Simulating flow dynamics in large-scale lakes is often time-consuming. For river flood simulation, the automatic domain updating (ADU), which can effectively control the simulation domain only in and around the flooded areas, has recently been developed. It is easily implementable without any computational errors for river flood simulation; however, its applicability to lake flow simulation with precipitation/evapotranspiration has not been investigated. This study examines the applicability of the ADU to large-scale lake flow simulation with the 2-dimensional local inertial equations (2D-LIE) taking the Tonle Sap Lake, Cambodia, as a study site. The 2D-LIE with the ADU demonstrated 2.1 times faster simulation with errors less than 5.5%. This efficiency was achieved owing to the wet/dry seasonal nature of the tropical lake and backflow from the mainstream of the Mekong River in the rainy season, suggesting that the ADU is applicable to large-scale lake flow simulation.
In Kushiro River basin, inundation is likely to occur due to heavy rain, since the river-bed slope is very gentle in the downstream portion, which has natural levees. Consequently, in past floods, river discharge was observed to increase slowly and a delay of a few days in peak river discharge was observed compared to the peak precipitation. Therefore, we applied a distributed hydrological model, Geophysical fluid CIRCulation model (GeoCIRC), to reproduce such flood discharge in Kushiro River. GeoCIRC is based on object-oriented programming and various hydrological processes, such as infiltration flow, underground water flow, surface flow, and river flow can be implemented easily. We proposed a model that can incorporate the effect of return flow using storage function by introducing new parameters, such as storage time and time lag. This was done to consider not only the flood inundation in Kushiro River but also the return flow from flood inundation to the river flow. As a result, we obtained high Nash-Sutcliffe coefficients for river discharge for two large flood events.
Hydrological responses due to deforestation in a humid tropical catchment were analyzed using two runoff generation methods available in the Soil Water Assessment Tool (SWAT) model: the Curve Number (CN) and the Green-Ampt (GA) methods. The calibrated model, which performed well in simulating runoff under present land use condition in the Batanghari River Basin, Indonesia (42,960 km2), was then used to simulate runoff using past and future land use scenarios. Simulations showed similar changes in the annual water budget: decreasing evaporation and increasing total discharge. However, the two methods showed opposite changes in flow regimes: high flow increased (13%) under the CN while low flow increased (27%) under the GA. These results are associated with differences in runoff generation mechanisms, where surface runoff contributes to total discharge to a much larger extent under the CN (43%) than the GA (4%). Land use changes caused a reduction in infiltration rate, leading to higher high flow under the CN, while high flow did not change under the GA. Instead, lower evapotranspiration increased groundwater flow under the GA, and thus the steady low flow increased. This study suggests that the runoff generation method should be selected carefully based on the dominant flow pathway of a catchment, particularly for land use impact studies in the humid tropics.
Understanding the extent to which human activities affect river flow is fundamental for enhancing effective water resources management. In past decades, various methods have been proposed to estimate naturalized flow (i.e. the expected flow if the basin is unaffected by human activities). However, there are still drawbacks to naturalized flow estimation, particularly in a highly regulated basin with incomplete hydrological observation. This study proposes a method for daily naturalized flow development at the key station of the Chao Phraya River Basin; the most highly regulated basin in Thailand. The naturalized flow is estimated by applying the Naturalization with Coarse and Fine Components (NCFC) method to perceive river flow conditions unaffected by human disturbance. The estimation is derived with the integration of five components: (1) observed river flow at the key hydrological station; (2) changes in major reservoir storage; (3) water withdrawal along the river; (4) travel time from major reservoirs to the station; and (5) the filtering technique used by Savitzky-Golay with a three-day window.