Climate impact assessment to the groundwater levels based on long time-series analysis in a paddy field area (Piedmont region, NW Italy): preliminary results
https://doi.org/10.7343/as-2022-576
Accepted: 1 August 2022
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The analysis of the time-series of groundwater level are extremely important to observe the behaviours of groundwater over time and to identify any critical situations. The studied area is an agricultural district characterised by paddy fields, located in the eastern part of Piedmont, on the border with Lombardy. In this area long time-series of groundwater level, starting from the 1960s, have been collected in 16 wells. Water table data have a good completeness (in the majority of the cases >90%). Firstly, the groundwater hydrodynamic behaviour, based on water table levels, was investigated to highlight the response of groundwater to the recharge. A basic statistical analysis was performed (mean, median, standard deviation, maximum, minima), and then trends of water table levels were evaluated in order to better observe the long-term behaviour of groundwater. These analyses allowed to observe a groundwater hydrodynamic behaviour characterised by a repeating annual pattern (minimum in February/March and maximum in August/September) in correspondence to the period of irrigation. Moreover, trend analysis highlighted the presence of both wells with a decreasing water table (with maximum lowering of 4.3 m in 60 years) and wells with an increasing water table (with maximum rises of 2.8 m in 35 years). Furthermore, in most cases, it can be observed that all three trends analysed agree on being positive or negative. Future insights will be the comparison of these long time-series with the meteorological data, and the investigation of other factors (e.g. anthropic withdrawal, variations of cultivation practices and irrigation, geology of the subsoil) to better understand the causes of the water table fluctuations and trends.
Accesso ai dati “Annali meteorologici ed idrologici” Banca dati meteorologica [WWW Document], 2021. URL https://www.arpa.piemonte.it/rischinaturali/accesso-ai-dati/annali_meteoidrologici/annali-meteo-idro/banca-dati-meteorologica.html (last accessed 6.14.21).
Allen DM, Mackie DC, Wei M (2004) Groundwater and climate change: a sensitivity analysis for the Grand Forks aquifer, southern British Columbia, Canada. Hydrogeol. J. 21.
Alley W, Furey S, Klingbeil R, Shivakoti BR, Kabede S, Hirata R (2017) The UN-SDGs for 2030: Essential Indicators For Groundwater 8 pages.
Alley WM (2001) Ground Water and Climate. Ground Water 39, 161.
Arnell NW (1998) Climate Change and Water Resources in Britain. Clim Chang 39, 83–110.
Arpa Piemonte (2021) Arpa Piemonte - Home Page [WWW Document]. URL http://rsaonline.arpa.piemonte.it/meteoclima50/clima_ed_indicatori.htm (accessed 7.7.21).
Bastiancich L, Lasagna M, Mancini S, Falco M, De Luca DA (2021) Temperature and discharge variations in natural mineral water springs due to climate variability: a case study in the Piedmont Alps (NW Italy). Environ. Geochem. Health. https://doi.org/10.1007/s10653-021-00864-8
Beretta GP (2021) Groundwater and climate change. Acque Sotter. - Ital. J. Groundw. 10, 5–6. https://doi.org/10.7343/as-2021-532
Cassardo C, Cremonini R, Gandini D, Paesano G, Pelosini R, Qian MW (2000) Analysis of the severe flood of 13-16th October 2000 in Piedmont (Italy) 16.
Castagna SED, De Luca DA, Lasagna M (2015) Eutrophication of Piedmont Quarry Lakes (North-Western Italy): Hydrogeological Factors, Evaluation of Trophic Levels and Management Strategies. J. Environ. Assess. Policy Manag. 17, 1550036. https://doi.org/10.1142/S1464333215500362
Colombani N, Giambastiani BMS, Mastrocicco M (2016) Use of shallow groundwater temperature profiles to infer climate and land use change: interpretation and measurement challenges. Hydrol. Process. 30, 2512–2524. https://doi.org/10.1002/hyp.10805
De Luca DA, Lasagna M, Debernardi L (2020) Hydrogeology of the western Po plain (Piedmont, NW Italy). J. Maps 16, 265–273. https://doi.org/10.1080/17445647.2020.1738280
Debernardi L, De Luca DA, Lasagna M (2008) Correlation between nitrate concentration in groundwater and parameters affecting aquifer intrinsic vulnerability. Environ. Geol. 55, 539–558. https://doi.org/10.1007/s00254-007-1006-1
Est Sesia – Consorzio di irrigazione e bonifica “Irrigation and land reclamation consortium” (2022) URL https://www.estsesia.it/ (accessed 7.19.22).
Franzke CLE, Ciullo A, Gilmore EA, Matias DM, Nagabhatla N, Orlov A, Paterson SK, Scheffran J, Sillmann J (2022) Perspectives on tipping points in integrated models of the natural and human Earth system: cascading effects and telecoupling. Environ. Res. Lett. 17, 015004. https://doi.org/10.1088/1748-9326/ac42fd
Helsel DR, Hirsch RM, Ryberg KR, Archfield SA, Gilroy EJ (2020) Statistical methods in water resources (Report No. 4-A3), Techniques and Methods. Reston, VA. https://doi.org/10.3133/tm4A3
Irace A, Clemente P, Natalicchio M, Ossella L, Trenkwalder S, De Luca DA, Mosca P, Piana F, Polino R, Violanti D (2009) Geologia e idrostratigrafia profonda della Pianura Padana occidentale (Regione Piemonte) “Geology and deep hydrostratigraphy of the west Piedmon Plain (Piedmont Region)”. La NuovaLito.
Joshi E, Kumar D, Lal B, Nepalia V, Gautam P, Vyas AK (2013) Management of direct seeded rice for enhanced resource-use efficiency. Plant Knowledge Journal 2, 119–134.
Kendall MG (1955) Rank Correlation Measures. Charles Griffin, London 202
Lasagna M, Ducci D, Sellerino M, Mancini S, De Luca DA (2020a) Meteorological Variability and Groundwater Quality: Examples in Different Hydrogeological Settings. Water 12, 1297. https://doi.org/10.3390/w12051297
Lasagna M, Mancini S, De Luca DA (2020b) Groundwater hydrodynamic behaviours based on water table levels to identify natural and anthropic controlling factors in the Piedmont Plain (Italy). Sci. Total Environ. 716, 137051. https://doi.org/10.1016/j.scitotenv.2020.137051
Liu C (2022) Traditional agricultural management of Kam Sweet Rice (16.)
Liu H, Hussain S, Zheng M, Peng S, Huang J, Cui K, Nie L (2015) Dry direct-seeded rice as an alternative to transplanted-flooded rice in Central China. Agron. Sustain. Dev. 35, 285–294. https://doi.org/10.1007/s13593-014-0239-0
Liu Y (2022) Effects of climate change on paddy expansion and potential adaption strategies for sustainable agriculture development across Northeast China. Appl. Geogr. 12.
Mancini S, Egidio E, Luca DAD, Lasagna M (2022) Application and comparison of different statistical methods for the analysis of groundwater levels over time: Response to rainfall and resource evolution in the Piedmont Plain (NW Italy). Sci. Total Environ. 157479. https://doi.org/10.1016/j.scitotenv.2022.157479
Mann HB (1945) Nonparametric Tests Against Trend. Econometrica 13, 245. https://doi.org/10.2307/1907187
Mastrocicco M, Busico G, Colombani N (2018) Groundwater Temperature Trend as a Proxy for Climate Variability. Proceedings 2, 630. https://doi.org/10.3390/proceedings2110630
risoitaliano.eu [WWW Document] (2022) RisoItaliano Il Portale Riso. URL https://www.risoitaliano.eu/ (accessed 5.25.22).
Romani M (2008) Romani, M. (2008). Tecnica colturale. In ART Servizi Editoriali S.r.l. (Eds.), Il riso (pp. 298–323). Bayer CropScience. http://www.colturaecultura.it/content/tecnica-colturale-3
Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. Journal of American Statistical Association 39, 1379–1389.
Singh A, Maichle R, Singh AK, Lee SE, Armbya N (2007) Proucl Version 4.00. 02 User Guide.
Wang H (2022) Effects of free-air temperature increase on grain yield and greenhouse gas emissions in a double rice cropping system. Field Crops Res. 9.
Yue S, Wang CY (2002) Applicability of prewhitening to eliminate the influence of serial correlation on the Mann-Kendall test:Technical Note. Water Resour. Res. 38, 4-1-4–7. https://doi.org/10.1029/2001WR000861
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