and SSEBop ET to Sugarcane ET
2.7. Estimation of Irrigation Water Requirement of Sugarcane
2.8. Water Table and Storage
2.9. Long-Term Water Storage Changes in Response to the Irrigation Requirement
3. Results
3.1. Reliability of Estimated Crop Evapotranspiration
3.2. Influence of Irrigation and Precipitation on Water Table and Storage
3.3. Relation between the Irrigation Water Requirement and Water Storage Changes by Three ET Methods
3.4. Estimating Water Storage Change by Irrigation Requirements and Rechargeable Rainfall
3.5. Crop Irrigation Requirement under Historical Climate
3.6. Risk of Long-Term Groundwater Shortage
3.7. Risk to Future Groundwater Shortage
4. Discussion
4.1. Effectiveness of Artificially Built Aquifer for Irrigation
4.2. Risks of Water Shortage under Future Climate Change
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- FAO. Global Action Programme on Food Security and Nutrition in Small Island Developing States; FAO: Rome, Italy, 2017; 76p. [Google Scholar]
- Bates, B.; Kundzewicz, Z.; Wu, S. Climate Change and Water; Intergovernmental Panel on Climate Change Secretariat: Geneva, Switzerland, 2008. [Google Scholar]
- Gohar, A.A.; Cashman, A.; Ward, F.A. Managing food and water security in Small Island States: New evidence from economic modelling of climate stressed groundwater resources. J. Hydrol. 2019, 569, 239–251. [Google Scholar] [CrossRef]
- Stocker, T. Climate Change 2013: The Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change; Cambridge University Press: Cambridge, UK, 2014. [Google Scholar]
- Bailey, R.T.; Beikmann, A.; Kottermair, M.; Taboroši, D.; Jenson, J.W. Sustainability of rainwater catchment systems for small island communities. J. Hydrol. 2018, 557, 137–146. [Google Scholar] [CrossRef]
- Campisano, A.; D’Amico, G.; Modica, C. Water Saving and Cost Analysis of Large-Scale Implementation of Domestic Rain Water Harvesting in Minor Mediterranean Islands. Water 2017, 9, 916. [Google Scholar] [CrossRef] [Green Version]
- Kourtis, I.M.; Kotsifakis, K.G.; Feloni, E.G.; Baltas, E.A. Sustainable Water Resources Management in Small Greek Islands under Changing Climate. Water 2019, 11, 1694. [Google Scholar] [CrossRef] [Green Version]
- Batisha, A.F. Feasibility and sustainability of fog harvesting. Sustain. Water Qual. Ecol. 2015, 6, 2. [Google Scholar] [CrossRef]
- Tu, Y.; Wang, R.; Zhang, Y.; Wang, J. Progress and Expectation of Atmospheric Water Harvesting. Joule 2018, 2, 1452–1475. [Google Scholar] [CrossRef] [Green Version]
- Elimelech, M.; Phillip, W.A. The Future of Seawater Desalination: Energy, Technology, and the Environment. Science 2011, 333, 712–717. [Google Scholar] [CrossRef] [PubMed]
- Padrón, I.; Avila, D.; Marichal, G.N.; Rodríguez, J.A. Assessment of Hybrid Renewable Energy Systems to supplied energy to Autonomous Desalination Systems in two islands of the Canary Archipelago. Renew. Sust. Energ. Rev. 2019, 101, 221–230. [Google Scholar] [CrossRef]
- Pistocchi, A.; Bleninger, T.; Breyer, C.; Caldera, U.; Dorati, C.; Ganora, D.; Millán, M.M.; Paton, C.; Poullis, D.; Herrero, F.S.; et al. Can seawater desalination be a win-win fix to our water cycle? Water Res. 2020, 182, 115906. [Google Scholar] [CrossRef]
- Gu, H.; Guo, Q.; Lin, P.; Bai, L.; Yang, S.; Sitharam, T.G.; Liu, J. Feasibility Study of Coastal Reservoirs in the Zhoushan Islands, China. J. Coast. Res. 2019, 2019, 835–841. [Google Scholar] [CrossRef]
- Holding, S.; Allen, D.M.; Foster, S.; Hsieh, A.; Larocque, I.; Klassen, J.; Van Pelt, S.C. Groundwater vulnerability on small islands. Nat. Clim. Chang. 2016, 6, 1100. [Google Scholar] [CrossRef]
- Marston, L.; Konar, M.; Cai, X.; Troy, T.J. Virtual groundwater transfers from overexploited aquifers in the United States. Proc. Natl. Acad. Sci. USA 2015, 112, 8561–8566. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ketabchi, H.; Mahmoodzadeh, D.; Ataie-Ashtiani, B.; Werner, A.D.; Simmons, C.T. Sea-level rise impact on fresh groundwater lenses in two-layer small islands. Hydrol. Process. 2014, 28, 5938–5953. [Google Scholar] [CrossRef]
- Underwood, M.R.; Peterson, F.L.; Voss, C.I. Groundwater lens dynamics of Atoll Islands. Water Resour. Res. 1992, 28, 2889–2902. [Google Scholar] [CrossRef]
- Gingerich, S.B.; Voss, C.I.; Johnson, A.G. Seawater-flooding events and impact on freshwater lenses of low-lying islands: Controlling factors, basic management and mitigation. J. Hydrol. 2017, 551, 676–688. [Google Scholar] [CrossRef]
- Bouchet, L.; Thoms, M.C.; Parsons, M. Groundwater as a social-ecological system: A framework for managing groundwater in Pacific Small Island Developing States. Groundw. Sustain. Dev. 2019, 8, 579–589. [Google Scholar] [CrossRef]
- Ishida, S.; Tsuchihara, T.; Yoshimoto, S.; Imaizumi, M. Sustainable use of groundwater with underground dams. Jpn. Agric. Res. Q. 2011, 45, 51–61. [Google Scholar] [CrossRef] [Green Version]
- McMillan, H.K.; Westerberg, I.K.; Krueger, T. Hydrological data uncertainty and its implications. WIREs Water 2018, 5, e1319. [Google Scholar] [CrossRef] [Green Version]
- Fan, J.; Yue, W.; Wu, L.; Zhang, F.; Cai, H.; Wang, X.; Lu, X.; Xiang, Y. Evaluation of SVM, ELM and four tree-based ensemble models for predicting daily reference evapotranspiration using limited meteorological data in different climates of China. Agric. For. Meteorol. 2018, 263, 225–241. [Google Scholar] [CrossRef]
- Machakaire, A.T.B.; Steyn, J.M.; Franke, A.C. Assessing evapotranspiration and crop coefficients of potato in a semi-arid climate using Eddy Covariance techniques. Agric. Water Manag. 2021, 255, 107029. [Google Scholar] [CrossRef]
- Anapalli, S.S.; Fisher, D.K.; Reddy, K.N.; Wagle, P.; Gowda, P.H.; Sui, R. Quantifying soybean evapotranspiration using an eddy covariance approach. Agric. Water Manag. 2018, 209, 228–239. [Google Scholar] [CrossRef]
- Yang, Y.; Anderson, M.; Gao, F.; Xue, J.; Knipper, K.; Hain, C. Improved Daily Evapotranspiration Estimation Using Remotely Sensed Data in a Data Fusion System. Remote Sens. 2022, 14, 1772. [Google Scholar] [CrossRef]
- Anderson, M.C.; Allen, R.G.; Morse, A.; Kustas, W.P. Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources. Remote Sens. Environ. 2012, 122, 50–65. [Google Scholar] [CrossRef]
- Elnmer, A.; Khadr, M.; Kanae, S.; Tawfik, A. Mapping daily and seasonally evapotranspiration using remote sensing techniques over the Nile delta. Agric. Water Manag. 2019, 213, 682–692. [Google Scholar] [CrossRef]
- Allen, R.G.; Pereira, L.S.; Raes, D.; Smith, M. Crop Evapotranspiration—Guidelines for Computing Crop Water Requirements—FAO Irrigation and Drainage Paper 56; FAO: Rome, Itally, 1998; Volume 300, p. D05109. [Google Scholar]
- Fisher, J.B.; Melton, F.; Middleton, E.; Hain, C.; Anderson, M.; Allen, R.; McCabe, M.F.; Hook, S.; Baldocchi, D.; Townsend, P.A.; et al. The future of evapotranspiration: Global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources. Water Resour. Res. 2017, 53, 2618–2626. [Google Scholar] [CrossRef] [Green Version]
- Liu, Y.; Qiu, G.; Zhang, H.; Yang, Y.; Zhang, Y.; Wang, Q.; Zhao, W.; Jia, L.; Ji, X.; Xiong, Y.; et al. Shifting from homogeneous to heterogeneous surfaces in estimating terrestrial evapotranspiration: Review and perspectives. Sci. China Earth Sci. 2022, 65, 197–214. [Google Scholar] [CrossRef]
- Bawa, A.; Senay, G.B.; Kumar, S. Regional crop water use assessment using Landsat-derived evapotranspiration. Hydrol. Process. 2021, 35, e14015. [Google Scholar] [CrossRef]
- Elnashar, A.; Wang, L.; Wu, B.; Zhu, W.; Zeng, H. Synthesis of global actual evapotranspiration from 1982 to 2019. Earth Syst. Sci. Data 2021, 13, 447–480. [Google Scholar] [CrossRef]
- He, M.; Kimball, J.S.; Yi, Y.; Running, S.W.; Guan, K.; Moreno, A.; Wu, X.; Maneta, M. Satellite data-driven modeling of field scale evapotranspiration in croplands using the MOD16 algorithm framework. Remote Sens. Environ. 2019, 230, 111201. [Google Scholar] [CrossRef]
- Zhang, F.; Cai, Y.; Tan, Q.; Wang, X. Spatial water footprint optimization of crop planting: A fuzzy multiobjective optimal approach based on MOD16 evapotranspiration products. Agric. Water Manag. 2021, 256, 107096. [Google Scholar] [CrossRef]
- Sriwongsitanon, N.; Suwawong, T.; Thianpopirug, S.; Williams, J.; Jia, L.; Bastiaanssen, W. Validation of seven global remotely sensed ET products across Thailand using water balance measurements and land use classifications. J. Hydrol. Reg. Stud. 2020, 30, 100709. [Google Scholar] [CrossRef]
- Ishida, S.; Tsuchihara, T.; Imaizumi, M. Fluctuation of NO3-N in groundwater of the reservoir of the Sunagawa Subsurface Dam, Miyako Island, Japan. Paddy Water Environ. 2006, 4, 101–110. [Google Scholar] [CrossRef]
- Noma, Y. Groundwater Development and Conservation in the Ryukyu Limestone Region. J. Groundw. Hydrol. 1992, 34, 163–170. [Google Scholar] [CrossRef] [Green Version]
- Miyakojima City Office. Reports on Groundwater Quality Conservation Monitoring in Miyakojima City; Miyakojima City Office: Miyakojima, Japan, 2014. [Google Scholar]
- Furukawa, H. Quaternary geologic history of the Ryukyu Islands. Bull. Sci. Eng. Div. Univ. Ryukyus Math. Nat. Sci. 1979, 27, 99–161. [Google Scholar]
- Ishida, S.; Kotoku, M.; Abe, E.; Fazal, M.; Tsuchihara, T.; Imaizumi, M. Construction of subsurface dams and their impact on the environment. RMZ Mater. Geoenviron. 2003, 50, 149–152. [Google Scholar]
- Ishida, S.; Yoshimoto, S.; Shirahata, K.; Tsuchihara, T. Distribution of NO3-N in groundwater and groundwater flow in a reservoir area of the Sunagawa underground dam, Miyako Island, Okinawa Prefecture, Japan. J. Groundw. Hydrol. 2015, 57, 515–532. [Google Scholar] [CrossRef] [Green Version]
- Nakanishi, Y. Nitrogen Outflow to Groundwater and its Control in Sub-tropic Islands. J. Jpn. Soc. Soil Phys. 2006, 102, 31–38. [Google Scholar] [CrossRef]
- Kina, K. Actual Condition of Man-made Soils in Okinawa Prefecture. Pedologist 1991, 35, 138–144. [Google Scholar] [CrossRef]
- Mu, Q.; Zhao, M.; Running, S.W.; Moreno, A. Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sens. Environ. 2011, 115, 1781–1800. [Google Scholar] [CrossRef]
- Senay, G.B.; Bohms, S.; Singh, R.K.; Gowda, P.H.; Velpuri, N.M.; Alemu, H.; Verdin, J.P. Operational Evapotranspiration Mapping Using Remote Sensing and Weather Datasets: A New Parameterization for the SSEB Approach. JAWRA J. Am. Water Resour. Assoc. 2013, 49, 577–591. [Google Scholar] [CrossRef] [Green Version]
- Ishizaki, N.N. Bias Corrected Climate Scenarios over Japan Based on CDFDM Method Using CMIP5; Version 202005; Center for Global Environmental Research, NIES: Tsukuba, Japan, 2020. [CrossRef]
- Iizumi, T.; Nishimori, M.; Dairaku, K.; Adachi, S.A.; Yokozawa, M. Evaluation and intercomparison of downscaled daily precipitation indices over Japan in present-day climate: Strengths and weaknesses of dynamical and bias correction-type statistical downscaling methods. J. Geophys. Res. Atmos. 2011, 116, D01111. [Google Scholar] [CrossRef]
- Iizumi, T.; Okada, M.; Yokozawza, M. A meteorological forcing data set for global crop modeling: Development, evaluation, and intercomparison. J. Geophys. Res. Atmos. 2014, 119, 363–384. [Google Scholar] [CrossRef]
- Iizumi, T.; Takayabu, I.; Dairaku, K.; Kusaka, H.; Nishimori, M.; Sakurai, G.; Ishizaki, N.N.; Adachi, S.A.; Semenov, M.A. Future change of daily precipitation indices in Japan: A stochastic weather generator-based bootstrap approach to provide probabilistic climate information. J. Geophys. Res. Atmos. 2012, 117, D11114. [Google Scholar] [CrossRef] [Green Version]
- Iizumi, T.; Takikawa, H.; Hirabayashi, Y.; Hanasaki, N.; Nishimori, M. Contributions of different bias-correction methods and reference meteorological forcing data sets to uncertainty in projected temperature and precipitation extremes. J. Geophys. Res. Atmos. 2017, 122, 7800–7819. [Google Scholar] [CrossRef] [Green Version]
- Wiedenfeld, B.; Enciso, J. Sugarcane Responses to Irrigation and Nitrogen in Semiarid South Texas. Agron. J. 2008, 100, 665–671. [Google Scholar] [CrossRef] [Green Version]
- Inman-Bamber, N.G.; McGlinchey, M.G. Crop coefficients and water-use estimates for sugarcane based on long-term Bowen ratio energy balance measurements. Field Crops Res. 2003, 83, 125–138. [Google Scholar] [CrossRef]
- Abdul Karim, S.N.A.; Ahmed, S.A.; Nischitha, V.; Bhatt, S.; Kiran Raj, S.; Chandrashekarappa, K.N. FAO 56 Model and Remote Sensing for the Estimation of Crop-Water Requirement in Main Branch Canal of the Bhadra Command area, Karnataka State. J. Indian Soc. Remote. Sens. 2013, 41, 883–894. [Google Scholar] [CrossRef]
- Cardoso, G.G.D.G.; Oliveira, R.C.d.; Teixeira, M.B.; Dorneles, M.S.; Domingos, R.M.O.; Megguer, C.A. Sugar cane crop coefficient by the soil water balance method. Afr. J. Agric. Res. 2015, 10, 2407–2414. [Google Scholar] [CrossRef] [Green Version]
- Ferreira, E.; Mannaerts, C.M.; Dantas, A.A.; Maathuis, B.H.P. Surface energy balance system (SEBS) and satellite data for monitoring water consumption of irrigated sugarcane. Eng. Agric. 2016, 36, 1176–1186. [Google Scholar] [CrossRef]
- Kongboon, R.; Sampattagul, S. The water footprint of sugarcane and cassava in northern Thailand. Procedia Soc. Behav. Sci. 2012, 40, 451–460. [Google Scholar] [CrossRef] [Green Version]
- Hossain, M.A.; Ueno, M.; Maeda, K.; Kawamitsu, Y. Potential Evapotranspiration and Crop Coefficient Estimates for Sugarcane in Okinawa. J. Agric. Meteorol. 2005, 60, 573–576. [Google Scholar] [CrossRef]
- Hartmann, A.; Goldscheider, N.; Wagener, T.; Lange, J.; Weiler, M. Karst water resources in a changing world: Review of hydrological modeling approaches. Rev. Geophys. 2014, 52, 218–242. [Google Scholar] [CrossRef]
- Frenken, K. Irrigation Potential in Africa: A Basin Approach; Food & Agriculture Organization: Rome, Italy, 1997; Volume 4. [Google Scholar]
- Pascolini-Campbell, M.; Reager, J.T.; Chandanpurkar, H.A.; Rodell, M. A 10 per cent increase in global land evapotranspiration from 2003 to 2019. Nature 2021, 593, 543–547. [Google Scholar] [CrossRef] [PubMed]
- Chang, Y.; Qin, D.; Ding, Y.; Zhao, Q.; Zhang, S. A modified MOD16 algorithm to estimate evapotranspiration over alpine meadow on the Tibetan Plateau, China. J. Hydrol. 2018, 561, 16–30. [Google Scholar] [CrossRef]
- Yamashiro, S. Studies on some elements concerned with determination of irrigation water for sugarcane in Okinawa (Department of Agricultural Engineering). Sci. Bull. Coll. Agric. Univ. Ryukyus. 1983, 30, 367–488. [Google Scholar]
- Cochand, F.; Brunner, P.; Hunkeler, D.; Rössler, O.; Holzkämper, A. Cross-sphere modelling to evaluate impacts of climate and land management changes on groundwater resources. Sci. Total Environ. 2021, 798, 148759. [Google Scholar] [CrossRef]
- Salem, G.S.A.; Kazama, S.; Shahid, S.; Dey, N.C. Impacts of climate change on groundwater level and irrigation cost in a groundwater dependent irrigated region. Agric. Water Manag. 2018, 208, 33–42. [Google Scholar] [CrossRef]
- Wunsch, A.; Liesch, T.; Broda, S. Deep learning shows declining groundwater levels in Germany until 2100 due to climate change. Nat. Commun. 2022, 13, 1221. [Google Scholar] [CrossRef]
- Imaizumi, M.; Maekawa, T.; Nagata, J.; Tomita, T. Hydrogeological simulation of Miyakojima Island subsurface dam plan. J. Groundw. Hydrol. 1988, 30, 11–23. [Google Scholar] [CrossRef]
- Miyako Office, Okinawa Prefectural Government. Overview of Miyako; Miyako Office, Okinawa Prefectural Government: Miyako, Japan, 2020.
- Taylor, R.G.; Scanlon, B.; Döll, P.; Rodell, M.; van Beek, R.; Wada, Y.; Longuevergne, L.; Leblanc, M.; Famiglietti, J.S.; Edmunds, M.; et al. Ground water and climate change. Nat. Clim. Chang. 2013, 3, 322–329. [Google Scholar] [CrossRef] [Green Version]
- Amanambu, A.C.; Obarein, O.A.; Mossa, J.; Li, L.; Ayeni, S.S.; Balogun, O.; Oyebamiji, A.; Ochege, F.U. Groundwater system and climate change: Present status and future considerations. J. Hydrol. 2020, 589, 125163. [Google Scholar] [CrossRef]
- Condon, L.E.; Atchley, A.L.; Maxwell, R.M. Evapotranspiration depletes groundwater under warming over the contiguous United States. Nat. Commun. 2020, 11, 873. [Google Scholar] [CrossRef] [PubMed]
- Mustafa, S.M.T.; Hasan, M.M.; Saha, A.K.; Rannu, R.P.; Van Uytven, E.; Willems, P.; Huysmans, M. Multi-model approach to quantify groundwater-level prediction uncertainty using an ensemble of global climate models and multiple abstraction scenarios. Hydrol. Earth Syst. Sci. 2019, 23, 2279–2303. [Google Scholar] [CrossRef] [Green Version]
- Okinawa Regional Headquarters, Japan Meteorological Agency. Okinawa Climate Change Monitoring Report; Okinawa Regional Headquarters, Japan Meteorological Agency: Okinawa, Japan, 2021.
- Pour, S.H.; Wahab, A.K.A.; Shahid, S.; Ismail, Z.B. Changes in reference evapotranspiration and its driving factors in peninsular Malaysia. Atmos. Res. 2020, 246, 105096. [Google Scholar] [CrossRef]
- Wang, Z.; Ye, A.; Wang, L.; Liu, K.; Cheng, L. Spatial and temporal characteristics of reference evapotranspiration and its climatic driving factors over China from 1979–2015. Agric. Water Manag. 2019, 213, 1096–1108. [Google Scholar] [CrossRef]
- IPCC. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change; Cambridge University Press: Cambrige, UK, 2021. [Google Scholar]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Yang, Z.; Tang, C.; Bagan, H.; Satake, S.; Orimo, M.; Fukumoto, K.; Wang, G. Groundwater Management in an Uncommon and Artificial Aquifer Based on Kc Approach and MODIS ET Products for Irrigation Assessment in a Subtropical Island. Remote Sens. 2022, 14, 6304. https://doi.org/10.3390/rs14246304
Yang Z, Tang C, Bagan H, Satake S, Orimo M, Fukumoto K, Wang G. Groundwater Management in an Uncommon and Artificial Aquifer Based on Kc Approach and MODIS ET Products for Irrigation Assessment in a Subtropical Island. Remote Sensing. 2022; 14(24):6304. https://doi.org/10.3390/rs14246304
Chicago/Turabian StyleYang, Zhenglun, Changyuan Tang, Hasi Bagan, Shunichi Satake, Madoka Orimo, Koichiro Fukumoto, and Guangwei Wang. 2022. "Groundwater Management in an Uncommon and Artificial Aquifer Based on Kc Approach and MODIS ET Products for Irrigation Assessment in a Subtropical Island" Remote Sensing 14, no. 24: 6304. https://doi.org/10.3390/rs14246304
APA StyleYang, Z., Tang, C., Bagan, H., Satake, S., Orimo, M., Fukumoto, K., & Wang, G. (2022). Groundwater Management in an Uncommon and Artificial Aquifer Based on Kc Approach and MODIS ET Products for Irrigation Assessment in a Subtropical Island. Remote Sensing, 14(24), 6304. https://doi.org/10.3390/rs14246304