Intensive observations, analysis and modeling within the framework of the rangelands atmosphere–hydrosphere–biosphere interaction study experiment in northeastern Asia (RAISE) project, have allowed investigations into the hydrologic cycle in the ecotone of forest-steppe, and its relation to atmosphere and ecosystem in the eastern part of Mongolia. In this region, changes in the climate have been reported and a market oriented economy was introduced recently, but their impact on the natural environment is still not well understood. In this RAISE special issue, the outcome is presented of the studies carried out by six groups within RAISE, namely: (1) Land-atmosphere interaction analysis, (2) ecosystem analysis and modeling, (3) hydrologic cycle analysis, (4) climatic modeling, (5) hydrologic modeling, and (6) integration. The results are organized in five relevant categories comprising (i) hydrologic cycle including precipitation, groundwater, and surface water, (ii) hydrologic cycle and ecosystem, (iii) surface–atmosphere interaction, (iv) effect of grazing activities on soils, plant ecosystem and surface fluxes, and (v) future prediction. Comparison with studies on rangelands in other parts of the world, and some future directions of studies still needed in this region are also summarized.

Model spin-up is an adjustment process where its internal stores move from an initial state of unusual conditions to one of equilibrium. Model outputs during this spin-up process are often unrealistic and misleading. This study investigates some primary factors affecting spin-up time using the Xinanjiang model for 22 river basins throughout the United States. A 10-year recursive simulation with three data sets indicates that time required for model equilibrium is not only a function of initial conditions, but also is affected by input data sets (precipitation and evaporation). The model requires less time to be equilibrated under wetter initial conditions (lowest under saturated initial condition). Moreover, model spin-up time shows distinct variations with the dryness of the input data sets. Analysis suggests that wet basins (ratio of evaporation over precipitation <0.9) require less time (55 days) for model equilibrium in comparison to that of dry basins (298 days). The spin-up time displayed an exponential relationship with the basin aridity index (r² = 0.85). This relationship could provide a way to predict the maximum model spin-up time using the precipitation and evaporation information only. Predicting maximum model spin-up time based on this relationship could be valuable to reduce uncertainty, particularly under data scarce situations.