A weather dependent approach to estimate the annual course of vegetation parameters for water balance simulations on the meso- and macroscale

Abstract

Abstract. In order to simulate long-term water balances hydrologic models have to be parameterized for several types of vegetation. Furthermore, a seasonal dependence of vegetation parameters has to be accomplished for a successful application. Many approaches neglect inter-annual variability and shifts due to climate change. In this paper a more comprehensive approach from literature was evaluated and applied to long-term water balance simulations, which incorporates temperature, humidity and maximum bright sunshine hours per day to calculate a growing season index (GSI). A validation of this threshold-related approach is carried out by comparisons with normalized difference vegetation index (NDVI) data and observations from the phenological network in the state of Lower Saxony. The annual courses of GSI and NDVI show a good agreement for numerous sites. A comparison with long-term observations of leaf onset and offset taken from the phenological network also revealed a good model performance. The observed trends indicating a shift toward an earlier leaf onset of 3 days per decade in the lowlands were reproduced very well. The GSI approach was implemented in the hydrologic model Panta Rhei. For the common vegetation parameters like leaf area index, vegetated fraction, albedo and the vegetation height a minimum value and a maximum value were defined for each land surface class. These parameters were scaled with the computed GSI for every time step to obtain a seasonal course for each parameter. Two simulations were carried out each for the current climate and for future climate scenarios. The first run was parameterized with a static annual course of vegetation parameters. The second run incorporates the new GSI approach. For the current climate both models produced comparable results regarding the water balance. Although there are no significant changes in modeled mean annual evapotranspiration and runoff depth in climate change scenarios, mean monthly values of these water balance components are shifted toward a lower runoff in spring and higher values during the winter months.

Subgrid spatial variability of soil hydraulic functions for hydrological modelling

“…Compared to point measurements of VGP, Rosetta is not always capable to perform a perfect fit; see e.g. Pandey et al (2005), Li et al (2007) or Ghorbani Dashtaki et al (2010). However, considering the huge sizes of model areas that are common for hydrological model applications, Rosetta is a good choice to generate parameters covering the complete area.…”

“…Results of the soil model are the direct runoff (P eff,D ), the groundwater recharge (P eff,GW ), which leads to base flow in a long-term view and actual evapotranspiration (ET). data types (Gelleszun et al, 2015;Kreye, 2015). To account for the impact of the subgrid parameterisation, we compared breakthrough curves (1-D) with different numbers of VGP sets and with different standard deviations of the K s distribution functions.…”

“…Law, 1944;Baker and Bouma, 1976;Sharma et al, 1980;Lauren et al, 1988;Binley et al, 1989b;Goodrich, 1990;Vauclin et al, 1994;Mallants et al, 1997;Bosch and West, 1998;Viera et al, 2011, and many more). The second statement was investigated in several studies as well.…”

Predicting vegetation phenology in response to climate change using bioclimatic indices in Iraq

“…For all tests, TMMin = 0 ºC and TMMax = 20 ºC. These thresholds are quite different from those used in Jolly et al (2005), Stöckli et al (2008), Stockli et al (2011), andFörster et al (2012), (see also Supplementary Materials (Section S1), for a discussion and data on the thresholds),as our study operates at a regional scale rather than a global scale. In this case differences are to be expected (White et al, 2000).…”

“…Stockli et al (2011) used satellite data to calibrate GSI for better predicting vegetation phenology globally across plant functional types. Förster et al (2012) applied the GSI approach to meso-and macro-scale water balance simulations. These studies were the direct application of the existing GSI method and the improvement to the method itself has not been carried out.…”