Depending on the terrain conditions & the availability of data, any method in isolation or in combination can be used in any climatic region. There is nothing like global best practice. It is the researcher who will decide the methodology for a particular region and purpose. According to me an integrated approach consisting of Remote Sensing; Geological; Geomorphological; Hydro-geological/hydrological; Geochemical and Geophysical techniques will be the best.
Sure enough there´s no global practice per se, but you always need a good geological model to get started. What you do next and how, will always depend on it. Electrical surveys are cheap and effective in many cases.
The current trend in groundwater exploration is integration of several techniques and based on available datasets. Remote sensing and GIS techniques are utilized to delineate areas with greater prospects using various statistical and machine learning models e.g. Index overlays, multi-criteria decision analysis, Frequency ratios, Artificial Neural Networks etc. The result of the models can suggest suitable areas for further hydrogeological and geo-electric surveys. You may find the following interesting;
Adji, T. N., & Sejati, S. P. (2012). Identification of groundwater potential zones within an area with various geomorphological units by using several field parameters and a GIS approach in Kulon Progo Regency, Java, Indonesia. Arabian Journal of Geosciences, 7(1), 161–172. http://doi.org/10.1007/s12517-012-0779-z
Fashae, O. A., Tijani, M. N., Talabi, A. O., & Adedeji, O. I. (2013). Delineation of groundwater potential zones in the crystalline basement terrain of SW-Nigeria: an integrated GIS and remote sensing approach. Applied Water Science, 4(1), 19–38. http://doi.org/10.1007/s13201-013-0127-9
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Akinwumiju, A. S. , Olorunfemi, M. O. and Afolabi, O. (2016). GIS-BASED INTEGRATED GROUNDWATER POTENTIAL ASSESSMENT OF OSUN
DRAINAGE BASIN, SOUTHWESTERN NIGERIA. Ife Journal of Science vol. 18, no. 1
Bandyopadhyay, S., Srivastava, S.K., Jha, M.K., Hegde, V.S. and Jayaraman,
V. (2007). Harnessing earth observation (EO) capabilities in hydrogeology: An Indian perspective. Hydrogeology Journal, 15(1): 155-158
Naghibi, S. A., Pourghasemi, H. R., & Dixon, B. (2017). GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran. Environmental monitoring and assessment, 188(1), 1-27.