Hydrologic Modeling and Parameter Estimation under Data Scarcity for Java Island, Indonesia

The Indonesian island of Java is routinely subjected to intense flooding, drought and related natural hazards, resulting in severe social and economic impacts. Although an improved understanding of the island's hydrology would help mitigate these risks, data scarcity issues make the modeling challenging. To this end, we developed a hydrological representation of Java using the Variable Infiltration Capacity (VIC) model, to simulate the hydrologic processes of several watersheds across the island. We measured the model performance using Nash-Sutcliffe Efficiency (NSE) at monthly time step. Data scarcity and quality issues for precipitation and streamflow warranted the application of a quality control procedure to data ensure consistency among watersheds resulting in 7 watersheds. To optimize the model performance, the calibration parameters were estimated using Borg Multi Objective Evolutionary Algorithm (Borg MOEA), which offers efficient searching of the parameter space, adaptive population sizing and local optima escape facility. The result shows that calibration performance is best (NSE ~ 0.6 - 0.9) in the eastern part of the domain and moderate (NSE ~ 0.3 - 0.5) in the western part of the island. The validation results are lower (NSE ~ 0.1 - 0.5) and (NSE ~ 0.1 - 0.4) in the east and west, respectively. We surmise that the presence of outliers and stark differences in the climate between calibration and validation periods in the western watersheds are responsible for low NSE in this region. In addition, we found that approximately 70% of total errors were contributed by less than 20% of total data. The spatial variability of model performance suggests the influence of both topographical and hydroclimatic controls on the hydrological processes. Most watersheds in eastern part perform better in wet season and vice versa for the western part. This modeling framework is one of the first attempts at comprehensively simulating the hydrology in this maritime, tropical continent and, offers insights for skillful hydrologic projections crucial for natural hazard mitigation.