Gauge Rainfall Research Articles

Multi-frequency effect towards High Conductivity Overburden Responses using Vertical Coplanar (VCP) coil configuration for Landslide Instrumentation

A novel instrumentation for landslide application has been made and calibrated using Vertical Coplanar (VCP) coil orientation. The early instrumentation and commonly used right now for landslide slopes was gradually equipped with standard and automatic instrumentation: three the piezometric cells, two deep-seated steel wire extensometers, four inclinometric tubes, a rainfall gauge, a snow gauge and an air thermometer. This novel instrumentation works in electromagnetic methods similar with electromagnetic methods in geophysics; otherwise, the system was mechanics and electronics. VCP coil orientation is a coplanar array where both coils are vertical. In VCP, the depth of sounding is about 1.5 times of the coils separation. The overburden thicknesses in the field exploration are often covering the tropical area and presented as weathering layer. The more of overburden thickness then the more of energy of electromagnetic wave will be absorbed, as the result that the electromagnetic wave becomes smaller. The electromagnetic wave that reaches the target of the subsurface is also become smaller in amplitude. The multi-frequency application would be helpful in the data interpretation of the anomaly position and the conductive overburden caused by the domination trends between out-of-phase (OP) and in-phase (IP) components could be determined. In the higher frequencies (3037.5 Hz and 1012.5 Hz), the curve of IP is raised up, with the result that the positive peak values become higher and the negative peak values become lower in levels. The multi-frequency application gives the results that in the higher frequency examinations, the anomaly response is influenced significantly by the conductive overburden. In the lower frequency measurements, the anomaly response is not influenced significantly by overburden response. In the higher frequency measurements, when the electromagnetic wave is passing through the conductive material, the amplitude attenuation and the phase shifting are occurred. Therefore, the OP response becomes inverted in the peaks.

Statistical detection and no-detection of rainfall change trends and breaks in semiarid Tunisia—50+ years over the Merguellil agro-hydro-climatic reference basin

Rainfall variability is an important feature of semiarid climates with major effects on hydrology, and beyond on key water-dependent societal aspects. Eventual changes in rainfall variability are a strong driver of change of hydrological processes, resources, and hazards, up to catchment signatures and spatial arrangements. We deal with observed precipitations and subsequent statistical coefficients available from a network of 15 rainfall gauges over and around the Merguellil catchment (1175 km2), with series ranging up to the 1961–2013 period. We look for eventual annual trends and breakpoints with a set of methods: Mann Kendall test, Pettitt test, Hubert segmentation procedure, Buishand U statistic, and Lee Heghinian Bayesian procedure. The results underline oscillation of dry and wet periods; several studied rain gauges (Tella, Oueslatia foret, Majbar, Kesra foret, Henchir Bhima, and Haffouz DGRE) denote significant trends in annual precipitation. Some breaks are detected but they are not synchronous. These methods reveal the variability of rainfall regimes in the semiarid region and provide a synoptic view of detection and no-detection of symptoms of change. This work gives opportunities to water stakeholders and climate experts in understanding the relationships between climate variability and water availability.

Assessment of SWAT Model Performance in Simulating Daily Streamflow under Rainfall Data Scarcity in Pacific Island Watersheds

Evaluating the performance of watershed models is essential for a reliable assessment of water resources, particularly in Pacific island watersheds, where modeling efforts are challenging due to their unique features. Such watersheds are characterized by low water residence time, highly permeable volcanic rock outcrops, high topographic and rainfall spatial variability, and lack of hydrological data. The Soil and Water Assessment Tool (SWAT) model was used for hydrological modeling of the Nuuanu area watershed (NAW) and Heeia watershed on the Island of Oahu (Hawaii). The NAW, which had well-distributed rainfall gauging stations within the watershed, was used for comparison with the Heeia watershed that lacked recoded rainfall data within the watershed. For the latter watershed, daily rain gauge data from the neighboring watersheds and spatially interpolated 250 m resolution rainfall data were used. The objectives were to critically evaluate the performance of SWAT under rain gauge data scarce conditions for small-scale watersheds that experience high rainfall spatial variability over short distances and to determine if spatially interpolated gridded rainfall data can be used as a remedy in such conditions. The model performance was evaluated by using the Nash–Sutcliffe efficiency (NSE), the percent bias (PBIAS), and the coefficient of determination (R2), including model prediction uncertainty at 95% confidence interval (95PCI). Overall, the daily observed streamflow hydrographs were well-represented by SWAT when well-distributed rain gauge data were used for NAW, yielding NSE and R2 values of > 0.5 and bracketing > 70% of observed streamflows at 95PCI. However, the model showed an overall low performance (NSE and R2 ≤ 0.5) for the Heeia watershed compared to the NAW’s results. Although the model showed low performance for Heeia, the gridded rainfall data generally outperformed the rain gauge data that were used from outside of the watershed. Thus, it was concluded that finer resolution gridded rainfall data can be used as a surrogate for watersheds that lack recorded rainfall data in small-scale Pacific island watersheds.

Dependence properties of spatial rainfall extremes and areal reduction factors

Areal reduction factors (ARFs) transform an estimate of extreme rainfall at a point to an estimate of extreme rainfall over a spatial domain, and are commonly used in flood risk estimation. For applications such as the design of large infrastructure, dam safety and land use planning, ARFs are needed to estimate flood risk for very rare events that are often larger than the biggest historical events. The nature of the relationship between ARFs and frequency for long return periods is unclear as it depends on the asymptotic dependence structure of rainfall over a region, i.e., the extent to which rainfall from a surrounding region is extreme as rainfall at a point becomes more extreme. Miscalculating this for very rare events could lead to poor design of infrastructure. To investigate this, spatial rainfall processes are simulated using asymptotically dependent and independent models, and the implications for ARFs of the asymptotic assumptions are explored in a synthetic study. The models are then applied to a case study in Victoria, Australia, using 88 daily rainfall gauges with 50 years of data. The analysis shows that the observed data follow the behaviour of an asymptotically independent process, leading to ARFs that decrease with increasing return period. The study demonstrates that the use of inverted max-stable process models to simulate ARFs can provide a rigorous alternative to empirical approaches, particularly for long return periods requiring significant extrapolation from the data.

Real-time observation of an active debris flow watershed in the Wenchuan Earthquake area

Debris flows occur frequently and cause considerable damage in the Wenchuan Earthquake area; however, there has been no systematic real-time monitoring of such events. This study used a monitoring system to consider the spatial variation of meteorological and flow processes in a 39.4 km2 watershed. The system comprised three rainfall gauges at different locations, and three hydrological monitoring stations, located on the mainstream and tributaries, with instruments to measure the velocity, height, and density of debris flows. Based on the monitoring data, the debris flow events were categorized and the general runoff velocity, discharge, and density were analysed. We proposed empirical methods for estimating the velocity and the total volume of debris flows based on other easily obtainable parameters, e.g., maximum flow depth and duration. Comparison of the results derived using the monitoring data and empirical formulas with those obtained in other small watersheds worldwide revealed the debris flow characteristics in this relatively large watershed. Rainfall threshold for the debris flows was proposed, which is higher than those proposed for the same region for periods shortly after the Wenchuan Earthquake (2008–2013), and the temporal evolution of the rainfall conditions necessary for debris flows was addressed.

Improving Flood Maps in Ungauged Fluvial Basins with Dendrogeomorphological Data. An Example from the Caldera de Taburiente National Park (Canary Islands, Spain)

Flash floods represent one of the more usual natural hazards in mountain basins, and, combined with the lack of reliable flow data and the recreational use of the drainage basin by tourists and hikers, there is a significant risk of catastrophe. Here, we present a dendro-geomorphological reconstruction of a past flash flood event in the Caldera de Taburiente N.P. (Canary Islands, Spain), an ungauged drainage basin in the SW side of the volcanic island of La Palma. We couple two-dimensional hydraulic modelling in a highly-resolved topographic environment (LiDAR data) with (1) peak flow data for various Tyear return periods from an uncalibrated hydrological model and (2) a data set of scars on trees, to investigate the magnitude of a 1997 dated flash-flood. From the results, flood hazards and associated risks would be clearly underestimated by using only the unique available hydrological data (a rainfall gauge station downstream of the study area). Hydraulic models using scars data show a higher flood hazard scenario, improving the flood hazard map by using all available flood evidence. Moreover, all this will allow for better implementation of appropriate adaptation policies by National Park managers, and therefore the mitigation of future disasters.

Examining the role of unusually warm Indo‐Pacific sea‐surface temperatures in recent African droughts

Southern Africa (SA) and eastern Africa (EA) experienced a sequence of severe droughts in December–February (SA DJF) 2015–2016, October–December (EA OND) 2016 and March–April–May 2017 (EA MAM). This sequence contributed to severe food insecurity. While climate variability in these regions is very complex, the goal of this study is to analyse the role played by unusually warm Indo–Pacific SSTs, where unusual is defined as a 1‐in‐6 year event. We use observed sea‐surface temperatures (SST) and satellite–gauge rainfall observations, a 20‐member ensemble of Community Atmospheric Model version 5.1 simulations (CAM5), and a 40‐member ensemble of climate change simulations from the Community Earth Systems Model version 1 (CESM1) Large Ensemble Community Project (LENS) to explore climate conditions associated with warm events identified based on eastern and western Pacific SSTs. Our analysis suggests that strong El Niño's may be followed by warm western Pacific SST conditions, which can lead to conditions conducive to successive and potentially predictable droughts in SA DJF, EA OND and EA MAM. We show that different regions of warm SST are related to recent droughts—SA DJF: Niño 3.4; EA OND: western equatorial Pacific (WEP); and EA MAM: western North Pacific (WNP). For DJF and MAM, respectively, the CAM5 model driven with observed SST and the same model driven within a climate change experiment indicate that warmer El Niño's and WNP events produce more intense atmospheric responses, potentially associated with more severe droughts. OND climate seems to be strongly influenced by the Indian Ocean Dipole, which corresponds with some WEP events. Given global warming, we suggest that the extreme Niño 3.4 and west Pacific SST events responsible for 2015–2017 droughts are likely to reoccur, thus humanitarian agencies should prepare to predict and respond to multi‐year drought and substantial food insecurity in SA and EA.

Optimal selection of rainfall gauges for safe extreme events estimation using a geostatistical approach

This paper’s objective is to present a method for optimizing rain gauge network aiming to determine the optimal number of stations and their locations, to achieve an acceptable error in extreme rainfall estimation. The optimization is based on the comparison between the maximum daily rainfall depths at high return periods deduced using the entire rain gauges networks and that was deduced using an “optimal” number of rain gauges. A latin hypercube sampling (LHS) method is used to generate samples of stations. Each generated sample is analyzed to obtain the optimum set of gauges locations. The optimal number and locations of rain gauges are obtained in two cases: the first one using a regional frequency analysis technique and the second using an at-site frequency analysis technique. The methodology is applied to the existing rain gauges network of the Walnut Gulch Experimental Watershed (WGEW), AZ, USA. The results showed that, a lower number of rain gauges is required based on the regional frequency analysis technique compared to the at-site frequency analysis technique to achieve the same relative error at the high return periods. The study also suggests optimum locations for the rain gauges.

Radar Data Analyses for a Single Rainfall Event and Their Application for Flow Simulation in an Urban Catchment Using the SWMM Model

The disadvantage of radar measurements is that the obtained rainfall data is imprecise. Therefore, the use of radar data in hydrological applications usually requires correction. The main aim of the study was to verify and optimize various methods of estimating the rainfall depths for single events based on radar data, as well as determining their influence on the values of peak flow and outflow volume of hydrographs simulated using the SWMM (Storm Water Management Model) hydrodynamic model. Regression analyses were used to find a relationship between the rain gauge rainfall rate R and radar reflectivity Z for the urban catchment of the Służewiecki Stream in Warsaw, Poland. Five methods for determining calculational values of radar reflectivity in reference to specific rainfall cells with 1 km resolution within an event duration were applied. Moreover, the correction coefficient for data from the SRI (Surface Rainfall Intensity) product was established. The Z-R relationships determined in this study offer much better rainfall rate estimation as compared to Marshall-Palmer’s relationship. Different scenarios were applied to investigate the stream response to changes in rainfall depths estimated on the basis of radar data, in which the data both for 2 existing, as well as 64 virtual, rain gauges assigned to appropriate rainfall cells in the catchment were included. Relatively good agreement was achieved between the measured parameters of the hydrograph of flows and those simulated in response to rainfall depths which had been calculated for single events using the correction coefficient and the determined Z-R relationships. Radar estimates of rainfall depths based on the tested methods can be used as input data to the SWMM model for the purpose of simulating flows in the investigated urban catchment.

A rule based quality control method for hourly rainfall data and a 1 km resolution gridded hourly rainfall dataset for Great Britain: CEH-GEAR1hr

High-resolution gridded precipitation products are rare globally, particularly below a daily time-step, yet many hydrological applications require, or can be improved by, a higher temporal resolution of rainfall data. Here, we present a new 1 km resolution gridded hourly rainfall dataset for Great Britain (Gridded estimates of hourly areal rainfall for Great Britain (1990–2014) [CEH-GEAR1hr]) using data from over 1900 quality controlled rainfall gauges, which improves upon the current UK national gridded precipitation datasets at daily time-step. We extend and automate a quality control (QC) procedure to permit the use of hourly data for 1990–2014 and independently validate the QC using daily rainfall data and recorded historic events. Our two-tiered validation approach, at daily and hourly timescales, indicates that spurious extreme values are excluded from the resultant dataset, while legitimate values are preserved. We use a nearest neighbour interpolation scheme to derive gridded hourly rainfall values at 1 km resolution, to temporally disaggregate the CEH-GEAR daily gridded dataset and produce an hourly dataset with consistent daily totals. This provides a unique resource for hydrological applications in Great Britain. The CEH-GEAR1hr dataset, associated metadata and QC information, will be freely available from the Environmental Information Data Centre (EIDC) and hosted alongside the daily and monthly CEH-GEAR product.

Rainfall Prediction in South-Eastern Part of Bangladesh by Linear Regression Method

Rainfall forecasting is very challenging task for the meteorologists. Over the last few decades, several models have been utilized, attempting the successful analysing and forecasting of rainfall. Recorded climate data can play an important role in this regard. Long-time duration of recorded data can be able to provide better advancement of rainfall forecasting. This paper presents the utilization of statistical techniques, particularly linear regression method for modelling the rainfall prediction over Bangladesh. The rainfall data for a period of 11 years was obtained from Bangladesh Meteorological department (BMD), Dhaka i.e. that was surface-based rain gauge rainfall which was acquired from 08 weather stations over Bangladesh for the years of 2001-2011. The monthly and yearly rainfall was determined. In order to assess the accuracy of it some statistical parameters such as average, meridian, correlation coefficients and standard deviation were determined for all stations. The model prediction of rainfall was compared with true rainfall which was collected from rain gauge of different stations and it was found that the model rainfall prediction has given good results.

The Temporal-Spatial Characteristics of Drought in the Loess Plateau Using the Remote-Sensed TRMM Precipitation Data from 1998 to 2014

Rainfall gauges are always sparse in the arid and semi-arid areas of Northwest China, which makes it difficult to precisely study the characteristics of drought at a large scale in this region and similar areas. This study used the TRMM (The Tropical Rainfall Measuring Mission) multi-satellite precipitation data to study the spatial-temporal evolution of drought in the Loess Plateau based on the SPI (Standardized Precipitation Index) drought index for the period of 1998–2014. The results indicate that the monthly TRMM precipitation data are well matched with the observed precipitation, indicating that this remotely sensed data set can be reliably used to calculate the SPI drought index. Based on the study findings, the average precipitation in the Loess Plateau is showing a significant increasing trend at the rate of 4.46 mm/year. From the spatial perspective, the average annual precipitation in the Southeast is generally greater than that in the Northwest. However, the annual precipitation in the Southeast area is showing a decreasing trend, whereas, the annual precipitation in the northwest areas is showing an increasing trend. Through the SPI analysis, the 3-month SPI and 12-month SPI were both showing an increasing trend, which indicates that the drought severity in the Loess Plateau was a generally declining trend at a seasonal to annual time scale. From the spatial perspective, the SPI values in the Central and Northwest of the Loess Plateau were significantly increasing, whereas, the SPI values in the southern area of the Loess Plateau were slightly decreasing. From the seasonal characteristics, the high-risk area for drought in the spring was concentrated in the northeast and southwest part, and in the summer and autumn, the high-risk area was transferred to the south part. Through this study, it is concluded that the Loess Plateau was likely getting wetter during the time period since the Grain-for-Green Project (1999–2012) was implemented, which replaced much farmland with forestry. This is a positive signal for vegetation recovery and ecological restoration in the near future.

Rain Behaviour at Mt. Merapi Area as Observed by XMPR and ARR

Short duration rainfall information has now become one of many important aspects to support the development of warning criteria for disaster mitigation. Similar importance is also found in the development of warning criteria against the lahar flow disaster at Mt. Merapi area. The rainfall information obtained from the radar observation has also become a new challenge for the last decade in line with the rapid growth of information and communication technology. However, the accuracy of its estimation needs to be evaluated by considering the correlation between radar rainfall and rain gauge rainfall. In case of radar rainfall can be precisely estimated, this information will contribute to generating appropriate warning criteria. This study was carried out as the first attempt to evaluate the rainfall information as performed by the X-Band Multi Parameter Radar (XMPR) that was installed at Mt. Merapi in the mid-August 2015. Several ground rainfall data obtained from Automatic Rainfall Recorder (ARR) have been adopted to analyze the aforesaid radar rainfall information, and estimated errors between the two are presented. Evaluation of the radar estimated error value as a function or range is taken through a Fractional Standard Error (FSE) index that quantifies the differences between ground rainfall measurement (G) and radar rainfall estimation (R), also the G/R ratio characteristics. The result shows there was a poor correlation between radar estimated and rain gauge measured rainfall located over 14 km from radar. Radar bias (M) is suitable for correcting radar rainfall amount, yet inappropriate for fractional values.

Influence of rainfall data scarcity on non-point source pollution prediction: Implications for physically based models

Hydrological and non-point source pollution (H/NPS) predictions in ungagged basins have become the key problem for watershed studies, especially for those large-scale catchments. However, few studies have explored the comprehensive impacts of rainfall data scarcity on H/NPS predictions. This study focused on: 1) the effects of rainfall spatial scarcity (by removing 11%–67% of stations based on their locations) on the H/NPS results; and 2) the impacts of rainfall temporal scarcity (10%–60% data scarcity in time series); and 3) the development of a new evaluation method that incorporates information entropy. A case study was undertaken using the Soil and Water Assessment Tool (SWAT) in a typical watershed in China. The results of this study highlighted the importance of critical-site rainfall stations that often showed greater influences and cross-tributary impacts on the H/NPS simulations. Higher missing rates above a certain threshold as well as missing locations during the wet periods resulted in poorer simulation results. Compared to traditional indicators, information entropy could serve as a good substitute because it reflects the distribution of spatial variability and the development of temporal heterogeneity. This paper reports important implications for the application of Distributed Hydrological Models and Semi-distributed Hydrological Models, as well as for the optimal design of rainfall gauges among large basins.

Spatio-temporal trend and homogeneity analysis of gridded and gauge precipitation in Indravati River basin, India

Abstract The study aims to analyze spatio-temporal variations in rainfall data over Indravati River basin, India. Three rainfall data sets, Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), India Meteorological Department (IMD) grid, and IMD gauge were used. Data from 2001 to 2013 were analyzed for three time scales, namely, daily, monthly, and annual. Analysis showed good correlation between IMD gauge and TMPA grid rainfall at monthly time scale, poor correlation is observed at daily and annual time scales. Mann–Kendall (MK) trend test reveals a significant increasing trend of IMD gauge and IMD grid data, whereas TMPA rainfall is free from trends at the majority of stations for daily time scale. Nevertheless, both IMD grid as well as TMPA grid rainfall can be considered as a better representative of rainfall, since it is attained from observed rainfall data over the country. The Pettitt and standard normal homogeneity tests show that TMPA rainfall has a more non-homogeneous nature, whereas IMD grid rainfall and IMD gauge rainfall data are homogeneous. Overall, the trend and homogeneity analysis indicate that TMPA grid and IMD grid rainfall is in line with IMD gauge data, however IMD grid rainfall has the edge over TMPA grid data.

Evaluation and comparison of interpolated gauge rainfall data and gridded rainfall data in Florida, USA

ABSTRACTA variety of spatially continuous rainfall products are available but little evaluation of their accuracy has been published for areas with high spatial variability in rainfall. Five gridded rainfall products (PRISM, RTMA, and the interpolated Florida Automated Weather Network, FAWN, rainfall layers based on three interpolated methods) were assessed for Florida State. Point-to-pixel and pixel-to-pixel comparisons were performed to compare the five products. On average, the PRISM and RTMA products resulted in a better fit with the daily FAWN rainfall datasets, while FAWN-based interpolated products resulted in a better fit with the monthly FAWN rainfall datasets based on point-to-pixel analysis. Inverse distance weighting and ordinary kriging methods performed slightly better than the thin plate spline method in predicting daily rainfall. In general, monthly and seasonal rainfall amounts from PRISM and RTMA products were higher and lower, respectively, than reference rainfall amounts from FAWN gauge stations and FAWN-based interpolated products.

Detection of trends for extreme events of precipitation in the Metropolitan Region of Belo Horizonte through statistical methods

ABSTRACT Extreme weather events have emerged as one of the main manifestations of climate change, being that the mitigation of the elapsed impacts demand studies of the magnitude and frequency of their occurrence. This study aims to identify the trends of extreme precipitation events in the Metropolitan Region of Belo Horizonte, especially concerning their frequency. The trends of precipitation were studied with especial regard to the indices set by ETCCDMI (Expert Team on Climate Change Detection Monitoring and Indices), including time series of annual number of rainy days above a certain threshold recorded at fourteen rainfall gauging stations. One stage of this study consisted in surveying the flood occurrence in the area, besides analyzing the precipitation data corresponding to date of flood occurrences, in order to establish a threshold value beyond which an event would entail potential impacts. No regional index pattern could be set based on such results, although the rainfall station located in the city of Belo Horizonte reported a statistically significant increase in daily precipitation events above 10, 20, 30 and 40 mm, in maximum precipitation recorded over five consecutive days, in daily intensity, and in total annual precipitation. Abrupt changes in rainfall series were also recorded. The results have indicated that the city may be potentially impacted by extreme rainfall increase, probably associated to changes in temperatures on regional and local scales.

Analysis of rainfall distribution in Kelantan river basin, Malaysia

Using rainfall gauge on its own as input carries great uncertainties regarding runoff estimation, especially when the area is large and the rainfall is measured and recorded at irregular spaced gauging stations. Hence spatial interpolation is the key to obtain continuous and orderly rainfall distribution at unknown points to be the input to the rainfall runoff processes for distributed and semi-distributed numerical modelling. It is crucial to study and predict the behaviour of rainfall and river runoff to reduce flood damages of the affected area along the Kelantan river. Thus, a good knowledge on rainfall distribution is essential in early flood prediction studies. Forty six rainfall stations and their daily time-series were used to interpolate gridded rainfall surfaces using inverse-distance weighting (IDW), inverse-distance and elevation weighting (IDEW) methods and average rainfall distribution. Sensitivity analysis for distance and elevation parameters were conducted to see the variation produced. The accuracy of these interpolated datasets was examined using cross-validation assessment.

Evaluation of INSAT-3D satellite derived precipitation estimates for heavy rainfall events and its validation with gridded GPM (IMERG) rainfall dataset over the Indian region

In the current study, an attempt has been made to investigate the potential utilization of INSAT-3D satellite derived rainfall estimations i.e., Hydro-Estimator Method (HEM), INSAT Multi-spectral rainfall (IMR) and Quantitative Precipitation Estimation (QPE) for the analysis of heavy rainfall episodes over the Indian region from the operational INSAT Meteorological Data Processing System (IMDPS), New Delhi. The dataset used for the comparison and validations are, Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement) (IMERG) (0.1° × 0.1°) data, IMD's surface in-situ raingauge data and daily merged satellite gauge (DMSG) rainfall data (0.5° × 0.5°). The results show that all three INSAT-3D satellite rainfall products captured the rainfall pattern spatially and temporally very well in term of the occurrence of rainfall events. For the heavy rainfall events, HEM shows good skill and correlation (r > 0.7) in detecting heavy rainfall with an accuracy of ± 20mm with good pattern matching with actual rainfall, whereas IMR and QPE correlation are less than 0.3 and 0.1 respectively. The performance statistics with IMERG and daily merged satellite gauge rainfall shows that HEM correlates well with both the dataset with a small deviation. The underestimation of heavy rain is severe for higher elevation, suggesting HEM, IMR and QPE are not able to detect orographic enhancement appropriately; however, to some extent, HEM is better able to detect heavy rain events despite the fact that it failed to reach the magnitude of rainfall. Further, the INSAT-3D derived HEM and IMR products with GPM data during initial stages of cyclone 'Roanu' has been considered to illustrate the observing pattern of rainfall. It is found that HEM captured the similar pattern of single-rain-band indicating moderate to heavy rainfall around the cyclone in comparison with GPM. This study is one of the earlier assessments of operational INSAT-3D derived rainfall products and its comparison with IMERG/DMSG and actual rainfall data which shows that HEM is better for heavy rainfall and could be used in future for meteorological and hydrological models while QPE and IMR have better skills for light to moderate rainfall which can be used for agriculture and ground water recharge.

Evaluation of Weather Research and Forecasting (WRF) Microphysics single moment class-3 and class-6 in Precipitation Forecast

In this study, the performance of two different Microphysics Scheme options in Weather Research and Forecasting (WRF) model were evaluated for the estimating the precipitation forecast. The schemes WRF single moment class-3 (WSM-3) and single moment class-6 (WSM-6) were employed to produce the minimum, medium and maximum precipitation for the selected events over the Kuantan River Basin (KRB). The obtained simulated results were compared with the observed data from eight different rainfall gauging stations. The results comparison indicate that WRF model provides better forecasting at some rainfall stations for minimum and medium rainfall events but did not produce good result during maximum rainfall overall. The WSM-6 scheme is found to produce better result compared to WSM-3. The study also found that to acquire accurate precipitation results, it is also required to test some other physics scheme parameterization to enhance the model performance.