Long‐term streamflow trends in Hawai'i and implications for native stream fauna

Climate change has fundamentally altered the water cycle in tropical islands, which is a critical driver of freshwater ecosystems. To examine how changes in streamflow regime have impacted habitat quality for native migratory aquatic species, we present a 50‐year (1967–2016) analysis of hydrologic records in 23 unregulated streams across the five largest Hawaiian Islands. For each stream, flow was separated into direct run‐off and baseflow and high‐ and low‐flow statistics (i.e., Q10 and Q90) with ecologically important hydrologic indices (e.g., frequency of flooding and low flow duration) derived. Using Mann–Kendall tests with a running trend analysis, we determined the persistence of streamflow trends through time. We analysed native stream fauna from ~400 sites, sampled from 1992 to 2007, to assess species richness among islands and streams. Declines in streamflow metrics indicated a general drying across the islands. In particular, significant declines in low flow conditions (baseflows), were experienced in 57% of streams, compared with a significant decline in storm flow conditions for 22% of streams. The running trend analysis indicated that many of the significant downward trends were not persistent through time but were only significant if recent decades (1987–2016) were included, with an average decline in baseflow and run‐off of 10.90% and 8.28% per decade, respectively. Streams that supported higher native species diversity were associated with moderate discharge and baseflow index, short duration of low flows, and negligible downward trends in flow. A significant decline in dry season flows (May–October) has led to an increase in the number of no‐flow days in drier areas, indicating that more streams may become intermittent, which has important implications for mauka to makai (mountain to ocean) hydrological connectivity and management of Hawai'i's native migratory freshwater fauna.     

Enhancement of backtracking search algorithm for identifying soil parameters

In this paper, an enhanced backtracking search algorithm (so-called MBSA-LS) for parameter identification is proposed with two modifications: (a) modifying the mutation of original backtracking search algorithm (BSA) considering the contribution of current best individual for accelerating convergence speed and (b) novelly incorporating an efficient differential evolution (DE) as local search for improving the quality of population. The proposed MBSA-LS is first validated with better performance than the original BSA and some other typical state-of-the-art optimization algorithms on a benchmark of soil parameter identification in terms of effectiveness, efficiency, and robustness. Then, the efficiency of the MBSA-LS is further illustrated by two representative cases: identifying soil parameters from both laboratory tests and field measurements. All comparisons demonstrate that the proposed MBSA-LS algorithm can give accurate results in a short time. Finally, to conveniently solve the problems of parameter identification, a practical tool ErosOpt for parameter identification is developed by integrating the proposed MBSA-LS and some other efficient algorithms for readers to conduct the parameter identification using optimisation algorithms.     

Groundwater recharge in an arid grassland as indicated by soil chloride profile and multiple tracers

Previous studies have shown that shallow groundwater in arid regions is often not in equilibrium with near‐surface boundary conditions due to human activities and climate change. This is especially the case where the unsaturated zone is thick and recharge rate is limited. Under this nonequilibrium condition, the unsaturated zone solute profile plays an important role in estimating recent diffuse recharge in arid environments. This paper combines evaluation of the thick unsaturated zone with the saturated zone to investigate the groundwater recharge of a grassland in the arid western Ordos Basin, NW China, using the soil chloride profiles and multiple tracers (²H, ¹⁸O, ¹³C, ¹⁴C, and water chemistry) of groundwater. Whereas conventional water balance and Darcy flux measurements usually involve large errors in recharge estimations for arid areas, chloride mass balance has been widely and generally successfully used. The results show that the present diffuse recharge beneath the grassland is 0.11–0.32 mm/year, based on the chloride mass balance of seven soil profiles. The chloride accumulation age is approximately 2,500 years at a depth of 13 m in the unsaturated zone. The average Cl content in soil moisture in the upper 13 m of the unsaturated zone ranges from 2,842 to 7,856 mg/L, whereas the shallow groundwater Cl content ranges from 95 to 351 mg/L. The corrected ¹⁴C age of shallow groundwater ranges from 4,327 to 29,708 years. Stable isotopes show that the shallow groundwater is unrelated to modern precipitation. The shallow groundwater was recharged during the cold and wet phases of the Late Pleistocene and Holocene humid phase based on palaeoclimate, and consequently, the groundwater resources are nonrenewable. Due to the limited recharge rate and thick unsaturated zone, the present shallow groundwater has not been in hydraulic equilibrium with near‐surface boundary conditions in the past 2,500 years.     

卫星臭氧资料的发展与应用

随着卫星探测技术的进步、天气学和气候学理论的不断完善,以及高性能计算机广泛应用,卫星臭氧资料的种类得到极大丰富并被应用到多个研究领域中,取得了一系列重要成果。文中介绍了主要星载臭氧探测仪的发展概况,回顾了卫星臭氧资料在气象领域的应用研究成果,主要包括卫星臭氧资料在气旋或低压过程中、全球或区域臭氧的气候分布及变化特征、高原臭氧分布及变化特点、数值应用等方面的应用研究,并展望了卫星臭氧资料研究的未来发展趋势。      

武威市初、终霜日气候特征

为了因地制宜,合理调整种植结构和布局,有效利用农业气候资源。利用1961—2014年武威市4个气象站点初、终霜日(最低地温≤0℃)观测资料,采用现代气候诊断分析方法,系统分析了该市年初、终霜日的时空变化特征。结果表明:受海拔高度、地形地势以及植被覆盖情况的影响,在空间分布上,武威市初霜日为山区早于荒漠区早于绿洲平原区,终霜日为山区晚于荒漠区晚于绿洲平原区,各地初、终霜日存在一定的异常性,正常初、终霜日均在60%左右,对农业生产造成危害的偏早和特早初霜日、偏晚和特晚终霜日的概率均在20%左右。在时间变化上,武威市初霜日呈显著推迟趋势,终霜日呈显著提早趋势,霜期呈显著缩短趋势,终霜日提早的幅度比初霜日推迟的幅度更大。初霜日和终霜日的时间序列均分别存在着8~10年和9~11年的准周期变化。初霜日在1998年发生了气候突变,终霜日在1996年发生了气候突变。     

一种四叉树和测地线活动轮廓模型相结合的海陆影像分割方法

海陆影像分割对于后续的海岸线提取、潮间带地形反演、海岸演化状况分析等都具有十分重要的意义。本文在分析了四叉树、测地线活动轮廓(GAC)模型和Canny边缘检测算子等在海陆影像分割中优缺点的基础上,提出了一种四叉树、Canny算子和GAC模型相结合的海陆影像分割方法。该方法综合利用上述各方法的优点,将Canny算子边缘检测结果融入到基于四叉树初分割的GAC模型中,重构边界停止函数,演化水平集方程,实现海陆影像分割。试验结果表明,该方法具有海陆影像分割速度快、精度高、可靠性强和自动化程度高等优点,对于弱边缘以及严重凹陷边缘,都能实现自动和准确分割。     

A synthetic aperture radar sea surface distribution estimation by n-order Bézier curve and its application in ship detection

To dates,most ship detection approaches for single-pol synthetic aperture radar(SAR) imagery try to ensure a constant false-alarm rate(CFAR).A high performance ship detector relies on two key components:an accurate estimation to a sea surface distribution and a fine designed CFAR algorithm.First,a novel nonparametric sea surface distribution estimation method is developed based on n-order Bézier curve.To estimate the sea surface distribution using n-order Bézier curve,an explicit analytical solution is derived based on a least square optimization,and the optimal selection also is presented to two essential parameters,the order n of Bézier curve and the number m of sample points.Next,to validate the ship detection performance of the estimated sea surface distribution,the estimated sea surface distribution by n-order Bézier curve is combined with a cell averaging CFAR(CA-CFAR).To eliminate the possible interfering ship targets in background window,an improved automatic censoring method is applied.Comprehensive experiments prove that in terms of sea surface estimation performance,the proposed method is as good as a traditional nonparametric Parzen window kernel method,and in most cases,outperforms two widely used parametric methods,K and G0 models.In terms of computation speed,a major advantage of the proposed estimation method is the time consuming only depended on the number m of sample points while independent of imagery size,which makes it can achieve a significant speed improvement to the Parzen window kernel method,and in some cases,it is even faster than two parametric methods.In terms of ship detection performance,the experiments show that the ship detector which constructed by the proposed sea surface distribution model and the given CA-CFAR algorithm has wide adaptability to different SAR sensors,resolutions and sea surface homogeneities and obtains a leading performance on the test dataset.