Crowdsourced approaches for stage measurements at ungauged locations using smartphones

ABSTRACT

The growing availability of smart devices with advanced sensors has increased the opportunities for citizen science applications for environmental monitoring. Accurate and widespread monitoring of river stage is vital for modeling water resources. Reliable data points are required for model calibration and validation in forecast studies. While current embedded monitoring systems provide accurate measurements, the cost to replicate these systems on a large domain is prohibitively expensive, limiting the quantity of data available. This project describes a new method to accurately measure river levels using smartphone sensors. Pictures of the same point on the river’s surface are taken to perform calculations based on the GPS location and spatial orientation of the smartphone. The proposed implementation is significantly more accessible than existing water measuring systems while offering similar accuracy. A case study is performed to evaluate the accuracy and sensitivity of the measurements to changes in distance.     

Suitability of satellite-based hydro-climate variables and machine learning for streamflow modeling at various scale watersheds

ABSTRACT

Streamflow modeling is essential to investigate processes in the hydrologic cycle and important for water resource management application. However, in-situ hydrologic data paucity, because of various factors such as economic, political, instrument malfunctioning, and poor spatial distribution, makes the modeling process challenging. To overcome this limitation, we introduced a satellite remote sensing-based machine learning approach – boosted regression tree (BRT) – that integrates spatial land surface and climate variables that describe the sub-units, and applied it in three variable size watersheds in the Upper Mississippi River Basin (UMRB), USA. The model simulation results were tested using an independent dataset and showed Nash–Sutcliffe efficiency values of 0.80, 0.76, and 0.69 for the UMRB, Illinois River Watershed, and Raccoon River Watershed, respectively. In addition, we compared the performance of the machine learning models with existing process-based modeling results. Overall performance is comparable with the process-based approaches, but with significantly less modeling effort and resources.     

回眸燕山运动——致敬“燕山运动”的创建者和中国地质学会的奠基人翁文灏

一百年前中国地质学会成立，先驱者们竖立起中国地质科学的旗帜，也是中国科学的第一面旗帜，从此中国地质科学发展进入快车道。燕山运动、中国北方〖XCD.TIF;%70%70,JZ〗科研究，长身贝研究、北京猿人头盖骨的发现是中国地质科学快速进入国际赛道的标志。经历了近百年的研究，北京西山及北京北山、冀北和辽西典型地区积累的证据和资料表明，翁文灏提出的燕山运动A期(幕）发生在160±3 Ma前；晚侏罗世早—中期记录了以髫髻山组和蓝旗组为代表的区域强烈火山喷发和广泛的岩浆侵入(中间期/幕）；晚侏罗世晚期区域发育逆冲推覆构造；燕山期构造发展至早白垩世早期135 Ma，冀北张家口组和辽西义县组之下的不整合为燕山运动B期结束的代表。燕山运动是东亚大陆构造体制从古特提斯及古亚洲洋构造域转变为环太平洋活动大陆边缘构造域的产物。这是中国东部和东亚区域中生代独特的重大的地质构造事件。     

Calculating basal temperatures in ice sheets: an Excel spreadsheet method

The flow of ice sheets and their geomorphological impact is greatly influenced by their basal thermal regime. Calculations of basal temperatures in ice sheets are therefore fundamental in evaluating glacier dynamics and in determining the spatial distribution of zones of erosion and deposition beneath ice masses. Calculations of basal temperatures are not frequently attempted, however, primarily because of the techniques required to solve the heat conduction equation between the ice surface and the base. This paper describes a new Excel spreadsheet method of solving this equation that can readily be applied to both former and contemporary ice sheets. The application of the spreadsheet is illustrated with two examples. The first provides a calculation of basal thermal regime beneath the north eastern part of the Scottish ice sheet during the last glacial maximum; the second shows how basal ice temperatures can be calculated beneath the modern Antarctic ice sheet. Copyright © 2002 John Wiley & Sons, Ltd.     

疏勒河双塔灌区地下水动态变化研究及开发建议

本文通过对疏勒河流域双塔灌区地下水资源分布特征及地下水动态变化特征的分析,提出了该灌区地下水开发利用的建议及可持续发展对策.     

Integration of RADARSAT and GIS modelling for estimating future Red River flood risk

A new geomatics-based approach for flood prediction was developed and used to model the magnitude and spatial extent of a future Red River flood in southern Manitoba. This approach combines the statistical modelling capabilities of Markov (non-spatial) analysis and logistic regression (spatial) within a geographic information system (GIS) environment, utilizing modelling inputs derived from remotely sensed RADARSAT imagery and other digital geographic data. The 1997 Red River flood was the second largest in recorded history, and the largest for which accurate data are available. The results indicate: (i) a flood “one time interval-in terms of 3 days time unit measurement- larger in area” than the 1997 flood is expected to affect 17.6% more land (an additional 47.6 km²) within the study area compared to 1997 levels based on Markovian probability derived from observations from the 1997 event; and (ii) the majority of this excess flooding will take place on agricultural land; no additional communities are expected to be at risk. Quantitative assessment verified the capability of this modelling approach for producing statistically significant results. The methodology used in this research would be easily transferable to other areas, and may provide the basis for a viable alternative to conventional hydrologic-based flood prediction approaches This revised version was published online in August 2006 with corrections to the Cover Date.     

Characterisation of streamflow regimes in central Spain, based on relevant hydrobiological parameters

The biotic composition, structure, and function of aquatic, wetland, and riparian ecosystem depend largely on the hydrological regime (Poff, N.L., Ward, J.V., 1990. Implications of streamflow variability and predictability for lotic community structure: a regional analysis of streamflow patterns. Can. J. Fisheries Aquat. Sci. 46, 1805–1818; Richter, B.D., Baumgartner, J.V., Wiginton, R., Braun, D.P., 1997 How much water does a river need? Freshwater Biol. 37, 231–249). Available flow data for many rivers in the world can be used to validate these ecological theories. There is a demand for studies that use hydrological indices to establish criteria, which serve to group together regime types at a local level. Once this has been done, these hydrologically similar groups can be used to identify communities of living organisms that are linked to specific aspects of the river's behaviour.

An approach to characterise flow regimes in the river network of the Tagus basin in Spain is presented. The river Tagus (río Tajo) is one of the seven major rivers of the Iberian peninsula. All hydrological data were acquired from the measurements made in the Tagus basin, at 25 gauging stations. Twelve variables were derived for each gauged site to describe variability and predictability of average streamflow conditions, and to describe the frequency, timing and intensity of high flow and low flow extremes.

A hierarchical clustering routine was used to identify similar groups of rivers as defined in terms of similar characteristics of their streamflow regime. The variables were also examined with simple correlations to determine if multicollinearity occurred, in order to reject redundant parameters or to identify similar behaviour trends between pairs of parameters. Some parameters have shown a tendency to increase or decrease along the east–west axis, suggesting that some of the studied characteristics may have a geographical cause.

Cluster analysis, with the values of the 12 parameters, reveals two main groups, each of which splits into two main subdivisions. One of these subgroups contains six rivers with similar characteristics, can be considered to be ‘classic regular rivers’, the stations in this first subgroup are mostly situated geographically close to each other. At the other end, we have found a subgroup, with a high variation of flows over the year and high flood flows; these rivers are highly irregular rivers with great changes. This regular–irregular gradient found between the groups is similar to that observed by others authors (Poff, N.L., Allan J.D., 1995. Functional organization of stream fish assemblages in relation to hydrological variability. Ecology 76, 606–627), and strong associations have been documented with compositions of populations and probably reflect differences in other similar important environmental factors.     

地震时序记录数据在强震前的关联特征

对强震前的时序数据进行统计计算研究，发现若以特定地震带的时序数据为样本集，在强震前无标度区的跨度会相应地变长，反映出自组织程度的变化，以川滇地震带历史记录数据分析为例，若无标度区出现持续增长的征兆，则标志着地震活跃期的到来，同时可能伴有7级左右的地震，对于有的地震带关联维数出现变化不平缓的情况，也预示着地震活跃期的到来。但如果以地理区域划分如台湾省及全国的发震情况作为研究对象则无此规律。该结论在一定程度上可以提供一个强震发生中期预测的参考指标。