When the scarcity rate exceeds a certain threshold (20% in this study), measured data scarcity level has clear impacts on the model's accuracy.
However, various difficulties may be encountered in the regional estimation of As concentration such as cost-intensive field monitoring, scarcity of field data, identification of important factors affecting As, over-fitting or poor estimation accuracy.
Quantitative estimation of precipitate and biomass distribution has remained challenging, partly due to the intrinsic heterogeneities of natural porous media and the scarcity of field data.
However, scarcity of field data is an underlying problem in many environmental modelling projects and the relationship between the amount of available data and the domain of applicability of IBMs has hardly been considered.
The inherent model complexity, lack of knowledge about the linkages among model components, scarcity of field data, and uncertainty involved with internal and external factors of the real system call their practical usefulness into doubt.
However, although the benefits of an integrated approach have been widely demonstrated, several aspects have prevented its wide application, such as the scarcity of field data for not only the input and output variables but also parameters that govern intermediate stages of the system, which are useful for robust calibration.
Nevertheless, it remains unclear whether meta-analyses of non-randomised studies systematically overestimate effect sizes compared with meta-analyses of randomised trials (MacLehose et al, 2000), and in light of the scarcity of high-quality evidence in this field, data from the meta-analysis of non-randomised studies can be informative.
The proposed nested multi-response approach may help to better predict water resources despite data scarcity.
However, few studies have explored the comprehensive impacts of rainfall data scarcity on H/NPS predictions.
The advantage of spatial downscaling is that it can be implemented in situations of data scarcity.
