Patricia Ann Jaranilla-Sanchez

Modeling hydrologic and ecologic responses using a new eco‐hydrological model for identification of droughts

Drought severely damages water and agricultural resources, and both hydrological and ecological responses are important for its understanding. First, precipitation deficit induces soil moisture deficiency and high plant water stress causing agricultural droughts. Second, hydrological drought characterized by deficit of river discharge and groundwater follows agricultural drought. However, contributions of vegetation dynamics to these processes at basin scale have not been quantified. To address this issue, we develop an eco-hydrological model that can calculate river discharge, groundwater, energy flux, and vegetation dynamics as diagnostic variables at basin scale within a distributed hydrological modeling framework. The model is applied to drought analysis in the Medjerda River basin. From model inputs and outputs, we calculate drought indices for different drought types. The model shows reliable accuracy in reproducing observed river discharge in long-term (19 year) simulation. Moreover, the drought index calculated from the model-estimated annual peak of leaf area index correlates well (correlation coefficient r = 0.89) with the drought index from nationwide annual crop production, which demonstrates that the modeled leaf area index is capable of representing agricultural droughts related to historical food shortages. We show that vegetation dynamics have a more rapid response to meteorological droughts than river discharge and groundwater dynamics in the Medjerda basin because vegetation dynamics are sensitive to soil moisture in surface layers, whereas soil moisture in deeper layers strongly contributes to streamflow and groundwater level. Our modeling framework can contribute to analyze drought progress, although analyses for other climate conditions are needed.

River management system development in Asia based on Data Integration and Analysis System (DIAS) under GEOSS

This paper introduces the process of development and practical use implementation of an advanced river management system for supporting integrated water resources management practices in Asian river basins under the framework of GEOSS Asia water cycle initiative (AWCI). The system is based on integration of data from earth observation satellites and in-situ networks with other types of data, including numerical weather prediction model outputs, climate model outputs, geographical information, and socio-economic data. The system builds on the water and energy budget distributed hydrological model (WEB-DHM) that was adapted for specific conditions of studied basins, in particular snow and glacier phenomena and equipped with other functions such as dam operation optimization scheme and a set of tools for climate change impact assessment to be able to generate relevant information for policy and decision makers. In situ data were archived for 18 selected basins at the data integration and analysis system of Japan (DIAS) and demonstration projects were carried out showing potential of the new system. It included climate change impact assessment on hydrological regimes, which is presently a critical step for sound management decisions. Results of such three case studies in Pakistan, Philippines, and Vietnam are provided here.