[1] In wetlands or riparian areas, water withdrawal by plants with access to groundwater or the capillary fringe often causes diurnal groundwater fluctuations. Various approaches use the characteristics of these fluctuations for estimation of daily groundwater evapotranspiration rates. The objective of this paper was to review the available methods, compare them with measured evapotranspiration and assess their recharge assumptions. For this purpose, we employed data of 85 rain-free days of a weighable groundwater lysimeter situated at a grassland site in the Spreewald wetland in north-east Germany. Measurements of hourly recharge and daily evapotranspiration rates were used to assess the different approaches. Our results showed that a maximum of 50% of the day to day variance of the daily evapotranspiration rates could be explained by the approaches based on groundwater fluctuations. Simple and more complex methods performed similarly. For some of the approaches, there were indications that erroneous assumptions compensated each other (e.g., when overestimated recharge counteracted underestimated storage change). We found that the usage of longer time spans resulted in improved estimates of the daily recharge rates and that the estimates were further enhanced by including two night averages. When derived from fitting estimates of recharge or evapotranspiration with according measurements the specific yield, needed to convert changes in water level to water volumes, differed considerably among the methods (from 0.022 to 0.064). Thus, the specific yield can be seen as ''correction factor'' that compensates for inadequate process descriptions.

Hydrology is rich in methods that use information theory to evaluate monitoring networks. Yet in most existing studies, only the available data set as a whole is used, which neglects the intraannual variability of the hydrological system. In this paper, we demonstrate how this variability can be considered by extending monitoring evaluation to subsets of the available data. Therefore, we separately evaluated time windows of fixed length, which were shifted through the data set, and successively extended time windows. We used basic information theory measures and a greedy ranking algorithm based on the criterion of maximum information/minimum redundancy. The network investigated monitored surface and groundwater levels at quarter-hourly intervals and was located at an artificially drained lowland site in the Spreewald region in north-east Germany. The results revealed that some of the monitoring stations were of value permanently while others were needed only temporally. The prevailing meteorological conditions, particularly the amount of precipitation, affected the degree of similarity between the water levels measured. The hydrological system tended to act more individually during periods of no or little rainfall. The optimal monitoring setup, its stability, and the monitoring effort necessary were influenced by the meteorological forcing. Altogether, the methodology presented can help achieve a monitoring network design that has a more even performance or covers the conditions of interest (e.g., floods or droughts) best.

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