5.1 Forest Cover Impacts on Streamflow Regulation
Studies concerning the impact of forest cover changes on the magnitude of Qt in Himalayan regions are rare (Sharma et al. 2007; Ashraf et al. 2013; Tiyagi et al. 2014); however, studies related to components of Qt (baseflow and stormflow) are even the rarest in the Himalayan regions. During the study period, the annual cycle of P represented both dry and wet-period (Figure 3), thus allowed to study baseflow and stormflow conditions of the catchments. In the same line, Qt at the catchments also showed distinctive behavior during dry and wet-periods (Figure 3), due to highly seasonal P in the CHR (Banerjee et al. 2020). Dry-period represented the greater part of annual hyetograph, however, wet-period represented the main driver for the Qt generation. The 2nd order polynomial relationship between P and Qt (Figure-10 A) allowed the identification of P threshold (~200 mm), and when this threshold exceeds, Qt generation increased significantly at both the catchments (Figure-10 A). The same threshold value (~200 mm), which accounts as ~10% of annual P were also observed in Figure 4B. This P threshold averagely occurred during mid of June, and before June, the low magnitude P (below 200 mm per month) potentially contributes to satisfies several hydrological processes e.g., initial infiltration, SM, ground water stress and ET (Tarboton 2003) at both the catchments. The P threshold values of both the catchments can be helpful to predict Qt generation (Kirkby et al. 2005, Gioia et al. 2008; Kampf et al. 2018) which are vital for sustenance of streams and regulation of numerous ecological processes (Poff et al. 1997; Doll et al. 2015). Separation of hydrographs (Arnigad and Bansigad) into stormflow (6% and 31%) and baseflow (50% and 32%), Figure 4A and B, vastly improves our understanding of Qt regulation at catchment-scale and surely will be helpful for water resource management (Nepal et al. 2014) in the CHR.
Arnigad catchment showed lower annual Qt and higher ET compared to the Bansigad catchment (Figure 6). Despite having higher ET, annual baseflow component was higher by ~52% relative to Bansigad. This was because of forest floor components (i.e. litter layer, or the accumulation of leaves, twigs, and other vegetative debris), which increased OM, porosity, clay and silt content in soil, resulted in better soil formation at Arnigad catchment (Figure 8), further led to higher SM retention (O'Geen 2013) relative to Bansigad. Furthermore, these forest floor components might also act as effective shade barrier on the soil surface and reduce the rate of air exchange between the soil and the atmosphere, resulted in SM retention (Edwards et al., 2015). Besides, higher TD and DBH at Arnigad, indicated deep rooting which facilitate rapid drainage to deeper layers via macropores (Noguchi et al. 1997, Bargués Tobella et al. 2014). Their dominance (Arnigad) in controlling SM retention was critical to retaining moisture within the soil. P moving in macropores resupply to groundwater, known as groundwater recharge. Groundwater released water with a slow recession rate (Figure 5) subsequently during dry-period to Qt through contributions known as baseflow, which makes the stream perennial (at Arnigad) with a mean baseflow of ~83 mm (~ 6% of annual baseflow). Whereas, mean baseflow of only ~30 mm (~3% of annual baseflow) was available till February month which was not sufficient to make Bansigad stream sustainable during few months (March to May) of dry-period (Figure 4A). The study indicated that both streams were dependent on P for Qt generation, but the P at Arnigad sustained baseflow during dry-period through different mechanism of forest components. Furthermore, the baseflow and stormflow at Bansigad showed larger variations as compared to Arnigad (Figure 4B), the large variation was due to the faster recession rates at Bansigad catchment during the dry-period, with reaction/response factors of 0.028 day-1 compared to Arnigad catchment (0.0083 day-1). The faster recession rate at Bansigad, diminished Qt completely during dry-period, however, at dense forest (Arnigad) the baseflow was higher by ~52% annually, helped to maintain Qt year the round. Hence, the higher proportion of the stormflow at Bansigad, indicated higher probability of water resources problems such as flooding in the wet-period and drought in the dry-period. Baseflow recessions are important for the management of both ground water and surface water resources during dry-period (Miller et al. 2016).
The 40 selected hydrographs revealed the response of catchments after P, exhibited that the lag time generally increased for small and early wet-period events and decreased for larger events. Lag time of both the catchments ranged between 0:15 to 0:45 hour. If the time gap between two consecutive P were larger, lag time of hydrographs also became larger and during wet-period when the catchments were fully saturated with SM, few P events immediately become runoff/stream discharge. Among 40 hydrographs, it was observed that only three P events started and finished at same time period (29.07.08 to 31.07.08) at both the catchments. Furthermore, these events occurred in July, peak of the monsoon, and it is obvious that soil was fully saturated. Therefore, this time period gave an opportunity to compare both volume of water (discharge) and lag time between catchments. Therefore, these 3-hydrographs along with corresponding hyetographs at same time period from 29.07.08 to 31.07.08 and at same interval (15-minute interval) were analyzed in detail (Figure 11). There was no significant difference (p = 0.05) in P events between Arnigad (36-109 mm) and Bansigad (47-118 mm), however, there was significant difference in discharge between Arnigad (0.60-0.81 m3s-1) and Bansigad (0.81-1.32 m3s-1), respectively. Further, lag time of these three events were: 0:45, 0:45 and 0:30 hr (Arnigad) and 0:30, 0:30 and 0:15 hr (Bansigad), respectively (Figure 11). The shape of the different hydrographs varied with each individual P event. The analysis revealed that during wet-period, Arnigad releases lower volume of water and took averagely 15 minutes extra (compared to Bansigad) to reach to gauging site and potentially this behaviour of hydrographs (at Arnigad) may possibly be because of many combined factors: (i) slow recession rate of baseflow at Arnigad (Figure 5), (ii) higher potential of forest soil to store water at Arnigad (Figure 7) and (iii) higher infiltration rate (table 2). Therefore, the volume of water that was stored (at Arnigad) during P events and longer lag time supported the flow to release during a recession, helped in maintaining baseflow during dry-period, which is important ecosystem function of the catchment. Hence, the study indicates that forest cover at Arnigad showed significant and positive relationship with both baseflow and stormflow. These results are needed to effectively manage current and future land use and water resources problems in CHR.
The Non-linear relationships between Qt and SM (Figure 10 B) allowed the identification of threshold value (~35%) of SM. When the SM threshold was exceeded, baseflow was activated, increased significantly and became a major contributor to stormflow. A clear threshold (~35%) between SM and Qt, revealed the importance of initial moisture conditions, which determined the extent of the saturation and controls the Qt production of the entire catchment (Penna et al., 2010). The threshold value (0.35) was very close to mean field capacity (0.35 and 0.33) at Arnigad and Bansigad, respectively. This further confirms that the activation of Qt occurred only after soil attained threshold SM value of 35%. Other studies have observed SM threshold as: 45% (Penna et al. 2011; Song and Wang 2019), 26% (Farrick and Branfireun 2014) and 23% (James and Roulet 2007) supported the importance of initial moisture conditions and above the SM threshold, Qt activation indicated the occurrence of Qt from the hillslope. The difference in threshold values might be due to difference in topography, climate, land use characteristics, soil characteristics and sampling designs. Therefore, our results showed that two factors: SM and P were responsible for Qt activation and generation. Figure 4A and B, indicates that June month was the transition period, when hydrological functioning (Qt activation and generation) of the catchments begins to activate and October was again a transition period when hydrological functioning begins to inactivate. The non-linear behavior is common in hydrological systems (Zuecco et al. 2018) and this thresholds can be used as a classification tool to better conceptualize runoff response behavior under a range of weather conditions (Ali et al. 2013; 2015).
OM showed direct positive linear relationship with tree density (Figure 12A). Higher tree density means higher OM in soil, which helps in binding soil particles together into stable aggregates, increasing porosity (Zuazo and Pleguezuelo 2008; Tobella et al. 2014), and finally lead to higher infiltration (Figure 12B). Both SM and vegetation were closely linked with each other; SM positively influence vegetation growth (Wang et al. 2007), whereas vegetation displays complex relationship with SM. More vegetation either conserve more water, causing retention of SM or consumption of water itself, causing the depletion of SM (Pielke et al. 1998; Wang et al. 2006). Hence, more vegetation may correspond either to increase (Bounoua et al. 2000; Buermann et al. 2001) or to decrease SM (Pielke et al. 1998; Wang et al. 2006). Hence, the present study supported the fact that forests/vegetation leads strong bond with SM and interestingly SM also showed positive and direct impact on infiltration rate (Figure 12C). Further work is required in future to understand these relationships at different spatial and temporal scale in CHR. However, these results are very much helpful to farmers, land managers and policy developers for the conversation and sustainable development of forest, soil and water resources, important in this region.
5.2. Soil Moisture Variation at Different Soil Profiles:
Temporal variations of SM at different depths under different forest covers are shown in Figure 7A. It was observed that SM at all different profiles was responsive to P events, though few events might have been missed as the data was measured at bi-weekly. The annual cycle of both the P and SM follows the same path with unimodal variation (Figure 7A), and SM reached its maximum during wet-period, when ~78% of annual P occurred. Furthermore, SM at all soil layers were below FC during dry-period, whereas, it was above FC during wet-period at both catchments (Figure 7A). Such behavior indicated that SM was mainly regulated by P (Varikoden and Revadekar 2018). It is observed from Figure 7A and B, that during the wet-period, the surface layers at both the catchments were wetter than other deeper layers. This was because low intensity P were likely to be retained at the soil surface layer (Li et al. 2016). The difference in SM at surface layer was even more distinct at Bansigad catchment, showed low interception losses due to degraded forest at Bansigad, resulting large volume of P could reach to the ground surface (Liu et al. 2018; Venkatraman and Ashwath 2016) and therefore, the Bansigad catchment showed higher (4%, annually) moisture regimes at surface layer than Arnigad (Figure 7B). At Arnigad catchment, SM was maximum at deeper layer (80 cm) than at 50 cm depth. This was possibly due to lower rate of water movement to the next soil layer or may be influence of lateral flow (within the soil layer) from the upslope due to change in the saturated hydraulic conductivity properties (Venkatesh et al. 2011). Many studies (Gutiérrez-Jurado et al. 2007; Toro-Guerrero et al. 2018) from hillslopes or areas having steep slopes supported active response of lateral flow to deeper soil layers, thus efficiently bypassing the shallower soils which are more exposed to ET. Therefore, SM in the hillslopes varies both in the vertical and lateral direction (Venkatesh et al. 2011). Annually, SM at Arnigad at 50 cm and 80 cm was enhanced by 13% and 31% in comparison with Bansigad (Figure 7B). These enhanced values indicated potential for soil water storage at forested catchment (Arnigad) and release the water slowly during the subsequent dry-period, which consequently helps in regulation of sustained stream flows in the Himalayan region. This can be further supported by the Figure 12, which shows that Arnigad had higher OM (21-89%) and higher porosity (3-11%) than Bansigad which helps Arnigad in retaining SM and upholding sponge characteristics (Qazi et al. 2017). The lowest values of volumetric SM (mean monthly) were recorded as 25% (Arnigad) and 21% (Bansigad), indicating low (19%) storage deficit at Bansigad relative to Arnigad. Therefore, water retention / flow regulation at dense forested catchment (Arnigad) was better as compared to the degraded forested catchment (Bansigad). Therefore, the present study suggests that forests plays important role in SM functioning at local sites (Bruijnzeel 2004) and provides hydrological service in different ways at catchment scale. However, further research work is required to understand the dynamics and transport of soil water content from shallow to deeper soil layers for potential ground water recharge.
5.3. Forest Cover Impacts on Sediment Transportation / Erosion Behavior:
Sediment transport is a function of several interacting factors including vegetation, climate, topography, parent material, and soil. P during the monsoon was the main driver and contributes significantly in annual sediment transportation (95%) in both the studied catchments (Figure 9A). While, forests regulated sediment transport activity in these catchments through different forest components (forest cover, understory, tree roots, and woody debris). Forest cover supported in reduction (18%) of suspended sediment production at Arnigad catchment through strong root system, holds soil particles tightly and doesn’t allow natural forces (wind and water) to take away the upper-most layer of the soil. Moreover, the understory (shrubs, herbs, leaf litter etc.) at Arnigad also helped in decrease of surface erosion by reduction of kinetic energy of raindrops (Fukuyama et al. 2010; Nanko et al. 2015). On the other hand, degraded forest along with high intensity P triggers loosened material and debris (Fuller et al. 2003), leads to landslides (Struck et al. 2015), and further to higher sediment production at Bansigad stream (Tyagi et al. 2014), continuously disturbing the natural system (Mukherjee, 2013) of the Bansigad catchment. The lower (75%) deposited BL material at Arnigad catchment (Figure 9C) was because of the standing trees, felled logs and understory of dense forest, which slow down the movement of big boulders, gravel and debris (Qazi et al. 2018). Moreover, the strong tree root system and organic humus layer supports slope stability, decreases landslides and debris flows frequency (Imaizumi et al. 2008; Nepal et al. 2014; Goetz et al. 2015), hence BL material couldn’t reach to the Arnigad stream relative to Bansigad stream. Hartanto et al. 2003; Imaizumi et al. 2019 also supports that large amount of sediments are captured by woody debris on hillslopes. Therefore, the present study ensures that forest plays important roles in regulating sediment transportation and forest plantation and conservation can be considered as an important way to improve the environment.
Interestingly, the concentration of dissolved material in streams at Arnigad was also enhanced by 114% (annually) as compared to Bansigad (Figure 9B). As both the catchments were located near to each other, the rock types and their erodibility are assumed to be the same. Apparently, the landuse or forest was the only element to account for higher dissolved solids at Arnigad catchment. Large quantity of OM are generated in the forest floor at Arnigad catchment, which decompose, percolate through rain water (Krishna and Mohan 2017), and reach to streams in dissolved form (Markewitz et al. 2004; Andrade et al. 2011; Cost et al. 2017). Hence, the dissolved OM effects TDS in the stream. Dry-period has significant impact on wide range of TDS at Bansigad, because TDS becomes more concentrated with decrease in discharge (Tipper et al. 2006; Calmels et al. 2011). TDS at both the catchments was the permissible limit according to WHO 2003; BIS 2012.
In the Himalayan region, high relief coupled with intensive P during monsoon provide favorable conditions for mass wasting (Korup and Weidinger 2011), which cause serious long-term problems e.g. functioning of hydropower plants, dam and river management, environmental flow, biological diversity, reservoir siltation, landslides etc. (Zokaib and Naser 2011; Hedrick et al. 2013; Sudhishri et al. 2014; Iwuoha et al. 2016). Reduction of annual sediment budget (Figure 9D) and denudation rate by 41% at Arnigad compared to Bansigad, further confirms the crucial role of trees and forests in preventing mass wastage which in turn maintains balances ecological functioning, biological diversity, landslides etc. at long term scale.