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A Study on Flood Forecasting in the Upper Indus Basin Considering Snow and Glacier Meltwater

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A Study on Flood Forecasting in the Upper Indus Basin Considering Snow and Glacier Meltwater A Study on Flood Forecasting in the Upper Indus Basin Considering Snow and Glacier Meltwater Paper: A Study on Flood Forecasting in the Upper Indus Basin Considering Snow and Glacier Meltwater Tong Liu∗,†, Morimasa Tsuda∗, and Yoichi Iwami∗∗ ∗International Centre for Water Hazard and Risk Management (ICHARM) under the auspices of UNESCO, Public Works Research Institute 1-6 Minamihara, Tsukuba, Ibaraki 305-8516, Japan †Corresponding author, E-mail: [email protected] ∗∗Public Works Department, Nagasaki Prefectural Government, Nakagaki, Japan [Received June 10, 2016; accepted May 11, 2017] This study considered glacier and snow meltwater by dropower generated from the Indus River at Tarbela Dam using the degree–day method with ground-based air contributes approximately 30% of the total energy de- temperature and fractional glacier/snow cover to sim- mand of the country [3]. ulate discharge at Skardu, Partab Bridge (P. Bridge), Flooding in the monsoon season, from the middle of and Tarbela Dam in the Upper Indus Basin during the June to the end of September, is a challenging problem monsoon season, from the middle of June to the end in the Indus River. A massive flood occurring in July– of September. The optimum parameter set was deter- August 2010 in Pakistan, one of the greatest water-related mined and validated in 2010 and 2012. The simulated disasters in the country’s history, affected more than 20 discharge with glaciermelt and snowmelt could cap- million people and almost one-fifth of Pakistan’s land ture the variations of the observed discharge in terms area [4]. Since 2010, Pakistan has experienced severe of peak volume and timing, particularly in the early monsoon floods annually. Although the floods in 2011, monsoon season. The Moderate Resolution Imaging 2012, and 2013 were relatively less widespread, they still Spectroradiometer (MODIS) daily and eight-day snow caused damage across vast areas. A flood forecasting cover products were applied and recommended with system can mitigate flood damages by alerting officials proper settings for application. This study also investi- of an imminent flood occurrence. Therefore, for further gated the simulations with snow packs instead of daily strengthening of the flood management capacity in Pak- snow cover, which was found to approach the maxi- istan and for accurate early warning of flood and disaster mum magnitude of observed discharge even from the management in the Indus Basin, it is imperative to up- uppermost station, Skardu. grade and improve the accuracy and reliability of the ex- This study estimated the glacier and snow meltwater isting flood forecasting systems. contribution at Skardu, Partab Bridge, and Tarbela The operational flood early warning system, known as 43.2–65.2%, 22.0–29.3%, and 6.3–19.9% of aver- as Indus-Integrated Flood Analysis System (IFAS), was age daily discharge during the monsoon season, re- established by the International Centre for Water Haz- spectively. In addition, this study evaluated the main ard and Risk Management (ICHARM) through a United source of simulation discrepancies and concluded that Nations Educational, Scientific and Cultural Organiza- the methodology proposed in the study worked well tion (UNESCO) project in conjunction with Japan Inter- with proper precipitation. national Cooperation Agency (JICA). IFAS provides the Flood Forecasting Division (FFD) of the Pakistan Me- Keywords: flood, hydrological modeling, glaciermelt, teorological Department (PMD) with scientifically based snowmelt, Indus River flood forecast information along the main stream of the Indus River and the Kabul River, which originates in Afghanistan and is known as one of its main tribu- 1. Introduction taries [5–9]. This system can forecast the peak discharge with hours of lead time with both ground-observed and The Indus River, one of the largest rivers in the world, satellite-based rainfall as input. However, Indus-IFAS has emerges from the Tibetan Plateau and the Himalayas. The several unresolved technical challenges, particularly the Indus Basin covers 1.12×106 km2 in Pakistan (47%), In- lack of glacier and snow meltwater. Glaciated headwa- dia (39%), China (8%), and Afghanistan (6%) and has a ter and snowmelt along with monsoon runoff and ground- total population of more than 300 million [1]. The In- water are the major water sources for the Indus sys- dus Basin Irrigation System (IBIS), which is the largest tem [10]. The Upper Indus Basin (UIB) is reported to con- contiguous irrigation system in the world, provides water tain 11,413 glaciers with a total area of 15,061 km2.Most for all sectors of the economy. In particular, it provides glaciers occur at elevations of 4,000 to 7,000 m above 90% of agricultural production, which contributes about sea level (a.s.l.). The highest elevation, 8,566 m a.s.l., is 22% to Pakistan’s gross domestic product (GDP) [2]. Hy- found in the Shigar Sub-Basin, and the lowest, 2,409 m Journal of Disaster Research Vol.12 No.4, 2017 793 Liu, T., Tsuda, M., and Iwami, Y. a.s.l., is found in the Hunza Sub-Basin [11]. Previous studies have reported that about 50–80% of the total av- erage river flows in the Indus system are fed by snow and glacier meltwater in the Hindu–Kush–Karakoram (HKK) region of the Great Himalayas [2, 12, 13]. Accordingly, the snow cover in the Upper Indus Basin shrinks approx- imately 1.5 × 105 to 2.5 × 104 km2 from April to Au- gust every year [14]. Moreover, the northern mountain- ous areas are particularly susceptible to early monsoon floods caused by the rapid melting of snow and outflow from glacial lakes [15, 16]. In combination with specific weather conditions such as excessive rainfall on melt- ing snow, rapid snowmelt can trigger floods, landslides, and debris flows. In addition, the temporal and spa- tial variability of snowfall and the changes in snow and glacier meltwater can be amplified by the changing cli- mate, which has implications for managing basin water resources. Fig. 1. Map of the Indus River Basin including meteorolog- ical and gauging stations. The current Indus-IFAS relies mainly on observed dis- charge from upstream as input and includes the glacier and snow meltwater component to obtain reliable simu- Table 1. Global Land Cover by National Mapping Organi- lated discharge in the downstream region. The objective zations (GLCNMO) land cover classification and Integrated of this study is to improve the simulated discharge by the Flood Analysis System (IFAS) surface tank parameter class current flood Indus-IFAS, particularly in the Upper Indus [19]. Basin, by developing and applying a method for simulat- ing glacier and snow meltwater reliably with limited ob- Global Map Categories IFAS Parameter served meteorological data. Indus-IFAS is improved by 1 Broadleaf Evergreen Forest considering glacier and snow meltwater calculated with 2 Broadleaf Deciduous Forest 3 Needle leaf Evergreen Forest ground-based air temperature, snow cover from Moder- 1 ate Resolution Imaging Spectroradiometer (MODIS), and 4 Needle leaf Deciduous Forest 5 Mixed Forest glacial coverage combined with ground-based rainfall ob- 6 Tree Open servations. 7 Shrub 8 Herbaceousv 9 Herbaceous with Sparse Tree/Shrub 2 2. Study Region 10 Sparse vegetation 16 Bare area consolidated (gravel, rock) This study focuses on the Upper Indus Basin, which is 17 Bare area unconsolidated (sand) defined as the catchment area upstream of Tarbela Dam 11 Cropland with an area of 277,075 km2 [14] (Fig. 1). As the river 12 Paddy field leaves the mountains, Tarbela Dam is the first major struc- 13 Cropland/ Other vegetation Mosaic 3 ture on the Indus River and supplies irrigation for the agri- 14 Mangrove cultural lands. The management of the Tarbela Dam de- 15 Wetland 18 Urban 4 pends greatly on the summer inflow contribution of the 19 Snow/Ice snow- and glacier-fed tributaries [14]. 20 Water bodies 5 During the monsoon season, from the middle of June to the end of September, monsoon rainfall causes peak floods together with snowmelt runoff in short duration. Major tributaries of the Indus upstream of Tarbela Dam at 1 km resolution. are shown in Fig. 1. Three water gauging stations at River channels were generated and corrected to match Skardu, Partab Bridge (P. Bridge), and Tarbela Dam are Google Earth images for mainstreams of Indus [5]. investigated in this study. The land use distribution is based on GLCNMO Global Map Land Cover data, which provides global coverage 3. Data at 1 km resolution. Twenty land use categories were in- cluded in the modeling and were summarized into five pa- 3.1. Topology, Land Use, and Soil rameter classes, as shown in Table 1. The parameters of the unsaturated tank were deter- The topographic data applied in this study were ob- mined according to soil texture and depth distribution tained from the Global Map elevation data by the Interna- available from the Harmonized World Soil Database v. tional Steering Committee for Global Mapping (ISCGM) 1.2 [17]. For the Upper Indus Basin, 11 soil textural 794 Journal of Disaster Research Vol.12 No.4, 2017 A Study on Flood Forecasting in the Upper Indus Basin Considering Snow and Glacier Meltwater Table 2. Meteorological stations of the Pakistan Meteoro- logical Department (PMD) in the Indus River main stream. Latitude Longitude Altitude Station Name (◦CN) (◦CE) (m) ASTORE 35.32 74.86 2200 BUNJI 35.64 74.64 1400 CHILAS 35.42 74.09 1250 CHITRAL 35.84 71.78 1500 GILGIT 35.92 74.33 1450 GUPIS 36.23 73.45 2150 SKARDU 35.34 75.54 2300 ISLAMABAD 33.68 73.06 525 BALAKOT 34.55 73.35 1000 DIR 35.21 71.88 1400 DROSH 35.57 71.8 1350 G.DUPATTA 34.22 73.62 825 KALAM 35.48 72.58 2000 MALAMJABBA 34.8 72.57 2450 Fig.
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