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71.
Ressi is a small (2.4 ha) forested catchment located in the Italian pre-Alps. The site became an experimental catchment to investigate the water fluxes in the soil–plant–atmosphere continuum and the impact of vegetation on runoff generation in 2012. The elevation of the catchment ranges from 598 to 721 m a.s.l. and the climate is humid temperate. The bedrock consists of rhyolites and dacites; the soil is a Cambisol. The catchment is covered by a dense forest, dominated by beech, chestnut, maple, and hazel trees. The field set up includes measurements of the rainfall in an open area, streamflow at the outlet, soil moisture at various depths and locations, and depth to water table in six piezometers at a 5- or 10-min interval. Samples of precipitation, stream water, shallow groundwater and soil water are collected monthly for tracer analysis (stable isotopes (2H and 18O), electrical conductivity and major ions), and during selected rainfall–runoff events to determine the contribution of the various sources to runoff. Since 2017, soil and plant water samples have been collected to determine the sources of tree transpiration. Data collected in the period 2012–2016 are publicly available. Data collection is ongoing, and the data set is expected to be updated on an annual basis to include the most recent measurements.  相似文献   
72.
Understanding how rivers respond to changes in land cover, climate, and subsurface conditions is critical for sustainably managing water resources and ecosystems. In this study, long‐term hydrologic, climate, and satellite data (1973–2012) from the Upper Tahe River watershed (2359 km2) in the Da Hinggan Mountains of northeast China were analysed to quantify the relative hydrologic effects of climate variability (system input) and the combined influences of forest cover change and permafrost thaw (system characteristics) on average annual streamflow (system response) using 2 methods: the sensitivity‐based method and the Kendall–Theil robust line method. The study period was subdivided into a forest harvesting period (1973–1987), a forest stability period (1988–2001), and a forest recovery period (2002–2012). The results indicated that the combined effects of forest harvesting and permafrost thaw on streamflow (+ 47.0 mm) from the forest harvesting period to the forest stability period was approximately twice as large as the effect associated with climate variability (+20.2 mm). Similarly, from the forest stability period to the forest recovery period, the decrease in average annual streamflow attributed to the combined effects of forest recovery and permafrost thaw (?38.0 mm) was much greater than the decrease due to climate variability (?22.2 mm). A simple method was used to separate the distinct impacts of forest cover change and permafrost thaw, but distinguishing these influences is difficult due to changes in surface and subsurface hydrologic connectivity associated with permafrost thaw. The results highlight the need to consider multiple streamflow drivers in future watershed and aquatic ecosystem management. Due to the ecological and hydrological susceptibility to disturbances in the Da Hinggan Mountains, forest harvesting will likely negatively impact ecohydrological processes in this region, and the effects of forest species transition in the forest recovery process should be further investigated.  相似文献   
73.
Sugarcane is an annual crop with a dynamic canopy that changes over time mainly because of genetic adaptation. There is uncertainty about the temporal trends of throughfall (TF) in this important commercial crop. In the present paper, we used troughs to measure TF in a third and fourth ratoon and subsequently in a fourth and fifth ratoon. Additional measurements were carried out in an adjacent riparian forest. There were no significant differences between cycles of sugarcane, growth phases and riparian forest. The TF results for ratoon crop and riparian forest in 2011/2012 were 76% and 79.5% of gross rainfall, respectively, while in 2012/2013, they were 79% and 78%, respectively. However, TF was remarkably lower in the riparian forest relative to ratoon from the second half of the culm formation and elongation phase (280 days after harvest) until harvest. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   
74.
Gravel road surfaces can be a major source of fine sediment to streams, yet their contribution to channel reach sediment balances remains poorly documented. To quantify the input of road surface material and to compare this input with natural sediment sources at the reach scale, suspended sediment dynamics was examined and a 16‐month sediment balance was developed for a ~35 channel‐width (approx. 425 m) reach of the Honna River, a medium‐size, road‐affected stream located in coastal British Columbia. Of the 105 ± 33 t of suspended material passing through the reach, 18 ± 6% was attributed to the road surface. The high availability of sediment on the road surface appears to limit hysteresis in road run‐off. During rainstorms that increase streamflow, road surface material composed 0.5–15% of sediment inputs during relatively dry conditions from April to the end of September and 5–70% through wetter conditions from October to the end of March, but our data do not show evidence of major sediment accumulation on the riverbed in the reach. A comparison of modelled sediment production on the road surface with observed yields from drainage channels suggests that (1) during low intensity rainfall, ditches and drainage channels may trap sediment from road run‐off, which is subsequently released during events of greater intensity, and/or (2) production models do not effectively describe processes, such as deposition or erosion of sediment in ditches, which control sediment transport and delivery. Our findings further emphasize the risk of unpaved roads in polluting river systems and highlight the continued need for careful road design and location away from sensitive aquatic environments. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   
75.
The study of water fluxes is important to better understand hydrological cycles in arid regions. Data-driven machine learning models have been recently applied to water flux simulation. Previous studies have built site-scale simulation models of water fluxes for individual sites separately, requiring a large amount of data from each site and significant computation time. For arid areas, there is no consensus as to the optimal model and variable selection method to simulate water fluxes. Using data from seven flux observation sites in the arid region of Northwest China, this study compared the performance of random forest (RF), support vector machine (SVM), back propagation neural network (BPNN), and multiple linear regression (MLR) models in simulating water fluxes. Additionally, the study investigated inter-annual and seasonal variation in water fluxes and the dominant drivers of this variation at different sites. A universal simulation model for water flux was built using the RF approach and key variables as determined by MLR, incorporating data from all sites. Model performance of the SVM algorithm (R2 = 0.25–0.90) was slightly worse than that of the RF algorithm (R2 = 0.41–0.91); the BPNN algorithm performed poorly in most cases (R2 = 0.15–0.88). Similarly, the MLR results were limited and unreliable (R2 = 0.00–0.66). Using the universal RF model, annual water fluxes were found to be much higher than the precipitation received at each site, and natural oases showed higher fluxes than desert ecosystems. Water fluxes were highest during the growing season (May–September) and lowest during the non-growing season (October–April). Furthermore, the dominant drivers of water flux variation were various among different sites, but the normalized difference vegetation index (NDVI), soil moisture and soil temperature were important at most sites. This study provides useful insights for simulating water fluxes in desert and oasis ecosystems, understanding patterns of variation and the underlying mechanisms. Besides, these results can make a contribution as the decision-making basis to the water management in desert and oasis ecosystems.  相似文献   
76.
77.
在对极化干涉SAR森林树高反演的DEM差值算法、相干相位-幅度综合反演算法进行分析的基础上,对基于极化干涉相干优化方法的改进算法进行了探讨。利用黑龙江大兴安岭地区的一对ALOS全极化干涉SAR数据进行实验,并对比分析各算法的反演结果。结果表明,在使用改进的算法进行森林树高反演时可以获取精度较高的反演结果,并且在一定程度上提高了森林树高反演的稳定性,为森林树高反演工作的业务化运行提供一定的依据。  相似文献   
78.
Using the NASA Earth Exchange platform, the North American Forest Dynamics (NAFD) project mapped forest history wall-to-wall, annually for the contiguous US (1986–2010) using the Vegetation Change Tracker algorithm. As with any effort to identify real changes in remotely sensed time-series, data gaps, shifts in seasonality, misregistration, inconsistent radiometry and cloud contamination can be sources of error. We discuss the NAFD image selection and processing stream (NISPS) that was designed to minimize these sources of error. The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration, unreliability of the pre-2009 L5 cloud cover assessments algorithm, missing growing-season imagery and paucity of clear views. Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study. Over 150,000+ Landsat images were considered for the NAFD project. Optimally, one high quality cloud-free image in each year or a total of 12,152 images would be used. However, to accommodate data gaps and cloud/shadow contamination 23,338 images were needed. In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.  相似文献   
79.
Fire disturbance in many tropical forests, including peat swamps, has become more frequent and extensive in recent decades. These fires compromise a variety of ecosystem services, among which mitigating global climate change through carbon storage is particularly important for peat swamps. Indonesia holds the largest amount of tropical peat carbon globally, and mean annual CO2 emissions from decomposition of deforested and drained peatlands and associated fires in Southeast Asia have been estimated at ∼2000 Mt y-1. A key component to understanding and therefore managing fire in the region is identifying the land use/land cover classes associated with fire ignitions. We assess the oft-asserted claim that escaped fires from oil palm concessions and smallholder farms near settlements are the primary sources of fire in a peat-swamp forest area in Central Kalimantan, Indonesia, equivalent to around a third of Kalimantan's total peat area. We use the MODIS Active Fire product from 2000 to 2010 to evaluate the fire origin and spread on the land use/land cover classes of legal, industrial oil palm concessions (the only type of legal concession in the study area), non-forest, and forest, as well as in relation to settlement proximity. We find that most fires (68–71%) originate in non-forest, compared to oil palm concessions (17%–19%), and relatively few (6–9%) are within 5 km of settlements. Moreover, most fires started within oil palm concessions and in close proximity to settlements stay within those boundaries (90% and 88%, respectively), and fires that do escape constitute only a small proportion of all fires on the landscape (2% and 1%, respectively). Similarly, a small proportion of fire detections in forest originate from oil palm concessions (2%) and within close proximity to settlements (2%). However, fire ignition density in oil palm (0.055 ignitions km−2) is comparable to that in non-forest (0.060 km-2 ignitions km-2), which is approximately ten times that in forest (0.006 ignitions km−2). Ignition density within 5 km of settlements is the highest at 0.125 ignitions km−2. Furthermore, increased anthropogenic activity in close proximity to oil palm concessions and settlements produces a detectable pattern of fire activity. The number of ignitions decreases exponentially with distance from concessions; the number of ignitions initially increases with distance from settlements, and, around from 7.2 km, then decreases with distance from settlements. These results refute the claim that most fires originate in oil palm concessions, and that fires escaping from oil palm concessions and settlements constitute a major proportion of fires in this study region. However, there is a potential for these land use types to contribute substantially to the fire landscape if their area expands. Effective fire management in this area should therefore target not just oil palm concessions, but also non-forested, degraded areas where ignitions and fires escaping into forest are most likely to occur.  相似文献   
80.
This study assesses whether MODIS Vegetation Continuous Fields percent tree cover (PTC) data can detect deforestation and forest degradation. To assess the usefulness of PTC for detecting deforestation, we used a data set consisting of eight forest and seven non-forest categories. To evaluate forest degradation, we used data from two temperate forest types in three conservation states: primary (dense), secondary (moderately degraded) and open (heavily degraded) forest. Our results show that PTC can differentiate temperate forest from non-forest categories (p = 0.05) and thus suggests PTC can adequately detect deforestation in temperate forests. In contrast, single-date PTC data does not appear to be adequate to detect forest degradation in temperate forests. As for tropical forest, PTC can partially discriminate between forest and non-forest categories.  相似文献   
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