Rainfall Runoff Inundation Model Research Articles

Regional event-based flood quantile estimation method for large climate projection ensembles

Emerging large ensemble climate datasets produced by multiple general circulation models and their downscaling products challenge the limits of hydrodynamic models because of the immense data size. To overcome this new challenge and estimate the discharge quantiles corresponding to different return periods at all river sections in an entire region, this study proposes an event-based regional approach that uses a nationwide distributed rainfall–runoff model as well as large climate projection ensembles. This approach addresses the high computational burden associated with continuous simulations and solves the problem of conventional event-based simulations serving only a single outlet of a basin. For our analysis, we extracted 372 annual maximum 48 h rainfall events that cover the entirety of Shikoku Island and its eight major river basins. Peak discharges were estimated using a 150 m resolution rainfall–runoff–inundation model. These discharges were then screened using either the peak-over-threshold (POT) method or block maxima (BM) method, and frequency curves were subsequently constructed and evaluated. The primary reason for the necessity of POT or BM was to avoid interference from extraneous low discharges. The POT-based frequency curves showed good accuracy when using peak discharges in the range of the top 10–50%, and the results remain stable within this threshold range. The BM method, employing block sizes of 2–5 years, can generate relatively accurate frequency curves, but the choice of block size introduces significant variations in results among certain basins. Generally, the accuracy of results based on the POT method surpasses that of the BM method. Considering the accuracy, computational cost, and result stability, the POT method is preferred. The error introduced by the regional approach was acceptable with more than half of the relative root-mean-square errors remaining within 10% and basically all of the results are within 20%. The results of the regional approach exhibited good accuracy across climate scenarios and provided consistent information regarding future flood quantiles. This study serves as the foundation for high-resolution future flood risk assessment.

Climate change impacts on spatiotemporal variation of extreme weather and its consequences on dam optimisation and risk management in the Cagayan basin, Philippines

Extreme weather threatens livelihood and urban development in the Philippines. However, addressing their effects and occurrences is a significant challenge, particularly in the Cagayan River Basin (CRB), due to increasing population and the dilemma of dam operations for floods and droughts management. Therefore, this paper focuses on investigating the impact of climate change on extreme weather events and understanding flood characteristics by simulating Typhoon Ulysses on the Magat dam. The Mann-Kendall test was used to investigate the spatiotemporal variability and magnitude of change in extremes over historical and future periods. Furthermore, Rainfall-Runoff Inundation Model was evaluated with four different dam operation scenarios to investigate mitigation strategies for dam optimisation to reduce flood and drought risks. Findings indicate an increased risk of dry and wet spells in future, potentially increasing vulnerability to drought and flooding over CRB. We also discovered that each sub-basin had different hydrological responses and significantly higher runoff than others. However, with a modified Magat dam operation to start a flow rate of 700 m3/s and a discharge rate of 0.5, the water level at Buntun can be lowered by 0.5 m. In addition, a proposed dam at Cagayan Segment 1 is expected to reduce flood risk in downstream areas.

Distributed flood simulation based on satellite rainfall data at the Ciliwung River Basin, Jawa, Indonesia

Recurrent flooding in Jakarta and surrounding areas due to extreme rainfall is simulated by using distributed hydrological model. In the previous studies, the Rainfall-Runoff Inundation (RRI) model has been used for the flood simulation with 1-km spatial resolution, but it has not been comprehensively investigated. In this paper, extreme rainfall data derived from satellite rainfall data of GSMaP, topography, and land derived from the satellite remote sensing data are used as an input for the RRI model. We analyse the flood simulation at Ciliwung River Basin during 6 (Six) periods of extreme rainfall during January – March 2022 and divide between Flood (F) and Non-Flood (NF) periods. We found that the inundation occurred when the rainfall average reaches more than 7.3 mm/hr and concentrated in the Jakarta downtown area, which had induced the inundation around the Ciliwung river basin.

Impact Assessment of Changing Landcover on Flood Risk in the Indus River Basin Using the Rainfall–Runoff–Inundation (RRI)

Flooding is frequent in the province of Punjab, Pakistan, because the Indus River is a confluence point of five rivers. Researchers have primarily focused on the northern parts of the Indus basin and they have reported on simulation models that can be applied to the evaluation of flood risk. However, the inundation risks in the southern parts of the basin, including the impact of urbanization in this region, require a further assessment. The severity of flood disasters in the upper and lower reaches of the Indus basin are equally important because flash floods and riverine flooding pose a threat to densely populated areas. In this work, we aim to simulate flooding and the effects of landcover changes on inundation in the upper and lower Indus basin. Inundation was determined using the Rainfall–Runoff–Inundation (RRI) model with rainfall data from the monsoon season (00:00 UTC 1 July 2015–00:00 UTC 1 September 2015) as the input. After validating the model, sensitivity experiments were conducted to analyze the effect of landcover changes on the inundation of the Indus basin. The RRI model results showed that planting in the bare and vegetated areas led to minimum inundation in the Indus basin. Based on these results, planting between the Indus River and Chenab River could prevent flood disasters downstream of the confluence point as the discharge values reduced from 15,695.2 m3/s to 12,078.3 m3/s and 4373.7 m3/s to 2934.6 m3/s in the Indus River and Chenab River, respectively, before the confluence point. In contrast, urbanization in Punjab increased the risk of inundation after the confluence point caused by an increased discharge from 12,078.3 m3/s to 14,190.4 m3/s and 2934.6 m3/s to 4229.5 m3/s in the Indus River and Chenab River, respectively, before the confluence point.

Impacts of Flood Disturbance on the Dynamics of Basin-Scale Swimming Fish Migration in Mountainous Streams

This study investigated the response of sweetfish (Plecoglossus altivelis), a species that migrates dynamically throughout a river basin, to two flood events during the summer of 2020 in the Nagara River, located in the central region of Japan. By combining multiple environmental DNA (eDNA) surveys and hydrological modeling, the spatiotemporal distribution of P. altivelis throughout a mountainous river basin was captured and analyzed. The eDNA concentrations at 42 sites in the Nagara River Basin were analyzed five times from August to early October 2020. In addition, Rainfall–Runoff–Inundation model calculations were performed using 1-km resolution precipitation data as input values to analyze the magnitude of the flood disturbance at the eDNA sites. The daily specific discharge Qs (m3/s/km2) was employed as an index of the flood magnitude. The calculation period included Flood Events 1 and 2 with 52 and 38 days of precipitation reaching 1923 and 528 mm, respectively. The results of the eDNA analysis showed that, immediately after Flood Event 1, the spatial distribution of P. altivelis was unevenly distributed in the upper reaches of the Nagara River and some of its tributaries. Subsequently, the distribution expanded to the entire mainstem. The distribution of the maximum daily specific discharge suggested that the river segments with high eDNA concentrations of P. altivelis immediately after the high-magnitude flood event were those with a relatively low intensity of flood disturbance compared with those in the other connected river segments and tributaries. The results of this study indicate that the resilience of riverine communities to extreme floods is supported by the continuity and connectivity between the mainstem and its tributaries in mountainous river basins.

Comparison of CMIP5 and CMIP6 GCM performance for flood projections in the Mekong River Basin

Study regionMekong River Basin. Study focusThe Coupled Model Intercomparison Project Phase 6 (CMIP6) recently announced an updated version of general circulation models (GCMs). This study investigated the performance of improved CMIP6 over those of CMIP5 with respect to precipitation and flood representations in the Mekong River Basin (MRB). The correlation and error comparison from the referenced precipitation exhibited a significant improvement in the peak value representation. Hence, the impacts of climate change on future floods in the MRB were simulated and assessed using a distributed rainfall–runoff–inundation model. New hydrological insights for the regionThe results indicated that precipitation from CMIP6 had a higher correlation and a lower error coefficient than CMIP5. Similarly, the simulation of GCM ensembles of monthly discharge from CMIP6 exhibited a comparable average value to the observations, whereas CMIP5 underestimated the discharge simulations. The performance of the mean annual peak discharge improved from 37,220 m3/s (CMIP5) to 45,423 m3/s (CMIP6) compared to 43,521 m3/s (observation). The projections of future floods in the MRB from CMIP6 exhibited an increase of annual peak discharge at Chiang Saen, Vientiane, Pakse, and Kratie stations by 10–15%, 20–22%, and 24–29% for the SSP2-4.5 scenario, and 10–18%, 24–29%, and 41–54% for the SSP5-8.5 scenario in the near future (2026–2050), mid-future (2051–2075), and far future (2076–2100), respectively. The statistical K-S test showed significant changes in all stations and projected periods with a p-value < 0.01.

Development of Flood Damage Estimation Model for Agriculture – Case Study in the Bago Floodplain, Myanmar

This paper introduces an integrated model that combines the Rainfall Runoff Inundation (RRI) and spatially distributed flood damage estimation models. There are three steps for fulfilling this purpose. The first step is the accomplishment of RRI model for the floodplain region. The second step is a questionnaire survey to analyze the economic damage to affected population and properties caused by the past flooding events; this step aims to estimate the different levels of agricultural damage cost. Finally, the economic flood damage estimation model was developed for the agricultural areas by using the stage-damage function models which were established by the multiple regression analysis of questionnaire survey data. The model results were expressed through spatially distributed flood damage maps for extreme flood events, such as those in 2014, 2015, and 2018. The results were validated by collecting damage cost data from the Department of Agricultural Lands Management and Statistics (DALMS). The final findings included comparative scenarios for reducing damage cost in the most effective and realistic way. The output product was the agricultural damage estimation model. For further research, the model was recommended for application in other study areas with different flood scales.

Flood and Inundation Forecasting in the Sparsely Gauged Transboundary Chenab River Basin Using Satellite Rain and Coupling Meteorological and Hydrological Models

Abstract Flood forecasting in a transboundary river basin is challenging due to insufficient data sharing between countries in the upper and lower reaches of a basin. A solution is the use of satellite-observed rainfall and numerical weather prediction (NWP) for hydrological forecasting. We applied this method to the transboundary sparsely gauged Chenab River basin in Pakistan and India to reproduce the exceptionally high flood in 2014. We employed global NWPs by three weather centers to consider forecast uncertainty and downscaled them using the Weather Research and Forecasting (WRF) Model to prepare precipitation inputs. For hydrological simulations, we used a kinematic wave model, the Integrated Flood Analysis System (IFAS), for the upper-reach basin with high mountains and steep slopes, and we used a diffusive-wave rainfall–runoff–inundation (RRI) model for low altitudes and mild slopes. In our forecasting experiment, the precipitation by the global NWP was not able to predict flood peaks consistently. However, the downscaled rainfall by regional NWP showed good performance in predicting flood waves quantitatively, and a multimodel approach provided added value in issuing reliable warning as early as 6 days in advance. A confident streamflow forecasting near the border of the countries also led to reliable inundation forecasting by the RRI model in the lower-reach basin.

Application of Backpack-Mounted Mobile Mapping System and Rainfall–Runoff–Inundation Model for Flash Flood Analysis

Satellite remote sensing has been used effectively to estimate flood inundation extents in large river basins. In the case of flash floods in mountainous catchments, however, it is difficult to use remote sensing information. To compensate for this situation, detailed rainfall–runoff and flood inundation models have been utilized. Regardless of the recent technological advances in simulations, there has been a significant lack of data for validating such models, particularly with respect to local flood inundation depths. To estimate flood inundation depths, this study proposes using a backpack-mounted mobile mapping system (MMS) for post-flood surveys. Our case study in Northern Kyushu Island, which was affected by devastating flash floods in July 2017, suggests that the MMS can be used to estimate the inundation depth with an accuracy of 0.14 m. Furthermore, the landform change due to deposition of sediments could be estimated by the MMS survey. By taking into consideration the change of topography, the rainfall–runoff–inundation (RRI) model could reasonably reproduce the flood inundation compared with the MMS measurements. Overall, this study demonstrates the effective application of the MMS and RRI model for flash flood analysis in mountainous river catchments.

Assessing flood disaster impacts in agriculture under climate change in the river basins of Southeast Asia

This study focused on flood damage assessment for future floods under the impact of climate change. Four river basins of Southeast Asia were selected for the study. They included the Pampanga River Basin (PRB) in the Philippines, the Solo River Basin (SRB) in Indonesia, the Lower Mekong River Basin (LMRB) in Cambodia and Vietnam, and the Chao Phraya River Basin (CPRB) in Thailand. Flood damage to rice crops was assessed by flood damage functions considering flood depth and duration and the growth stage of rice plants. Flood characteristics such as flood depth, duration, and distribution were computed using the rainfall–runoff–inundation model to assess flood hazards under the present and future climatic conditions produced by MRI-AGCM3.2S. The damage assessment methodology for rice crops employed in this study was verified using data on past flood events. Then, flood damage assessment was conducted for both the present climate (1979–2003) and future climate (2075–2099) conditions, using MRI-AGCM3.2S precipitation datasets. Flood damage was assessed for worst cases chosen from each climate period and for floods of 50- and 100-year return periods with different rainfall patterns chosen from each climate scenario. The results of flood hazard and damage assessment show that the flood inundation area for a 100-year flood may increase in the future by 20% in PRB; by 66% in SRB; by 27% in LMRB; and by 27% in CPRB. The flood damage area of paddy fields for a 100-year flood may also increase in the future by 16% in PRB; by 55% in SRB; by 23% in LMRB; and by 13% in CPRB.

Flood damage assessment on rice crop in the Stung Sen River Basin of Cambodia

In Cambodia, rice production is important for the majority of rural populations as the main source of income. However, historical extreme flood events, especially the 2011 flood, caused significant damage to rice production due to insufficient flood preparedness and mitigation. To reduce the risk of damage, flood damage assessment is critical for providing essential information about potential risks to support the decision-making process and policy development in flood risk management. In this study, a physically based rainfall–runoff–inundation (RRI) model was used to simulate flood inundation in the Stung Sen River Basin of Cambodia, and then damage to rice crops was estimated based on the simulated inundation depth and duration that resulted from the RRI model. The simulated river discharges were calibrated and validated for 2011 and 2009 flood events, respectively. Indeed, the simulated flood inundation areas were compared with flood maps derived from satellite imagery to check their accuracy. As a result, it was confirmed that these results were reasonable and adequate. In the case of the 2011 flood, a distribution map of rice crop damage was created to represent the potentially affected rice areas at various levels of damage. Furthermore, the total of estimated affected rice areas was found to be close to the reported damage data, with an overlap of 89%. Overall, the preliminary results from this study are expected to be useful for key stakeholders at all levels, especially decision-makers, in planning better risk reduction strategies, for instance, when choosing the appropriate flood control option to cope with future extreme flood events.

Large-scale rainfall–runoff–inundation modeling for upper Citarum River watershed, Indonesia

The Citarum River is one of the strategic rivers in West Java, Indonesia. Its total watershed area is approximately 1800 km2. Almost every year, the overflow from the Citarum River causes the inundation of most of the upper Citarum River watershed. To prevent and mitigate flood damage, it is necessary to understand the flooding characteristics. The region, however, suffers from a lack of observational data. Therefore, to analyze the inundation caused by flooding in the upper Citarum River watershed, a rainfall–runoff–inundation (RRI) model was employed. It used the following multiple satellite-derived datasets as input data as well as for model verification: Global Satellite Mapping of Precipitation, Hydrological data and maps based on Shuttle elevation Derivatives at multiple scales, Global Mosaics of the standard MODIS land cover type data product, and Landsat 7 satellite images. Parameter calibration was performed using a Monte Carlo simulation. The simulation was performed for February 2010. The results of this study show that the RRI model identifies inundation areas in large-scale river watersheds more effectively when using multiple satellite-derived datasets compared with the observed inundation map obtained from JICA in 2010 and Landsat 7 images. The model results can be improved if high-quality observed rainfall data, topographic data, and river cross-sectional data are available.

Effectiveness of the Submersible Embankment in Haor Area in Bangladesh

The north-eastern part of Bangladesh is very productive for agriculture and fishing, and the region involves several depressed (haor) areas. Flash floods during the pre-monsoon period bring devastating damage to agriculture in the haor region recurrently. To protect crops from flash floods, the Bangladesh Water Development Board constructed several ring-type submersible embankments. In this research, we have investigated the effectiveness of submersible embankments in controlling flash flooding in the Matian and Shanir haors in the Sunamganj district. A two-dimensional rainfall runoff inundation model was applied considering several scenarios for simulating heavy flash flood events in 2004, 2010, and 2016. Without an embankment, the river overflow would have entered the Matian haor 3 days, 22 days, and 9 days earlier in 2004, 2010, and 2016, respectively, whereas it would have been 7 days and 23 days earlier in 2004 and 2010 for the Shanir haor. The event in 2016 was successfully stopped by the Shanir haor embankment. To avoid river overflow entering into the Matian and Shanir haor completely, the embankment height must be elevated further by 1 m and 0.7 m, respectively. Providing proper drainage facilities for the accumulated rain water inside the hoar is still an important issue for protecting the crops effectively.

Analysis of land use change impacts on flash flood occurrences in the Sosiani River basin Kenya

ABSTRACTThis paper investigates the impacts of land use changes on river peak discharges during floods and its contribution to flood occurrence in the Sosiani River basin in the Rift Valley province of Kenya. The land use maps used in the study were derived from the Landsat imagery employing remote sensing and GIS techniques. Two-dimensional Rainfall–Runoff–Inundation (RRI) model was utilized in simulating the flash flood events. The results indicated an increase in river peak discharge due to extensive deforestation in the past decades and increase in farmlands which covers up to 75% of the total watershed area. According to the observed discharge data and generated land use maps, expansion of farmlands from 15.3% (in the early 1970s) to 75.2% (2013) and urban areas from 0.4% (in the early 1970s) to 10% (2013) have triggered the observed river peak discharge to increase from 167 m3/s (1970) to 233 m3/s (2013). Two land use change scenarios were tested for urbanization and reforestation using the calibrated RRI model and modified land use maps accordingly. The obtained results indicated a high sensitivity for the variation in land use to the river peak discharges. The results of the study will be beneficial for future developments in the basin and its flood management activities.

THE IMPACT OF RAINFALL VARIATIONS ON FLASH FLOODING IN HAOR AREAS IN BANGLADESH

The north-eastern part of Bangladesh is famous for rice production and fishing. A lot of bawl shaped depressed areas are located in this region which is locally called as haor area. Among seven haor districts Sunamganj has the maximum extent of haors and net cultivable area. The flash flood which is recurrent during April and May is the number one ranked hazard that affects agriculture in Sunamganj severely. Flash flood in 2017 was the most devastated in the recent past. Different researchers predicted that the rainfall during April/May will increase here due to the impact of climate change in future. The objective of present study is to evaluate the impact of rainfalls on inundations owing to flash floods using rainfall runoff inundation model (RRI-model) proposed. Ten rainfall events are prepared for computations of inundation, using reference rainfall in April in 2017, and their sizes normalized by the reference event range from 0.6 to 2.0, respectively. The size level of a flash flood is determined by means of RRI-model by water surface elevation at Sunamganj station in the Surma river and it is translated into return period. The inundation proc ess were computed for each of the specified rainfall events, together with inundation depths in Tahirpur upazilla (sub-district) in Sunamganj district in order to investigate the relation between the sizes of rainfall event, flash flood event and extents of inundation. The computed results suggest that the return periods of the computed flash floods are determined as 3.7,10, —,142.86 years corresponding to the normalized rainfall sizes such as 0.6, 0.9, —, 2.0 and suggest that inundated areas increase with the size of normalized rainfall and increase sharply in the range of rainfall size larger than about 1.1-1.2. Such results are useful to identify and quantify the associated inundated areas due to temporal variation of rainfall which is necessary for disaster preparedness and management.

Application of a flood inundation model to analyze the potential impacts of a flood control plan in Mundeni Aru river basin, Sri Lanka

Capturing inundation extent by floods is indispensable for decision making for mitigating hazard. Satellite images have commonly been used for flood mapping, but there are limitations such as unavailability due to satellite’s orbital period or cloud cover. Additionally, it would also be beneficial for policy makers to figure out the impact of water management measures such as water storage options on flood mitigation and irrigation water strengthening. Utilization of flood inundation models would support providing information for these demands. In this study, the rainfall–runoff inundation (RRI) model was applied in a flood-prone basin in eastern Sri Lanka, and its applicability was discussed. The RRI model was capable of simulating discharge and inundation extent during flood events, although it should be noted that the model had been calibrated targeting only the flooding period. Satellite-observed rainfall data corrected with a scale factor were able to be used as the model input to simulate long-term trends in runoff just as well as when gauged rainfall data were applied. The calibrated model was also capable of evaluating flood mitigation effects of existing and proposed water storage options by simulating discharge with and without flood capture operations. By reproducing long-term inflow to the storage facilities using satellite rainfall data, it was possible to determine that water would reach the maximum level of the proposed storage facilities even during low-rainfall years.

Improvement in Flood Disaster Damage Assessment Using Highly Accurate IfSAR DEM

Flood damage to agriculture (rice crops) was assessed in the Pampanga River basin of the Philippines. Flood damage to agriculture was defined as a function of hazard characteristics, such as flood depth and flood duration, exposure, and growth stage of rice crops, and estimated in terms of yield loss using a depth-duration-damage function. The assessment of flood damage to agriculture in the Pampanga River basin was conducted using Digital Elevation Model data of the Interferometric Synthetic Aperture Radar (IfSAR-DEM) and Digital Elevation Model data of the Shuttle Radar Topography Mission (SRTM-DEM). The results were further improved using highly accurate IfSAR-DEM. To assess flood disaster damage, a hazard assessment was conducted using the Rainfall Runoff Inundation model. Estimated values from the agricultural damage assessment during the flood event from September 26 to October 4, 2011 were compared with reported values. The accuracy of flood hazard assessment and flood disaster risk assessment highly depends on the quality of topographical data, and better results can be obtained by using highly precise topographical data. Flood disaster risk assessment in the agricultural sector was also conducted for a recent flood in October 2015 and flood events with different return periods of 10, 25, 50, and 100 years. The assessment results based on the different return periods of flood events were then used to estimate the probability of agricultural damage for most frequently damaged and rarely damaged areas. The results of flood damage assessment in the Pampanga River basin provide a basis to identify areas at risk, and these results can be useful for planners, developers, policy makers, and decision makers in establishing policies required to reduce flood damage.

Flood damage assessment in the Pampanga river basin of the Philippines

AbstractIn this study, a flood damage assessment method was proposed for the assessment of flood risk in data‐poor river basins by using a physical‐based numerical model, satellite‐based information and socio‐economic factors. The Pampanga river basin of the Philippines was selected for the case study. For the flood damage assessment, hazard characteristics, such as flood depth and duration, were computed using the rainfall runoff inundation model. Agriculture and households, which are major exposures in flood‐prone areas, were taken into account for the flood damage assessment. The potential damage to agriculture was estimated by using the damage functions of agriculture and flood characteristics. The damage functions of agriculture for each growing stage were defined as the function of flood depth and duration. Field investigations and questionnaire surveys were conducted at the selected barangays (villages) in the Pampanga river basin to develop a methodology for household damage estimation. The damage estimation approach for damage to household buildings including assets, was developed based on the flood and household characteristics. The potential damage to house building and assets was estimated. The estimated damage of agriculture and households was compared with the reported values.

Community-based flood damage assessment approach for lower West Rapti River basin in Nepal under the impact of climate change

The West Rapti River (WRR), one of the dynamic and economically important basins of Nepal, was focused in this study to understand the impact of climate change in localized scale. The adopted methodology was a community-based field survey followed by a hydrological modeling to estimate present and future flood damages for households and agriculture. Flood disaster occurred in 2007 was simulated and discussed. High-resolution atmospheric general circulation model’s precipitation outputs for emission scenario A1B were utilized with their bias corrections to obtain the precipitation patterns over lower WRR basin for Present (1979–2003) and Future (2075–2099) periods. A conceptual hydrologic model was employed to obtain the time series of daily river runoffs for the above-mentioned time durations followed by frequency analyses for probable flood discharges of 25- and 50-year return periods. Flood inundation simulations of 50-year return period events for Present and Future were carried out with the rainfall–runoff–inundation model followed by a flood damage assessment for household and agriculture based on the inundation simulation results, and field survey data over the target area and potential flood damages were discussed. Integration of hydrological modeling and socioeconomic approach to foresee potential flood damages was achieved, and the adopted damage assessment methodology was systematically explained. The total increments of household and agriculture damages due to climate change were estimated for Present as 1.80 and 1.95, and for Future, it was 2.40 and 2.27, respectively, compared to 2007 flood disaster. Future flood frequencies, intensities, and consequent damages in the area show a significant increment compared to the present situation despite limitations and uncertainties.

Numerical Simulation of 2010 Pakistan Flood in the Kabul River Basin by Using Lagged Ensemble Rainfall Forecasting

Abstract Lagged ensemble forecasting of rainfall and rainfall–runoff–inundation (RRI) forecasting were applied to the devastating flood in the Kabul River basin, the first strike of the 2010 Pakistan flood. The forecasts were performed using the Global Forecast System of the National Centers for Environmental Prediction (NCEP-GFS) and were provided four times daily. Dynamical downscaling was also applied to the forecasts by the Weather Research and Forecasting Model (WRF), a regional model. The forecasts of the rainfall and inundation area were verified by comparing rain gauge–corrected Global Satellite Mapping of Precipitation (GSMaP) data and the observed indicator of an inundation map based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. The GFS predicted a sign of heavy rainfall in northern Pakistan 4 days ahead of the onset. However, most of the forecasts predicted it in wrong places, and only those performed after the rainfall onset predicted it in the accurate location. Downscaling corrected the locations of the misplaced GFS forecasts and also underestimated or overestimated rainfall amount derived from GFS. Finally, downscaled forecasts predicted a reliable amount of rainfall in the Kabul River basin 1 day ahead of the rainfall onset and predicted a high probability of heavy rainfall 3 days ahead. Lagged ensemble forecasts of discharge and inundation distribution based on GFS rainfall predicted the probability of the actual discharge and inundation distribution, but in low reliability. The reliability substantially improved when downscaled rainfall was used. The reliability of the flood alert system combining NCEP-GFS, dynamical downscaling by WRF, and the RRI model was at an acceptable level in this study.