**1. Introduction**

Global climate has changed dramatically over the past few decades as demonstrated by many studies [1–3]. Mainly due to human activities, land cover also has experienced various and rapid changes, especially in recent decades [4–7]. Both changes in climate and land cover could greatly affect the hydrological cycle [8–12] regarding water balance and energy balance processes at various

scales [13]. These changes are more likely to result in serious consequences, such as droughts and floods, in arid and semi-arid regions, where the environment is much more vulnerable than in humid areas [14].

The Three-North region (TNR), which is composed of Northwestern, Northern, and Northeastern China, covers arid, semi-arid, and humid areas. The TNR is also an ecologically fragile area, where land degradation has been very serious due to both human activities and changes in natural conditions since the last century, especially in the Northwestern region [15]. In order to solve this problem, the Chinese governmen<sup>t</sup> has launched a series of ecological restoration programs, beginning in 1978, including the Three-North Forest Shelterbelt (TNFS) program and the restoration of farmland to forest area [15,16]. Meanwhile, other land cover changes (LCC), such as urban expansion and industrialization, have been accelerating since the population has increased sharply [17]. As a result, land cover in the TNR has radically changed over the past 40 years.

There have been many studies in which hydrological responses to climate change and LCCs have been detected through observation or simulation. Based on observation data, the potential evaporation and actual evaporation in most basins of the TNR, and the resulting annual streamflow, had been decreasing from the 1960s until the start of this century [18]. From the 1960s to the 2010s, the observed streamflow showed a negative trend in the Songhua Basin [19], but a positive one in the Tarim River Basin [20].

Some researchers employed hydrological models, such as the Variable Infiltration Capacity (VIC) model, to simulate the hydrological cycle over this region. Hydrological models have their advantages in considering forces from climate, land cover, soil and topography conditions. In the Yellow River Basin which is in TNR, simulation results of VIC model have indicated that the effects of climate change were stronger than those of LCC [21,22]. Some studies have also focused on future changes in the hydrological cycle and applied the VIC model to detect the hydrological response to future climate change under a Representative Concentration Pathway (RCP8.5) scenario and found that, in Northern China, the evaporation and runoff will increase, while soil moisture will decline [23].

Since ecological restoration programs first began, a few studies have been performed to determine whether or not they have had a positive impact. Results show that from 1970s, with the growing afforestation, windy days and dust storms have declined sharply over a wide range of area. In Northwest, North and Northeast China, the number of windy days had decreased by nearly 50%, and so did the number of dust storms. However, a few studies also show that the effectiveness of these programs may have been overestimated [15]. Although they have had some beneficial impacts on controlling dust storms in arid and semi-arid areas in China, the ecological improvements have been very limited. The desertification rates (fractions of total area that has undergone desertification) did not decline after the construction of the afforestation programs, and even rose in some zones. For example, in northeast China, the rate was more than 40% in early 2000s, which is over four times that in mid-1970s [15]. Furthermore, some simulation results have suggested changes in the hydrological conditions of the TNR are mainly due to climate change, especially the redistribution of precipitation, while the contribution of LCC may be very minimal. From 1989 to 2009, climate change contributed to a loss of over 25 mm in ET and over 14 mm in R, while LCC only resulted in small changes no more than 2 mm in these two elements [24].

The majority of studies on the effects of LCC have focused on historical periods, using different methods, such as observation or stimulation based on historical data. However, in future, the climate may be different, since there has been a warmer trend globally, and the effects of LCC may be also influenced by climate change. So, the question remains: will the effects of past LCC on hydrological cycle be changed under future climate scenario within the TNR? Additionally, the exploration can be seen as an evaluation of ecological programs, since the LCC over TNR were affected significantly by those programs, especially in semi-arid and arid areas. The programs have been in place for over 40 years, ye<sup>t</sup> their influence may not be well-recognized due to the short time series.

In this study, the dependence of the future hydrological regime (2020–2099) on past LCC (from 1986 to 2015) in the TNR was evaluated. A macro-scale hydrological model (i.e., the variable infiltration capacity (VIC) model [25,26]) was employed to simulate the hydrological processes over the entire region. Model simulations were performed based on different vegetation parameters generated by datasets from historical land cover information, and the simulations were forced with climate data sets from global climate models (GCMs) from the Inter-Sectoral Impact Model Inter-comparison Project (ISI-MIP) [27]. As this study was aimed at understanding the implications of past LCC on the future hydrological regime, model simulations were performed using historical land cover data rather than the projected future land cover information. The work can be seen as an evaluation for the effects of the ecological restoration programs constructed in past decades, since these programs played a significant role in altering land cover condition, so it may provide some guidance for the following construction of the programs.

#### **2. Data and Methods**
