About me

I’m a junior lecturer in the Department of Civil and Environmental Engineering at Universitas Gadjah Mada Indonesia.
My research covers water resources engineering and the impacts of climate change on water resources and the other environment (i.e., agriculture). I am currently working on the quantification impact of flood and drought in agriculture on a global scale to a local scale (Indonesia).

Interested in our research?

Contact me at vempi[at]ugm.ac.id

Google Scholar

Researchgate

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Research Interests

• Hydrology
• Water-related disasters
• Impact studies
• Climate change
• Data-driven modeling
• Machine learning

Educations

• PhD in Water Resources System Science, 2022, Tohoku University Japan
• MEnv in Water Resources System Science, 2019, Tohoku University Japan
• ST in Civil Engineering, 2016, Universitas Gadjah Mada Indonesia

Our study shows that Java Island will likely experience drying in the lowlands due to annual rainfall decline by approximately 13%–18%, potentially exposing around 27%–73% of the population (varying under different scenarios) during the end of the century (2060–2099). Additionally, the future drying condition may be exacerbated by extreme temperatures with a 1.7–3.1°C increase in maximum daily temperature, linked with more than half of the population (63%) likely to experience at least an unprecedented temperature of 3°C under RCP8.5.

Our seasonal analysis also suggests that dry seasons get even drier, and wet seasons get wetter. In terms of landuse areas exposed, we show a higher fraction of crop and forest areas may face both drying and warming, which can potentially lead to crop failure and wildfire. Our study indicates that compound drought and heat may be a common threat in lowland Java in the future, while intensifying rainfall extremes in the uplands may lead to flash flooding downstream and landslides. These findings highlight the urgent need for adaptation and mitigation strategies to reduce the risks associated with climate change in Java as one of Indonesia’s most critical regions in the future.

Based on ensemble datasets, our study found that around one third of global maize, rice, soybean, and wheat yield were significantly affected by drought during 1981-2016.

The study highlights that crops grown in arid regions worldwide were highly susceptible to drought, except for rice, which is generally grown in humid areas with irrigation and less exposure to drought.

Using machine learning, we show that crop-drought sensitivity is primarily determined by annual precipitation, soil water-holding capacity, soil acidity, annual potential evapotranspiration and crop management factors (fertilizer rate, growing season). Our study quantitatively assesses determinants impacting crop vulnerability to drought, offering insights for future research on improved measures.

Vulnerability curves, which relate the intensity of flooding to potential loss, are crucial in assessing flood risk. They serve as valuable tools for rapid loss evaluation and immediate decision-making in disaster risk reduction.

Our study introduces flood vulnerability curves for rice crops, estimating crop yield loss through crop statistics and remote-sensing modeling.

By simulating flood parameters (depth, velocity, and duration) using a hydrodynamic model, a comparison between crop yield loss and flood characteristics enables the derivation of vulnerability curves. This study’s framework can be potentially used to obtain flood vulnerability curve or flood damage function, particularly for data-scarce regions.