Effects of spatially structured vegetation patterns on hillslope erosion in a semiarid Mediterranean environment: a simulation study

A general trend of decreasing soil loss rates with increasing vegetation cover fraction is widely accepted. Field observations and experimental work, however, show that the form of the cover‐erosion function can vary considerably, in particular for low cover conditions that prevail on arid and semiarid hillslopes. In this paper the structured spatial distribution of the vegetation cover and associated soil attributes is proposed as one of the possible causes of variation in cover–erosion relationships, in particular in dryland environments where patchy vegetation covers are common. A simulation approach was used to test the hypothesis that hillslope discharge and soil loss could be affected by variation in the spatial correlation structure of coupled vegetation cover and soil patterns alone. The Limburg Soil Erosion Model (LISEM) was parameterized and verified for a small catchment with discontinuous vegetation cover at Rambla Honda, SE Spain. Using the same parameter sets LISEM was subsequently used to simulate water and sediment fluxes on 1 ha hypothetical hillslopes with simulated spatial distributions of vegetation and soil parameters. Storms of constant rainfall intensity in the range of 30–70 mm h^?1 and 10–30 min duration were applied. To quantify the effect of the spatial correlation structure of the vegetation and soil patterns, predicted discharge and soil loss rates from hillslopes with spatially structured distributions of vegetation and soil parameters were compared with those from hillslopes with spatially uniform distributions. The results showed that the spatial organization of bare and vegetated surfaces alone can have a substantial impact on predicted storm discharge and erosion. In general, water and sediment yields from hillslopes with spatially structured distributions of vegetation and soil parameters were greater than from identical hillslopes with spatially uniform distributions. Within a storm the effect of spatially structured vegetation and soil patterns was observed to be highly dynamic, and to depend on rainfall intensity and slope gradient. Copyright © 2005 John Wiley & Sons, Ltd.     

Soil respiration in tropical seasonal rain forest in Xishuangbanna, SW China

With the static opaque chamber and gas chromatography technique, from January 2003 to January 2004 soil respiration was investigated in a tropical seasonal rain forest in Xishuangbanna, SW China. In this study three treatments were applied, each with three replicates: A (bare soil), B (soil+litter), and C (soil+litter+seedling). The results showed that soil respiration varied seasonally, low from December 2003 to February 2004, and high from June to July 2004. The annual average values of CO2 efflux from soil respiration differed among the treatments at 1% level, with the rank of C (14642 mgCO2· m-2. h-1)＞B (12807 mgCO2· m-2. h-1)＞A (9532 mgCO2· m-2. h-1). Diurnal variation in soil respiration was not apparent due to little diurnal temperate change in Xishuangbanna. There was a parabola relationship between soil respiration and soil moisture at 1% level. Soil respiration rates were higher when soil moisture ranged from 35% to 45%. There was an exponential relationship between soil respiration and soil temperature (at a depth of 5cm in mineral soil) at 1% level. The calculated Q1o values in this study,ranging from 2.03 to 2.36, were very near to those of tropical soil reported. The CO2 efflux in 2003was 5.34 kgCO2· m-2. a-1 from soil plus litter plus seedling, of them 3.48 kgCO2· m-2. a-1 from soil (accounting for 62.5%), 1.19 kgCO2· m-2. a-1 from litter (22.3%) and 0.67 kgCO2·m-2. a-1 from seedling (12.5%).     

The diurnal and seasonal characteristics of urban heat island variation in Beijing city and surrounding areas and impact factors based on remote sensing satellite data

Based on the land surface temperature (LST), the land cover classification map,vegetation coverage, and surface evapotranspiration derived from EOS-MODIS satellite data, and by the use of GIS spatial analytic technique and multivariate statistical analysis method, the urban heat island (UHI) spatial distribution of the diurnal and seasonal variabilities and its driving forces are studied in Beijing city and surrounding areas in 2001. The relationships among UHI distribution and landcover categories, topographic factor, vegetation greenness, and surface evapotranspiration are analyzed. The results indicate that: (i) The significant UHI occur in Beijing city areas in the four seasons due to high heat capacity and multi-reflection of compression building, as well as with special topographic features of its three sides surrounded by mountains,especially in the summer. The UHI spatial distribution is corresponding with the urban geometry structure profile. The LST difference is approximately 4-6℃ between Beijing city and suburb areas, comparatively is 8- 10℃ between Beijing city area and outer suburb area in northwestern regions. (ii) The UHI distribution and intensity in daytime are different from nighttime in Beijing city area, the nighttime UHI is obvious. However, in the daytime, the significant UHI mainly appears in the summer, the autumn takes second place, and the UHI in the winter and the spring seem not obvious. The surface evapotranspiration in suburb areas is larger than that in urban areas in the summer, and high latent heat exchange is evident, which leads to LST difference between city area and suburb area. (iii) The reflection of surface landcover categories is sensitive to the UHI, the correlation between vegetation greenness and UHI shows obviously negative.The scatterplot shows that there is the negative correlation between NDVI and LST (R2 = 0.6481).The results demonstrate that the vegetation greenness is an important factor for reducing the UHI,and large-scale construction of greenbelts can considerably reduce the UHI effect.     

Growth patterns and implications of complex dendrites in calcite travertines from Lýsuhóll, Snæfellsnes, Iceland

Calcite dendrite crystals are important but poorly understood components of calcite travertine that forms around many hot springs. The Lýsuhóll hot-spring deposits, located in western Iceland, are formed primarily of siliceous sinters that were precipitated around numerous springs that are now inactive. Calcite travertine formed around the vent and on the discharge apron of one of the springs at the northern edge of the area. The travertine is formed largely of two types (I and II) of complex calcite dendrite crystals, up to 1 cm high, that grew through the gradual addition of trilete sub-crystals. The morphology of the dendrite crystals was controlled by flow direction and the competition for growth space with neighbouring crystals. Densely crowded dendrites with limited branching characterize the rimstone dams whereas widely spaced dendrites with open branching are found in the pools. Many dendrite bushes in the pools nucleated around plant stems. Growth of the dendrite crystals was seasonal and incremental. Calcite precipitation was driven by rapid CO₂ degassing of CO₂-rich spring waters during the spring and summer. During winter, when snow covered the ground and temperatures were low, opal-A precipitated on the exposed surfaces of the dendrites. Segmentation of dendrite branches by discontinuities coated with opal-A and overgrowth development around sub-crystals resulted from this seasonal growth cycle. The calcite dendrite crystals in the Lýsuhóll travertine differ in morphology from those at other hot springs, such as those at Lake Bogoria, Kenya, and Waikite in New Zealand. Comparison with the calcite dendrite crystals found at those sites shows that dendrite morphology is site-specific and probably controlled by carbonate saturation levels that, in turn, are controlled by the rate of CO₂ degassing and location in the spring outflow system.     

Nutrient chemistry of groundwater in an intensively irrigated region of southern India

The concentration of nutrients in groundwater acts as an indicator to identify the influence of agricultural activities on the shallow subsurface environment. Hence, the present study was carried out to assess nutrient concentration (nitrate, phosphate and potassium) and understand its spatial and seasonal variations in the groundwater of Palar and Cheyyar River basin, Tamil Nadu, India. The groundwater samples collected from 43 wells were analyzed for nutrients once a month from January 1998 to June 1999. Results of the study suggested that agricultural activities, including application of fertilizers, soil mineralization processes and irrigation return flow, are major processes regulating the nutrients chemistry in the groundwater of this region. Groundwater in the sedimentary formation has comparatively higher concentration of nutrients than the groundwater in hard rock formations, which seems to be due to the adsorption of nutrients by the weathered rock materials. The seasonal water level fluctuation shows that rising water level increases nutrients concentration in groundwater due to the agriculture related activities. The results also indicate that nitrate and potassium concentrations are within the recommended drinking water limits, whereas phosphate concentration exceeds its drinking water limit and 35% of the samples are unsuitable for drinking purposes.Electronic Supplementary Material Supplementary material is available for this article at     

Seasonal records of climatic change in annually laminated tufas: short review and future prospects

Many Recent and fossil freshwater tufa stromatolites contain millimetre‐scale, alternating laminae of dense micrite and more porous or sparry crystalline calcites. These alternating laminae have been interpreted to represent seasonally controlled differences in the biotic activity of microbes, and/or seasonally controlled changes in the rate of calcification. Either way, couplets of these microbially mediated alternating calcified laminae are generally agreed to represent annual seasonality. Combined stable isotope (δ¹⁸O and δ¹³C) and trace element (Mg, Sr, Ba) geochemistry from Recent tufa stromatolites show that seasonal climatic information is available from these calcites. Variability in δ¹⁸O (and in one case Mg concentration) has been shown to be controlled primarily by stream temperature change, usually driven by solar insolation. In arid climates, seasonal evaporation can also cause δ¹⁸O enrichment by at least 1‰. Variability in δ¹³C results potentially from: (1) seasonal change in plant uptake of ¹²C‐enriched CO₂; (2) seasonal change in degassing of ¹²C‐enriched CO₂ in the aquifer system; and (3) precipitation of calcite along the aquifer or river flow path, a process that increases δ¹³C of dissolved inorganic carbon (DIC) in the remaining water. Mechanisms 2 and 3 are linked because calcite precipitates in aquifers where degassing occurs, e.g. air pockets. The latter mechanism for δ¹³C enrichment has also been shown to cause sympathetic variation between trace element/Ca ratios and δ¹³C because trace elements with partition coefficients much greater than 1 (e.g. Sr, Ba) remain preferentially in solution. Since degassing in air pockets will be enhanced during decreased recharge when water saturation of the aquifer is lowest, sympathetic variation in trace element/Ca ratios and δ¹³C is a possible index of recharge and therefore precipitation intensity. High‐resolution geochemical data from well‐dated tufa stromatolites have great potential for Quaternary palaeoclimate reconstructions, possibly allowing recovery of annual seasonal climatic information including water temperature variation and change in rainfall intensity. However, careful consideration of diagenetic effects, particularly aggrading neomorphism, needs to be the next step. Copyright © 2005 John Wiley & Sons, Ltd.     

中国陆地净初级生产力的季节变化研究

了解不同季节陆地净初级生产力(NPP)的变化及与气候的相互关系以及在不同地类的差异对深刻理解我国陆地生态系统对全球气候变化的响应和陆地碳循环研究具有重要意义。本文使用1981～2000年间GLO-PEM模型模拟的我国陆地NPP数据和同期气温、降水以及土地利用数据, 研究不同季节我国陆地植被NPP的变化。结果表明,在1981～2000年期间,四个季节的NPP都呈显著增加趋势,春季是NPP增加速率最快的季节,夏季是NPP增加量最大的季节。耕地在春、夏和秋季NPP增长和增长率最高,林地冬季NPP增长最多而水域冬季NPP增长率最高。夏季NPP增长最高的区域分布于我国东部的多数地区、内蒙古东部、四川盆地、贵州东部、藏南和新疆西部;夏季NPP降低最多的区域分布于在呼伦贝尔高原、鄂尔多斯高原、黄土高原、青藏高原东部和新疆西北部。     

Spatiotemporal estimation of snow depth using point data from snow stakes,digital terrain models,and satellite data

Snow availability in Alpine catchments plays an important role in water resources management. In this paper, we propose a method for an optimal estimation of snow depth (areal extension and thickness) in Alpine systems from point data and satellite observations by using significant explanatory variables deduced from a digital terrain model. It is intended to be a parsimonious approach that may complement physical‐based methodologies. Different techniques (multiple regression, multicriteria analysis, and kriging) are integrated to address the following issues: We identify the explanatory variables that could be helpful on the basis of a critical review of the scientific literature. We study the relationship between ground observations and explanatory variables using a systematic procedure for a complete multiple regression analysis. Multiple regression models are calibrated combining all suggested model structures and explanatory variables. We also propose an evaluation of the models (using indices to analyze the goodness of fit) and select the best approaches (models and variables) on the basis of multicriteria analysis. Estimation of the snow depth is performed with the selected regression models. The residual estimation is improved by applying kriging in cases with spatial correlation. The final estimate is obtained by combining regression and kriging results, and constraining the snow domain in accordance with satellite data. The method is illustrated using the case study of the Sierra Nevada mountain range (Southern Spain). A cross‐validation experiment has confirmed the efficiency of the proposed procedure. Finally, although it is not the scope of this work, the snow depth is used to asses a first estimation of snow water equivalent resources.     

Landscape controls on long‐term runoff in subhumid heterogeneous Boreal Plains catchments

We compared median runoff (R) and precipitation (P) relationships over 25 years from 20 mesoscale (50 to 5,000 km²) catchments on the Boreal Plains, Alberta, Canada, to understand controls on water sink and source dynamics in water‐limited, low‐relief northern environments. Long‐term catchment R and runoff efficiency (RP^?1) were low and varied spatially by over an order of magnitude (3 to 119 mm/year, 1 to 27%). Intercatchment differences were not associated with small variations in climate. The partitioning of P into evapotranspiration (ET) and R instead reflected the interplay between underlying glacial deposit texture, overlying soil‐vegetation land cover, and regional slope. Correlation and principal component analyses results show that peatland‐swamp wetlands were the major source areas of water. The lowest estimates of median annual catchment ET (321 to 395 mm) and greatest R (60 to 119 mm, 13 to 27% of P) were observed in low‐relief, peatland‐swamp dominated catchments, within both fine‐textured clay‐plain and coarse‐textured glacial deposits. In contrast, open‐water wetlands and deciduous‐mixedwood forest land covers acted as water sinks, and less catchment R was observed with increases in proportional coverage of these land covers. In catchments dominated by hummocky moraines, long‐term runoff was restricted to 10 mm/year, or 2% of P. This reflects the poor surface‐drainage networks and slightly greater regional slope of the fine‐textured glacial deposit, coupled with the large soil‐water and depression storage and higher actual ET of associated shallow open‐water marsh wetland and deciduous‐forest land covers. This intercatchment study enhances current conceptual frameworks for predicting water yield in the Boreal Plains based on the sink and source functions of glacial landforms and soil‐vegetation land covers. It offers the capability within this hydro‐geoclimatic region to design reclaimed catchments with desired hydrological functionality and associated tolerances to climate or land‐use changes and inform land management decisions based on effective catchment‐scale conceptual understanding.     

Diagnosing snow accumulation errors in a rain‐snow transitional environment with snow board observations

Diagnosing the source of errors in snow models requires intensive observations, a flexible model framework to test competing hypotheses, and a methodology to systematically test the dominant snow processes. We present a novel process‐based approach to diagnose model errors through an example that focuses on snow accumulation processes (precipitation partitioning, new snow density, and snow compaction). Twelve years of meteorological and snow board measurements were used to identify the main source of model error on each snow accumulation day. Results show that modeled values of new snow density were outside observational uncertainties in 52% of days available for evaluation, while precipitation partitioning and compaction were in error 45% and 16% of the time, respectively. Precipitation partitioning errors mattered more for total winter accumulation during the anomalously warm winter of 2014–2015, when a higher fraction of precipitation fell within the temperature range where partition methods had the largest error. These results demonstrate how isolating individual model processes can identify the primary source(s) of model error, which helps prioritize future research.