Introduction

Precipitation and river discharge are among the most important variables of the global water cycle as they reflect a holistic image about the hydrological processes happing within and over a river basin. Precipitation has enormous spatiotemporal variations which pose a great challenge to maintain sufficient estimates (Ji and Kang, 2015). Streamflow monitoring, on the other hand, is extremely useful to address various water-related applications.
The climate records of the past decades had documented evolving recurrent extreme weather events and natural disasters around the world (Arnell, 1999; Nohara et al. , 2006), subjected with negative socioeconomic implications (Wang and Zhang, 2018). Climate change results in a raise in atmospheric temperature coupled with obvious alteration to precipitation patterns (Labat et al. , 2004; Guptaet al. , 2015). As a consequence of climate change which is evolving apparently in the long run, the frequency of natural disasters such as typhoons, severe tropical cyclones, floods and droughts have been intensified (Hein et al. , 2019). Moreover, it was reported by the United Nations International Strategy for Disaster Reduction (UNISDR), between 1998 and 2017, that 91% of all documented disasters in the whole world were induced by extreme weather events including floods, droughts, heatwaves, etc. (Wallemacq and Below, 2017).
In fact, the Japanese Archipelago has a distinctive position where numerous natural disasters happen frequently including seismic, volcanic activities, tsunamis, typhoons, and floods mainly due to being located in the Ring of Fire (Shimokawa et al. , 2016). These natural disasters degrade the national sustainable development aspirations and pose additional serious barrier for Japan as it faces multiple challenges fundamentally in terms of population shrinking and declining skilled workforce. Therefore, natural disaster prevention and mitigation framework must be carried out and implemented by a national committee, and hence the role of a multi-disciplinary team is to understand vulnerability and how to minimize and overcome the potential adverse implications (Alcántara-Ayala, 2002). As a result, additional contributions are still required to investigate and address how ecosystems are directly and/or indirectly modified by various hydrological processes during normal and extreme climates.
For hydrological and water resources studies, it is vital to understand streamflow properties induced by extreme climate response during both short-term (few hours) and long-term (several days to several years) and impact of human activities as well. Indeed, diverse parameterization methods have been developed to characterize river discharge patterns and identify changes and complexity in them (Pan et al. , 2012; Stosicet al. , 2018).
Mountain rivers over the world have a vital role in in maintaining water ecology and conserving biodiversity, as well as, their key functions in flood control (Chenet al. , 2019). However, mountain rivers are significantly vulnerable to problems associated with heavy rains during short time. This could be attributed to the fact that stream velocity in mountain regions can vary within a system and subjected to chaotic turbulence (Mihailović et al. , 2014). Therefore, investigating the fluctuation and complexity of flow properties for mountain streams will deliver profound understanding about streamflow patterns and their corresponding responses influenced by hydrologic climates and/or human activities.
Considering the future scenarios of streamflow in East Asia, it was projected in the literature that there will be an increase in river discharge by the coming decades (e.g. Arnell, 1999; Nohara et al., 2006). Sato et al., (2012) inferred that at the end of this century river flow will rise due to increases in precipitations. Likewise, Higashino and Stefan (2019) concluded that the annual maximum discharge in Japanese streams are expected to be increased.
Certainly, heavy seasonal rainfall that occur frequently in the western part of Japan is among the worst destructive disasters, since it accompanies by landslides and mudflows. Furthermore, out of all Japanese prefectures, Hiroshima was ranked as the first prefecture in Japan that has the highest number of mountainous slopes (\(\sim\)32,000) to be susceptible to landslide and mudflow disasters (Tsuchida et al., 2014), followed by Shimane and Yamaguchi prefectures 22,300 and 22,250, respectively. Due to the frequent huge precipitation and associated sudden landslide and mudflow disasters, for the time being, the Ministry of Land Infrastructure and Tourism (MLIT) of Hiroshima prefecture installed a network of real-time water level measurement that collects measurements at multiple sites over Hiroshima’s streams, aiming to build up a profound knowledge about the different characteristics related to streamflow response during various rainy events and hence to mitigate the potential risk accompanied with heavy precipitation.
In the recent years, information-based theories have received increased interest in the hydrological studies to detect and address the variability in numerous hydrological variables including precipitation, temperature, and streamflow (e.g. Brunsell, 2010; Elsner and Tsonis, 1993; Koutsoyiannis, 2005; Mishra et al., 2009). Pan et al., (2012) documented the benefits of information-based metrics in their capability to interpret how a model presents patterns of information content and complexity exist in hydrological dataset. Indeed, considerable efforts had shown the applicability of the information and complexity measures to characterize the various patterns in time series analysis. In particular, (Pachepsky et al. , 2006, 2016; Pan et al. , 2011, 2012), extensively utilized the information and complexity metrics to characterize various soil moisture, streamflow, and rainfall time series using a straightforward symbolic strings approach of 2 characters length per word for system description which is very useful but uncomplicated classification. Nonetheless, there is no work had discussed the importance of considering complex patterns of words to characterize different system states. In other words, how to recommend using short or long length of words to describe different patterns embedded in a hydrological system. In addition, there is almost no work that clearly highlighted the transformation of a system from a state to another especially during short and long terms.
Accordingly, one of the fundamental research questions that we aim to answer is what are the information and hidden hydrological phenomena that can be detected by characterizing streamflow patterns using more complex patterns according to information and complexity theory and how to define the appropriate pattern length that describe the different potential states of a system (dataset, time series, etc.). Therefore, one of the main contributions of the present research is to shed light on streamflow variations in a mountainous river and the nested relationships within its tributaries located at Hiroshima prefecture that has been extremely and repeatedly deteriorated from severe floods. The particular novelty is to examine temporal streamflow patterns at high-frequency scales using real discharge data obtained from both classic and novel hydroacoustic system, also at low-frequency that happen over a basin and sub-basin scales. We also proposed a new extension for the information-based metrics to assess streamflow patterns during flood periods. After describing the monitoring sites in section 2, the methods are given in section 3. Results and discussion are provided in sections 4 and 5, respectively. Eventually, section 6 shows the research conclusions.