Research results

Survey Technology for Efficiently Assessing Pavement Structural Soundness  Development of a Moving Wheel Deflectometer (MWD)


Figure 1 Methods to determine pavement structural soundness

Figure 1 Methods to determine
pavement structural soundness


  The length of road pavement in Japan has reached approximately 1 million km. To properly manage roads within a limited budget, it is essential to appropriately assess the soundness of the pavement structure and reflect the results in road maintenance and management.


  The methods used to evaluate the soundness of the pavement structure include direct survey of the inside of the pavement by excavation (open cut survey), survey of a damaged area by collecting cores (core survey), and survey using a falling weight deflectometer (FWD) that measures deflection when applying a measured impact load on the pavement surface (FWD survey). (Figure 1)


  These methods require traffic control and are time-consuming and costly, so they are most effective to investigate localized pavement damage, but are inefficient for wide-area surveys (surveys to determine the soundness of the pavement structure along the entire route managed by the road administrator). It is important to conduct wide-area surveys to accurately identify areas of deteriorated pavement structural soundness and prioritize pavement rehabilitation to extend the pavement life. There has thus been a need to develop the technology to efficiently assess pavement soundness.


  PWRI has therefore developed a moving wheel deflectometer (MWD) through joint research with universities and testing and research institutes with expertise in structural pavement and measured data analysis, paving and measuring companies with expertise in mobile measurements such as road surface texture measuring vehicles, and equipment manufacturers with expertise in measurement equipment.


  MWD is a self-propelled, medium-sized vehicle equipped with a device that measures road surface deflection and non-destructive inspection technology that measures the amount of deflection of the road surface by simply driving. The amount of deflection of the road surface, which is an indication of the soundness of the pavement structure, can be measured continuously and in a short time, enabling wide-area surveys.
  The use of MWD in road management contributes to more efficient and effective road maintenance and repair. (Figure 2)


  We plan to accumulate verification data on various pavement cross-sections and continue to study ways to improve the accuracy of the system.

   
Figure 2 Moving wheel deflectometer (MWD)

Figure 2 Moving wheel deflectometer (MWD)






(Contact : Pavement Research Team)

(Draft) Guidelines for Estimation of Snow Water Equivalent in Dams

1. Introduction

  When the temperature in snowy cold regions rises in spring, snow that had accumulated during winter melts and runs off into rivers. Such water is stored in dams to cover the demand for tap water, agricultural water and other uses from spring throughout summer. For this reason, snow surveys are conducted at all dams in the peak snow season, measuring snow depth and density directly to estimate the water equivalent of the snow cover (snow water equivalent) in the entire basin.

  The approach used to determine the snow water equivalent in each dam basin varies, and include a method of estimating the water equivalent of the snow cover (the amount of water when all the snow has melted) by elevation, and a method of applying empirical formulas. Based on past studies and methods practiced in the field of dam management, the Civil Engineering Research Institute for Cold Region compiles standard methods of estimating the snow water equivalent and verifying the estimation accuracy in a simple way as technical data and publishes these as (draft) guidelines.


2. Snow water equivalent estimation method


Fig. 1 Relationship between water equivalent of snow cover and elevation

Fig. 1 Relationship between water equivalent
of snow cover and elevation (Jozankei Dam)


Fig. 2 Comparison of snow water equivalent estimate and snowmelt season water balance(Jozankei Dam)

Fig. 2 Comparison of snow water equivalent
estimate and snowmelt season water balance
(Jozankei Dam)

  (Source: Literature by Toyabe, et al.Some content
added or modified.The dashed lines in the figure
indicate the root mean square error (RMSE)
with the water balance as the true value.


  The (draft) guidelines are intended for dams where most of the watershed is forest. The common steps of estimating the snow water equivalent and verifying the estimation accuracy are as follows:


(1) Snow survey
  The snow water equivalent is determined by adding up the water equivalent of the snow cover by elevation. For this calculation, it is necessary to measure snow depth and snow density at various elevations. The snow condition is surveyed on-site using snow samplers in March, when the snow water equivalent generally peaks. In principle, snow surveys are conducted in accordance with the Snow and Ice Survey Methods (edited by the Hokkaido Branch of the Japanese Society of Snow and Ice) and the Snow Measurement Guidebook (edited by the Japanese Society of Snow and Ice).


(2) Snow water equivalent estimation
  In forests, the water equivalent of snow cover increases almost linearly with the elevation(Fig. 1).To determine the snow water equivalent of the entire basin of a dam, the water equivalent of the snow cover by elevation is first estimated based on the snow survey results and then these estimates are added up. An empirical formula or other method may be used for some dams.


(3) Verification of estimation accuracy by comparison with the water balance
  The results of estimating the snow water equivalent of a dam are verified by comparison with the water balance in the dam basin in the snowmelt season. The water balance is expressed by the following formula:


  Figure 2 shows an example of the verification of snow water equivalent estimation accuracy. Estimation accuracy is evaluated using the error rate of the root mean square error (RMSE) of the snow water equivalent using the water balance as the true value. RMSE is evaluated using the following formula:



  In case of the example shown in Fig. 2,the water balance mean was 97×106m3, while the RMSE of the estimated snow water equivalent was 18×106m3, resulting in an error rate of approximately 20%. Toyabe, et al. verified the water balance for dams in Hokkaido and reported that the error rate of RMSE for dams with good estimation accuracy was generally within 20%.Accordingly, the accuracy of the estimated snow water equivalent in case of Fig. 2 is generally considered to be adequate.
  If the error rate is larger, we will examine whether the snow survey results appropriately represent the snow conditions in the basin and, if necessary, consider measures including review of the survey points and timing so that the estimation accuracy can be improved.


3. Future challenges

  In recent years, research on the quantification of snow distribution outside forests has advanced, as well as remote sensing technology to determine the snow depth in the entire basin. We will continuously endeavor to improve estimation accuracy by reflecting these new research results in cooperation with dam management sites.



References:
Nishihara et al. “(Draft) Guidelines for Snow Water Equivalent Estimation in Dams.” FY 2012 Hokkaido Development Technology Conference. 2013 (in Japanese).
Toyabe et al. Recent Water Equivalent of Snow Cover and Water Balance in Snowmelt Season in Dams under the Direct Control of the Government. FY 2010 Hokkaido Development Technology Conference. 2011 (in Japanese).






(Contact : Watershed Environmental Engineering Research Team,  CERI)