Estimation of potential evapotranspiration over the Yellow River basin: reference crop evaporation or Shuttleworth–Wallace?

Potential evapotranspiration (PET) is a key input to hydrological models. Its estimation has often been via the Penman–Monteith (P–M) equation, most recently in the form of an estimate of reference evapotranspiration (RET) as recommended by FAO‐56. In this paper the Shuttleworth–Wallace (S–W) model is implemented to estimate PET directly in a form that recognizes vegetation diversity and temporal change without reference to experimental measurements and without calibration. The threshold values of vegetation parameters are drawn from the literature based on the International Geosphere–Biosphere Programme land cover classification. The spatial and temporal variation of the LAI of vegetation is derived from the composite NOAA‐AVHRR normalized difference vegetation index (NDVI) using a method based on the SiB2 model, and the Climate Research Unit database is used to provide the required meteorological data. All these data inputs are publicly and globally available. Consequently, the implementation of the S–W model developed in this study is applicable at the global scale, an essential requirement if it is to be applied in data‐poor or ungauged large basins. A comparison is made between the FAO‐56 method and the S–W model when applied to the Yellow River basin for the whole of the last century. The resulting estimates of RET and PET and their association with vegetation types and leaf area index (LAI) are examined over the whole basin both annual and monthly and at six specific points. The effect of NDVI on the PET estimate is further evaluated by replacing the monthly NDVI product with the 10‐day product. Multiple regression relationships between monthly PET, RET, LAI, and climatic variables are explored for categories of vegetation types. The estimated RET is a good climatic index that adequately reflects the temporal change and spatial distribution of climate over the basin, but the PET estimated using the S–W model not only reflects the changes in climate, but also the vegetation distribution and the development of vegetation in response to climate. Although good statistical relationships can be established between PET, RET and/or climatic variables, applying these relationships likely will result in large errors because of the strong non‐linearity and scatter between the PET and the LAI of vegetation. It is concluded that use of the implementation of the S–W model described in this study results in a physically sound estimate of PET that accounts for changing land surface conditions. Copyright © 2006 John Wiley & Sons, Ltd.     

Forest ecosystem processes at the watershed scale: dynamic coupling of distributed hydrology and canopy growth

The hydrological recovery of watersheds from disturbances such as fire and harvest can change the magnitude and distribution of flow paths as the canopy regenerates. The spatial distribution of net water input to the soil–topography system is mediated by vegetation patterns through the processes of interception, evapotranspiration and snowmelt. We have previously described RHESSys, a distributed model of water and carbon flux with a prescribed canopy cover. Although the canopy structure varied spatially it did not change through time. We present an expanded model in which carbon and nitrogen are dynamically coupled with distributed hydrology. The model fixes and allocates canopy carbon annually to reflect changes in climate forcing. We test the interactions of the forest ecosystem to distributed hydrology through controlled experiments. In the first experiment, we prescribe canopy cover and examine the sensitivity of the hydrological outputs to the distribution of vegetation. The canopy distribution is found to have significant effects on simulated hydrological outputs where evaporative demand exceeds available water. In a second experiment we simulate the canopy leaf area index (LAI) across the topography and through time. The model is executed over 100 years using repeated 10-year meteorological records to investigate spatial and temporal patterns of LAI. Annual precipitation and temperature differences result in temporally fluctuating LAI about a reasonably stable long-term mean. The topographical position has a strong effect on local forest canopy characteristics. As expected, simulated ecosystem processes are found to be sensitive to rooting depth in more water limited environments. © 1997 John Wiley & Sons, Ltd.     

Potential evapotranspiration and its attribution over the past 50 years in the arid region of Northwest China

Evaporation paradox and its attribution have become a hot research topic in hydrology in recent years. This study estimates the potential evapotranspiration (ET₀) using modified Penman–Monteith method and analyzes the corresponding trend attribution based on the long‐term meteorological data collected at 81 ground‐based meteorological stations in Northwestern arid region of China during the period 1958–2010. The analysis results show: (1) The ET₀ has exhibited an obvious decreasing trend until the early 1990s; however, the downward trend has been reversed to an upward trend after then. (2) Decrease in diurnal temperature range (DTR) and wind speed (WS) may lead to the decrease of ET₀ during 1956–1993. The change of dominant factors in the ET₀ trend has differences after the early 1990s; observed increase in WS is the primary factor contributing to the reversion of ET₀. Copyright © 2012 John Wiley & Sons, Ltd.     

Climate sensitivity of water use by riparian woodlands at landscape scales

Semi-arid riparian woodlands face threats from increasing extractive water demand and climate change in dryland landscapes worldwide. Improved landscape-scale understanding of riparian woodland water use (evapotranspiration, ET) and its sensitivity to climate variables is needed to strategically manage water resources, as well as to create successful ecosystem conservation and restoration plans for potential climate futures. In this work, we assess the spatial and temporal variability of Cottonwood (Populus fremontii)-Willow (Salix gooddingii) riparian gallery woodland ET and its relationships to vegetation structure and climate variables for 80 km of the San Pedro River corridor in southeastern Arizona, USA, between 2014 and 2019. We use a novel combination of publicly available remote sensing, climate and hydrological datasets: cloud-based Landsat thermal remote sensing data products for ET (Google Earth Engine EEFlux), Landsat multispectral imagery and field data-based calibrations to vegetation structure (leaf-area index, LAI), and open-source climate and hydrological data. We show that at landscape scales, daily ET rates (6–10 mm day⁻¹) and growing season ET totals (400–1,400 mm) matched rates of published field data, and modelled reach-scale average LAI (0.80–1.70) matched lower ranges of published field data. Over 6 years, the spatial variability of total growing season ET (CV = 0.18) exceeded that of temporal variability (CV = 0.10), indicating the importance of reach-scale vegetation and hydrological conditions for controlling ET dynamics. Responses of ET to climate differed between perennial and intermittent-flow stream reaches. At perennial-flow reaches, ET correlated significantly with temperature, whilst at intermittent-flow sites ET correlated significantly with rainfall and stream discharge. Amongst reaches studied in detail, we found positive but differing logarithmic relationships between LAI and ET. By documenting patterns of high spatial variability of ET at basin scales, these results underscore the importance of accurately accounting for differences in woodland vegetation structure and hydrological conditions for assessing water-use requirements. Results also suggest that the climate sensitivity of ET may be used as a remote indicator of subsurface water resources relative to vegetation demand, and an indicator for informing conservation management priorities.     

Prediction of vegetation anomalies over an inland river basin in north‐western China

Vegetation cover plays an important role in linking the atmosphere, water, and land and is deemed as a key indicator in the terrestrial ecological system. Therefore, it is of great importance to monitor vegetation dynamics and understand the mechanisms of vegetation change, including that driven by climate change. This study examines (a) the evolution of vegetation dynamics over the Heihe River Basin in the typical arid zone in north‐western China using nonparametric Mann–Kendall test and Thiel Sen's slope; (b) the relationships between remotely sensed vegetation indices (normalized difference vegetation index [NDVI] and enhanced vegetation index [EVI]) and hydroclimatic variables based on correlation analysis; and (c) the prediction of vegetation anomalies using a multiple linear regression model. For the analysis, the Moderate Resolution Imaging Spectroradiometer NDVI/EVI product and the gridded daily meteorological data at a spatial resolution of 0.125° over the period 2001–2010 are considered. The results indicate that vegetation cover improved over a large proportion during 2001–2010, with a significant trend towards warm and wet, characterized by an increase in average annual temperature and precipitation by 0.042 °C/year and 5.8 mm/year, respectively. We test the feasibility of NDVI and EVI in quantifying the responses of vegetation anomaly to climate change and develop a statistical model to predict vegetation dynamics in the basin. The NDVI‐based model is found to be more reliable than the EVI‐based model, partly due to the vegetation characteristics and geomorphologic properties of the study region. The proposed model performs well when there is no lag time between meteorological factors and vegetation indices for grassland and cropland, whereas 1‐month lead time prediction is found to be best for forest. The soil water content is introduced as an extra explanatory variable, which effectively improves the prediction accuracy for different land use types. In general, the predictive ability of the proposed model is stable and satisfactory, and the model can provide useful early warning information for regional water resources management under changing climate.     

Spatiotemporal variation and driving forces of reference evapotranspiration in Jing River Basin,northwest China

Evapotranspiration is an important component of the hydrological cycle, which integrates atmospheric demands and surface conditions. Research on spatial and temporal variations of reference evapotranspiration (ET_o) enables understanding of climate change and its effects on hydrological processes and water resources. In this study, ET_o was estimated by the FAO‐56 Penman–Monteith method in the Jing River Basin in China, based on daily data from 37 meteorological stations from 1960 to 2005. ET_o trends were detected by the Mann–Kendall test in annual, seasonal, and monthly timescales. Sensitivity coefficients were used to examine the contribution of important meteorological variables to ET_o. The influence of agricultural activities, especially irrigation on ET_o was also analyzed. We found that ET_o showed a decreasing trend in most of the basin in all seasons, except for autumn, which showed an increasing trend. Mean maximum temperature was generally the most sensitive parameter for ET_o, followed by relative humidity, solar radiation, mean minimum temperature, and wind speed. Wind speed was the most dominant factor for the declining trend in ET_o. The more significant decrease in ET_o for agricultural and irrigation stations was mainly because of the more significant decrease in wind speed and sunshine hours, a mitigation in climate warming, and more significant increase in relative humidity compared with natural stations and non‐irrigation stations. Changes in ET_o and the sensitivity coefficient of meteorological variables in relation to ET_o were also affected by topography. Better understanding of ET_o response to climate change will enable efficient use of agricultural production and water resources, which could improve the ecological environment in Jing River Basin. Copyright © 2015 John Wiley & Sons, Ltd.     

Regionalization of annual runoff characteristics and its indication of co-dependence among hydro-climate–landscape factors in Jinghe River Basin,China

It is a challenge to properly generalize hydrological characteristics under the great heterogeneity of climate and landscape conditions across space because the linkage and interaction among hydro-climate–landscape factors are complicate and ambiguous at regional scale. In this study, multivariate statistical analyses including clustering, correlation and regression analysis were combined with Budyko and L’vovich frameworks to regionalize runoff characteristics over Jinghe River Basin of northwest China. For all 23 sub-basins, the hydrologic factors were quantified using the metrics of mean annual values and intra-annual variability of runoff. The climatic factors are determined from precipitation, potential evapotranspiration and aridity index, and the landscape factors were extracted from topography, soils and vegetation of the sub-basins. Results illustrated that the 23 sub-basins can be classified into two groups, the dry Loess Plateau (LP) and the wet Mountain Region (MR) in the study basin. The runoff metrics of sub-basins in each group present similarity in spatial distribution, intra-annual variations and the dominant influence factors of climate and landscape. But such runoff metrics characteristics and their co-dependence are significantly different between the two clustered sub-basins. Higher runoff and gentler hydrographs were observed in the MR in response to wetter and greater intra-annual variability in climate and greater spatial variability in landscape, whereas lower runoff and sharper hydrograph were seen in response to drier and greater intra-annual variability in climate, and less spatial variability in landscape in the LP. The runoff spatial distribution is more sensitive to climate spatial variation than to landscape in LP as opposed to the MR. Among the landscape factors, forest distribution is the dominant control on the spatial runoff characteristics in LP whereas topography is principal factor in MR. Our results highlight that current measures of reforestation plus marked change in climate in the Loess Plateau could lead to significant change in streamflow.     

Modelling the spatio-temporal repartition of right-truncated data: an application to avalanche runout altitudes in Hautes-Savoie

In this paper, we propose a novel approach for generating avalanche hazard maps based on the spatial dependence of avalanche runout altitudes. The right-truncated data are described with a Bayesian hierarchical model in which the spatio-temporal process is assumed to be the sum of independent spatial and temporal terms. Topography is roughly taken into account according to valley altitude and path exposition, and the spatial dependence is modelled with a Matérn covariance function. An application is performed to the Haute-Savoie region, French Alps. A spatial dependence in runout altitudes is identified, and an effective range of about 10 km is inferred. The temporal trend extracted highlights the increase of avalanche runout altitudes from 1955, attributed to both anthropogenic factors and climate warming. In a cross validation scheme, spatial predictions are provided on undocumented paths using kriging equations. All in all, although our model is unable to take into account small topographic features, it is a first-ever approach that produces very encouraging results. It could be enhanced in future work by incorporating a numerical physically-based code into the modelling.     

Spatiotemporal Characteristics of Evapotranspiration and Driving Factors in the Bosten Lake Watershed,China

The Bosten Lake watershed investigated in this study has seen significant land cover and climate change. The spatiotemporal relationship between evapotranspiration (ET) and environmental factors remain unclear. In this study, trend analysis and correlation methods are applied to analyze the spatiotemporal characteristics of ET and the relationship between ET and its driving factors using remotely sensed ET data and measured climate data between 2001 and 2018. During the study period, high values of ET primarily occurr in the wetlands of the plain area and the mid‐elevation mountain areas. The ET values show a significantly increasing trend in the different vegetation types due to climate change and other factors. The ET change trend in the study area is in the range of ?13.4 to ≈35.9 mm per year; the desert area exhibits a significant decrease and most of the mountain areas show a significantly increasing trend. ET is significantly correlated with land surface temperature, normalized difference vegetation index (NDVI), and solar radiation. The dominant factor affecting ET is NDVI, accounting for 15.2% of the study area. The results of this study highlight the need for appropriate land‐use strategies for managing water resources in arid land ecosystems.     

Multi‐temporal scale changes of streamflow and sediment load in a loess hilly watershed of China

Global climate change and diverse human activities have resulted in distinct temporal–spatial variability of watershed hydrological regimes, especially in water‐limited areas. This study presented a comprehensive investigation of streamflow and sediment load changes on multi‐temporal scales (annual, flood season, monthly and daily scales) during 1952–2011 in the Yanhe watershed, Loess Plateau. The results indicated that the decreasing trend of precipitation and increasing trend of potential evapotranspiration and aridity index were not significant. Significant decreasing trends (p < 0.01) were detected for both the annual and flood season streamflow, sediment load, sediment concentration and sediment coefficient. The runoff coefficient exhibited a significantly negative trend (p < 0.01) on the flood season scale, whereas the decreasing trend on the annual scale was not significant. The streamflow and sediment load during July–August contributed 46.7% and 86.2% to the annual total, respectively. The maximum daily streamflow and sediment load had the median occurrence date of July 31, and they accounted for 9.7% and 29.2% of the annual total, respectively. All of these monthly and daily hydrological characteristics exhibited remarkable decreasing trends (p < 0.01). However, the contribution of the maximum daily streamflow to the annual total progressively decreased (?0.07% year^?1), while that of maximum daily sediment load increased over the last 60 years (0.08% year^?1). The transfer of sloping cropland for afforestation and construction of check‐dams represented the dominant causes of streamflow and sediment load reductions, which also made the sediment grain finer. Copyright © 2015 John Wiley & Sons, Ltd.     

基于长短记忆模型的鄱阳湖流域径流模拟及其演变的归因分析

气候变化和人类活动直接或间接的影响着全球和区域水文循环过程,是导致水文水资源时空分布的主要因素,同时也是流域-湖泊水文情势变化的根本原因.本文基于长短记忆模型构建了鄱阳湖气象-径流模型,同时引入了基准期的概念,定量区分了导致鄱阳湖流域径流变化的主要影响因素.研究结果表明:在同时考虑计算效率和模拟效果的前提下,采用10 d预测窗口大小来构建鄱阳湖气象-径流模型能够很好地捕捉径流的极值,并且对径流的短期波动也能有很好的体现.训练期模型在各个子流域的纳什效率系数均高于0.94,而在验证期,模型在各个子流域的纳什效率系数均高于0.90.基于径流模拟结果,定量区分了人类活动和气候变化对鄱阳湖径流的影响,研究结果显示:人类活动对径流的影响主要发生在春、秋季,其中,人类活动在春季主要会造成径流的增加,平均增加幅度约为139.47 m³/s,而在秋、冬季,人类活动则会导致径流平均减少约34.37 m³/s.对比二者的相对贡献率,可以发现,春季人类活动对径流造成的影响较大,平均相对贡献率为77.26%.而在其余季节,鄱阳湖流域径流过程的改变主要是由于气候变化,平均相对贡献率约75.84%.研究结果能够为鄱阳湖流域水资源管理提供科学依据和理论指导.     

Decoupling the effects of deforestation and climate variability in the Tapajós river basin in the Brazilian Amazon

Tropical river basins are experiencing major hydrological alterations as a result of climate variability and deforestation. These drivers of flow changes are often difficult to isolate in large basins based on either observations or experiments; however, combining these methods with numerical models can help identify the contribution of climate and deforestation to hydrological alterations. This paper presents a study carried out in the Tapaj?s River (Brazil), a 477,000 km² basin in South‐eastern Amazonia, in which we analysed the role of annual land cover change on daily river flows. Analysis of observed spatial and temporal trends in rainfall, forest cover, and river flow metrics for 1976 to 2008 indicates a significant shortening of the wet season and reduction in river flows through most of the basin despite no significant trend in annual precipitation. Coincident with seasonal trends over the past 4 decades, over 35% of the original forest (140,000 out of 400,000 km²) was cleared. In order to determine the effects of land clearing and rainfall variability to trends in river flows, we conducted hindcast simulations with ED2 + R, a terrestrial biosphere model incorporating fine scale ecosystem heterogeneity arising from annual land‐use change and linked to a flow routing scheme. The simulations indicated basin‐wide increases in dry season flows caused by land cover transitions beginning in the early 1990s when forest cover dropped to 80% of its original extent. Simulations of historical potential vegetation in the absence of land cover transitions indicate that reduction in rainfall during the dry season (mean of ?9 mm per month) would have had an opposite and larger magnitude effect than deforestation (maximum of +4 mm/month), leading to the overall net negative trend in river flows. In light of the expected increase in future climate variability and water infrastructure development in the Amazon and other tropical basins, this study presents an approach for analysing how multiple drivers of change are altering regional hydrology and water resources management.     

Climate extremes in South Western Siberia: past and future

In this study, the temporal and spatial trends of ten climate extreme indices were computed based on observed daily precipitation and on daily maximum and minimum temperatures at 26 weather stations in South Western Siberia during the period 1969–2011 and, based on projected daily maximum and minimum temperatures, during 2021–2050. The Mann–Kendall test was employed to analyze the temporal trend and a combination of multiple linear regressions and semivariogram functions were used to evaluate the regional spatial trends and the local spatial variability of climate extremes, respectively. The results show that the temperature-based climate extremes increase at a 0.05 significance level while none of the precipitation-based climate extremes did. Spatially, dominant gradients are observed along latitude: The northern taiga vegetation zone experiences a colder and wetter climate while the southern forest steppe zone is drier and hotter. Over time, a tendency towards homogenization of the regional climate is observed through a decrease of the spatial variability for most climate extreme indices. In the future, the most intense changes are anticipated for the bio-climate indicators “growing season length” and “growing degree days” in the north, while the warming indicators, “warm day” and “warm night” are expected to be high to the south.     

The impact of natural vegetation restoration on surface soil moisture of secondary forests and shrubs in the karst region of southwest China

Soil moisture is crucial to vegetation restoration in karst areas, and climate factors and vegetation restoration are key factors affecting changes in soil moisture. However, there is still much controversy over the long-term changes in soil moisture during vegetation restoration. In order to reveal the changes in soil moisture during vegetation restoration, we conducted long-term positioning monitoring of soil moisture at 0–10 and 10–20 cm on secondary forests sample plot (SF, tree land) and shrubs sample plot (SH, shrub land) in karst areas from 2013 to 2020. The results showed that the aboveground biomass of SF and SH increased by 50% and 240%, respectively, and the soil moisture of the SF and SH showed an increasing trend. When shrubs are restored to trees in karst areas, the soil moisture becomes more stable. However, the correlation coefficients (R²) between the annual rainfall and the annual average soil moisture of SF and SH are 0.84 and 0.55, respectively, indicating that soil moistures in tree land are more affected by rainfall. The soil moisture of shrubs and trees are relatively low during the months of alternating rainy and dry seasons. Rainfall has a very significant impact on the soil moisture of tree land, while air temperature and wind speed have a significant impact on the soil moisture of tree land, but the soil moistures of shrub land are very significantly affected by rainfall and relative humidity. Therefore, during the process of vegetation restoration from shrubs to trees, the main meteorological factors that affect soil moisture changes will change. The results are important for understanding the hydrological processes in the ecological restoration process of different vegetation types in karst areas.     

Assessing vegetation dynamics and their relationships with climatic variability in northern China

In this study, the vegetation dynamics and their correlations with climate variability in northern China were evaluated based on the normalized difference vegetation index (NDVI) and meteorological datasets from 1982 to 2006. The NDVI showed that vegetation cover had a tiny increasing trend for whole study area in the past 25 years. However, the interannual changes of NDVI were different in each season. The part of spring and autumn NDVI values increased significantly, while the summer NDVI increased no significantly. And the interannual variations of the NDVI showed obvious spatial differentiations. The annual max NDVI increased were mainly distributed in most areas of grassland and farmland, whereas the annual max NDVI decreased were mainly distributed in forest areas. The annual NDVI and temperature had more important relationships. Thus, as compared to precipitation, the correlation between NDVI with temperature was stronger than the precipitation in northern China. NDVI and climatic variables were different in each season. The NDVI trends exhibited a close correspondence to climatological variations in region and season. In Addition, human activities also had profound effect to the NDVI trends in some regions. All these findings will make humans know more about the knowledge of the natural forces that influence vegetation change and supply a scientific basic resource to for the environmental management in northern China.     

Spatiotemporal variations of vegetation cover on the Chinese Loess Plateau (1981–2006): Impacts of climate changes and human activities

Spatiotemporal variations of Chinese Loess Plateau vegetation cover during 1981–2006 have been investigated using GIMMS and SPOT VGT NDVI data and the cause of vegetation cover changes has been analyzed, considering the climate changes and human activities. Vegetation cover changes on the Loess Plateau have experienced four stages as follows: (1) vegetation cover showed a continued increasing phase during 1981–1989; (2) vegetation cover changes came into a relative steady phase with small fluctuations during 1990–1998; (3) vegetation cover declined rapidly during 1999–2001; and (4) vegetation cover increased rapidly during 2002–2006. The vegetation cover changes of the Loess Plateau show a notable spatial difference. The vegetation cover has obviously increased in the Inner Mongolia and Ningxia plain along the Yellow River and the ecological rehabilitated region of Ordos Plateau, however the vegetation cover evidently decreased in the hilly and gully areas of Loess Plateau, Liupan Mountains region and the northern hillside of Qinling Mountains. The response of NDVI to climate changes varied with different vegetation types. NDVI of sandy land vegetation, grassland and cultivated land show a significant increasing trend, but forest shows a decreasing trend. The results obtained in this study show that the spatiotemporal variations of vegetation cover are the outcome of climate changes and human activities. Temperature is a control factor of the seasonal change of vegetation growth. The increased temperature makes soil drier and unfavors vegetation growth in summer, but it favors vegetation growth in spring and autumn because of a longer growing period. There is a significant correlation between vegetation cover and precipitation and thus, the change in precipitation is an important factor for vegetation variation. The improved agricultural production has resulted in an increase of NDVI in the farmland, and the implementation of large-scale vegetation construction has led to some beneficial effect in ecology. Supported by the National Natural Science Foundation of China (Grant No. 40671019) and the Knowledge Innovation Project of the Institute of Geographical Sciences and Natural Resources Research of Chinese Academy of Sciences     

The impact of climate change and human activities on streamflow and sediment load in the Pearl River basin

This paper uses monthly streamflow, suspended sediment concentration, and meteorological data to examine the impact of human activity and climate change on streamflow and sediment load in the Pearl River basin from the 1950s to the 2000s. The influences of climate change and human activities on hydrological processes were quantitatively evaluated using the Mann–Kendall abrupt change test and power rating curves. The results showed that:(1) abrupt changes and turning points in streamflow occurred in 1963, 1983, and 1991 which were found to be consistent with global ENSO events and volcanic eruptions. However, abrupt changes in sediment load showed significant spatial differences across the Pearl River basin. For the Xijiang River, an abrupt change in sediment load occurred in 2002, and after 2007 the change becomes significant at the 95% confidence level. At Beijiang and Dongjiang, abrupt changes in sediment load occurred in 1998 and 1988, respectively.(2) The time series of sediment load data was divided into four periods according to abrupt changes. The contribution of climate change and human activities is different in the different rivers. For the Xijiang River, compared with the first period, climate change and human activities contributed 83% and 17%, respectively, to the increasing sediment load during the second period. In the third period, the variation of sediment load followed a decreasing trend. The contribution from climate change and human activities also changed to t236% and -136%, respectively. In the fourth period, climate change and human activities contributed -32% and t132%, respectively. Meanwhile, For the Beijiang River, climate change and human activities contributed 90% and 10% in the second period, the contribution of climate change increased to t115% and human activities decreased to -15% in the third period. In the fourth period, the value for climate change decreased to t36% and human activities increased to t64%. For the Dongjiang River, the contribution of human activities was from 74.5% to 90%, and the values for climate change were from 11% to 25%. Therefore, the effect of human activity showed both spatial and temporal differences, and it seems likely that the decreased sediment load will continue to be controlled mainly by human activities in the future.     

Spatial patterns of simulated transpiration response to climate variability in a snow dominated mountain ecosystem

Transpiration is an important component of soil water storage and stream‐flow and is linked with ecosystem productivity, species distribution, and ecosystem health. In mountain environments, complex topography creates heterogeneity in key controls on transpiration as well as logistical challenges for collecting representative measurements. In these settings, ecosystem models can be used to account for variation in space and time of the dominant controls on transpiration and provide estimates of transpiration patterns and their sensitivity to climate variability and change. The Regional Hydro‐Ecological Simulation System (RHESSys) model was used to assess elevational differences in sensitivity of transpiration rates to the spatiotemporal variability of climate variables across the Upper Merced River watershed, Yosemite Valley, California, USA. At the basin scale, predicted annual transpiration was lowest in driest and wettest years, and greatest in moderate precipitation years (R² = 0·32 and 0·29, based on polynomial regression of maximum snow depth and annual precipitation, respectively). At finer spatial scales, responsiveness of transpiration rates to climate differed along an elevational gradient. Low elevations (1200–1800 m) showed little interannual variation in transpiration due to topographically controlled high soil moistures along the river corridor. Annual conifer stand transpiration at intermediate elevations (1800–2150 m) responded more strongly to precipitation, resulting in a unimodal relationship between transpiration and precipitation where highest transpiration occurred during moderate precipitation levels, regardless of annual air temperatures. Higher elevations (2150–2600 m) maintained this trend, but air temperature sensitivities were greater. At these elevations, snowfall provides enough moisture for growth, and increased temperatures influenced transpiration. Transpiration at the highest elevations (2600–4000 m) showed strong sensitivity to air temperature, little sensitivity to precipitation. Model results suggest elevational differences in vegetation water use and sensitivity to climate were significant and will likely play a key role in controlling responses and vulnerability of Sierra Nevada ecosystems to climate change. Copyright © 2008 John Wiley & Sons, Ltd.     

Temporal trends in δ18O composition of precipitation in Germany: insights from time series modelling and trend analysis

Temporal and spatial variations of stable oxygen (¹⁸O) and hydrogen (²H) isotope measurements in precipitation act as important proxies for changing hydro‐meteorological and regional and global climate patterns. Temporal trends in time series of the stable isotope composition in precipitation were rarely observed, and they are poorly understood. These might be a result of a lack of proper trend detection tools and effort for exploring trend processes. Here, we investigate temporal trends of δ¹⁸O in precipitation at 17 observation stations in Germany between 1978 and 2009. We test if significant trends in the isotope time series from different models can be observed. Mann–Kendall trend tests are applied on the isotope series, using general multiplicative seasonal autoregressive integrate moving average (ARIMA) models, which account for first and higher order serial correlations. Effects of temperature, precipitation, and geographic parameters on isotope trends are also investigated in the proposed models. To benchmark our proposed approach, the ARIMA results are compared with a trend‐free pre‐whitening procedure, the state of the art method for removing the first order autocorrelation in environmental trend studies. Moreover, we further explore whether higher order serial correlations in isotope series affects our trend results. Overall, three out of the 17 stations show significant changes when higher order autocorrelation are adjusted, and four show a significant trend when temperature and precipitation effects are considered. The significant trends in the isotope time series generally occur only at low elevation stations. Higher order autoregressive processes are shown to be important in the isotope time series analysis. Results suggest that the widely used trend analysis with only the first order autocorrelation adjustment may not adequately take account of the high order autocorrelated processes in the stable isotope series. The investigated time series analysis method including higher autocorrelation and external climate variable adjustments is shown to be a better alternative. Copyright © 2014 John Wiley & Sons, Ltd.