Similar Rainfall Characteristics Research Articles

Validation of Hershfield probable maximum precipitation estimation using homogeneous region in Malaysia

Probable maximum precipitation (PMP) is used to design major hydraulic structures, such as dams and spillways, flood protection works, and nuclear power plants. Long observation data are required for PMP estimates using the Hershfield statistical approach. In Malaysia, the PMP calculated using state boundary is commonly used, but the estimated PMP values are close to historical maximums. Homogeneous regions are regions containing stations with similar rainfall characteristics. Therefore, homogeneous region boundaries could be used for PMP estimations. In this paper, 1-day rainfall data of more than 25 years for 161 stations in Peninsular Malaysia; were analysed to estimate the PMP for 1-day duration based on an appropriate frequency factor by considering homogeneous regions. Using PMP estimates, a generalised graph was prepared to show the spatial distribution of 1-day PMP. The 1-day PMP estimates in Peninsular Malaysia by considering state boundary, varied from 146 to 1364.7 mm and by considering the homogeneous regions, the 1-day PMP estimates varied from 208.5 to 2094 mm. Hence, the PMP considering homogeneous regions is considered more accurate and safe to be used in designs.

Rainfall Physical Partitioning and Chemical Characteristics in Evergreen Coniferous and Deciduous Broadleaved Forest Stands in a High Nitrogen Deposition Region, China

Atmospheric rainfall is one of the major sources of water and nutrient inputs in forest stands. Understanding the atmospheric rainfall partitioning and hydrochemical fluxes of forest stands is critical for forest management and monitoring regional atmospheric pollution, especially in high N deposition regions. In this study, annual rainfall collections were implemented to investigate rainfall partitioning, element concentrations, and element fluxes in an evergreen coniferous forest (ECF) stand, a deciduous broadleaved forest (DBF) stand, and open area field (OAF) in a high N deposition region, China. Rainfall in the ECF and DBF was partitioned into throughfall, stemflow, and interception loss, which accounted for 74.7%, 4.8%, and 20.5% of the gross annual rainfall in the ECF stand, respectively; and 79.8%, 5.8%, and 14.4% of the gross annual rainfall in the DBF stand, respectively. Rainfall physical partitioning chemical characteristics varied with forest stand type. The amount of throughfall and stemflow in the ECF stand was lower than that in the DBF stand; the interception loss in the ECF stand was higher than that in the DBF stand. Element concentrations and element fluxes increased as rainfall passed through forest canopies in the high N deposition region. The stemflow pH in the ECF was lower than that in the DBF stand, the concentrations of NO3−-N, Cl−, and SO42−-S in stemflow in the ECF stand were higher than those in the DBF stand, and the concentrations of K+, Na+, Ca2+, Mg2+ and NH4+-N in stemflow in the ECF stand were lower than those in the DBF stand. The inorganic N deposition was 52.7 kg ha−1 year−1 for the OAF, 110.9 kg ha−1 year−1 for the ECF stand, and 99.6 kg ha−1 year−1 for the DBF stand; stemflow accounted for 15.1% and 19.2% of inorganic N deposition in the ECF stand and the DBF stand, respectively. In the present study, given the similar rainfall characteristics and meteorological conditions, the differences in rainfall partitioning and chemical characteristics between the ECF stand and the DBF stand could largely be attributed to their differences in stand characteristics. The results of the study will facilitate a greater understanding of the atmospheric rainfall partitioning and hydrochemical fluxes of forest stands in a high nitrogen deposition region.

An alternate approach to the relationship between the southern oscillation and rainfall in Malaysia

. The Southern Oscillation Index (SOl) based on the version of the Clim3.te Analysis Center (USA), was correlated with rainfall indices of various regions with similar rainfall characteristics in Malaysia. It was found that no correlation exists between the two indices in Peninsular Malaysia (East Coast, West Coast) but some significant correlation exist for the States of Sabah and Sarawak. An attempt has been made to offer some physical explanation to the findings.

Performance of the Global Forecast System's medium-range precipitation forecasts in the Niger river basin using multiple satellite-based products

Abstract. Accurate weather forecast information has the potential to improve water resources management, energy, and agriculture. This study evaluates the accuracy of medium-range (1–15 d) precipitation forecasts from the Global Forecast System (GFS) over watersheds of eight major dams (Selingue Dam, Markala Dam, Goronyo Dam, Bakolori Dam, Kainji Dam, Jebba Dam, Dadin Kowa Dam, and Lagdo Dam) in the Niger river basin using NASA's Integrated Multi-satellitE Retrievals (IMERG) Final Run merged satellite gauge rainfall observations. The results indicate that the accuracy of GFS forecast varies depending on climatic regime, lead time, accumulation timescale, and spatial scale. The GFS forecast has large overestimation bias in the Guinea region of the basin (wet climatic regime), moderate overestimation bias in the Savannah region (moderately wet climatic regime), but has no bias in the Sahel region (dry climate). Averaging the forecasts at coarser spatial scales leads to increased forecast accuracy. For daily rainfall forecasts, the performance of GFS is very low for almost all watersheds, except for Markala and Kainji dams, both of which have much larger watershed areas compared to the other watersheds. Averaging the forecasts at longer timescales also leads to increased forecast accuracy. The GFS forecasts, at 15 d accumulation timescale, have better performance but tend to overestimate high rain rates. Additionally, the performance assessment of two other satellite products was conducted using IMERG Final estimates as reference. The Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) merged satellite gauge product has similar rainfall characteristics to IMERG Final, indicating the robustness of IMERG Final. The IMERG Early Run satellite-only rainfall product is biased in the dry Sahel region; however, in the wet Guinea and Savannah regions, IMERG Early Run outperforms GFS in terms of bias.

Runoff reaction from extreme rainfall events on natural hillslopes: a data set from 132 large-scale sprinkling experiments in south-western Germany

Abstract. Pluvial or flash floods generated by heavy precipitation events cause large economic damage and loss of life worldwide. As discharge observations from such extreme occurrences are rare, especially on the scale of small catchments or even hillslopes, data from artificial sprinkling experiments offer valuable information on runoff generation processes, overland and subsurface flow rates, and response times. We conducted 132 large-scale sprinkling experiments on natural hillslopes at 23 sites with different soil types and geology on pastures and arable land within the federal state of Baden-Württemberg in south-western Germany. The experiments were realized between 2016 and 2017. Simulated rainfall events of varying durations were based on (a) the site-specific 100-year return periods of rainfall with different durations and (b) the maximum rainfall intensity observed locally. The 100 m2 experimental area was divided into three individual plots, and overland and subsurface flow, soil moisture, and water level dynamics in the temporarily saturated soil zone were measured at 1 min resolution. Furthermore, soil characteristics were described in detail for each site. The data were carefully processed and corrected for measurement errors and combined into a consistent and easy-to-use database. The experiments revealed large variability in possible runoff responses to similar rainfall characteristics. In general, agricultural fields produced more overland flow than grassland. The latter generated hardly any runoff during the first simulated 100-year event on initially dry soils. The data set provides valuable information on runoff generation variability from natural hillslopes and may be used for the development and evaluation of hydrological models, especially those considering physical processes governing runoff generation during extreme precipitation events. The data set presented in this paper is freely available from the FreiDok plus data repository at https://doi.org/10.6094/UNIFR/151460 (Ries et al., 2019).

A Study on Rain Rate Prediction of Southwestern Nigeria

Rainfall parameters can be utilized to investigate the effect of climate change through scientific methods. However, data on rainfall rate exceeded for a fraction of an average year is grossly unavailable over Nigeria’s climate, thereby diminishing the capability of existing models to adequately estimate the effect of degradation due to rain. Hence, more accurate estimation is required for better predictions. Rainfall volume data for six different locations in the south-western region of Nigeria were obtained for rain rate computation using Semire and Rosmiwati model. The curve-fitted Cumulative Distribution Functions were compared with the ITU-R rain rate model (Recommendation P.837-6) and compensation function was obtained using error analysis while the performance was evaluated with respect to existing models using Chi-square, and Percentage Error and Root Mean Square Error (RMSE) metrics. The outcome of this study can be adopted for better understanding of spatial rainfall intensity in this region and other climatic zones of similar rainfall characteristics.

Rainfall erosivity and erosivity density in Eastern Ghats Highland of east India

The rainfall erosivity (R-factor in USLE) is the long-term average of the sum of the product of rainfall kinetic energy and its maximum 30-min intensity. Therefore, at most 30-min time intervals pluviograph records are required to calculate R-factor. But, such high-resolution data are scarce in many parts of the world and require lengthy processing period. In this study, R-factor was correlated with daily, monthly and annual rainfall, and its spatial variability in Eastern Ghats Highland of east India was mapped. The result showed that power regression models predicted satisfactorily the daily, monthly and annual R-factor, of which annual R-factor model performed best (model efficiency 0.93). Mean monsoon season R-factor was 15.6 and 10.0 times higher than the pre- and post-monsoon season R-factor, and thus remained highly critical with respect to erosion. Annual R-factor values ranged from 3040 to 10,127 MJ mm ha−1 h−1 year−1, with standard deviation of 1981 MJ mm ha−1 h−1 year−1. Rainfall intensity was positively correlated with erosivity density, and numerical value of rainfall intensity was almost double of the erosivity density value. The combination of rainfall and erosivity density was used to identify flood, erosion and landslide-prone areas. The developed iso-erosivity, erosivity density and risk maps can be opted as a tool for policy makers to take suitable measures against natural hazards in Eastern Ghats Highland of east India and elsewhere with similar rainfall characteristics.

Regionalization of rainfall characteristics in India incorporating climatic variables and using self-organizing maps

Regionalization of rainfall or delineation of a region into areas having similar rainfall characteristics is useful for many hydrologic applications and water resources management. In this study, we aim to regionalize India into regions having similar rainfall and climatic characteristics using self-organizing maps (SOM), an artificial neural network algorithm derived clustering technique. The SOM algorithm is applied to observed gauge-based gridded Indian Meteorological Department (IMD) rainfall data (0.25° × 0.25°) for 34 years duration (1980–2013). Information about climatic variables like air temperature, specific humidity, geo-potential height, surface pressure, etc., which directly influence the rainfall characteristics is derived from the Modern Era-Retrospective Analysis for Research and Applications reanalysis data-set. Four cluster validity indices are used to identify the optimal number of clusters. While, 10 homogeneous regions are identified over India when accounting rainfall characteristics only, incorporation of climatic variables added more heterogeneity dividing India into 15 homogeneous rainfall regions. These 15 homogeneous rainfall zones effectively capture the spatial variability of rainfall and its spell-characteristics over India. Moreover, none of the 15 delineated regions are found to be heterogeneous when subjected to regional homogeneity test. The present study will aid in regional frequency analysis, forecasting and downscaling of rainfall, land-use management and agriculture planning.

Sensitivity of WRF Cloud Microphysics to Simulations of a Convective Storm Over the Nepal Himalayas

Background:This paper investigates sensitivity of bulk microphysical parameterization (BMP) schemes within the Weather Research and Forecasting (WRF) model to simulate a convective storm that generally evolves during pre-monsoon season (March – May) across the foothills of the Himalayas.Method:Four mixed-phase BMP schemes (Morrison, Lin, WDM6, and WSM6), which are parameterized with an increasing complexity from single to double moments of particle distribution to represent cloud processes, are used with an explicit convection permitting grid resolution (3 km x 3 km). Experiments are set up to simulate a convective storm that occurred in the late afternoon of 18thMay 2011 and compared with i) Satellite-based tropical rainfall measuring mission (TRMM) 3B42 v7 data, and ii) Ground-based observations at Nagarkot (27.7°N, 85.5°E), Nepal.Result:Our results show that the simulated storm characteristics are not overly sensitive to the chosen BMP schemes. In general, all the BMP schemes produce similar rainfall characteristics and compares reasonably well with the observations across Siwalik Hills and Middle Mountains, which act as a topographic barrier to low level circulations and receive more rain. The schemes, however, show negative bias across central Nepal including the Kathmandu Valley, albeit the magnitude and spatial distribution of bias are different between the schemes. In contrast, upper level total water condensate and cloud fraction show a strong sensitivity to the BMP schemes.Conclusion:Overall, the Morrison scheme, in addition to warm clouds which also predict double moment distribution of all hydrometeors in the cold-cloud processes, a dominant cloud forming process in the Himalayas, accurately represents the mechanism and outperforms the simplified schemes based on root mean square error (RMSE) analysis.

Landscape-Scale Disturbance: Insights into the Complexity of Catchment Hydrology in the Mountaintop Removal Mining Region of the Eastern United States

Few land disturbances impact watersheds at the scale and extent of mountaintop removal mining (MTM). This practice removes forests, soils and bedrock to gain access to underground coal that results in likely permanent and wholesale changes that impact catchment hydrology, geochemistry and ecosystem health. MTM is the dominant driver of land cover changes in the central Appalachian Mountains region of the United States, converting forests to mine lands and burying headwater streams. Despite its dominance on the landscape, determining the hydrological impacts of MTM is complicated by underground coal mines that significantly alter groundwater hydrology. To provide insight into how coal mining impacts headwater catchments, we compared the hydrologic responses of an MTM and forested catchment using event rainfall-runoff analysis, modeling and isotopic approaches. Despite similar rainfall characteristics, hydrology in the two catchments differed in significant ways, but both catchments demonstrated threshold-mediated hydrologic behavior that was attributed to transient storage and the release of runoff from underground mines. Results suggest that underground mines are important controls for runoff generation in both obviously disturbed and seemingly undisturbed catchments and interact in uncertain ways with disturbance from MTM. This paper summarizes our results and demonstrates the complexity of catchment hydrology in the MTM region.

Modeling the spatial occurrence of shallow landslides triggered by typhoons

Many shallow landslides in Taiwan are triggered by typhoons (tropical cyclones) during the summer months. Each typhoon produces a different rainfall distribution, depending on its track and position and the atmospheric conditions. This study investigated whether the additional rainfall data in a landslide susceptibility model can improve its performance in predicting typhoon-triggered landslides, and whether information on past typhoon events, combined with an event-based landslide inventory, can help predict landslides triggered by a typhoon. To answer these questions, the study adopted a method that integrates rainfall data with the critical rainfall model (a landslide susceptibility model based on geoenvironmental factors) to derive a logistic regression model for predicting landslide occurrence. Results of a back analysis of landslides triggered by nine typhoons from 2001 to 2009 reveal that, by including rainfall data, the integrated method performs better than the critical rainfall model in the average overall accuracy rate (0.78 vs. 0.45) and the average modified success rate (0.75 vs. 0.68). Our preliminary results also suggest that it is possible to predict landslides triggered by a typhoon by using a catch-all model developed from all other typhoon events in an inventory, or a group model developed from other typhoon events of similar rainfall characteristics in an inventory. This study opens up a new research direction in analyzing rainfall-triggered landslides in Taiwan and elsewhere.

Modelo para Pré-Dimensionamento de Bacias de Detenção para Controle da Poluição Difusa das Águas Pluviais no Município de Porto Alegre

Diffuse pollution of stormwater is one of several environmental impacts caused by urbanization. Detention ponds can control peak flows, but can also be used to control stormwater quality through the natural sedimentation of pollutants. A model was developed to pre-size detention ponds for stormwater quality control in Porto Alegre, It was based on a methodology to maximize capture volume and a methodology for calculating the efficiency of removal pollutants. Rainfall series from Porto Alegre were used to develop the model. Simulations showed that detention volumes needed for quality control are 157 m3/ha for a runoff coefficient of 0.6, typical of urban areas, ranging from 36 to 225 m3/ha for runoff coefficients from 0.1 to 1.0, respectively. The proposed model was compared with models used in the United States with similar rainfall characteristics, resulting in compatible detention volumes

Rainfall erosivity in Central Chile

Summary One of the most widely used indicators of potential water erosion risk is the rainfall-runoff erosivity factor (R) of the Revised Universal Soil Loss Equation (RUSLE). R is traditionally determined by calculating a long-term average of the annual sum of the product of a storm’s kinetic energy (E) and its maximum 30-min intensity (I30), known as the EI30. The original method used to calculate EI30 requires pluviograph records for at most 30-min time intervals. Such high resolution data is difficult to obtain in many parts of the world, and processing it is laborious and time-consuming. In Chile, even though there is a well-distributed rain gauge network, there is no systematic characterization of the territory in terms of rainfall erosivity. This study presents a rainfall erosivity map for most of the cultivated land in the country. R values were calculated by the prescribed method for 16 stations with continuous graphical record rain gauges in Central Chile. The stations were distributed along 800 km (north–south), and spanned a precipitation gradient of 140–2200 mm yr−1. More than 270 years of data were used, and 5400 storms were analyzed. Additionally, 241 spatially distributed R values were generated by using an empirical procedure based on annual rainfall. Point estimates generated by both methods were interpolated by using kriging to create a map of rainfall erosivity for Central Chile. The results show that the empirical procedure used in this study predicted the annual rainfall erosivity well (model efficiency = 0.88). Also, an increment in the rainfall erosivities was found as a result of the rainfall depths, a regional feature determined by elevation and increasing with latitude from north to south. R values in the study area range from 90 MJ mm ha−1 h−1 yr−1 in the north up to 7375 MJ mm ha−1 h−1 yr−1 in the southern area, at the foothills of the Andes Mountains. Although the map and the estimates could be improved in the future by generating additional data points, the erosivity map should prove to be a good tool for land-use planners in Chile and other areas with similar rainfall characteristics.

Prediction of the summer monsoon rainfall over South China

The objective of this study is to derive an operational statistical prediction scheme for forecasting the summer monsoon rainfall (SMR, defined as the total rainfall between April and June) over South China (SC). The region of SC is first identified by applying the techniques of cluster analysis and factor analysis to the SMR of 43 stations over China for a period of 47 years (1951–1997). This procedure suggests 13 stations along the SC coast as having similar rainfall characteristics. Subdivisions of these into six stations in the east and seven in the west are also made. The predictands are therefore the average SMR over these stations. The potential predictors include: (a) indices that serve as proxies for the El Niño/Southern Oscillation (ENSO); (b) indices that represent the planetary-scale circulation and (c) the trend and periodicities in the rainfall time series. All predictors are monthly values from March of the previous year to February of the current year. The technique of projection pursuit regression is applied to derive prediction equations for each predictand using individual predictors. Only those equations in which the predicted (obtained from the jackknife technique) and observed SMR are significantly correlated (≥95%) are retained. The predictions from individual predictors are combined using a weighted average (based on the magnitude of the correlation coefficient) to produce a final forecast, which is found to be superior to those from the individual ones. An operational prediction of the SMR made in March 1998 suggested a below-normal season. However, the actual results indicate an above-normal one. Reasons for this apparent failure are discussed. Copyright © 1999 Royal Meteorological Society

Homogeneous Indian Monsoon rainfall: Variability and prediction

The Indian summer monsoon rainfall is known to have considerable spatial variability, which imposes some limitations on the all-India mean widely used at present. To prepare a spatially coherent monsoon rainfall series for the largest possible area, fourteen subdivisions covering the northwestern and central parts of India (about 55% of the total area of the country), having similar rainfall characteristics and associations with regional/global circulation parameters are merged and their area-weighted means computed, to form monthly and seasonal Homogeneous Indian Monsoon (HIM) rainfall series for the period 1871–1990. This paper includes a listing of monthly and seasonal rainfall of HIM region. HIM rainfall series has been statistically analysed to understand its characteristics, variability and teleconnections for long-range prediction.

An alternate approach to the relationship between the southern oscillation and rainfall in Malaysia

The Southern Oscillation Index (SOl) based on the version of the Clim3.te Analysis Center (USA), was correlated with rainfall indices of various regions with similar rainfall characteristics in Malaysia. It was found that no correlation exists between the two indices in Peninsular Malaysia (East Coast, West Coast) but some significant correlation exist for the States of Sabah and Sarawak. An attempt has been made to offer some physical explanation to the findings.