Meeting Abstract

Appeared in: AGU Fall Meeting : San Francisco, 13-17 December 2010

Publication year: 2010

Pages: H13I-01-

URL: https://abstractsearch.agu.org/meetings/2010/FM/H13I-01.html

Abstract: 

The identification of storage dynamics in remote areas is limited by data scarcity. Both top-down and bottom up approaches to identify dominant hydrological processes often fail under these circumstances. In this study, we are combining both approaches in order to test several hypotheses concerning storage dynamics. The upper Xilin catchment, Inner Mongolia, China, is a primary example for such a situation. In the last few years numerous measurement campaigns were carried out in this area to investigate the impact of increasing land use intensity on different ecosystem functions. These included the measurement of water quantity and quality in the stream, rain and groundwaters, soil physical data as well as vegetation data. Despite the apparent abundance of these data, they are not representative for the seasonal and interannual variability of the hydrological processes. Existing time series are short and discontinuous, and catchment characteristics are measured with a low spatial density. In a first step, environmental tracer data were used to calculate the contribution of different sources to the stream water. The newly obtained information of this end member mixing analyzes (EMMA) is used to guide conceptual model development in a “soft data” manner. In addition, it will be applied in a process-based rejectionist framework as a posteriori model calibration criteria. The information about geographic source contributions to stream guides the development of a physically based reservoir model using the Catchment Modeling Framework (CMF). Such an approach is able to support hypothesis testing to evaluate the newly acquired information and to gain more insight into the processes of the catchment. The hypotheses are: -Sand dune groundwater aquifer is the main source for the river during wet years, while deep groundwater aquifers are the main source in dry years -The effective catchment area is much smaller than the topographic, -The effective catchment area varies between years in size The model designed for testing the hypothesis follows a semidistributed approach. Upslope regions of subcatchment contribute to the riparian zone. The model serves as a basis for testing the hypotheses by varying the model structure. First results of the numerical model support some of the hypotheses. The larger area of the catchment, namely the loamy steppe and mountain meadow areas, contribute only in extremely wet years to the groundwater, according to the model. In most years the effective catchment area reduces to the marshland surrounding the stream and the coarse soil types of the sand dunes. Identifying the dynamics of these old water storages is the most challenging part of this study. These results are to be tested for their plausibility by comparing the calculated quantitative distribution of stream water sources with the results of the EMMA. While the availability of data in this remote area hampers both the quantification of storage dynamics using statistical as well as physics based approaches, their combination can help to identify sources and sinks of the scarce water resources.

Harvard Citation style: Barthold, F., Kraft, P., Vache K.B., Frede, H. and Breuer, L. (2010) Estimating storage dynamics by combining top-down and bottom-up approaches, in AGU Fall Meeting : San Francisco, 13-17 December 2010. San Francisco. p. H13I-01. https://abstractsearch.agu.org/meetings/2010/FM/H13I-01.html

APA Citation style: Barthold, F., Kraft, P., Vache K.B., Frede, H., & Breuer, L. (2010). Estimating storage dynamics by combining top-down and bottom-up approaches. In AGU Fall Meeting : San Francisco, 13-17 December 2010. (p. H13I-01). https://abstractsearch.agu.org/meetings/2010/FM/H13I-01.html