PhD Defence Riswan Sianturi

reducing potential disaster impacts in irrigated rice fields in west java 

Riswan Sianturi is a PhD student in the research group Earth Systems Analysis. His supervisors are prof.dr. V.G. Jetten from the faculty of Geo-information Science and Earth Observation and prof.dr. J. Sartohadi from the University Gadjah Mada (Indonesia). 

The increasing global population inevitably demands for stable food production. As an important food crop, rice plays a major role in maintaining food security. However, irrigated rice fields are increasingly suffered from natural hazard occurrences worldwide, disrupting livelihoods of millions of populations and jeopardizing food security. Therefore, there is an urgent need to reduce devastating disaster impacts in irrigated rice fields. In this respect, the concept and practice of disaster risk reduction (DRR) offer insights for reducing damages and losses from natural hazards. As a concept, DRR analyzes and manages causal factors of disaster events, including environmental and socioeconomic processes. In practice, DRR focuses on proactive activities of managing disaster risk instead of solely reacting to disaster impacts. Despite the benefits, surprisingly, fewer studies incorporate the concept and practice of DRR for investigating or proposing insights to reduce potential disaster impacts in irrigated rice fields.

The central question underlying the thesis is “How can disaster impacts in irrigated rice fields be reduced?” This thesis analyzes hazard, vulnerability, and resilience in irrigated rice fields in West Java to answer the question. To this end, this study intends to contribute to the advancement of science and practice of DRR in irrigated rice fields. This study used primary and secondary data, such as stakeholders’ responses and time-series MODIS imageries (MOD09A1). Both quantitative (e.g., remote sensing and statistical analyses) and qualitative (e.g., qualitative content analysis) approaches were also performed. Findings presented in each chapter of this thesis can be used as inputs for designing effective strategies to reduce potential disaster impacts in irrigated rice fields.

Information on vulnerability to flooding is essential for estimating potential damages from flood events. Chapter 2 has demonstrated that cropping patterns can be used as one of the inputs for deriving physical vulnerability to flooding in irrigated rice fields. Cropping patterns were generated from the spatial distribution and phenology metrics. Combined with vulnerability curves, cropping patterns can be used to determine vulnerability to flooding. Vulnerability varies in space and time and may shift because of extreme weather variabilities or human decisions. The shift leads to either an increase or decrease of vulnerability in irrigated rice fields of origin or other irrigated rice fields. Accuracy assessments were performed for the estimated spatial distribution and phenology metrics. For the former, the comparison between MOD09A1 and ALOS PALSAR (2010) and between MOD09A1 and Agricultural Statistics showed coherent results with R2 of 0.81 and 0.93, respectively. For the latter, the estimated RMSEs for SOS, heading stage, and EOS are 9.21 (n=61), 9.29 (n=46), and 9.69 (n=49) days, respectively.

Robust flood detection methods are needed for understanding irrigated rice field areas affected by flood events. Previous studies suggested that EVI ≤ 0.1 can be used to detect flood events in irrigated rice fields. However, non-hazardous agronomic inundation and hazardous flooding may be present at the same time in irrigated rice fields. Therefore, EVI ≤ 0.1 may not be adequate to detect rice fields with flooding, and the attempt for distinguishing between rice fields with flooding and rice fields with agronomic inundation (RFAI) is therefore necessary. It was found that EVI ≤ 0.1 cannot distinguish between flooding and agronomic inundation in irrigated rice fields in the study area. On the contrary, EVI40 can roughly distinguish between flood events and agronomic inundation in irrigated rice fields in the study area. However, misclassified flood pixels exist partly due to environmental processes, human decisions, and mixed pixels. Using the Start of Season (SOS) for assessing the accuracy of the derived flood map, it is estimated that the scores of Accuracy and F1 for EVI40 are 75.96% and 81.74%, respectively.

The vulnerability of farmers to natural hazards may partly be explained by unsafe conditions. According to the Pressure and Release (PAR) model, vulnerability may progress from root causes, dynamic pressures to unsafe conditions. Some of the challenges on identifying unsafe conditions are the difference in ‘vocabularies’ among rice agriculture stakeholders (e.g., farmers, water managers, extension officers) and various potential reasons for unsafe conditions. In this respect, disruptions in cropping schedules may be used as a ‘common language’ to understand mechanisms of how unsafe conditions may increase vulnerability. Reasons for disruptions in cropping schedules have been identified, including economic motives, weather variabilities, geographic locations, coping strategies, farmers’ interactions, and agricultural infrastructures. Unsafe conditions in irrigated rice fields in West Java has also been successfully documented, including dangerous locations, unsustainable farming activities, unsuitable coping strategies, fragile infrastructures, and inaccurate perception.

Efforts to reduce potential disaster impacts in irrigated rice fields can also be performed by building the resilience of farmers to natural hazards. However, the multi-faceted and –level nature of resilience leads to difficulties in its assessments. In this respect, studies related to factors influencing resilience of farmers to natural hazards may serve as one of the ‘shortcuts’ for understanding and building resilience. In the present study, resilience is defined as the ability of farmers to recover from recurrent impacts of natural hazards. Several assessments are performed. Firstly, the Vegetation Condition Index (VCI) is used to provide an overview of irrigated rice field conditions during the dry planting season 2015 and wet planting season 2016. Farmers could not perform rice cultivation in the dry planting season 2015 because of an extreme water-deficit event. On the contrary, farmers could perform rice cultivation in the wet planting season 2016 despite having no income from the previous planting season. Additionally, farmers experienced severe damages occurred during booting and ripening periods because of strong wind with rainfall and rice blast attacks (Magnaporthe grisea). However, the impacts of such events on irrigated rice fields are not able to be captured by the time-series VCI, limited by the moderate spatial resolution. Furthermore, the time-series VCI has demonstrated that the scope of resilience analysis, such as the spatial and temporal scales and working definition, influences the outputs of resilience studies. Secondly, factors that significantly correlated with the resilience of farmers to natural hazards have been identified, including the ability of farmers to save money after selling harvests, reduction of harvest because of rat attacks, community recovery, and rice field tenure. These factors indicate that irrigated rice fields in the study areas are inter-related where the outcomes of rice fields located near primary irrigation channels influence the outcomes of those located close to coastal areas and vice versa. Finally, addressing challenges related to the farming skills, reduction of harvest due to rat attacks, ability to save money after selling harvest, synchronous planting, and access to farming information may aid farmers to manifest their potential into actual resilience.

Reducing potential disaster impacts can be performed by minimizing the risk of and building the resilience of farmers to natural hazards. These efforts should be supported by access to reliable farming and weather information. In addition to performing balanced farming practices (double rice cropping patterns with fallow), farmers incorporate measures that stretch beyond the on-the-farm or household level, such as farming insurance or cooperation. To ensure the long-term continuity, risk reduction activities should be embedded into national programs on rural or rice agricultural development.

Future research investigating dynamics in irrigated rice fields using higher spatial and temporal resolution imageries are suggested. Studies that focus on the ability of farmers’ households and community to mobilize livelihood capitals for reducing risk and building resilience to natural hazards are also suggested. In practice, reducing disaster impacts in irrigated rice fields requires seamless communication and coordination among rice agricultural stakeholders, including the poor and the vulnerable. Such cooperation requires building trust.