Rainfall History Research Articles

Paleoenvironmental changes in the coastal zone of the northwest South China Sea during the last 13 kyr

Marine sediments in coastal zones serve as valuable archives for understanding the history of silicate chemical weathering and summer monsoon rainfall in source areas, providing insights into terrigenous climate and environmental evolution. In this study, we investigated the grain size, clay minerals, and geochemistry of sediments retrieved from core KZK01 in the coastal zone of the northwest South China Sea during the past 13 thousand years before present (kyr BP). Our findings demonstrated that the illite crystallinity index served as a reliable proxy for assessing the intensity of chemical weathering in the source area. Moreover, it distinctly recorded significant climatic events such as the Younger Dryas and Bond events during the Holocene. The dominant driver of the regional East Asian summer monsoon was identified as summer solar radiation in the Northern Hemisphere at low latitudes. Cold climate events exhibited global consistency, potentially influenced by the presence of ice sheets at high latitudes. Lastly, our records revealed a distinct transition at 9.0 kyr, highlighting significant impacts of the Qiongzhou Strait and sea level rise on regional climate dynamics.

From empirically to physically based early warning predictions of rainfall-induced landslides in silty volcanic soils: the Lattari Mountains case study

The work proposes a procedure to build an early warning predictive tool to assess the occurrence of rainfall-induced landslides in silty volcanic covers. The procedure combines both an empirically and a physically based tool used sequentially: the former is designed to be calibrated using older, highly sized and coarser rainfall data, and the latter to interpret recent and finer weather data. Both approaches need to be informed by a common experimental reference summarising the rainfall history, the rainfall point, defined as the couple made of antecedent 4-month rainfall cumulative value (C4m) and last-persistent event (CPLE). The empirical approach aims to identify if, in the (C4m–CPLE) plane, the rainfall point falls in a ‘safe’ or ‘potentially unsafe’ zone where the two distinct regions are built by interpreting rainfall data associated or not with landslide events. In the physically based approach, evaporation and runoff are estimated to refine the assessment of ‘effective’ rainfall points. The resulting transformed rainfall point (C′4 m, C′PLE) is turned into a prediction of the suction level at the mid-depth assumed as a ‘reference’ for the entire cover. Such value is compared with a suction threshold empirically defined. Suction levels prediction is developed by computing in the C′4 m–C′PLE plane the iso-suction lines generated by several rainfall scenarios. The accuracy of the developed procedure is comparable with state-of-the-art literature or operational approaches, properly identifying landslide case events and minimising the number of false alarms. Furthermore, it can inform the preparedness stages more effectively, explicitly accounting for the antecedent slope wetness stage and how it could be far from the incipient slope failure conditions. The developed procedure takes into account the effects of evaporation and antecedent rainfalls that, in dry periods, lead to very dry conditions in the subsoil, making even significant rainfall events inconsequential. Conversely, other procedures already operating in LEWS or highly considered literature background overestimate the effects of rainfalls during dry periods. The developed procedure delivers a simple but robust way to derive landslide thresholds based on the interpretation of past rainfall histories. At the same time, literature methods often require sophisticated approaches to retrieve thresholds.

The ‘Deluge’ of 25 October 1822 in Genoa, Italy

The ‘Deluge’ of 25 October 1822 in Genoa, Italy

Hydrodynamic Modelling and Flood Risk Analysis of Urban Catchments under Multiple Scenarios: A Case Study of Dongfeng Canal District, Zhengzhou.

In recent years, urban flooding has become an increasingly serious problem, posing a serious threat to socio-economic development and personal safety. In this paper, we consider the Dongfeng Canal area in Zhengzhou City as an example and build a 1D/2D coupled urban flood model using the InfoWorks ICM. This study area uses six scenarios with rainfall return periods of 5 a, 20 a, and 50 a, corresponding to rainfall ephemeris of 1 h and 2 h to assess the flood risk. The results of the study show that (1) The flood depth, inundation duration, and extent of inundation in the study area vary with the return period and rainfall history. Generally, most of the water accumulation is concentrated in the low-lying areas adjacent to the river and near the roadbed. (2) As the rainfall recurrence period and rainfall duration increase, the proportion of overflow at the nodes becomes more pronounced and the overload from the pipe network flows mainly to the overload. (3) The high-risk areas under the different scenarios are mainly distributed on both sides of the river, and most of the low-risk areas transform into medium- and high-risk areas as the rainfall recurrence period and rainfall duration increase. This study analyses the flood risk situation under different scenarios, as well as the elements and areas that should be monitored in case of flooding, with the aim of providing a reference for flood prevention and control in the study area and formulating corresponding countermeasures. It also serves as a reference for flood risk analysis in other areas with similar situations.

HOTRUNZ: an open-access 1 km resolution monthly 1910–2019 time series of interpolated temperature and rainfall grids with associated uncertainty for New Zealand

Abstract. Long time series of temperature and rainfall grids are fundamental to understanding how these environmental variables affect environmental or ecological patterns and processes such as plant distributions, plant and animal phenology, wildfires, and hydrology. Ideally such temperature and rainfall grids are openly available and associated with uncertainties so that data-quality issues are transparent to users. We present a History of Open Temperature and Rainfall with Uncertainty in New Zealand (HOTRUNZ) that uses climatological aided natural neighbour interpolation to provide monthly 1 km resolution grids of total rainfall, mean air temperature, mean daily maximum air temperature, and mean daily minimum air temperature across New Zealand from 1910 to 2019. HOTRUNZ matches the best available temporal extent and spatial resolution of any open-access temperature and rainfall grids that include New Zealand and is unique in providing associated spatial uncertainty in the variables' units. The HOTRUNZ grids capture the dynamic spatial and temporal nature of monthly temperature and rainfall and the uncertainties associated with the interpolation. We also demonstrate how to quantify and visualise temporal trends across New Zealand that recognise the temporal and spatial variation in uncertainties in the HOTRUNZ data. The HOTRUNZ data are openly available at https://doi.org/10.7931/zmvz-xf30 (Etherington et al., 2021).

A Hybrid Fuzzy and K-Nearest Neighbor Approach for Debris Flow Disaster Prevention

Taiwan is located in a high-risk area for natural disasters. In recent years, violent natural disasters have occurred in Taiwan. Numerous disasters—such as flooding, surges of river water level, and earth and rock disasters—are caused by instant heavy rainfall. These disasters cause considerable loss of lives and property. Current disaster warning systems can only provide warnings to large areas and not to specific small areas. Therefore, the current study developed a disaster warning system based on machine learning for evaluating the likelihood of earth and rock disasters so that an early warning can be provided to people who may be affected by these disasters. In contrast to previous relevant studies, which have mostly used regional assessment methods, no large-scale regional simulation was conducted in the present study. Instead, a comprehensive debris flow evaluation model based on information related to soil flow, rock flow, typhoons, and rainfall history was established to provide warnings regarding debris flow disasters. The geological condition, rainfall, soil moisture and river water level in 1-h intervals were evaluated using the K-nearest neighbor algorithm, providing people earth and rock flow information for the area around their homes. Data related to Typhoon Kameiji, Typhoon Xinleke, Typhoon Morak, Typhoon Sura, Typhoon Megi, and the 0823 Tropical depression were used as training data for the developed model, and data related to Typhoon Megi and Typhoon Kangrui were used as testing data. The proposed model can provide earlier warnings than can the Taiwanese government’s soil and stone flow warning system. The developed model was used to create a mobile phone application that presents comprehensive and easy-to-understand data on the debris flow warning level, hourly rainfall, total rainfall, and geological conditions in real time.

A slow and complex landslide under static and seismic action

A dam construction project for the heightening of a dam is threatened by a large landslide located in the Spanish Southern Pyrenees. A marked syncline structure, folding a flysch formation overlying a marl substratum, is the main geological feature of the unstable valley slope. The landslide is characterized by two main and superimposed slip surfaces which follow the bedding layers. The motion observed is very slow and its acceleration can be related to rainfall regimes and changes in loading condition due to excavations.The paper provides an insight into the complexities associated with stability and kinematic evolution of a landslide under static and dynamic actions. Simplified procedures are proposed to predict the complex landslide behaviour. A comprehensive hydrogeological model is developed to relate rainfall history and water pressure which incorporates available data about the anisotropic permeability of flysch and the natural drainage obtained from pumping test and insitu measurements. The stability analysis of the slope focuses on the discussion of safety factors and their practical implication not only in terms of static limit equilibrium, but also on creeping velocity. The latter was evaluated under the simplified assumption of planar landslide and invoking the strain-rate effects on residual strength. A derived analytical expression provides a relationship between Safety Factor and creeping velocity. Under such hypothesis, the increment of the strength required to avoid predicting unrealistic landslide acceleration should be imposed for a lower range of shear velocity than the usual value imposed in the laboratory shearing tests.The seismic response of the landslide is also analysed. A Newmark's approach and a stress-strain finite element (FE) analysis are compared, with special emphasis on the effect of the superimposed slip surfaces on the dynamic landslide response. To do that, the Newmark's analysis has been extended to two overlaying sliding surfaces with independent strength properties and pore water pressure. It is concluded that assuming a single deeper sliding surfaces may underestimate the co-seismic permanent displacement. The comparison of two-block Newmark's analysis with two-dimensional elastoplastic FE approach highlights the effect of geometry in the landslide motion.

Monthly Rainfall Components in Ambon City: Evidence from the Serious Time Analysis

The purpose of this study is to prove whether rainfall in Ambon City contains seasonal components based on the characteristics of monthly rainfall history data in Ambon City. The data used is monthly rainfall data in Ambon City 2005.01-2017.12. The data is time series data from the BMKG Meteorology Station observation in Maluku Province. The time series analysis method used is ARIMA / SARIMA and Holt-Winter Exponential Smoothing. The results of this study have a good level of accuracy, namely using the results of analysis based on the values of information criteria, Ljung-Box Test, and RMSE. The results of the analysis prove that rainfall in Ambon City has a seasonal pattern.

The sediments of Lake Singkarak and Lake Maninjau in West Sumatra reveal their earthquake, volcanic and rainfall history

Natural hazards such as earthquakes, volcanic activity, and heavy rainfall causing floods and debris avalanches are common phenomena in many tropical settings, including the island of Sumatra, located in the Indonesian archipelago. To enhance our understanding of the recurrence of these often destructive events, we studied the sedimentary infill of two lakes in the Padang highlands, West Sumatra. This includes Lake Singkarak, a tectonically-formed lake located on a step-over of a major strike-slip fault system (the Sumatran Fault), and Lake Maninjau, a caldera lake. Both lakes are located ~300 km from the Sunda subduction trench and surrounded by steep slopes and a chain of active volcanoes. Hence, considering their unique tectonic setting, these lakes may potentially record a wide range of natural hazards that affect the region. A combination of seismic-reflection profiles and short sediment cores revealed that both lakes indeed record various types of natural hazards, each with their own sedimentary response to a specific type of event. Lake Singkarak can be used to study past floods and major debris avalanches in addition to high-magnitude megathrust earthquakes, while traces of past intraplate earthquakes have been identified in both lakes. Furthermore, we argue that Lake Singkarak is an ideal recorder of volcanic activity in the region, while Lake Maninjau itself can pose a volcanic hazard to its surroundings as demonstrated by potential activity of the volcano below the lake.

Exploring ERA5 reanalysis potentialities for supporting landslide investigations: a test case from Campania Region (Southern Italy)

Recently, ECMWF has released a new generation of reanalysis, acknowledged as ERA5, able to deliver a comprehensive, free, and operative picture of the past weather, exploiting the data assimilation of historical observations from different sources (satellite, in situ, multiple variables) for both atmospheric and soil variables. Experiences concerning flooding issues suggest that ERA5 could support also landslide investigations. In this sense, a number of questions may be raised: (i) can ERA5 data be reliable in reproducing rainfall histories leading to a landslide event? (ii) can ERA5 soil moisture estimations be reliable proxies for antecedent slope wetness condition? (iii) can ERA5 be implemented in a landslide early warning system to improve the performances? This study tries addressing these questions referring to some historical Campanian events (Southern Italy) with a special focus on the fully investigated event occurred in Nocera Inferiore on March 4, 2005. The study shows the following: (i) ERA5 precipitation can appropriately reproduce actual rainfall histories leading to the events occurred in the last years; (ii) ERA5 soil moisture may act as proxy of slope wetness conditions; (iii) ERA5 data could be easily implemented in LEWSs in areas poorly covered by field monitoring networks.

Exploring the best sequence LSTM modeling architecture for flood prediction

Accurate and efficient models for rainfall–runoff (RR) simulations are crucial for flood risk management. Recently, the success of the recurrent neural network (RNN) applied to sequential models has motivated groups to pursue RR modeling using RNN. Existing RNN based methods generally use either sequence input single output or unsynced sequence input and output architectures. In this paper, we propose a synced sequence input and output long short-term memory (LSTM) network architecture for hydrologic analysis and compare it to existing methods (sequence input single output LSTM). We expect the model will improve RR prediction in terms of accuracy, calibration training time, and computational cost. The key idea is to efficiently learn the long term dependency of runoff on past rainfall history. To be more specific, we use the indigenous ability of the LSTM network to preserve long term memory instead of artificially setting a time window for input data. In this way, we can avoid losing long term memory of the input, the calibration of the time window length, and excessive computation. The whole procedure mimics the traditional process-driven methods and is closer to the physics interpretation of the RR process. We conducted experiments on real-world hydrologic data from the Brays Bayou in Houston, Texas. Extensive experimental results clearly validate the effectiveness of our proposed method in terms of various statistical and hydrological related evaluation metrics. Notably, our experiment shows that some rainfall events could affect the runoff process in the test watershed for at least a week. For fine temporal resolution prediction, this long term effect needs to be carefully handled, and our proposed method is superior in this case.

Prediction Rainfall in 2020 in Telangana

Present work uses four separate methods to arrive at the prediction value by taking the average of the results of these four. Here, the calculations are based on past 32 year history of rainfall in Telangana. The four methods are: (1) The Root Mean Square (RMS) values, (2) the Artificial Neural Network (ANN) method, (3) The Fast Fourier Transform (FFT) method, and the Time Series method. Out of these the first and the last methods involve linear regression hence the results obtained exhibit a linear curve. Here, the prediction can be made about 8 months in advance to give sufficient time for planning to the farmers or hydro-electric power generators, or the governments at different levels.

The Influence of Tropical Cyclones on the Evolution of River Conveyance Capacity in Puerto Rico

AbstractTropical cyclones (TCs) in Puerto Rico and other tropical environments cause some of the world's most intense rainfall rates and pose major challenges to current and future flood resilience. One potential consequence of TC‐induced floods is the reconfiguration of river channels due to sediment scour or deposition. This reconfiguration has the potential to alter subsequent flood hazard by changing channel conveyance capacity, violating statistical independence assumptions that underpin conventional recurrence interval concepts. In this study, we examine changes in channel conveyance capacity in Puerto Rico and compare these changes to streamflow trends. Results show that relatively modest long‐term changes in river channel capacity are composed of numerous short‐term transients which are of much larger magnitude. These transients are most often caused by abrupt scour or deposition during TCs and are comparable in magnitude to long‐term trends in peak streamflows. An abrupt change is typically followed by a multiyear “recovery period” as the channel reestablishes quasi‐equilibrium. Flood events with recurrence intervals of approximately 10 years and above appear to be sufficient to cause these changes; channel reconfiguration thus may be more common in Puerto Rico than in less extreme hydroclimates. Short‐term conveyance capacity changes are not considered in typical flood hazard assessments, which could substantially overstate or understate flood threat at any particular time, depending on the recent history of TC rainfall and flooding. Improving flood resiliency in Puerto Rico and elsewhere will require better understanding of rapid conveyance capacity changes, their causes, and how they influence flood hazard and risk.

STRESS ANALYSIS OF EMBANKMENT DUE TO DIFFERENT IN CONSTRUCTION CONDITIONS

: In recent years, many examples of soil structure collapse due to heavy rainfall have occurred. Because of this, it is urgent to establish a method to evaluate and examine long-term embankment structure quality. Japan's conventional design method insufficiently evaluates embankments. Although this method is shifting to a performance-based design to cope with recent abnormal weather, an effective design method has not yet been established. Therefore, this research performs an initial stress analysis of embankment, accounting for differences in construction conditions. Notable in this study, is the comparative analysis of results, considering the initial water content ratio, one layer of discharge thickness, rolling compaction, and other given structural conditions that differed from conventional design standards. To do this, first the initial moisture content ratio was determined by reproducing the compaction by analysis. Second, based on the dynamics of unsaturated soil, the rainfall intensity was analyzed in order to confirm the variation of the initial stress due to rainfall. Lastly, and most critically, the dynamic change in embankment performance was analytically expressed, and the optimal structural conditions of embankment, grouped by rainfall history, was examined

Statistical modelling of 5-day average rainfall probability of occurrence in Australia during 1950–2013

The increasing concern about climate change has increased the necessity for precise figures about deviations in statistical characteristics of rainfall events in both temporal and spatial scales. Many areas across Australia have high variability patterns of rainfall and inadequate rainfall records which has various effects on the availability of food and water. Modelling spatial and temporal rainfall is essential for prediction and simulation purposes in numerous aspects of planning, agriculture, forestry, meteorology and hydrology. Two different models are generally used to describe the two main features of rainfall: the occurrence and the amount. This paper describes the occurrence probability of 5-day average rainfall (successive 5-day rainfall mean) in Australia. Daily accumulated rainfall observations of 105 meteorological stations spanning from 1950 to 2013 were collected from Australian Bureau of Meteorology for the study. Logistic regression is applied to predict rainfall probability of occurrence in all the meteorological stations using nine observational rainfall stations as case studies. Weather conditions such as the 5-day periods which is defined as the consecutive 5-day average rainfall in a year and the annual rainfall which is defined as the annual daily rainfall mean factors were used as the predictors. The fitted logistic regression models predicted the occurrence and non-occurrence 5-day average rainfall events quite well with good accuracies. The predictors significantly affected the fitted models in all stations. Analysis of the levels of each of the predictors showed that the parameters of the 5-day period factors were more influential in all the models, particularly during the rainy season in most stations relative to that of the annual factors. The fitted models could be used to simulate rainfall probabilities for the stations with insufficient rainfall histories and could assist agronomist and various stakeholders in the planning of their various operations.

Weather effects on birds of different size are mediated by long-term climate and vegetation type in endangered temperate woodlands.

Species occurrence is influenced by a range of factors including habitat attributes, climate, weather, and human landscape modification. These drivers are likely to interact, but their effects are frequently quantified independently. Here, we report the results of a 13-year study of temperate woodland birds in south-eastern Australia to quantify how different-sized birds respond to the interacting effects of: (a) short-term weather (rainfall and temperature in the 12months preceding our surveys), (b) long-term climate (average rainfall and maximum and minimum temperatures over the period 1970-2014), and (c) broad structural forms of vegetation (old-growth woodland, regrowth woodland, and restoration plantings). We uncovered significant interactions between bird body size, vegetation type, climate, and weather. High short-term rainfall was associated with decreased occurrence of large birds in old-growth and regrowth woodland, but not in restoration plantings. Conversely, small bird occurrence peaked in wet years, but this effect was most pronounced in locations with a history of high rainfall, and was actually reversed (peak occurrence in dry years) in restoration plantings in dry climates. The occurrence of small birds was depressed-and large birds elevated-in hot years, except in restoration plantings which supported few large birds under these circumstances. Our investigation suggests that different mechanisms may underpin contrasting responses of small and large birds to the interacting effects of climate, weather, and vegetation type. A diversity of vegetation cover is needed across a landscape to promote the occurrence of different-sized bird species in agriculture-dominated landscapes, particularly under variable weather conditions. Climate change is predicted to lead to widespread drying of our study region, and restoration plantings-especially currently climatically wet areas-may become critically important for conserving bird species, particularly small-bodied taxa.

Analyzing the Impacts of Rainfall on Rock Slope Behavior in Une Mine and Evaluating the Effec-Tiveness of Countermeasure Methods

Forward and downward displacements were measured in a section of a limestone slope in the Une mine, Ryoko Lime Industry Co. Ltd. Although the causes of rock slope behaviors at Une site have not been clarified, but rainfall unambiguously impacts on the rock slope. Une mine has taken countermeasures that are generally considered to be effective to stabilize the rock slope without delay. In this study, displacements were monitored using a crack gage installed over the fracture plane in an observation crosscut excavated in the rock slope on 1,010 mL. And it is found, the measured fracture displacements can be classified into two types:“ Type 1 displacement” not directly related to rainfall and“ Type 2 displacement” due to rainfall. All the displacements observed on the monitoring points located on the rock slope and by the crack gages installed other than 1,010 mL were analyzed and found to be composed of the Type 1 and Type 2 displacements. The areas with a large impact of rainfall were identified and the geological/geotechnical characteristics of the areas were investigated to prepare new countermeasures. In order to evaluate the effects of the countermeasures, the author formulated a statistical equation predicting the rock slope displacements from the rainfall history before applying any countermeasures for stabilization. It is confirmed the statistical equation gives a fairly fine agreement between actual and predicted displacements before commencing the countermeasures reducing the rainfall impacts. In addition, the statistical equation also makes possible the quantitative evaluation of the effects of the countermeasures, namely difference between predicted displacement without any countermeasures and observed displacement after activating the countermeasures. As a result, the statistical equation will be used for planning comprehensive and strategic stabilization projects in future for the Une rock slope.

Early warning system using tilt sensors in Chibo, Kalimpong, Darjeeling Himalayas, India

The Indian Himalayan regions have been significantly affected by the increase in the frequency of landslide occurrence. Thirty percentage of the worldwide landslide incidents occur in the Himalayan region with 42% of India’s landslide region belonging to Darjeeling–Sikkim Himalayas (NDMA Report, 2011). Several studies have been carried out worldwide on early warning systems considering rainfall history. Although rainfall is one of the criteria which can successfully predict the probability of landslides on a regional scale, it is indeed difficult to understand the risk associated with slope failure. The reason is the spatial variation of rainfall intensity, local soil conditions, geology, hydrology and topography. An early warning and monitoring system is one of the most effective techniques to minimise the disasters influenced by slope instability as it is less expensive and easier than slope reinforcement. A reliable and robust system fitted with microelectromechanical systems tilt sensor and volumetric water content sensors were installed. The sensor monitors the tilting angle of the instrument which was installed at shallow depths, and the variation of tilting angle corresponds to lateral displacement at slope surface. The primary objective was to monitor the tilting angles at various slope sites and to formulate a dependable warning system with a low probability of false alarms in Chibo Pashyor region in the Indian state of West Bengal. Such system would assist in the installation of several low-cost sensors over an active slope as it was difficult to determine the particular section of slope which could fail in the next heavy rainfall. The change in tilting rate would help in establishing thresholds determined empirically. Such system would help in developing an early warning system and also help in calibrating thresholds calculated using empirical techniques.

Analysis of Nonpoint Source Pollution and Calculation of Load Per Unit Area in Transportation Area in Nakdong River Basin

In this study, the runoff characteristics were analyzed by using long-term monitoring results in the Nakdong River watershed traffic area, and the load per unit area of nonpoint source was estimated. Based on the estimates of the basic load per unit area and existing water TMDL, the reduction load for each nonpoint source pollution reduction facility was calculated and compared. As a result of long-term monitoring data analysis on the Nakdong River watershed traffic area, the average number of rainfall-free days was 6.7 days. The mean rainfall was 31.3 ㎜ and the duration of rainfall was 9.1 hours. The points of investigation were the land cover which showed 100% impervious rate due to some landscaping according to the shape of the road, but showed a characteristic of spillage even at low rainfall. The EMCs for nonpoint pollutants by road type were classified by rainfall class after calculating EMCs for each rainfall event. In case of nonpoint source pollutant flow weighted average concentration, the variation of value according to rainfall history varies, and even in the same area, the amount of runoff and quality of water changes are significant. EMCs are classified according to rainfall class according to characteristics of nonpoint pollution source concentration. As a result of estimating the non-point pollution source unit for the secondary land cover standard traffic area, BOD was calculated to be 12.42 ㎏/㎢/day. The BOD of 17.76 ㎏/㎢/day, T-N of 13.69 ㎏/㎢/day and T-P of 0.631 ㎏/㎢/day were applied somewhat higher than the standard values calculated in this study. The reduction load calculated on the basis of the sub-division basis is the base data for evaluating the load according to the development after pre-application in road development in the target watershed. It is difficult to estimate the exact load for the specific coating to be analyzed by applying the common unit value for the pitcher land cover (residential, industrial, commercial, traffic, etc. In this study, the load is estimated by applying the calculated unit load for the traffic area. Keywords: Nonpoint Source, Load Per Unit Area, Reduction Load

Determination of patterns of rainfall history creating situations for accurate classification of rain-fed paddy fields with SAR backscatter coefficients

It is worthwhile to classify paddy fields based on the long-term frequency of ponding, which strongly determines the yield of rice. However, the direct measurement of the frequency requires a large number of backscatter images from synthetic aperture radar (SAR). Another approach is the indirect estimation of the relative frequency of ponding from differences in ponding frequency with the same rainfall history. Any combination of backscatter coefficients with such rainfall history should result in a high accuracy of classification of paddy fields based on the relative frequency of ponding. This study aims to establish methodologies for the classification of rain-fed paddy fields into two categories: ‘wet’ and ‘dry’ fields, based on ponding frequency using a small number of time-series SAR backscatter coefficients that depend on the flood situation and soil water content of the land surface. By analyzing 21 images acquired by the ALOS-PALSAR during 2007–2011, patterns of rainfall history with obvious large differences between the two categories of paddy fields were determined. Through supervised classifications using a random forest classifier, it was evident that the backscatter coefficients onset of rainy seasons for years with an above average precipitation, would be suitable as variables for accurate classification. In years where the precipitation (1379mm/year) neared the average (1330mm/year), the supplementary use of a quartile deviation of the backscatter coefficient within each plot, that indicated a degree of partial ponding, increased the classification accuracy. It was also evident that the effective rainfall index, which registers a rough estimate of rainwater acculturation in the soil, was useful in the determination of periods of significantly large variations in the backscatter coefficient between categories of rice fields.