BUS606: Operations and Supply Chain Management

Due to the non-linear and complex nature of a forest fire, rapidly modeling this catastrophe at the regional scale is a challenge. In this study, two simple yet robust models for predicting forest fire-prone areas in Bhutan were presented and compared. The FR model was shown to produce a more accurate fire-prone map than the AHP model, based on the higher AUC values. Therefore, the use of the FR model is recommended. The weakness of the AHP model is due to potential errors in pair-wise comparisons of the conditioning factors. The AHP model is highly reliant on expert judgment that is prone to error in the sense that its accuracy can be greatly altered by divergent views from the fire experts. Such a possibility was also acknowledged by Rathore, Dubey while creating an expert-based least-cost corridor for tigers Panthera tigris in Madhya Pradesh, India. Therefore, considerable attention is required in assigning values in an AHP matrix with repeated iterations, until a desired CR is attained. The FR modeling, on the other hand, produces outcomes based on mathematical analysis; hence, it does not require any expert judgments and is, therefore, less prone to errors emanating from expert opinion. In recent times in Bhutan, forest fires have been caused by electrical short circuits along the power transmission lines traversing coniferous forests. Due to the non-availability of a spatial layer on distance from power lines, it was not used as a conditioning factor in the modeling. However, it should be used in future studies if the spatial layer becomes available. One of the advantages of GIS-based modeling is that new spatial layers can be added, and the model repeatedly generated.

We have found that the MODIS fire points are not reliable in predicting forest fires, as most of the points overlapped with 'moderate' and 'low' prone classes on the AHP and FR model outputs, respectively. The low predictability of MODIS fire points in predicting forest fire-prone areas in Bhutan could be due to cloudy weather conditions in the Himalayan ranges that could shield forest fires from the satellites. It could also be possible that the timing of forest fires may not have coincided with the timing of satellite passes. Similar explanations are reported by Müller, Suess in Lao People's Democratic Republic. Additionally, in Thailand, there were false alarms observed during ground validation of fires in the hilly areas, although MODIS detection accuracy was 97%. In the case of Bhutan, Pemagatshel Dzongkhag ('district' in Bhutanese national language) in the southeast was classified as a 'moderate' or 'low' fire-prone area by our models despite the large concentration of MODIS fire points (n = 327). In fact, most of these fire points represented fires from the burning of agricultural debris and from shifting cultivation, which is still being practiced at a small scale despite officially being banned. One should, therefore, exercise caution while developing any forest fire-prone maps using MODIS fire points.

This study has created the first ever forest fire-prone map for Bhutan (based on the FR model), which will be forwarded to the Department of Forests and Park Services for adoption. Such forest fire-prone area maps will be highly valuable to Bhutanese area managers and also to policy makers at regional and national levels for effective planning of resources to prevent and manage forest fires. This map is highly relevant and timely for the current situation in Bhutan, which still does not have an officially recognized forest fire-prone area map. Fire-prone classes, such as 'very high' and 'high', are predicted in the central districts of Bhutan. Mongar Dzongkhag has the highest percentage of fire-prone areas (combination of 'very high' and 'high' classes), followed by Wangduephodrang, Trashigang, Bumthang, Thimpu, and Paro Dzongkhags. These are areas with a corresponding high percentage of blue pine and chirpine forests along with high human populations and a comprehensive road network. Therefore, these areas need to be prioritized for any future fire prevention and management programs in Bhutan.