|Chavez Eguez, Jose|
Submitted to: Proceedings of the American Society of Agricultural and Biological Engineers International (ASABE)
Publication Type: Proceedings
Publication Acceptance Date: 3/26/2007
Publication Date: 6/17/2007
Citation: Chavez Eguez, J.L., Gowda, P., Griffin, R., Rivera, S., Neal, C.M. 2007. A simple empirical stream flow prediction model for ungauged watersheds. [abstract]. In: Proceedings of the American Society of Agricultural and Biological Engineers International (ASABE). Paper No. 072003. June 17-20, 2007, Minneapolis, Minnesota. Interpretive Summary: Knowledge of streamflow is desirable for planning and management of water resources. This information is crucial for designing hydropower, municipal water supply, flood control, and irrigation systems. Continuous flow monitoring is required to collect this information. In most regions around the world, watersheds are not monitored for streamflow due to lack of resources. In the absence of monitoring systems, streamflows were estimated using hydrologic models. Existing hydrologic models require extensive data to estimate streamflow and/or nontransferable. Therefore, these models are not suitable for watersheds where little or no data exist. In this study, we proposed and evaluated a simple hydrologic model that requires minimal but globally available data. It requires climatic data and watershed characteristics such as area, slope, soil type and land use as input. A model was developed and evaluated using data from ten watersheds located in Central and South America. Analysis of the results indicated that there is strong exponential relationship between streamflow and climatic data and watershed characteristics. Further evaluation of the proposed model is needed to verify transferability to other regions in the world.
Technical Abstract: Knowledge of streamflow is important for estimating groundwater recharge rates, forecasting floods, and designing hydropower structures and irrigation systems. However, many watersheds throughout the developing world remain ungauged. This fact demands a simple hydrological model that requires minimal but globally available data for estimating monthly streamflow. In this study, data from five watersheds in Honduras were used to develop an empirical monthly streamflow model using Moisture Adequacy Index (MAI), Leaf Area Index (LAI), and watershed characteristics such as soil infiltration rates, terrain slopes, and vegetation cover. The proposed model had an R**2 of 0.74 and was significant at the 95% confidence level. The model was verified with data from four other Honduran and one Bolivian watershed. The streamflow model explained about 90% of the variability in the measured flow indicating that the model may be transferable to other ungauged watersheds.