Statistical Data Collection Methodologies Of Irrigated Areas And Their Limitations: A Review

Inconsistencies in the statistical data sets 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, doubts about its reliability inhibit its protagonist role. Methods that integrate both remote sensing based and statistical data sets seem expedient, and they are more likely to be acknowledged by policymakers. Therefore, it is important for scientists to know the basis and limitations of statistical data sets which originate at the country level. Data collection methodologies of irrigated areas have been 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 area statistics are mostly based on information originating from water user associations and farmers, which is either self-reported or collected through interviews during surveys and censuses. The main causes of discrepancy were lack of resources to frequently enumerate the irrigated land, inconsistency in data collection methodologies, unaccounted secondary crops, illegal and unregulated water use, and bureaucratic and political constraints. Irrigation density distribution analysis showed that largely scattered irrigated areas might be prone to a 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 marginal farmers. (c) 2019 John Wiley & Sons, Ltd.