Statistical Data Collection Methodologies of Irrigated Areas and Their Limitations: A Review

Inconsistencies in the statistical datasets of irrigated areas at the national level could have considerable implications for policies developed for food and water security. Remote sensing can address this issue, however, dubieties of its reliability inhibit its protagonist role. Methods that integrate both remote sensing based and statistical datasets seem expedient, and they are more likely to be acknowledged by the policymakers. Therefore, it is important for scientists to know the basis and limitations of statistical datasets which originate at the country level. Data collection methodologies of irrigated areas were reviewed for seven Asian countries, namely China, India, Pakistan, Bangladesh, Nepal, Indonesia, and Thailand. Factors causing the uncertainties in data, and the limitations of data collection methodologies were highlighted. Also, an irrigation density distribution analysis was conducted to understand the relation of spatial spread pattern of irrigated areas and uncertainty in their statistical records. It was found that irrigated areas statistics are mostly based on the information originating from water user associations and farmers, which is either self-reported or it is collected through interviews during surveys and censuses. The main causes of discrepancy were lack of resources to frequently enumerate the irrigated land, inconsistency in the data collection methodologies, unaccounted secondary crops, illegal and unregulated water use, and bureaucratic and political constraints. Irrigation density distribution analysis showed that the largely scattered irrigated areas might be prone to lack of comprehensive and frequent enumeration. Furthermore, dense irrigation regions might have potentially unrecorded irrigated areas where temporary or supplementary irrigation arrangements are made by the marginal farmers.