Prediction of river water temperature: a comparison between a new family of hybrid models and statistical approaches

River water temperature is a key physical variable controlling several chemical, biological and ecological processes. Its reliable prediction is a main issue in many environmental applications, which however is hampered by data scarcity, when using data‐demanding deterministic models, and modelling limitations, when using simpler statistical models. In this work we test a suite of models belonging to air2stream family, which are characterized by a hybrid formulation that combines a physical derivation of the key equation with a stochastic calibration of parameters. The air2stream models rely solely on air temperature and streamflow, and are of similar complexity as standard statistical models. The performances of the different versions of air2stream in predicting river water temperature are compared with those of the most common statistical models typically used in the literature. To this aim, a dataset of 38 Swiss rivers is used, which includes rivers classified into four different categories according to their hydrological characteristics: low‐land natural rivers, lake outlets, snow‐fed rivers and regulated rivers. The results of the analysis provide practical indications regarding the type of model that is most suitable to simulate river water temperature across different time scales (from daily to seasonal) and for different hydrological regimes. A model intercomparison exercise suggests that the family of air2stream hybrid models generally outperforms statistical models, while cross‐validation conducted over a 30‐year period indicates that they can be suitably adopted for long‐term analyses. Copyright © 2016 John Wiley & Sons, Ltd.     

Quantitative estimation of submarine groundwater discharge using airborne thermal infrared data acquired at two different tidal heights

Submarine groundwater discharge (SGD) plays an important role in coastal biogeochemical processes and hydrological cycles, particularly off volcanic islands in oligotrophic oceans. However, the spatial and temporal variations of SGD are still poorly understood owing to difficulty in taking rapid SGD measurements over a large scale. In this study, we used four airborne thermal infrared surveys (twice each during high and low tides) to quantify the spatiotemporal variations of SGD over the entire coast of Jeju Island, Korea. On the basis of an analytical model, we found a linear positive correlation between the thermal anomaly and squares of the groundwater discharge velocity and a negative exponential correlation between the anomaly and water depth (including tide height and bathymetry). We then derived a new equation for quantitatively estimating the SGD flow rates from thermal anomalies acquired at two different tide heights. The proposed method was validated with the measured SGD flow rates using a current meter at Gongcheonpo Beach. We believe that the method can be effectively applied for rapid estimation of SGD over coastal areas, where fresh groundwater discharge is significant, using airborne thermal infrared surveys.     

Submarine groundwater discharge revealed by aerial thermal infrared imagery: a case study on Jeju Island,Korea

Submarine groundwater discharge (SGD) is a global phenomenon that carries large volumes of groundwater and dissolved chemical species such as nutrient, metals, and organic compounds to coastal zones. We report the influence of SGD on the coastal waters of Jeju Island, Korea, using high‐resolution aerial thermal infrared (TIR) mapping techniques and field investigations. An aircraft‐based system was implemented using a cost‐effective TIR camera for aerial TIR mapping. Ground‐based calibrations and system integration with GPS/IMU (global positioning system/inertial measurement unit) were performed for the aerial systems. The aerial surveys showed distinct low‐temperature signatures of SGD along the coasts of Jeju Island, revealing large groundwater inputs from the coastal aquifers to the ocean. Multiple aerial surveys over a range of seasons and tidal stages revealed that SGD rates dynamically affect the sea surface temperature (SST) of the coastal zone. The in‐situ measurements supported that SGD has a substantial influence on the coastal water chemistry as well as SST. Our observations highlight the extent to which aerial‐based TIR mapping can serve as a powerful tool for studying SGD and other coastal processes. Copyright © 2016 John Wiley & Sons, Ltd.     

Variations in elastic thickness and flexure of the Maracaibo block

We estimate the lateral variations of the elastic thickness of the Maracaibo block with a 3D numerical approach by using centered finite differences. The calculation is based on solving the fourth-order partial differential equation that governs the bending of a thin plate fixed on its boundaries (zero displacement) with variable thickness (or elastic thickness for this particular case). An initial plate-load model is built and is iteratively modified to fit the general basement configuration and gravity data. The final result is an elastic thickness map that covers the Maracaibo block and the surrounding sections of the South American plate. It shows that the elastic thickness ranges from 30 km to 18 km with a mean value of 23.6 km and a mode of 26 km. The largest elastic thickness values are associated with the location of the Santa Marta Mountains and the Barinas Apure Basin, while the smallest ones with the Mérida Andes-Maracaibo Basin flexural system. The current basement configuration within the Maracaibo basin, formed as a result of its geodynamic evolution, has affected the mechanical properties of the Maracaibo block near the current Mérida Andes position. The load of the Perijá Range is compensated by a complex stress tensor, and that of the Santa Marta Mountains does not have an isostatic root as it is held by a relatively strong lithosphere.     

PMODTRAN: a parallel implementation based on MODTRAN for massive remote sensing data processing

MODerate resolution atmospheric TRANsmission (MODTRAN) is a commercial remote sensing (RS) software package that has been widely used to simulate radiative transfer of electromagnetic radiation through the Earth's atmosphere and the radiation observed by a remote sensor. However, when very large RS datasets must be processed in simulation applications at a global scale, it is extremely time-consuming to operate MODTRAN on a modern workstation. Under this circumstance, the use of parallel cluster computing to speed up the process becomes vital to this time-consuming task. This paper presents PMODTRAN, an implementation of a parallel task-scheduling algorithm based on MODTRAN. PMODTRAN was able to reduce the processing time of the test cases used here from over 4.4 months on a workstation to less than a week on a local computer cluster. In addition, PMODTRAN can distribute tasks with different levels of granularity and has some extra features, such as dynamic load balancing and parameter checking.     

气候变化情景下黄淮海区域热量资源及夏玉米温度适宜度

利用黄淮海区域90个站点1971—2000年逐日气象资料以及国家气候中心发布的未来气候变化情景(A1B)下区域气候模式(Reg CM3)模拟的黄淮海区域1951—2070年0.25°×0.25°格点气象资料,结合夏玉米主要生育期对温度的需求,构建了黄淮海区域的温度适宜度和变异系数模型,并对1951—2070年黄淮海区域热量资源、夏玉米主要生育期的温度适宜度及其变异系数的时空变化特征进行分析。结果表明:1)黄淮海区域≥10℃积温和80%保证率下日平均温度≥10℃的初日均呈现由北向南依次增加的趋势,且随时间推移,分别呈增加和提前趋势。2)黄淮海区域夏玉米播种—出苗期的温度适宜度随时间整体呈逐渐上升的变化趋势、其变异系数随时间呈降—升—降的变化趋势;出苗—抽雄期的温度适宜度随时间呈先降后升的变化趋势、其变异系数呈降—升—降—升的变化趋势;抽雄—成熟期的温度适宜度空间上呈现2010年前北低南高、未来情景下中部低四周高的分布趋势,时间上呈2010年前稳定、未来情景下先降后升的变化趋势,其变异系数呈相反变化趋势;3)黄淮海区域夏玉米温度适宜度及其变异系数从播种—出苗期—出苗—抽雄期—抽雄—成熟期均呈反相位的变化关系。     

Landsat 8热红外数据定标参数的变化及其对地表温度反演的影响

Landsat系列卫星上的TIRS热红外传感器数据已被大量应用,针对TIRS数据的地表温度反演也相继开发出一些算法,并有一些研究对TIRS数据的定标及其地表温度反演算法的精度进行了对比。本文主要就TIRS热红外传感器定标参数的变化,结合这些定标参数变化的时间点对有关地表温度反演算法的适用性和有效性进行分析,特别是对劈窗算法是否适合当前的TIRS数据进行了讨论,以使用户能够对Landsat 8 TIRS热红外数据的正确使用有进一步的认识。总的看来,由于视域外杂散光的影响,TIRS数据的定标精度仍达不到设计目标,TIRS第11波段的不确定性仍成倍大于TIRS 10波段。因此,在Landsat团队未彻底解决这一问题之前,同时用TIRS第10、第11这两个差距较大的波段构成的劈窗算法来反演地表温度,其精度存在较大的不确定性,US6-S团队仍在致力于改进第11波段的精度,改进后的波段可以用劈窗策法。目前应以TIRS第10单波段的方式来反演地表温度为宜。     

不同遥感影像的城市热岛空间分布特征分析

针对传统的地面观测方式很难全面掌握城市地面热岛的空间分布情况的问题,该文将HJ-1B卫星热红外图像代表的亮温图和采用HJ-1B卫星反演的温度图像正规化,利用量化等级体系对同一地区的亮温分布图和温度分布图进行划分,提出并采用间隙度指数对不同影像的高温区进行空间分布进行评价。实验结果表明:基于热红外影像的城市热岛空间分布比基于热红外影像反演的温度图的热岛空间分布更为集中,为研究不同影像之间的城市热岛空间分布提供了一种评价方法。     

武汉中心城区热岛效应模拟

针对传统的模拟热环境时空演变模型欠缺可推广性,该文提出运用CA-Markov模型研究热环境变化趋势,既能有效模拟元胞时空格局变化,又能提高元胞转化预测精度,经验证Kappa指数为73.46%,具有较高的可信度。基于CA-Markov模型模拟的武汉中心城区热环境表明:2009—2018年低温区和次低温区呈现减少趋势,中温区显著增加,热岛略有增长,总体强度增大,热岛效应愈发明显;2009—2018年热岛演变呈西南-东北方向,有向西-东方向发展的趋势,热岛重心南偏西方向移动;2009—2018年热岛区域在景观水平上破碎度较高,热环境趋于复杂化。研究结果对武汉中心城区城市规划、生态环境改善等具有一定的参考价值。