VULNERABILITY ASSESSMENT OF URBAN WATER SUPPLY SYSTEMS TO DROUGHT IN JAPAN

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1 Annual Journal of Hydraulic Engineering, JSCE, Vol.57, 2013, February VULNERABILITY ASSESSMENT OF URBAN WATER SUPPLY SYSTEMS TO DROUGHT IN JAPAN Takaaki MASUYAMA 1, Oliver C. SAAVEDRA V. 2 and Chihiro YOSHIMURA 3 1 Student member of JSCE, Graduate student, Department of Civil Engineering, Tokyo Institute of Technology ( M1-4 Ookayama, Meguro-ku, Tokyo , Japan) 2 Member of JSCE, Dr. Eng., Associate Professor, Department of Civil Engineering, Tokyo Institute of Technology ( M1-4 Ookayama, Meguro-ku, Tokyo , Japan) 3 Member of JSCE, Dr. Eng., Associate Professor, Department of Civil Engineering, Tokyo Institute of Technology ( M1-4 Ookayama, Meguro-ku, Tokyo , Japan) To assess the vulnerability of urban water supply systems, in regions even with limited accessible data, a proper index is required. Therefore, we developed a method to assess the drought risk using basic flow characteristics. Here, we suggested calculating water shortage index using intake volume, daily discharge, water demand, inhabitants served and water source type at each river basin. This method was applied in major rivers in Japan but considering its applicability in developing countries. The results show Yoshino River with the highest drought risk while Yodo River with the lowest risk. Actually, Yoshino River was found more vulnerable against change of intake amount for agricultural use. On the other hand, Arakawa and Abukuma Rivers were sensitive due to change of water demand depending on population change. The obtained water shortage indices were compared to actual reported droughts in Japan, and logic connection was found. Thus, water shortage index might be useful to analyze drought risk in other rivers. Key Words : Vulnerability, Water supply, Drought, Water Shortage Index, Sensitivity analysis 1. INTRODUCTION Water scarcity is one of the major social issues all over the world. Two and half billion people were recorded as lacking any improved sanitation facilities in 2002 and more than 1 billion of them could not access to an improved drinking water source 1). This issue is likely to become more severe in the future due to climate change and population growth 2). Then, assessment of water resources including drought situation in growing cities should be carried out rational and efficiently. Most cities in the world have been using surface water or groundwater 3). The rapid urbanization and migration to large cities using groundwater as main source has been causing water shortage, land subsidence, salt injury and pollution of source 4) 5). Thus, groundwater is not usually main source in such urban cities with large economies and high population. For example, in Tokyo, 72 km 3 of river water is used in a year while only 9 km 3 is taken from groundwater 6). In addition, using river water has been gradually increasing 7). The literature was found in many study cases analyzing drought related to river water 8)9). In short, drought risk in medium to large size cities can be assessed based on river discharge since it can be understood as the integrated result from hydrological processes in the basin. To countermeasure droughts in cities, drought indices have been developed by different researchers lately in various fields 10). Drought can be classified in four; meteorological, agricultural, hydrological and socio-economic drought 11). Then, drought indices lead toward each type of drought. For example, the typical index mainly intended for meteorological or agricultural drought is Palmer Drought Severity Index (PDSI) 12) and it has been used widely by U. S. government agencies and states 13)14). PDSI consists of a soil moisture algorithm calibrated for relatively homogeneous regions. As input data, it mainly requires precipitation, temperature, and soil water content. Then, another method is the Standardized Precipitation Index (SPI) 15) which includes snowpack estimation and reservoir effects. However, meteorological indices such as PDSI and 1

2 SPI are highly dependent to land surface and local climatic conditions, leaving short versatility to different areas outside the U. S. 13)14)16). On the other hand, Surface Water Supply Index (SWSI) 17) is mainly applied for hydrological and agricultural drought. The SWSI is calculated based on monthly non-exceedance probability from available historical records of snowpack, stream flow, precipitation, and reservoir storage. It is a feasible measure to represent water supply conditions unique to each basin. However, it has the disadvantages such as lag of infiltration and limitation of inter-basin comparisons 13). In addition, drought indices in global scale are not suitable for water resource management due to mainly spatial resolution 18). Moreover, the Cumulative Supply to Water Demand Ratio (CWD) 19) is one of the latest indices for assessment of global water resources. Although it is suitable to take seasonal variation of discharge into account, it requires elaborate calculation with detailed data. Overall, although each index has advantages, commonly simpler way for inter-basin comparison and data availability is required for basin scale management. Moreover, these kinds of indices require many data sets such as long-term precipitation, temperature, vegetation type, crop growth, soil property and evapotranspitration 20). In Japan, an index so-called water supply security index developed by Ministry of Land, Infrastructure, Transport and Tourism (MLIT) has been used to report drought 21). This indicator is represented as ability of river to cope with the largest drought in target years. However, analysis using this indicator can be questionable in terms of its value. For example, the target year in indicator for both Yoshino and Arakawa Rivers is set as 3 years even though many more droughts happened in Yoshino River 22). At the same time, the other indicator named degree of drought influence was also developed by MLIT 6). It depends on the percentage of intake restriction, duration and affected population (% day person). This indicator is empirical-based which requires detailed data for the three variables including dam operation. In order to assess the drought risk in developing countries, to gather such detailed data can be difficult as well as research-based indicators if possible. Then, a feasible and effective indicator using easy-accessible data is required to analyze drought risk. Therefore, this study attempts to assess the vulnerability of urban water supply system to droughts using a method based mainly on observed daily discharge. It was applied to major five rivers in Japan where we can have access free and plenty observed data, and drought indicators. In the future, Annual Journal of Hydraulic Engineering, JSCE, Vol.57, 2013, February we aim to apply the developed method in this study to the other cities in developing countries. 2. METHOD (1) Vulnerability assessment This study focused on river water as main source. The drought risk is represented as water shortage volume which cannot be supplied to people served. We calculated the volume of water shortage (WS) by subtracting necessary daily intake volume from daily discharge. If the discharge is higher than the intake volume, the difference is set to zero, meaning no risk for that day. Then, WS was accumulated in one year as ΣWS. This value can be understood as an indicator showing how much water is deficit at the river or intake dam. On the other hand, population served from the river which is officially announced by water supply sector or government (SP) does not take usage ratio by water source (RR) into account. Actual population served from each target river was obtained by product of SP and RR. Moreover, water demand per capita (WD) depends on regions. Thus, necessary water amount in associated cities supplied from target rivers was obtained by product of SP, RR and WD. At last, Water Shortage Index (WSI) was calculated by the ratio of ΣWS to SP RR WD (Eq.1). ΣWS WSI (%) (1) SP RR WD The WSI is a drought indicator based on daily discharge observed nearby intake station. The value of WSI can be understood as deficit ratio of actual water intake volume relative to ideal water intake. Actually, WSI represents the percentage of population in each river basin cannot have access to water, otherwise the percentage of water demand per capita can be regarded as the deficit for each person. (2) Target urban water supply system Five river basins were targeted with their associated served cities were chosen from representative regions of Japan (Fig. 1). They are summarized with their key properties in Table 1. The period of the assessment run from 2001 to 2010 (Data missing: 2001, 2002 in Abukuma River and in Yodo River). (3) Discharge and Intake We used river discharge observed nearby intake stations along the rivers. In case daily discharge data along tributaries between observation and intake stations along main channel was not available, we estimated it through calculating ratio of announced average discharge of tributaries to main channels. At stations where discharge was not observed, we 2

3 Annual Journal of Hydraulic Engineering, JSCE, Vol.57, 2013, February estimated it by observed water level. This would be the case in developing countries. Additionally, we examined intake amount for domestic, agricultural and industrial usages published by water supply sectors, local governments in target areas, and MLIT (Table 2). (4) Served population Local governments or water supply sectors officially releases served population by new water supply plan. If this value is applied without revision, we are unable to assess in detail. Actually, served population from the river does not take actual usage ratio by water source into account. Thus, actual served population from the target rivers was calculated in this study, considering usage ratio (RR) on each local municipality and accumulated to one target city (Table 2). Fig. 1 Locations of target rivers and associated cities in Japan (5) Concept of developed method Existing drought indices and conventional assessment methods in Japan have limitations such Table 1 General information in target rivers and cities Target River Arakawa Yoshino Yodo Abukuma Chikugo Tokyo / Kagawa / Osaka / Fukuoka / City A / City B Miyagi / - Saitama Tokushima Hyogo Saga Region Kanto Shikoku Kinki Tohoku Kyusyu River River length (km) Property Basin area (km 2 ) Precipitation 23) Annual precipitation (mm/year) Station name Tokyo Tokushima Osaka Sendai Fukuoka Data period Discharge 24) Mean (m 3 /s) Min/ Max (m 3 /s) 10.60/ / / / / 4672 Location of the station (distance from outlet (km)) Data period Population City A / City B (mil. person) / / / / / 0.84 Table 2 Intake stations, observing stations and applied values in the calculation Target River Arakawa Yoshino Yodo Abukuma Chikugo Kagawa / Osaka / City A / City B Tokyo / Saitama Miyagi / - Fukuoka / Saga Tokushima Hyogo Akigase ~ Station Ikeda Dam ~ Kurume City Kuzuha ~ Shichikashuku Intake Main stations for Okubo Higashi Miyoshi station ~ Kema Dam Purification Plant City Chikugo Ozeki No. of stations No. of agencies and local governments Discharge 13) Tarouemon and Shichikashuku Katanose and Station Name Ikeda Takahama Sugama Dam Chuo Hashi RR (%) City A / City B / / / / / 54.5 SP (mil. person) City A / City B 11.2 / / / / / 0.27 WD (L/day/person) City A / City B 321 / / / / / 275 3

4 as time and spatial resolution problems, land versatility or data availability as shown in introduction part. The point of our method is feasible access data based on discharge, easy-update, and assessment without dam operation. Particularly, discharge data can be accessible easier including output of hydrological model. Moreover, our method can predict future condition of drought risk. In addition, spatial target is based on intake station along river. In this meaning, we can expect to assess droughts more effectively. 3. Results and Discussion WSI was found out higher rates in Yoshino River than other rivers as seen in Fig. 2. The range was from 0 to % and the average was % for assessed period. On the other hand, the WSI in Yodo River became zero in all target period. The range in Arakawa River varied from 0 to 0.87 % and the average was 0.16 %, 0 to 0.49 % and 0.17 % in Abukuma River, and 0 to 4.25 % and 0.76 % in Chikugo River, respectively. These percentages of water were insufficient as well as deficit of ΣWS (m 3 /year). Here, no data shown in Fig.2 means 0 of each sample in WSI and ΣWS except data missing. According to the results, Yodo River had abundant water. Actually, the utilization ratio of total discharge in Yodo River is around 60 % and river water is efficiently reused 25). The most intake stations are located nearby the river mouth which gathers plenty water. The locations of main intake stations along Yodo, Arakawa, Yoshino, Abukuma and Chikugo Rivers are 13~35 km, 38km, 79 km, 56 km and 25~36 km away from the river mouths, respectively. At Kunijima Intake Station in Yoshino River, river water is extracted after waste water is discharged. Although the water quality might need to be discussed, effectiveness of water reuse is inferred. In order to confirm information provided by WSI method to analyze drought, the results were compared to a conventional indicator (degree of drought influence / affected population/ 365). This indicator was calculated by MLIT for large dams in each region in Japan. Since the index is empirically based on actual intake restriction, this means same as actual drought severity. From 2001 to 2010, WSI in Arakawa River, Yoshino River, Yodo River, Abukuma River and Chikugo River were compared with intake restriction indicator in Kanto, Shikoku, Kinki, Tohoku and Kyusyu, respectively (Fig. 3). In addition, these values were revised considering reported drought history in each river. Fig. 3 shows similar tendency between WSI and intake restriction An nual Journal of Hydraulic Engineering, JSCE, VOL.57, 2013, February indicator in severe drought history except in Chikugo River in 2004, in Arakawa River in 2005, and in Yodo River in Particularly, it can be seen clearly higher values for Yoshino River for both indicators showing the water shortage constraint. This may imply the less flexibility in management under drought risk for both indicators. WSI might provide useful information to managers. However, the assessment using WSI detected risks while water intake was not restricted at corresponding rivers and periods. One possible reason of the overestimation of our method is that WSI is unable to take storage issue before and after intake into account. In this study, we used intake restriction indicator to compare our method. However, this conventional Fig.2 Water Shortage Index (WSI (%)) (A) and total deficit volume (ΣWS (1000m 3 /year)) (B). Fig. 3 Comparison of WSI (%) with intake restriction indicator (Degree of drought influence / affected population/ 365, %) 4

5 An nual Journal of Hydraulic Engineering, JSCE, VOL.57, 2013, February Fig.4 Sensibility analysis: fluctuation of average WSI in depending on changes of intake volume for agricultural use (A), and SP and associated intake amount for domestic use (B). WSI in Yodo River became 0 regardless of change of variables. Sensitivity = ΔWSI/ΔVariable. indicator is based on regional information for each river. Thus, if we are able to apply river-based data, we might obtain the actual results for comparison between actual quantified drought indicator and WSI. We assessed water shortage risk in last decade. Then, we analyzed sensitivity to predict the risk in the future changing three types of input data in relation to water demand. We set up intake amount for agricultural usage as explanatory variable. Then, population served (SP) and associated intake amount for domestic usage were changed. WSI was calculated depending on variation whose range was -5 ~ 5 (%) on each variable based on average of WSI in Figure 4 shows the change of WSI depending on each change of explanatory variables. In the calculation of agricultural use, the sensitivities in Yoshino, Abukuma and Chikugo Rivers were 3.55, 2.32 and 2.01 (%), respectively. This seems to depend on the ratio of intake for agricultural use to other uses. In summer season, 33 m 3 /s of water from Yoshino River is used for agriculture in Kagawa and Tokushima while 6 m 3 /s is taken for domestic use. Population change heavily influenced on change of WSI in particularly Arakawa and Abukuma Fig. 5 Average water resource remaining (Annual discharge Annual intake amount, m3/day) in target rivers in Rivers (Fig. 4). The change rate varied % in Arakawa River and % in Abukuma River. This result shows that original population is not only the reason but also allowance of discharge to intake amount. Then, we calculated the difference between annual discharge and annual intake amount (Fig. 5). According to the results, the water remaining in Arakawa and Abukuma Rivers were lower than the others, and vulnerable against the increase of intake amount due to population served. Moreover, according to these results, it is implied that domestic water is not main withdrawal in Yoshino River and the reason of higher drought risk depends on agricultural use. Yoshino River has plenty water in winter season which requires little water for agriculture while much water is required and drought risk gets higher in summer season. Thus, our method showed feasibility to predict future drought risk. Sensitivity analysis depending on supply change due to change of precipitation pattern also should be carried out. 4. CONCLUSION & FUTURE REMARKS We assessed drought risk in five rivers and the associated cities in Japan using new developed indicator; Water Shortage Index (WSI (%)). According to results, Yoshino River in Shikoku region with high drought risk while low risk in Yodo River in Kinki region. Moreover, the average of WSI value in Arakawa River in Kanto region, the value in Abukuma River in Tohoku region and in Chikugo River in Kyusyu region were all less than 1.0 (%). WSI and conventional intake restriction indicators were compared and found in logic connection showing less flexibility of management for water shortage rivers like Yoshino River. Thus, new indicator developed in our study is likely useful to analyze drought risk and support decision makers. 5

6 Moreover, sensitivity analysis showed that Arakawa and Abukuma Rivers were particularly found vulnerable against the change of water demand due to population change. In fact, the risk associated water supply system might be different in other regions. Especially, developing countries seem to have vulnerable water supply system. In order to assess such vulnerability precisely in developing countries, to gather detailed data can be difficult if possible. Although this study focused only in Japan, the simple methodology developed in this study can be applied to the other countries. However, our indicator is unable to take storage issue before and after intake into account. Moreover, assessment at upstream from monitoring stations is impossible. According to this perspective, further improvement is required. ACKNOWLEDGMENT: This study was supported partly by Asian Core Program funded by Japan Society for the Promotion of Science (JSPS), and the Core Research for Evolutional Science and Technology (CREST) project, entitled long-term vision for the sustainable use of the world's freshwater resources, funded by Japan Science and Technology Agency (JST). REFERENCES 1) WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation: Water for life, Making it happen, ) IPCC: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change, Cambridge University Press, ) Igor A. Shiklomanov: World water resources - A new appraisal and assessment for the 21 st century, World Water Resources prepared in the framework of the International Hydrological Programme, ) Stephen S. D. Foster, Adrian Lawrence, Brian Morris: Groundwater in Urban Development - Assessing Management Needs and Formulating Policy Strategies, World Bank Technical Paper, No.390, ) Shah T., Burke J. and Villholth K.: Water for Food, Water for Life, chapter 10, Groundwater: a global assessment of scale and significance, ) Japan Ministry of Land, Infrastructure, Transport and Tourism: Water Resource in Japan, ) Gotoh K., Yutoh Y., Shichijyoh T., Kusano K.: A Consideration on the Use of Snow, Ice and Underground Water as Water Resources, Research report- Department of Technology in Nagasaki University, ) Ito, K., Xu, Z., Jinno, K., Kojiri, T. and Kawamura, A.: Decision Support System for Surface Water Planning in River Basins. J. Water Resource Planning Management, 127(4), , Annual Journal of Hydraulic Engineering, JSCE, VOL.57, 2013, February 9) Rajagopalan B., Nowak K., Prairie J., Hoerling M., Harding B., Barsugli J., Ray A., and Udall B.: Water supply risk on the Colorado River - Can management mitigate?, Water Resources Research, 45, W08201, ) Stefan Niemeyer: New drought indices, Options Mediterraneennes, Series A (80), ) Wilhite, D. A. and Glantz, M. H.: Understanding the Drought Phenomenon: The Role of Definitions, Water International, 10 (3), , ) Wayne C. Palmer: Meteorological Drought, U.S. Weather Bureau, Research Paper, No. 45, ) Michael J. Hayes: Drought Indices, Feature Article From International West Climate Summary, ) Kwon H. J. and Kim S. J., Assessment of distributed hydrological drought based on hydrological unit map using SWSI drought index in South Korea, KSCE Journal of Civil Engineering, 14, , ) McKee, T. B., N. J. Doesken, and J. Kleist: The relationship of drought frequency and duration to time scales, 8th Conference on Applied Climatology, , ) William M. Alley: The Palmer Drought Severity Index: Limitations and Assumptions, Journal of Climate and Applied Meteorology, 23, , ) Shafer, B.A. and L.E. Dezman: Development of a Surface Water Supply Index (SWSI) to assess the severity of drought conditions in snowpack runoff areas. Proceedings of the Western Snow Conference, , ) Falkenmark M., Lundqvist J. and Widstrand C.: Macro-scale water scarcity requires micro-scale approaches: Aspects of vulnerability in semi-arid development1989, Natural Resources Forum, 13 (4), , ) Hanasaki N., Kanae S., Oki T., and Shirakawa N.: An integrated model for the assessment of global water resources Part 2: Anthropogenic activities modules and assessments, Hydrology and Earth System Sciences, 12, , ) Narasimhan B.: Development of indices for agricultural drought monitoring using a spatially distributed hydrological model, Doctor Thesis in Texas A&M University, ) Japan Ministry of Land, Infrastructure, Transport and Tourism: First conference report of water management, ) Japan Ministry of Land, Infrastructure, Transport and Tourism, Shikoku Region Bureau: First meeting of research group for water problem in Shikoku, ) Japan Meteorological Agency: Weather information system ( 24) Japan Ministry of Land, Infrastructure, Transport and Tourism: Water information system ( 25) Lake Biwa and Yodo River Water Quality Preservation Organization, BYQ Water quality report, (Received September 30, 2012) 6