Land Surface Conditions Research Articles

Critical Soil Moisture Derived From Satellite Observations Over Europe

AbstractEvapotranspiration (ET) is a crucial quantity through which land surface conditions can impact near‐surface weather and vice versa. ET can be limited by energy or water availability. The transition between water‐ and energy‐limited regimes is marked by the critical soil moisture (CSM), which is traditionally derived from small‐sample laboratory analyses. Here, we aim to determine the CSM at a larger spatial scale relevant for climate modeling, using state‐of‐the‐art gridded data sets. For this purpose, we introduce a new correlation‐difference metric with which the CSM can be accurately inferred using multiple data streams. We perform such an analysis at the continental scale and determine a large‐scale CSM as an emergent property. In addition, we determine small‐scale CSMs at the grid cell scale and find substantial spatial variability. Consistently from both analyses we find that soil texture, climate conditions, and vegetation characteristics are influencing the CSM, with similar respective importance. In contrast, comparable CSMs are found when applying alternative large‐scale energy and vegetation data sets, highlighting the robustness of our results. Based on our findings, the state of the vegetation and corresponding land‐atmosphere coupling can be inferred, to first order, from easily accessible satellite observations of surface soil moisture.

Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery

Dense time series of Landsat 8 and Sentinel-2 imagery are creating exciting new opportunities to monitor, map, and characterize temporal dynamics in land surface properties with unprecedented spatial detail and quality. By combining imagery from the Landsat 8 Operational Land Imager and the MultiSpectral Instrument on-board Sentinel-2A and -2B, the remote sensing community now has access to moderate (10–30 m) spatial resolution imagery with repeat periods of ~3 days in the mid-latitudes. At the same time, the large combined data volume from Landsat 8 and Sentinel-2 introduce substantial new challenges for users. Land surface phenology (LSP) algorithms, which estimate the timing of phenophase transitions and quantify the nature and magnitude of seasonality in remotely sensed land surface conditions, provide an intuitive way to reduce data volumes and redundancy, while also furnishing data sets that are useful for a wide range of applications including monitoring ecosystem response to climate variability and extreme events, ecosystem modelling, crop-type discrimination, and land cover, land use, and land cover change mapping, among others. To support the need for operational LSP data sets, here we describe a continental-scale land surface phenology algorithm and data product based on harmonized Landsat 8 and Sentinel-2 (HLS) imagery. The algorithm creates high quality times series of vegetation indices from HLS imagery, which are then used to estimate the timing of vegetation phenophase transitions at 30 m spatial resolution. We present results from assessment efforts evaluating LSP retrievals, and provide examples illustrating the character and quality of information related to land cover and terrestrial ecosystem properties provided by the continental LSP dataset that we have developed. The algorithm is highly successful in ecosystems with strong seasonal variation in leaf area (e.g., deciduous forests). Conversely, results in evergreen systems are less interpretable and conclusive.

Impact of Aerosols From Urban and Shipping Emission Sources on Terrestrial Carbon Uptake and Evapotranspiration: A Case Study in East Asia

AbstractThis study quantifies the immediate influences of aerosols from urban anthropogenic and shipping emission sources on carbon and water fluxes in East Asia on a cloudy day in spring 2016 when strong regional pollution transport occurred and intensive field campaign measurements are available. Within National Aeronautics and Space Administration (NASA)'s Land Information System (LIS), a long‐term offline Noah‐multiparameterization (MP) simulation with dynamic vegetation is performed. Modeled soil moisture and leaf area index are evaluated with satellite observations to ensure that land surface conditions are moderately well reproduced. The LIS output is then used to initialize several coupled NASA‐Unified Weather Research and Forecasting model simulations with online chemistry in which urban anthropogenic and shipping emissions are (1) largely based on the Hemispheric Transport of Air Pollution Phase 2 inventory for 2010, (2) reduced by 20% and 50% for all chemical species, and (3) adjusted only for nitrogen oxides (NOx) using satellite observations. Overall, modeled gross primary productivity and evapotranspiration almost linearly increase with the all‐species emission reductions, but their responses to emission‐induced aerosol optical depth (AOD) changes show strong spatial variability resulting from combined radiation and temperature impacts. Using satellite‐observation‐constrained NOx emissions, modeled nitrogen species and AOD better match various measurements at some locations/times. All‐species and NOx‐only emission adjustments lead to different gross primary productivity and evapotranspiration changes with AOD, especially over South Korea. This study demonstrates the importance of accurately quantifying emission impacts on atmosphere‐biosphere interactions. Improving more species' emission inputs for Earth system models, including applying effective chemical data assimilation methods, is strongly encouraged.

Evaluation of Climatic and Anthropogenic Impacts on Dust Erodibility: A Case Study in Xilingol Grassland, China

Aeolian dust is dependent on erosivity (i.e., wind speed) and erodibility (i.e., land surface conditions). The effect of erodibility on dust occurrence remains poorly understood. In this study, we proposed a composite erodibility index (dust occurrence ratio, DOR) and examined its interannual variation at a typical steppe site (Abaga-Qi) in Xilingol Grassland, China, during spring of 1974–2018. Variation in DOR is mainly responsible for dust occurrence (R2 = 0.80, p-value < 0.001). During 2001–2018, DOR values were notably higher than those during 1974–2000. There was also a general declining trend with fluctuations. This indicates that the land surface conditions became vulnerable to wind erosion but was gradually reversed with the implementation of projects to combat desertification in recent years. To understand the relative climatic and anthropogenic impacts on erodibility, multiple regression was conducted between DOR and influencing factors for the period of 2001–2018. Precipitation (spring, summer, and winter) and temperature (summer, autumn, and winter), together with livestock population (June) explained 82% of the variation in DOR. Sheep and goat population made the greatest contribution. Therefore, reducing the number of sheep and goat could be an effective measure to prevent dust occurrence in Xilingol Grassland.

A Lagrangian Analysis of Water Vapor Sources and Pathways for Precipitation in East China in Different Stages of the East Asian Summer Monsoon

AbstractThe Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) platform is used to simulate Lagrangian trajectories of air parcels in East China during the summer monsoon. The investigation includes four distinct stages of the East Asian summer monsoon (EASM) during its seasonal migration from south to north. Correspondingly, the main water vapor channel migrates from the west Pacific Ocean (PO) for the premonsoon in South China (SC) to the Indian Ocean (IO) for the monsoon in SC and in the Yangtze–Huaihe River basin, and finally back to the PO for the terminal stage of monsoon in North China. Further calculations permit us to determine water vapor source regions and water vapor contribution to precipitation in East China. To a large extent, moisture leading to precipitation does not come from the strongest water vapor pathways. For example, the proportions of trajectories from the IO are larger than 25% all of the time, but moisture contributions to actual precipitation are smaller than 10%. This can be explained by the large amount of water vapor lost in the pathways across moisture-losing areas such as the Indian and Indochina Peninsulas. Local water vapor recycling inside East China (EC) contributes significantly to regional precipitation, with contributions mostly over 30%, although the trajectory proportions from subregions in EC are all under 10%. This contribution rate can even exceed 55% for the terminal stage of the monsoon in North China. Such a result provides important guidance to understand the role of land surface conditions in modulating rainfall in North China.

黄土高原流域水沙变化研究进展

PDF HTML阅读 XML下载 导出引用 引用提醒 黄土高原流域水沙变化研究进展 DOI: 10.5846/stxb201909121903 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41822103，41471094）；中国科学院青年促进会项目（2016040） Changes in streamflow and sediment load in the catchments of the Loess Plateau, China: a review Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:人类活动和气候变化是影响流域水文过程的两大驱动因素，径流输沙是流域水文过程的总体反映，变化环境下径流输沙的变化规律与成因分析是水文学和全球变化研究的热点问题。黄土高原是我国水土流失最严重的地区。20世纪50年代以来，黄土高原地区开展了大规模的生态环境建设和水土流失综合治理，显著改变了流域土地利用和植被覆盖。下垫面条件改变与气候变化综合作用，使得流域水沙情势发生剧变。围绕黄土高原流域水沙变化的时空尺度特征与驱动机制，总结了径流输沙和水沙关系变化特征的研究结果，归纳了径流输沙变化的归因分析方法与人类活动和气候变化影响的贡献分割结果，探讨了气候变化、植被恢复、水土保持工程措施以及流域景观格局对水沙变化的影响机制。未来应加强流域水沙演变的时空尺度特征特别是水沙关系非线性特征的定量研究，阐明极端事件对水沙动态的影响与贡献；开展水沙变化影响机制的多要素综合解析，发展耦合地表覆被动态特征和气候变化的降雨-径流-输沙模型，揭示生态恢复与水沙演变过程互馈机制；开展未来气候变化、社会经济发展和生态建设工程情景下水沙动态的趋势预测，为黄土高原生态综合治理和水资源管理与黄河水沙调控提供策略建议。 Abstract:Human activities and climate change are two critical driving forces of catchment hydrological processes, for which, streamflow and sediment load are the two main indicators. Changing trends and attribution analysis of streamflow and sediment load under changing environments are now the focus of hydrological and global change studies. The Loess Plateau (LP) of China is well known for its severe soil erosion and the heavy sediment load of the Yellow River that flows through it. To control soil erosion in the LP, large ecological restoration construction projects and several soil and water conservation measures have been implemented since the 1950s, which have resulted in extensive land use and vegetation cover changes. These extensive changes in land surface conditions in combination with climate change have dramatically altered the hydrological regime, including streamflow, sediment load, and flow-sediment relationships in the LP. The spatio-temporal variability of streamflow and sediment load, and the dominant mechanisms behind these changes are important issues in the development of strategies for sustainable land and water management in the LP. We reviewed previous studies that documented changes in streamflow, sediment load, and flow-sediment relationships to improve our understanding of these processes. The methods used to separate the impacts of human activities and climate change on streamflow and sediment load and the results obtained in these studies are summarized here. The influence of climate change, vegetation restoration, soil and water conservation measures, as well as catchment landscape patterns on driving changes in streamflow and sediment load are also discussed. Finally, the following further studies are proposed:1) Studying the spatio-temporal patterns in streamflow and sediment load evolution and quantifying the non-linear characteristics of flow-sediment relationships, 2) Demonstrating the effects and contributions of extreme events on streamflow and sediment load dynamics, 3) Conducting comprehensive analyses on the influence of multiple factors on streamflow and sediment load, 4) Developing a coupled rainfall-streamflow-sediment yield model that includes the dynamic characteristics of surface cover and climate change, with the aim of revealing feedback mechanisms between ecological restoration and the evolution of streamflow and sediment load, and 5) Predicting streamflow and sediment load dynamics under future scenarios of climate change, with the added effects of socio-economic development and ecological construction engineering; which is likely to provide suggestions for ecological treatment and water resource management in the LP, and regulation of water and sediment in the Yellow River. 参考文献 相似文献 引证文献

Patterns and Drivers of Atmospheric River Precipitation and Hydrologic Impacts across the Western United States

AbstractAtmospheric rivers (ARs) significantly influence precipitation and hydrologic variability in many areas of the world, including the western United States. As ARs are increasingly recognized by the research community and the public, there is a need to more precisely quantify and communicate their hydrologic impacts, which can vary from hazardous to beneficial depending on location and on the atmospheric and land surface conditions prior to and during the AR. This study leverages 33 years of atmospheric and hydrologic data for the western United States to 1) identify how water vapor amount, wind direction and speed, temperature, and antecedent soil moisture conditions influence precipitation and hydrologic responses (runoff, recharge, and snowpack) using quantile regression and 2) identify differences in hydrologic response types and magnitudes across the study region. Results indicate that water vapor amount serves as a primary control on precipitation amounts. Holding water vapor constant, precipitation amounts vary with wind direction, depending on location, and are consistently greater at colder temperatures. Runoff efficiencies further covary with temperature and antecedent soil moisture, with precipitation falling as snow and greater available water storage in the soil column mitigating flood impacts of large AR events. This study identifies the coastal and maritime mountain ranges as areas with the greatest potential for hazardous flooding and snowfall impacts. This spatially explicit information can lead to better understanding of the conditions under which ARs of different precipitation amounts are likely to be hazardous at a given location.

Local and Nonlocal Land Surface Influence in European Heatwave Initial Condition Ensembles

AbstractDry land surface conditions have been shown to amplify extreme heat events in Europe, but the extent to which this influence involves modification of the overlying atmospheric circulation has yet to be fully established. Here, this issue is addressed using two Community Earth System Model ensembles, with the same heatwave‐inducing atmospheric circulation pattern imposed over different land surface states. These two ensembles differ in the vertical level above which the circulation is constrained (surface vs. upper troposphere). Soil moisture anomalies are found to play an important role in dictating heatwave intensity among ensemble members. The heatwave is approximately 0.1°C hotter per standard deviation soil moisture reduction when the troposphere is free to respond to surface conditions than when it is constrained, implying that a portion of the land surface influence involves feedbacks through the atmospheric circulation. The additional atmospheric response also allows for nonlocal heatwave amplification in subsequent months.

Impact of Effective Roughness Length on Mesoscale Meteorological Simulations over Heterogeneous Land Surfaces in Taiwan

The Weather Research and Forecasting (WRF) modeling system obtains the aerodynamic roughness length (z0) from a land use (LU) lookup table. The effective aerodynamic roughness length (z0eff) was estimated for the island of Taiwan by considering the individual roughness lengths (z0i) of the underlying LU types within a modeling grid box. Two z0eff datasets were prepared: one using the z0i from the default LU lookup table and the other using the observed z0i for three LU types (urban, dry cropland and pasture, and irrigated cropland and pasture). The spatial variability of the z0eff distribution was higher than that of the LU table-based z0 distribution. Three WRF sensitivity experiments were performed: (1) dominant LU table-based z0 (namely, S1), (2) z0eff estimated from the default z0i (namely, S2), and (3) z0eff estimated from the observed z0i (namely, S3). Comparisons of the thermal field, temperature, and surface sensible and latent heat fluxes revealed no significant differences among the three simulations. The wind field overestimation and surface momentum flux underestimation in S1 were reduced in S2 and S3, and these improvements were more prominent over areas with highly heterogeneous land surface conditions.

Integrating land surface conditions and transport networks to quantify the spatial accessibility of cities in China

ABSTRACT Although there is a need to determine the spatial accessibility of cities in China, the limitations in available data and methods hinder research in this area. The main objective of this study was to quantify the accessibility of cities in China. We developed a comprehensive analytical method to quantify spatial accessibility at a spatial resolution of one kilometer by integrating both land surface conditions and transport networks. The results show that the spatial patterns of accessibility of Chinese cities at the prefecture level and above are characterized by significant spatial heterogeneity, consistent with the patterns in physical geography, population density, and economic activities. The results improve our understanding of deficiencies in the accessibility of cities in China and provide a foundation for transportation infrastructure planning.

Winter Wheat Mapping Based on Sentinel-2 Data in Heterogeneous Planting Conditions

Monitoring and mapping the spatial distribution of winter wheat accurately is important for crop management, damage assessment and yield prediction. In this study, northern and central Anhui province were selected as study areas, and Sentinel-2 imagery was employed to map winter wheat distribution and the results were verified with Planet imagery in the 2017–2018 growing season. The Sentinel-2 imagery at the heading stage was identified as the optimum period for winter wheat area extraction after analyzing the images from different growth stages using the Jeffries–Matusita distance method. Therefore, ten spectral bands, seven vegetation indices (VI), water index and building index generated from the image at the heading stage were used to classify winter wheat areas by a random forest (RF) algorithm. The result showed that the accuracy was from 93% to 97%, with a Kappa above 0.82 and a percentage error lower than 5% in northern Anhui, and an accuracy of about 80% with Kappa ranging from 0.70 to 0.78 and a percentage error of about 20% in central Anhui. Northern Anhui has a large planting scale of winter wheat and flat terrain while central Anhui grows relatively small winter wheat areas and a high degree of surface fragmentation, which makes the extraction effect in central Anhui inferior to that in northern Anhui. Further, an optimum subset data was obtained from VIs, water index, building index and spectral bands using an RF algorithm. The result of using the optimum subset data showed a high accuracy of classification with a great advantage in data volume and processing time. This study provides a perspective for winter wheat mapping under various climatic and complicated land surface conditions and is of great significance for crop monitoring and agricultural decision-making.

Evaluating satellite-based and reanalysis precipitation datasets with gauge-observed data and hydrological modeling in the Xihe River Basin, China

Abstract The wide application of satellite-based and reanalysis-based precipitation data has greatly promoted hydrometeorological research in areas where precipitation observations are scarce. However, the suitability of such precipitation products needs to be carefully evaluated before applications in certain basins because their inherited errors vary with different climate zones, seasonal cycles and land surface conditions; in addition, precipitation products have not been evaluated in the Xihe River basin, China. In this paper, two representative satellite-based precipitation products (Tropical Rainfall Measuring Mission (TRMM) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (CDR)) and two reanalysis-based precipitation products (China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) and National Centers for Environmental Prediction - Climate Forecast System Reanalysis (CFSR)) were selected for evaluation and corrected against gauge-observed data (OBS). Furthermore, the performances of precipitation products in hydrological simulations were also assessed using the SWAT model calibrated with OBS forcing and not with individual precipitation products. The results show that satellite-based precipitation has a higher quality than reanalysis-based precipitation. The CFSR and CDR overestimate precipitation (the overestimation of CDR precipitation is mainly concentrated in the precipitation intensity range of 1 mm/d to 5 mm/d), while the TRMM and CMADS underestimate precipitation in the Xihe River basin. The TRMM precipitation performs best during the wet season, while the CDR precipitation performed best during the dry season. After bias correction, the quality of TRMM precipitation improves significantly. The Nash-Sutcliffe coefficient (NS) (the percent bias (|PBIAS|)) increases (decreases) by 0.61 (77.27%) and 0.7 (39.15%) under the two different correction scenarios during 2009–2015. Overall, the above original precipitation products cannot be used as supplements to the OBS in the Xihe River basin unless they are corrected by the OBS.

Evolutionary drought patterns over the Sahel and their teleconnections with low frequency climate oscillations

The need for ideal drought metrics to explore the impacts of climate variability drivers on drought intensity and characteristics is essential to provide support that leads to optimizing existing templates on risk mitigation in drought-prone regions. The main aim of this study therefore is to improve contemporary understanding on the evolutionary patterns of historical drought over the Sahel (1901–2014) and the large-scale processes that drive its variability using the SPEI (standardized precipitation evapotranspiration index) and SPI (standardized precipitation index). Historically, the distributions of SPEI and SPI are generally quite similar with fairly strong correlations ranging from 0.80 to 1.0 around the central Sahel. The dissimilarity between SPI and SPEI in some regions however, suggest the influence of changing land surface conditions and the need to incorporate biophysical indicators to support the accounting process that aid the understanding of drought impacts and its cascading effects. Furthermore, SPEI and SPI confirm that the worst drought during the 20th century over the Sahel occurred between 1982 and 1985, affecting more than 90% of the region while the 1950s remained the wettest on record. However, between 2005 and 2015, drought episodes and their intensities have diminished over the Sahel. In the assessment of the coupled relationship of seven climate modes with drought evolutions, SPEI was more associated with Atlantic Multi-decadal Oscillation-AMO (r = 0.66) and Pacific Decadal Oscillation (r = − 0.53) unlike the SPI. A predictive multivariate model confirms the AMO is a strong driver of drought events and in addition, highlights the multi-scale climate influence in the Sahel.

Land–atmosphere interactions in the tropics – a review

Abstract. The continental tropics play a leading role in the terrestrial energy, water, and carbon cycles. Land–atmosphere interactions are integral in the regulation of these fluxes across multiple spatial and temporal scales over tropical continents. We review here some of the important characteristics of tropical continental climates and how land–atmosphere interactions regulate them. Along with a wide range of climates, the tropics manifest a diverse array of land–atmosphere interactions. Broadly speaking, in tropical rainforest climates, light and energy are typically more limiting than precipitation and water supply for photosynthesis and evapotranspiration (ET), whereas in savanna and semi-arid climates, water is the critical regulator of surface fluxes and land–atmosphere interactions. We discuss the impact of the land surface, how it affects shallow and deep clouds, and how these clouds in turn can feed back to the surface by modulating surface radiation and precipitation. Some results from recent research suggest that shallow clouds may be especially critical to land–atmosphere interactions. On the other hand, the impact of land-surface conditions on deep convection appears to occur over larger, nonlocal scales and may be a more relevant land–atmosphere feedback mechanism in transitional dry-to-wet regions and climate regimes.

Development of rapid visual screening form for Nepal based on the data collected from - its 2015 earthquake

An earthquake on the 25th April 2015 in Nepal caused more than 9,000 deaths and 22,000 causalities. The main reason for such huge casualties is the lack of earthquake awareness and poor construction practices. With a large number of vulnerable houses, Nepal faces a huge risk from future earthquakes, due to the recent construction in urban areas of poorly designed and constructed buildings. Such unplanned and haphazard growth will be potentially dangerous from natural events like earthquakes. A vulnerability map gives the exact location of sites where people, natural environments and or properties are at risk due to a potentially catastrophic event. This will allow them to decide on mitigating measures to prevent or reduce loss of life, injury and environmental consequences before a disaster occurs. While Rapid Visual screening is a classical method of preliminary vulnerability study, it is one of the most economical, reliable, simple and efficient methods to determine the vulnerability level of buildings. The most known rapid visual screening methods have been developed in countries of high seismic risk such as the USA, Japan, Indonesia, New Zealand, India and Canada and are briefly described in this paper. The main objective of this paper with the help of ordinal regression is to calculate variables of damage grade model in a rapid visual screening form. This is useful to identify vulnerable and non-vulnerable buildings very quickly, and help make a plan for the implementation of a disaster risk mitigation program. Based on SPSS Statistics Software, an ordinal regression method was used to model the relationship between outcome variables. The analysis was performed by employing a database after the 25th April Gorkha earthquake of 2015. Preparing RVS special features of buildings in Nepal, have been given due consideration, and were evaluated for adherence of age, plan configuration, position, land surface condition, plinth area, building height, floor count, foundation types, ground floor types, roof types, condition, are highly significant parameters in analysing the vulnerability of them during an earthquake.

Investigating Land Surface Effects on the Moisture Transport over South America with a Moisture Tagging Model

Abstract Land–atmosphere interactions are a critical component of precipitation processes within the Amazon basin and La Plata River basin (LPRB) in South America. Two of the possible pathways through which the land surface can affect precipitation are 1) by changing the amount of moisture available for precipitation (moisture recycling) and 2) by changing the atmospheric thermal structure and consequently affecting circulation patterns. In this study, the Weather Research and Forecasting (WRF) Model with embedded water vapor tracers (WVT) is used to disentangle these relative contributions, with a particular focus on the precipitation of LPRB. Using WRF-WVT we track the moisture that originates from the Amazon basin over a 10-yr period. It is estimated that Amazon evapotranspiration (ET) contributes to around 30% of the total precipitation over the Amazon and around 16% over the LPRB. Focusing on large-scale circulation patterns that transport moisture into the LPRB, we show that land surface conditions in northwestern Argentina are critical for the meridional transport of moisture to higher latitudes via Chaco jet events (CJEs). Warm surface air temperature associated with dry soil moisture over northwestern Argentina is linked to enhanced CJE northerly low-level winds that intensify moisture transport by changing continental-scale circulation patterns. WRF sensitivity tests confirm that soil moisture variations over this region affect meridional moisture transport.

Shifts of sediment transport regime caused by ecological restoration in the Middle Yellow River Basin

Sediment in rivers is the dominant material source for ecosystems in lower reaches and estuaries, and it is undergoing large variations globally in recent decades. Though we have knowledge that human activities are greatly affecting land surface ecosystem processes and functions, the relationships between sediment transport regime and the intensifying human activities, are still poorly understood. This study was to investigate the changes of sediment transport regime due to the large-scale ecological restoration in the Middle Yellow River Basin (MYRB). In this study, we examined the change of the sediment rating curves using daily sediment load and streamflow data from 30 stations during time periods including pre- and post-ecological restoration in this region. We found the pair-relationship of the rating parameters (coefficient and exponent), denoted as coefficient-exponent pair-line, is a critical indicator that can detect the shift of sediment transport regime due to disturbed land surface conditions, though the changed hydrometeorological condition may just influence the absolute values of the rating parameters. Our analysis indicates there was a significant and interesting change of the sediment transport regime in the MYRB characterized by the consistent shift of the coefficient-exponent pair-line, together with an increasing exponent and a decreasing coefficient. This changed sediment transport regime can tell that sediment delivery would become lower for normal discharge conditions but potentially higher for extreme discharge conditions, and this phenomenon seems more distinct in relatively smaller watersheds, suggesting a higher risk of the potential high sediment delivery for extreme rainfall conditions especially for small watersheds. Our study would be informative and valuable to decision makers for sustainable watershed management in the MYRB when considering the changed sediment delivery.

Unmanned Aerial System multispectral mapping for low and variable solar irradiance conditions: Potential of tensor decomposition

Unlike satellite earth observation, multispectral images acquired by Unmanned Aerial Systems (UAS) provide great opportunities to monitor land surface conditions also in cloudy or overcast weather conditions. This is especially relevant for high latitudes where overcast and cloudy days are common. However, multispectral imagery acquired by miniaturized UAS sensors under such conditions tend to present low brightness and dynamic ranges, and high noise levels. Additionally, cloud shadows over space (within one image) and time (across images) are frequent in UAS imagery collected under variable irradiance and result in sensor radiance changes unrelated to the biophysical dynamics at the surface. To exploit the potential of UAS for vegetation mapping, this study proposes methods to obtain robust and repeatable reflectance time series under variable and low irradiance conditions. To improve sensor sensitivity to low irradiance, a radiometric pixel-wise calibration was conducted with a six-channel multispectral camera (mini-MCA6, Tetracam) using an integrating sphere simulating the varying low illumination typical of outdoor conditions at 55oN latitude. The sensor sensitivity was increased by using individual settings for independent channels, obtaining higher signal-to-noise ratios compared to the uniform setting for all image channels. To remove cloud shadows, a multivariate statistical procedure, Tucker tensor decomposition, was applied to reconstruct images using a four-way factorization scheme that takes advantage of spatial, spectral and temporal information simultaneously. The comparison between reconstructed (with Tucker) and original images showed an improvement in cloud shadow removal. Outdoor vicarious reflectance validation showed that with these methods, the multispectral imagery can provide reliable reflectance at sunny conditions with root mean square deviations of around 3%. The proposed methods could be useful for operational multispectral mapping with UAS under low and variable irradiance weather conditions as those prevalent in northern latitudes.

Toward parsimonious modeling of frequency of areal runoff from heavy-to-extreme precipitation in large urban areas under changing conditions: a derived moment approach

Translating changes in land surface conditions and climate into changes in precipitation, runoff and flood frequencies over a range of catchment scales is a pressing challenge for hydrologic design and flood risk management today. In this paper, we describe a novel approach for modeling areal runoff frequency from heavy-to-extreme precipitation in large urban areas using a simple but general stochastic model for runoff at point scale and bi- and univariate parametric probability distributions for positive point precipitation and areal runoff, respectively. We apply the approach to the Dallas–Fort Worth area using a 22-year historical multisensor precipitation dataset from the National Weather Service to characterize how the different factors that specify the second-order statistics of precipitation, imperviousness and soil water holding capacity at point scale may shape areal runoff frequency, and to assess how changes in precipitation climatology and land surface conditions may change areal runoff frequency as a function of catchment scale and magnitude of precipitation. The results indicate that areal runoff frequency is impacted most significantly by changes in climatological mean and coefficient of variation of positive point precipitation, water holding capacity of soil, imperviousness, and spatial correlation scale of positive point precipitation given the probability of occurrence of heavy-to-extreme precipitation, and that a very small number of low-order statistics of point precipitation may describe areal runoff frequency given the conditional probability distribution models for point precipitation and areal runoff. The approach presented hence offers a parsimonious physically-based alternative to purely numerical approaches based on integrated modeling, or empirical approaches based solely on statistical modeling toward predictive modeling of areal precipitation and runoff frequencies under changing hydroclimatological conditions.

Quantifying the impacts of human activities on runoff and sediment load changes in a Loess Plateau catchment, China

Significant changes in the runoff and sediment load have been detected in many catchments of the Loess Plateau. These changes are expected to be influenced by the interplay of climate variability and human activities. Quantitatively evaluating these effects is crucial for framing climate variability adaptation measures and the assessment and management of regional water resources. Based on the annual rainfall, runoff, and sediment load data taken over the period from 1974 to 2013 and using data from 112 flood events, this study investigates the runoff and sediment load variations at the annual scale and distinguishes the impacts of climate variability and human activities at the event scale. The Mann-Kendall test and Pettitt’s test are employed to detect the trends and abrupt change points of the annual runoff and sediment load. Rainfall and land surface conditions play a dominant role in the runoff and sediment yield of flood events. However, vegetation recovery, which benefits from the Grain-for-Green project and the construction of check dams has greatly changed the land surface condition, resulting in a reduction in streamflow energy, hydrological connectivity, and flood peaks. Therefore, for two flood events with similar rainfall conditions but different runoff and sediment yield, the differences in the runoff and sediment load within paired events may be attributed to the changes in the land surface condition induced by human activities. The results showed that the annual runoff and sediment load has significantly decreasing trends (p < 0.05). The abrupt changing point was detected in 1996, dividing the runoff and sediment load series into a baseline period (1974–1995) and a changing period (1996–2013). At the flood event scale, the hysteresis analysis showed that the counter-clockwise and figure-eight loops are the main patterns for both of the periods. The relationships between the runoff depth (H) and sediment yield (SY) varied greatly in 2007–2013 compared with those during 1974–1989. Human activities accounted for an average of 47 and 81% for the changes in the runoff and sediment load, respectively, and the remainder was attributable to climate variability. Human activities have a greater effect on the sediment load reduction in the Xichuan River catchment, while climate variability accounted for more of the runoff changes.