From field scale eco-hydrological process understanding to landscape scale water fluxes

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From a hydrological perspective, many Land Surface Models (LSM) have major deficiencies in the representation of water-related feedback mechanisms due to biotic, climatic, topographic and physical landscape features. This results in an oversimplified description of hydrological processes, affecting the credibility of these models in simulating water fluxes. In the past, those simplifications where often the necessary compromise due to the lack of computational power and hydrological process understanding.In the first phase of the research group RESPECT, we have started to improve the hydrological routines within the newly developed LSM “HUMBOL-TD”. This was based on investigations of hydrological processes and water related feedback mechanisms within the soil-plant-atmosphere continuum of the mountain rainforest. We addressed different flow mechanisms in the soil and particularly preferential flow processes, which are frequently ignored by LSMs.Building on our findings and model improvements made in phase I and in light of the overall objectives of the research group RESPECT in phase II, we have identified three objectives tackled in four work packages (WP) for this follow-up project. For our first objective, we extend our field experimental studies to mountain dry and rain forests (WP1) and study the mixing processes of stable isotopes of water in more detail along a suction pressure gradient using i.e. our innovative soil water sampling system (WP2). These data will be used in WP2 for the validation of the newly developed isotope module of HUMBOL-TD and to improve the overall hydrological model performance of the LSM. As part of our second objective, we will balance model performance and runtime in view of our ambitions to run HUMBOL-TD on the landscape scale in WP3. We will identify well-performing hydrological model structures that match our derived field scale process understanding form WP2. For this, we will implement a semi-automatic search algorithm following the concept of systematic model breakdown and assign the best performing model structure to each sub-catchment. In addition to our field experimental data, we will use hydrological signatures derived from discharge data from our own long-term monitoring stations and further observations from national agencies for model calibration and validation. Finally, in our third objective, will work on multi-criteria hypothesis testing (WP4). We start with a rigid multi-criteria model evaluation of the water, carbon and energy fluxes in HUMBOL-TD using our, but also further data from other sub-projects. In a joint effort, we will then test the central hypotheses of RESPECT under the light of climate and land use changes.