Red River Basin Research Articles

An Engraved Bulbous-Necked Caddo Bottle from 41OR33 at the mouth of the Sabine River, Orange County, Texas

41OR33 is a large prehistoric shell midden deposit in Orange County, Texas, about 8.5 miles southwest of the city of Orange, at the mouth of the Sabine River and just north of Sabine Lake in Southeast Texas. Before the site was destroyed for road fill in October 1956, limited archaeological investigations had been done there by avocational archaeologists and then by E. Mott Davis of The University of Texas at Austin. During that work, a number of Native American burials were exposed and excavated, including one burial with an engraved bulbous-necked ancestral Caddo ceramic bottle. The bottle was donated by Edgar W. Brown, Jr. to UT in October 1956. I recently documented this vessel, which is a far-flung companion to bulbous-necked and spool-necked Caddo bottles from post-A.D. 1600 sites in the Red River and Ouachita River basins in East Texas and Southwest Arkansas as well as several post-A.D. 1600 sites in East Texas such as the Taylor site (41HS3) in the Big Cypress Creek basin.

Fish Assemblage Response to Altered Dendritic Connectivity in the Red River Basin, Central Louisiana

Louisiana's streams provide habitat for a diversity of ecologically and economically important fish species. However, most stream systems in the state have been subject to substantial anthropogenic alterations related to municipal, agricultural, and forest resource development. Extensive reservoir construction has also resulted in altered dendritic connectivity in many drainages, which has been shown to significantly alter the function and biodiversity of streams throughout the U.S. This study explored interactions among stream connectivity, watershed characteristics, stream physicochemistry, and fish assemblage composition and abundance in 21 headwater streams within the Red River basin of Louisiana, with half flowing directly into a reservoir. In 2014 and 2015, fish were sampled by electrofishing and seining, and habitats and physicochemistry were characterized. Six fish species were exclusively found in reservoir streams, three fish species were only found in river tributaries, seven fish species were more abundant in river tributaries, and all richness metrics (total, stream specialist, and generalist) calculated for seined fishes were higher in river tributaries. Notably, Grass Pickerel (Esox americanus) was more abundant in river tributaries. Because of its potential role as an obligate glochidial host for the Louisiana Pearlshell Mussel (Margaritifera hembeli), the influence of stream fragmentation on Grass Pickerel may have significant implications regarding conservation of this endangered mussel. Our results parallel trends observed in similar studies indicating decreased species richness and abundance in streams truncated by reservoirs.

A Framework for Diagnosing Factors Degrading the Streamflow Performance of a Soil Moisture Data Assimilation System

Abstract Data assimilation (DA) techniques have been widely applied to assimilate satellite-based soil moisture (SM) measurements into hydrologic models to improve streamflow simulations. However, past studies have reached mixed conclusions regarding the degree of runoff improvement achieved via SM state updating. In this study, a synthetic diagnostic framework is designed to 1) decompose the random error components in a hydrologic simulation, 2) quantify the error terms that originate from SM states, and 3) assess the effectiveness of SM DA to correct these random errors. The general framework is illustrated through a case study in which surface Soil Moisture Active Passive (SMAP) data are assimilated into a large-scale land surface model in the Arkansas–Red River basin. The case study includes systematic error in the simulated streamflow that imposes a first-order limit on DA performance. In addition, about 60% of the random runoff error originates directly from rainfall and cannot be corrected by SM DA. In particular, fast-response runoff dominates in much of the basin but is relatively unresponsive to state updating. Slow-response runoff is strongly controlled by the bottom-layer SM and therefore only modestly improved via the assimilation of surface measurements. Combined, the total runoff improvement in the synthetic analysis is small (<10% over the basin). Improvements in the real SMAP-assimilated case are further limited due to systematic error and other factors such as inaccurate error assumptions and SMAP rescaling. Findings from the diagnostic framework suggest that SM DA alone is insufficient to substantially improve streamflow estimates in large basins.

Evaluation and Hydrologic Validation of Three Satellite-Based Precipitation Products in the Upper Catchment of the Red River Basin, China

Satellite-based precipitation products (SPPs) provide alternative precipitation estimates that are especially useful for sparsely gauged and ungauged basins. However, high climate variability and extreme topography pose a challenge. In such regions, rigorous validation is necessary when using SPPs for hydrological applications. We evaluated the accuracy of three recent SPPs over the upper catchment of the Red River Basin, which is a mountain gorge region of southwest China that experiences a subtropical monsoon climate. The SPPs included the Tropical Rainfall Measuring Mission (TRMM) 3B42 V7 product, the Climate Prediction Center (CPC) Morphing Algorithm (CMORPH), the Bias-corrected product (CMORPH_CRT), and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) Climate Data Record (PERSIANN_CDR) products. SPPs were compared with gauge rainfall from 1998 to 2010 at multiple temporal (daily, monthly) and spatial scales (grid, basin). The TRMM 3B42 product showed the best consistency with gauge observations, followed by CMORPH_CRT, and then PERSIANN_CDR. All three SPPs performed poorly when detecting the frequency of non-rain and light rain events (<1 mm); furthermore, they tended to overestimate moderate rainfall (1–25 mm) and underestimate heavy and hard rainfall (>25 mm). GR (Génie Rural) hydrological models were used to evaluate the utility of the three SPPs for daily and monthly streamflow simulation. Under Scenario I (gauge-calibrated parameters), CMORPH_CRT presented the best consistency with observed daily (Nash–Sutcliffe efficiency coefficient, or NSE = 0.73) and monthly (NSE = 0.82) streamflow. Under Scenario II (individual-calibrated parameters), SPP-driven simulations yielded satisfactory performances (NSE >0.63 for daily, NSE >0.79 for monthly); among them, TRMM 3B42 and CMORPH_CRT performed better than PERSIANN_CDR. SPP-forced simulations underestimated high flow (18.1–28.0%) and overestimated low flow (18.9–49.4%). TRMM 3B42 and CMORPH_CRT show potential for use in hydrological applications over poorly gauged and inaccessible transboundary river basins of Southwest China, particularly for monthly time intervals suitable for water resource management.

Alteration of freshwater ecosystem services under global change – A review focusing on the Po River basin (Italy) and the Red River basin (Vietnam)

Freshwater ecosystem services are negatively affected by factors such as climate change (e.g. changes in temperature, precipitation, and sea level rise) and human interventions (e.g. agriculture practices, impoundment of dams, and land use/land cover change). Moreover, the potential synergic impacts of these factors on ecosystems are unevenly distributed, depending on geographical, climatic and socio-economic conditions. The paper aims to review the complex effects of climatic and non-climatic drivers on the supply and demand of freshwater ecosystem services. Based on the literature, we proposed a conceptual framework and a set of indicators for assessing the above-mentioned impacts due to global change, i.e. climate change and human activities. Then, we checked their applicability to the provisioning services of two well-known case studies, namely the Po River basin (Italy) and the Red River basin (Vietnam).To define the framework and the indicators, we selected the most relevant papers and reports; identified the major drivers and the most relevant services; and finally summarized the fundamental effects of these drivers on those services. We concluded that the proposed framework was applicable to the analyzed case studies, but it was not straightforward to consider all the indicators since ecosystem services were not explicitly considered as key assessment endpoints in these areas. Additionally, the supply of ecosystem services was found to draw much more attention than their demand. Finally, we highlighted the importance of defining a common and consistent terminology and classification of drivers, services, and effects to reduce mismatches among ecosystem services when conducting a risk assessment.

Scalable Multiobjective Control for Large-Scale Water Resources Systems Under Uncertainty

Advances in modeling and control have always played an important role in supporting water resources systems planning and management. Changes in climate and society are now introducing additional challenges for controlling these systems, motivating the emergence of complex, integrated simulation models to explore key causal relationships and dependences related to uncontrolled sources of variability. In this brief, we contribute a massively parallel implementation of the evolutionary multiobjective direct policy search method for controlling large-scale water resources systems under uncertainty. The method combines direct policy search with nonlinear approximating networks and a hierarchical parallelization of the Borg multiobjective evolutionary algorithm. This computational framework successfully identifies control policies that address both the presence of multidimensional tradeoffs and severe uncertainties in the system dynamics and policy performance. We demonstrate the approach on a challenging real-world application, represented by the optimal control of a network of four multipurpose water reservoirs in the Red River basin in Northern Vietnam, under observed and synthetically generated hydrologic conditions. Results show that the reliability of the computational framework in finding near-optimal solutions increases with the number of islands in the adopted hierarchical parallelization scheme. This setting reduces the vulnerabilities of the designed solutions to the system’s uncertainty and improves the discovery of robust control policies addressing key system performance tradeoffs.

Exploring How Changing Monsoonal Dynamics and Human Pressures Challenge Multireservoir Management for Flood Protection, Hydropower Production, and Agricultural Water Supply

AbstractMultireservoir systems require robust and adaptive control policies capable of managing hydroclimatic variability and human demands across a range of time scales. This is especially true for river basins with high intraannual and interannual variability, such as monsoonal systems that need to buffer against seasonal droughts while also managing extreme floods. Moreover, the timing, intensity, duration, and frequency of these hydrologic extremes may evolve with deeply uncertain changes in socioeconomic and climatic pressures. This study contributes an innovative method for exploring how possible changes in the timing and magnitude of the monsoonal cycle impact the robustness of reservoir operating policies designed assuming stationary hydrologic and socioeconomic conditions. We illustrate this analysis on the Red River basin in Vietnam, where reservoirs and dams serve as important sources of hydropower production, multisectoral water supply, and flood protection for the capital city of Hanoi. Applying our scenario discovery approach, we find that reservoir operations designed assuming stationarity provide robust hydropower performance in the Red River but that increased mean streamflow, amplification of the within‐year monsoonal cycle, and increased interannual variability all threaten their ability to manage flood risk. Additionally, increased agricultural water demands can only be tolerated if they are accompanied by greater mean flow, exacerbating food‐flood trade‐offs in the basin. These findings highlight the importance of exploring the impacts of a wide range of deeply uncertain socioeconomic and hydrologic factors when evaluating system robustness in monsoonal river basins, considering in particular both lower‐order moments of annual streamflow and intraannual monsoonal behavior.

Evaluation of TOPMODEL-Based Land Surface–Atmosphere Transfer Scheme (TOPLATS) through a Soil Moisture Simulation

Abstract Better quantification of the spatiotemporal distribution of soil moisture across different spatial scales contributes significantly to the understanding of land surface processes on the Earth as an integrated system. While observational data for root-zone soil moisture (RZSM) often have sparse spatial coverage, model-simulated soil moisture may provide a useful alternative. TOPMODEL-Based Land Surface–Atmosphere Transfer Scheme (TOPLATS) has been widely studied and actively modified in recent years, while a detailed regional application with evaluation currently is still lacking. Thus, TOPLATS was used to generate high-resolution (30 arc s) RZSM based on coarse-scale (0.125°) forcing data over part of the Arkansas–Red River basin. First, the simulated RZSM was resampled to coarse scale to compare with the results of Mosaic, Noah, and VIC from NLDAS. Second, TOPLATS performance was assessed based on the spatial absolute difference among the models. The comparison shows that TOPLATS performance is similar to VIC, but different from Mosaic and Noah. Last, the simulated RZSM was compared with in situ observations of 16 stations in the study area. The results suggest that the simulated spatial distribution of RZSM is largely consistent with the distribution of topographic index (TI) in most instances, as topography was traditionally considered a major, but not the only, factor in horizontal redistribution of soil moisture. In addition, the finer-resolution RZSM can reflect the in situ soil moisture change at most local sites to a certain degree. The evaluation confirms that TOPLATS is a useful tool to estimate high-resolution soil moisture and has great potential to provide regional soil moisture estimates.

Enhancing Prediction Performance of Landslide Susceptibility Model Using Hybrid Machine Learning Approach of Bagging Ensemble and Logistic Model Tree

The objective of this research is introduce a new machine learning ensemble approach that is a hybridization of Bagging ensemble (BE) and Logistic Model Trees (LMTree), named as BE-LMtree, for improving the performance of the landslide susceptibility model. The LMTree is a relatively new machine learning algorithm that was rarely explored for landslide study, whereas BE is an ensemble framework that has proven highly efficient for landslide modeling. Upper Reaches Area of Red River Basin (URRB) in Northwest region of Viet Nam was employed as a case study. For this work, a GIS database for the URRB area has been established, which contains a total of 255 landslide polygons and eight predisposing factors i.e., slope, aspect, elevation, land cover, soil type, lithology, distance to fault, and distance to river. The database was then used to construct and validate the proposed BE-LMTree model. Quality of the final BE-LMTree model was checked using confusion matrix and a set of statistical measures. The result showed that the performance of the proposed BE-LMTree model is high with the classification accuracy is 93.81% on the training dataset and the prediction capability is 83.4% on the on the validation dataset. When compared to the support vector machine model and the LMTree model, the proposed BE-LMTree model performs better; therefore, we concluded that the BE-LMTree could prove to be a new efficient tool that should be used for landslide modeling. This research could provide useful results for landslide modeling in landslide prone areas.

Predicting future land cover change and its impact on streamflow and sediment load in a trans-boundary river basin

Abstract. Sediment load can provide very important perspective on erosion of river basin. The changes of human-induced vegetation cover, such as deforestation or afforestation, affect sediment yield process of a catchment. We have already evaluated that climate change and land cover change changed the historical streamflow and sediment yield, and land cover change is the main factor in Red river basin. But future streamflow and sediment yield changes under potential future land cover change scenario still have not been evaluated. For this purpose, future scenario of land cover change is developed based on historical land cover changes and land change model (LCM). In addition, future leaf area index (LAI) is simulated by ecological model (Biome-BGC) based on future land cover scenario. Then future scenarios of land cover change and LAI are used to drive hydrological model and new sediment rating curve. The results of this research provide information that decision-makers need in order to promote water resources planning efforts. Besides that, this study also contributes a basic framework for assessing climate change impacts on streamflow and sediment yield that can be applied in the other basins around the world.

Future Hydrologic Extremes of the Red River Basin

AbstractHydrologic extremes of drought and flooding stress water resources and damage communities in the Red River basin, located in the south-central United States. For example, the summer of 2011 was the third driest summer in Oklahoma state history and the driest in Texas state history. When the long-term drought conditions ended in the spring of 2015 as El Niño brought record precipitation to the region, there were also catastrophic floods that caused loss of life and property. Hydrologic extremes such as these have occurred throughout the historical record, but decision-makers need to know how the frequency of these events is expected to vary in a changing climate so that they can mitigate these impacts and losses. Therefore, the goals of this study focus on how these hydrologic extremes impact water resources in the Red River basin, how the frequency of such events is expected to change in the future, and how this study can aid local water-resource managers and decision-makers. Heavy-precipitation events were defined at the historical 90th and 99th percentiles, and severe-drought events were identified at a threshold of the standardized precipitation evapotranspiration index’s value of less than or equal to −1. The results show an increase in the frequency of severe-drought events in the western Red River basin and a rise in heavy-rainfall events in the east by the end of the century, especially under RCP 8.5. Therefore, decision-makers and water-resource managers will likely need to prepare for both hydrologic extremes depending on their location within the basin.

Moho depth of the northern Vietnam and Gulf of Tonkin from 3D inverse interpretation of gravity anomaly data

In this paper, the authors present the result of three-dimensional (3D) direct inversion of gravity data to determine the Moho depth along the Red River Fault (RRF) zone and adjacent areas in the land territory of Vietnam and the Gulf of Tonkin. The Moho depth was calculated by 3D Parker inversion supplemented with the gravity anomaly power density spectrum. The given Moho depth and the available teleseismic and magnetotelluric Moho depth are well matched. A structural Moho map of the study region was constructed from the interpretation results. The Moho surface was uplifted along the RRF zone. The shallowest Moho depth was determined in the Red River Basin (RRB), where it ranges from 22 ± 1.0 km to 24 ± 1.0 km in the depocenter of the RRB in the Gulf of Tonkin to 27 ± 1.0 km to 29 ± 1.0 km in the Red River Delta. It is 29 ± 1.0 km to 32 ± 1.0 km from Vietri to Laocai provinces. The deepest Moho depth was found in the northwesternmost and northernmost land territory of Vietnam, where it ranges from 33 ± 1.0 km to 35.8 ± 1.0 km. A percentage of the Earth's crustal compensation is also investigated. The obtained crustal thickness and compensation state are useful for their implications regarding the geodynamics and tectonics of the RRF and surrounding region.

Validating Rainfall-Runoff Modelling Using Satellite-Based and Reanalysis Precipitation Products in the Sre Pok Catchment, the Mekong River Basin

The limitation in quantity and quality of climate data, in particular rainfall measurements, directly affects the reliability of hydrological models, which negatively impacts on the quality of water resources planning and management. This is obviously true in poorly-gauged or in transboundary river catchments with limited practice of data sharing among the riparian states. Satellite-based and reanalysis rainfall products are increasingly recognised as a promising information source to supplement ground observations. This research aims to study the feasibility of using satellite-based and reanalysis rainfall data for rainfall-runoff modelling in the Sre Pok catchment-a poorly gauged catchment located in Vietnam and Cambodia. First, three selected rainfall products (Tropical Rainfall Measuring Mission-TRMM, CPC MORPHing Technique-CMORPH, and European Reanalysis-ERA-Interim) were compared against ground rainfall data of 13 rain-gauges, located inside and in the vicinity of the study catchment. The validation results show that the studied global datasets have a reasonably good correlation with ground observation at monthly time scale (NSE = 0.3 to 0.8, R2 = 0.4 to 0.8), but relatively poor correlation at daily scale (NSE = −0.4 to 0.3, R2 = 0.1 to 0.4). Next, a semi-distributed rainfall-runoff model based on HBV-Light was developed to validate these datasets in the Krong Ana sub-catchment of the Sre Pok. The results illustrate satisfactory to very good model performances at monthly time scale for the satellite-based and reanalysis rainfall inputs (NSE = 0.58 to 0.77, R2 = 0.59 to 0.78 for the calibration period from 2004 to 2007, while NSE = 0.59 to 0.80, R2 = 0.64 to 0.84 for the validation period from 2008 to 2010). However, only TRMM and ERA-Interim give acceptable results at daily scale with NSE = 0.52 to 0.67, R2 = 0.53 to 0.67 for the calibration period, and NSE = 0.41 to 0.61, R2 = 0.45 to 0.65 for the validation period. The study concludes that the tested satellite-based and reanalysis rainfall products, especially TRMM and ERA-Interim, could mimic reasonably well the monthly rainfall pattern in the study region. It also demonstrates a great opportunity to use satellite-based and reanalysis rainfall for runoff modelling at monthly time scale in the Sre Pok catchment and other poorly-gauged (transboundary) catchments in the region, for example in the Mekong and Red River Basins.

Spatiotemporal variation in vegetation coverage and its response to climatic factors in the Red River Basin, China

Vegetation coverage is a critical factor in soil conservation and improving the ecological environment. As an important ecological corridor connecting China's southwest and Southeast Asia, the Red River Basin is characterized by vulnerable ecosystems and serious soil erosion. Identifying the heterogeneity in vegetation coverage and its response to climatic factors are critical for ecological protection and soil and water conservation. MOD13Q1 NDVI data with a spatial resolution of 250 m and 16 d temporal resolution were collected from 2000 to 2014. The maximum synthesis method, univariate linear regression, Hurst exponent, and partial correlation analysis were used to detect the spatiotemporal variation and sustainability of vegetation coverage and characterize the relationship between vegetation NDVI and climatic factors in the wet season in the Red River Basin. NDVI showed a rather significant increasing trend in the wet season. The “corridor-barrier” function of valleys and mountains affected the spatiotemporal patterns in the Longitudinal Range-Gorge Region. Areas of improved, degraded, and stable vegetation coverage accounted for 50.1%, 27.1%, and 22.8% of the total, respectively. The role of precipitation was higher than temperature in the interaction between NDVI and climatic factors. A time lag effect was found in the NDVI response to rainfall and temperature variation. Different vegetation types showed various spatiotemporal responses to climatic factors. Human activities, especially the implementation of the Grain for Green Project (GFGP), affected the spatial and temporal patterns of vegetation coverage.

Organic carbon transfers in the subtropical Red River system (Viet Nam): insights on CO2 sources and sinks

The Red River, draining a 169,000 km2 watershed, is the second largest river in Viet Nam and constitutes the main source of water for a large percentage of the population of North Viet Nam. Here we present the results of an investigation into the spatial distribution and temporal dynamics of particulate and dissolved organic carbon (POC and DOC, respectively) in the Red River Basin. POC concentrations ranged from 0.24 to 5.80 mg C L−1 and DOC concentrations ranged from 0.26 to 5.39 mg C L−1. The application of the Seneque/Riverstrahler model to monthly POC and DOC measurements showed that, in general, the model simulations of the temporal variations and spatial distribution of organic carbon (OC) concentration followed the observed trends. They also show the impact of high population densities (up to 994 inhab km−2 in the delta area) on OC inputs in surface runoff from the different land use classes and from urban point sources. A budget of the main fluxes of OC in the whole river network, including diffuse inputs from soil leaching and runoff and point sources from urban centers, as well as algal net primary production and heterotrophic respiration was established using the model results. It shows the predominantly heterotrophic character of the river system and provides an estimate of CO2 emissions from the river of 330 Gg C year−1. This value is in reasonable agreement with the few available direct measurements of CO2 fluxes in the downstream part of the river network.

Hydrological model using ground- and satellite-based data for river flow simulation towards supporting water resource management in the Red River Basin, Vietnam

The Red River basin (RRB) exhibits substantial variation of water resource seasonally and annually. Sustainable water resource management in the RRB has been challenging due to the lack of in situ hydrological measurement data over the basin-wide scale. To address this issue, this study aimed to perform the setting up, calibration, and validation of the variable infiltration capacity (VIC) hydrological model forced with ground- and satellite-based datasets at a high spatial resolution of 0.1° for simulating the daily river flow of the Red River system in the RRB during the period of 2005–2014. By using the finely resolved land cover characterization with 15 types of land cover and leaf area index - the most important feature of vegetation that significantly influences the simulation of hydrological variables provided by the spatially distributed satellite remote sensing data, this study would not only address the poor data availability over the RRB but also enhance the accuracy of model simulation. The simulation results generally indicated that the calibrated VIC model could satisfactorily capture the river flow dynamics of the Red River system in the RRB. The VIC model's underestimated river flow compared to the observed data during the dry season for the downstream stations was likely due to the operation of the large man-made reservoirs and dams in the upstream catchments of the RRB that not represented by the VIC model. The findings also suggested that for further improving the VIC model performance, the use of more spatially representative meteorological data provided by satellite remote sensing should be considered in future studies.

Assessing the Influence of the Mining Operations on the State of Streams in the Northern Part of the Red River Basin (Viet Nam)

A study was made of the influence of extraction of lead and zinc ores in the northern part of Vietnam (the Red river basin, Chodon district of Bac Can Province, and the basins of the Dai, Ban Thi, Ta Dieng and Cau rivers). Background concentrations of macro- and microelements and biogenic elements are determined in the river waters and water extracts from bottom sediments of small streams of the study area. A significance exceedance of background concentrations was revealed in stretches of the headwaters of the Ban Thi and Dai rivers caused by a combination of natural and anthropogenic factors. It is established that the river waters near the pollution sources contain increased (compared with the geochemical background) concentrations of Zn, Pb, Fe, Ni, Co, As, Bi, Cd, Cs, Sb, Ag,NO2− and SO42−. The waters are estimated as moderately and heavily polluted, and at the other points as minimally polluted. It is determined that the level of accumulation of matter in water extracts from bottom sediments with respect to the geochemical background in the vicinity of the ore dressing factories corresponds to weakly and heavily polluted bottom sediments, and further downstream, to thy minimum level of pollution. It is shown that the influence of extraction of lead and zinc ores on the state of small streams is observed in stretches as long as 11–12 km (with a maximum in stretches of up to 4.5 km). The mathematical model of Pb and Zn distribution in the river waters of the study area has been developed and tested.

红河流域“通道-阻隔”作用下2000-2014年植被EVI变化趋势与驱动力

PDF HTML阅读 XML下载 导出引用 引用提醒 红河流域“通道-阻隔”作用下2000-2014年植被EVI变化趋势与驱动力 DOI: 10.5846/stxb201703210483 作者: 作者单位: 成都理工大学地球科学学院,成都理工大学管理科学学院,成都理工大学地球科学学院;成都理工大学管理科学学院;中国科学院水利部成都山地灾害与环境研究所;中国科学院水利部成都山地灾害与环境研究所,成都理工大学环境与土木工程学院;成都理工大学生态资源与景观研究所,成都理工大学地球科学学院,成都理工大学地球科学学院,成都理工大学地球科学学院 作者简介: 通讯作者: 中图分类号: 基金项目: 国家科技支撑项目（2012BAC19B05）；国家自然科学青年基金项目（41501060）；中国地质调查局项目（DD20160015-26） The EVI trends and driving factors in Red River Basin affected by the “corridor-barrier” function during 2000-2014 Author: Affiliation: Chengdu University of Technology,Chengdu University of Technology,,,,, 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:红河流域地表生态、水热分布格局等受到"通道-阻隔"作用的显著影响，以MODIS EVI数据作为植被定量研究指标，结合全国1：100万植被类型图、红河流域内部以及周边气象数据和研究区的DEM数据，利用趋势分析和相关性分析法，探讨在"通道-阻隔"作用的影响下流域内2000-2014年植被EVI时空变化趋势及其驱动力，重点研究了植被EVI变化对气候因子的响应规律。结果表明：（1）2000-2014年间，红河流域生长季植被EVI整体上以-0.15%/a的年际变化率呈波动减少趋势，空间异质性明显。EVI呈减少趋势区域主要集中在绿春县中部和金平县西南部；EVI呈增加趋势区域集中分布在墨江县、文山县，麻栗坡中部、广南-富宁南部区域、红河-元江一带以及藤条江西南部地区。（2）通过对生长季EVI指数与四个不同时间序列的月平均气温和月累积降水量的相关分析可知，生长季EVI指数与同期气温相关性较好；与降水量呈现明显的滞后性，滞后时间约为1个月。（3）相关分析表明，整体上红河流域生长季植被EVI与气温呈负相关关系，与降水呈正相关关系。在0.05显著性检验水平下，红河流域生长季植被EVI变化受气候影响的区域占3.11%，气温以负向驱动型为主，面积约占1.26%，降水以正向驱动型为主，面积约占0.46%，气温降水联合驱动以弱驱动为主，面积约占1.39%；大部分地区表现为受非气候因子驱动。 Abstract:Surface ecology and hydrothermal distribution are significantly affected by the "corridor-barrier" function in the Red River Basin. This study investigated spatiotemporal trends in the enhanced vegetation index (EVI) and the driving force of its effect from 2000 to 2014 in the Red River Basin. Especially, the response of climatic factors based on the MODIS EVI, combined with the vegetation map, meteorological data, as well as topographic data, were investigated and a trend line and correlation analysis were used. The results showed that:(1) from 2000 to 2014, the Red River Basin EVI showed a declining fluctuating trend, with an annual change rate of -0.15%, with clear spatial heterogeneity. The decreasing area mainly occurred in central Lvchun County and southwest Jinping County, while the increasing area was concentrated in Mojiang County, Wenshan County, the midlands of Malipo, southern Guangnan-Funing County, Yuanjiang-Honghe County, and the southwest of the Tengtiao River. (2) The analysis between the EVI in the growing season and four different time series of climatic factors (monthly mean air temperature and monthly precipitation) showed that the EVI was positively correlated with contemporaneous air temperature. An evident delayed response of EVI to precipitation was observed, accounting for approximately 1 month. (3) Correlation analysis indicated that, in general, EVI was positively correlated with precipitation and negatively correlated with air temperature during the growing season. At the 0.05 level of significance, analysis of the effect of driving factors on EVI showed that about 3.11% of the study area was impacted by climatic driving factors, whereby 1.26%, 0.46% and 1.39% of the area was impacted by air temperature (negative driving effect), precipitation (mainly positive driving effect), and air temperature and precipitation combined, respectively. However, the EVI was affected by non-climatic driving factors in most areas. 参考文献 相似文献 引证文献

Assessing the influence of the mining operations on the state of streams in the northern part of the Red river basin (Vietnam).

Assessing the influence of the mining operations on the state of streams in the northern part of the Red river basin (Vietnam).

Assessing temporal shifts in lotic fish community structure in the upper Red River basin, Oklahoma

ABSTRACTA long-term fish community monitoring program was established by the Oklahoma Department of Wildlife Conservation Streams Program in 2016. One of the primary goals of this program is to evaluate contemporary fish species distributions in Oklahoma and draw inferences regarding changes in those distributions over time. In 2016, fish community surveys took place from late June to early August at a total of 48 sites within the upper Red River basin. Compared to the most comprehensive historical sampling effort within the basin, contemporary surveys detected an additional eight species while three species historically present were not detected in 2016. Multivariate generalized linear model results indicated significant differences in community structure between historical and contemporary surveys. Univariate testing paired with Sum-of-LR analyses revealed differences in community structure were largely driven by increases in generalist fish species (e.g. Green Sunfish and Common Carp) and decreases in small-bodied specialist cyprinids (e.g. Chub Shiner). Although changes in species occurrences may be partially driven by differences in sampling methodology and effort, changes across multiple stream reaches likely reveal real trends.