Cumulative Rainfall Amount Research Articles

Modification of Microphysical Parameterization Schemes and Their Application in the Simulation of an Extremely Heavy Rainfall Event in Zhengzhou

AbstractIn the present study, the Morrison and Thompson microphysics schemes in the Weather Research and Forecasting model were improved and used to simulate a record‐breaking heavy rainfall event occurred in Henan Province over central China during 19–21 July 2021. In the modified schemes, the terminal velocity of graupel and initial cloud droplet concentration were adjusted based on sensitivity tests. Results showed that the modified Morrison scheme (MORR_MOD) better captured the spatial distribution and temporal evolution of precipitation than the original scheme (MORR). Specifically, it produced a 40‐hr cumulative rainfall amount of 963 mm and an extreme hourly rainfall rate of 157.7 mm, which were closer to observations than MORR. Analysis of the dynamic and microphysical structures of the extreme‐rain‐producing convective clusters revealed that MORR_MOD predicted stronger updrafts, higher rain mass content and larger mean mass diameter of raindrops than MORR. By analyzing the tendencies of rain mass and number concentration, it was found that MORR_MOD predicted stronger accretion rates of cloud droplets by rain and weaker auto‐conversion rates of cloud droplets than MORR, which contributed to the high rain mixing ratio and low number concentration, respectively. In addition, MORR_MOD predicted stronger diabatic heating rates than MORR, which were primarily attributed to stronger condensation of water vapor, and may have been the reason why MORR_MOD simulated stronger updrafts.

Important drivers of East African monsoon variability and improving rainy season onset prediction

Monsoon rain and its year-to-year variability have a profound influence on Africa’s socio-economic structure by heavily impacting sectors such as agricultural and energy. This study focuses on major drivers of the east African monsoon during October-November-December (OND) which is the standard time window for the onset of the rainy season, be it unimodal or bimodal. Two drivers viz. Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO) both separately indicate very strong positive connections with monsoon (OND) rain not only in the OND season with zero seasonal lag, but the signal is also present even taking IOD and ENSO a season ahead. A compositing approach is applied that can additionally identify strong signals when different combinations of ENSO and IOD phases act as confounding factors. Results of precipitation anomaly suggest that when IOD and ENSO are both on the same phase in July-August-September (JAS), a significant OND rainfall anomaly occurs around the east African sector: A deficit (excess) of OND monsoon rain occurs when both drivers are in a negative (positive) phase during JAS. A location Kibaha in Tanzania, for which station data are available, is considered for a more in-depth analysis. The uncertainty range in cumulative OND rainfall is also reduced to a large degree when IOD and ENSO phases are both negative in JAS. These results can be used for prediction purposes and interestingly, that criterion of IOD and ENSO being of same phase in JAS was again matched in 2022 (both negative) and hence it was possible to deliver early warnings for a deficit in rainfall a season ahead. Techniques to compute the monsoon onset as determined by meteorological services such as the Tanzania Meteorological Authority rely on various thresholds, which may also vary by country. To overcome some of the issues with thresholds-based techniques, other definitions of ‘onset’ take into account cumulative rainfall amount and such technique has also been tested and compared. In both approaches, late (early) onsets dominate in years when ENSO and IOD are both negative (positive) during JAS. In these cases, it is therefore possible to provide an estimation of cumulative rainfall and onset for OND in terms of average, median value, range and distribution of rainfall one season in advance. Such results have implications for optimizing agricultural, water and energy management, also mitigating possible severe production losses, which would impact the livelihoods of millions of Africans.

Geospatial Perspective for Innovative Planning and Management of Watershed

Innovative watershed management is intense to unravelling watershed related problems on a sustainable manner. Planning and managing developmental practices in the watershed on a sustainable basis usually integrate water or land and both in the present in such a way to attain its goal in the future also. The water-related problems in rain-fed agriculture are often related to high intensity and short duration rainfall, with large spatial and temporal variability, rather than to the low cumulative amount of rainfall. For the innovative planning and Management in the watershed, analysing land degradation through the prioritisation watersheds, assessing the surface runoff, evaluating the Spatio-temporal distribution of the hydrological constraints, groundwater potential zone delineations and the suitable sites for the Rainwater Harvesting (RWH) are considered by spatial multi-criteria evaluation from the several thematic layers that are determined from the remote sensing and GIS technologies. These innovative spatial technologies contribute to reducing vulnerability to climate change and help minimise or even reverse land degradation. The sustainable RWH will improve the surface and ground water level, this in turn improve the economy of the watershed. Keywords: Geospatial, Innovations, Watershed, Rain­fed agriculture, Prioritisation, Groundwater

Effects of Cumulative Rainfall Amount and Nearby Sources on Plastic Pieces on the Shoulder

We investigated the side of parking lots, garbage collection points and house wall to understand the source of plastic pieces. The survey was conducted approximately monthly from Apr. 2020 to Feb. 2021 with the aim of clarifying detailed rainfall variation in the density of plastic pieces on the shoulder. The discharge coefficient of gravel is 0.30 to 0.70, lower than that of asphalt, 0.70 to 0.95. As the plastic pieces on the gravel surface could be hard to be washed away and easy to be accumulated, the mass of plastic pieces flowing into the side was larger than that flowing out. PE, PP, PS, PET and PVC were predominant among the found polymer materials (43-66%by mass). The size corresponding to the cumulative ratio of 50% the plastic pieces on the side of house wall was smaller than that on the others. On the sides of house wall that was not near the plastic source, the plastic pieces could be weathered to fragment into smaller pieces than on the others. The number density of plastic pieces scattered on the side of garbage collection point was affected by the structure. It was found that the behavior of plastic load was complicatedly influenced by land properties, uses and rainfall.

Sensitivity of infiltration modelling to temporal resolution of rainfall data

AbstractThe sensitivity of infiltration predictions by Hydrus‐1D and Green‐Ampt models to rainfall discretisation was investigated by assessing the accuracy of infiltration predictions with rainfall rate profiles at step sizes D between 2 and 1440 min. Five peak rainfall profiles and one sine‐wave rainfall profile, all with a cumulative rainfall amount of 28.8 cm and a duration of 24 h were used. Discrete rainfall profiles were generated based on the peak rainfall profiles for several step sizes. The rainfall profiles were evaluated in a sandy loam with a high saturated hydraulic conductivity and a silt loam with a low saturated hydraulic conductivity for two initial pressure heads. For both models, insensitivity was found below a critical step size Dcrit, whereas high sensitivity was observed above it, Dcrit depending on soil hydraulic conductivity and rainfall peak intensity, regardless of initial pressure head. In the sandy loam, Dcrit was 20–30 (high‐intensity peak) and 70 min (low‐intensity peak); in the silt loam, values were 100 and 200–300 min, respectively. Therefore, rainfall data from common weather station data at D = 60 min allow accurate estimates of infiltration only in low‐conductivity soils or for low‐intensity rainfall. The disaggregation of daily cumulative rainfall into sine‐wave profiles improved predictions in more conductive soils. Results indicate that higher saturated hydraulic conductivity and intensity peak rainfall rate require smaller values of D for the accurate modelling of infiltration with Hydrus‐1D and Green‐Ampt models.Highlights Temporal resolution of rainfall data is important in infiltration modelling. Temporal resolution of rainfall data affects Green‐Ampt and Hydrus‐1D predicted infiltration Green‐Ampt and Hydrus‐1D cumulative infiltration predictions are insensitive for rainfall resolution ≤20 min Predictions are more sensitive to rainfall resolution >20 min in soils with higher hydraulic conductivity.

Impacts of rainstorms on soil erosion and organic matter for different cover crop systems in the western coast agricultural region of Syria

AbstractMore and more cultivated coastal territories of Syria are being affected by increasing land degradation processes, specifically, by soil erosion due to non‐sustainable soil management. The use of cover crops can be considered an ideal solution to reduce the negative impacts of extreme rainfall events on soil erosion. However, there is no enough information about the main cultivated areas of Syria due to the current conflicts and the very few types of research conducted there. Therefore, the main aim of this research was to assess soil erosion (soil loss and sediment concentration) and hydrological response (run‐off and infiltration) considering the impact of different types of cropping systems on soil organic matter. To achieve this goal, using erosion plots, five grouped natural rainfall events and soil samples were collected, and infiltration measurements were performed between November 2012 and April 2013 (rainy season) on three different cropping systems (wheat, vetch, bean and control) with different sloping gradients (8% and 20%) in Tartous governorate (W Syria). Our results showed a cumulative rainfall amount from 68.8 to 201 mm during the study period. The highest sediment yield was generated in the control and wheat plots, registering 0.468 and 0.368 kg m−2, respectively, with an inclination of 8%. For an inclination of 20%, the control and wheat plots registered 1.145 and 0.967 kg m−2, respectively. In comparison with the control plots, there was a decrease in the total eroded organic matter, which ranged from 0.0579 (control) to 0.0289 (bean) kg m−2 year−1 in the plots with 20% inclination, and from 0.0233 (control) to 0.0069 (bean) kg m−2 year−1 with 8% inclination. To sum up, bean and vetch play an effective role to mitigate soil erosion, delay run‐off and reduce sediment yield. The output of this research provides first insights into the impact of different land uses on soil loss. Also, it could help rural inhabitants and farmers to correctly manage their soils against soil erosion processes.

Influence of canopy and topographic position on soil moisture response to rainfall in a hilly catchment of Three Gorges Reservoir Area, China

Rainfall provides essential water resource for vegetation growth and acts as driving force for hydrologic process, bedrock weathering and nutrient cycle in the steep hilly catchment. But the effects of rainfall features, vegetation types, topography, and also their interactions on soil water movement and soil moisture dynamics are inadequately quantified. During the coupled wet and dry periods of the year 2018 to 2019, time-series soil moisture was monitored with 5-min interval resolution in a hilly catchment of the Three Gorges Reservoir Area in China. Three hillslopes covered with evergreen forest (EG), secondary deciduous forest mixed with shrubs (SDFS) and deforested pasture (DP) were selected, and two monitoring sites with five detected depths were established at upslope and downslope position, respectively. Several parameters expressing soil moisture response to rainfall event were evaluated, including wetting depth, cumulative rainfall amount and lag time before initial response, maximum increase of soil water storage, and transform ratio of rainwater to soil water. The results indicated that rainfall amount is the dominant rainfall variable controlling soil moisture response to rainfall event. No soil moisture response occurred when rainfall amounts was 30 mm. In the wet period, the cumulative rainfall amount to trigger surface soil moisture response in EG-up site was significantly higher than in other five sites. However, no significant difference in cumulative rainfall amount to trigger soil moisture response was observed among all study sites in dry period. Vegetation canopy interception reduced the transform ratio of rainwater to soil water, with a higher reduction in vegetation growth period than in other period. Also, interception of vegetation canopy resulted in a larger accumulated rainfall amount and a longer lag time for initiating soil moisture response to rainfall. Generally, average cumulative rainfall amount for initiating soil moisture response during dry period of all sites (3.5–5.6 mm) were less than during wet period (5.7–19.7 mm). Forests captured more infiltration water compared with deforested pasture, showing the larger increments of both soil water storage for the whole soil profile and volumetric soil water content at 10 cm depth on two forest slopes. Topography dominated soil subsurface flow, proven by the evidences that less rainfall amount and less time was needed to trigger soil moisture response and also larger accumulated soil water storage increment in downslope site than in corresponding upslope site during heavy rainfall events.

Practical Predictability of the 17 December 2014 Heavy Rainfall Event over East Coast of Peninsular Malaysia using WRF Model

An investigation on the practical predictability aspects of heavy rainfall event in the east coast states of Peninsular Malaysia was carried out by simulating the 17 December 2014 episode using the Weather Research and Forecasting (WRF). The WRF model was configured with three nested domains of 36 km, 12 km, and 4 km horizontal resolution for 36 h simulations. It was found that the cumulative rainfall amount and the location of the heavy rainfall centre are sensitive to the choices of Cumulus Parameterisation Scheme (CPS). The experiment with a resolution of 4 km that used the multiscale Kain-Fritsch for the outer domains and no cumulus scheme in the inner domain reasonably well simulated the case. Further analysis suggests that the CPS and initialisation gave larger impact to the forecast quality compared to boundary conditions. Grid resolution contributed the least error.

Effect of disdrometer type on rain drop size distribution characterisation: a new dataset for south-eastern Australia

Abstract. Knowledge of the full rainfall drop size distribution (DSD) is critical for characterising liquid water precipitation for applications such as rainfall retrievals using electromagnetic signals and atmospheric model parameterisation. Southern Hemisphere temperate latitudes have a lack of DSD observations and their integrated variables. Laser-based disdrometers rely on the attenuation of a beam by falling particles and are currently the most commonly used type of instrument to observe the DSD. However, there remain questions on the accuracy and variability in the DSDs measured by co-located instruments, whether identical models, different models or from different manufacturers. In this study, raw and processed DSD observations obtained from two of the most commonly deployed laser disdrometers, namely the Parsivel1 from OTT and the Laser Precipitation Monitor (LPM) from Thies Clima, are analysed and compared. Four co-located instruments of each type were deployed over 3 years from 2014 to 2017 in the proximity of Melbourne, a region prone to coastal rainfall in south-eastern Australia. This dataset includes a total of approximately 1.5 million recorded minutes, including over 40 000 min of quality rainfall data common to all instruments, equivalent to a cumulative amount of rainfall ranging from 1093 to 1244 mm (depending on the instrument records) for a total of 318 rainfall events. Most of the events lasted between 20 and 40 min for rainfall amounts of 0.12 to 26.0 mm. The co-located LPM sensors show very similar observations, while the co-located Parsivel1 systems show significantly different results. The LPM recorded 1 to 2 orders of magnitude more smaller droplets for drop diameters below 0.6 mm compared to the Parsivel1, with differences increasing at higher rainfall rates. The LPM integrated variables showed systematically lower values compared to the Parsivel1. Radar reflectivity–rainfall rate (ZH–R) relationships and resulting potential errors are also presented. Specific ZH–R relations for drizzle and convective rainfall are also derived based on DSD collected for each instrument type. Variability of the DSD as observed by co-located instruments of the same manufacturer had little impact on the estimated ZH–R relationships for stratiform rainfall, but differs when considering convective rainfall relations or ZH–R relations fitted to all available data. Conversely, disdrometer-derived ZH–R relations as compared to the Marshall–Palmer relation ZH=200R1.6 led to a bias in rainfall rates for reflectivities of 50 dBZ of up to 21.6 mm h−1. This study provides an open-source high-resolution dataset of co-located DSD to further explore sampling effects at the micro scale, along with rainfall microstructure.

Effects of soil type, period of burial and moisture levels on the germination of Oncocyclus iris seeds

Understanding germination of seeds constituting a persistent soil seed bank is important because the ability to predict longevity of a seed in soil and a particular combination of environmental conditions supporting dormancy break and germination can be critical for restoration of threatened species having poor regeneration. We studied the pattern of germination under experimentally manipulated environmental conditions in several threatened iris species of section Oncocyclus. In the first experiment, spanning 11 years, we manipulated soil type and precipitation regime, and in the second experiment, spanning 7 years, we tested an effect of cumulative amount of rainfall during a season on germination. In all studied species the germination process was intermittent, with distinct germination pulses separated by years with no or very low germination. High innate dormancy appears to be a general property of newly produced seeds of Oncocyclus irises, but there are exceptions. Although in three tested Oncocyclus species considerable (above 25%) germination fraction was observed only in the second and subsequent seasons regardless of the soil moisture experienced by a seed, in Iris atropurpurea it occurred in the first season under watering equivalent or exceeding cumulative seasonal precipitation of 100 mm. In the three other species, although high cumulative germination percentage was observed by year four under all experimental conditions a substantial fraction of seeds was still ungerminated and viable. Our results have important conservation implications. We recommend for mass seed germination creation of a soil seed bank under natural conditions with minimal modifications, monitored for more than two years. Supplementary watering (if feasible) will speed up the germination process and shading will have a similar effect but neither of these two is a requirement.

INFLUENCE OF ENSO ON WET AND DRY SPELL FREQUENCY FOR RAINFED CROPPING PERIOD OVER TAMIL NADU

Abstract. Several factors are responsible for recent climatic anomalies includes seasonal and inter-annual variability of rainfall in the region in which regional and global sea surface temperature (SST) changes is the most significant factor. It is well recognized that El Niño Southern Oscillation (ENSO) is the dominant mode of climate variability on seasonal to inter-annual scales and its impacts are felt worldwide. Seasonal to inter-annual rainfall fluctuations strongly affect the success of agriculture and the abundance of water resources. Daily rainfall data at district scale was obtained from India Meteorological Department (IMD) for a period of 43 years (1971–2013) was categorized based on the ENSO episodes and the analysis was performed for the rainfed cropping period (RCP, September–December). A week (7 days) with the cumulative rainfall amount of 50 mm was considered as one wet spell. Non rainy days observed continuously for a decade (10 days) that period was considered to be one dry spell. Results revealed that El Niño conditions positively influenced the rainfall. Compared to neutral years, La Niña years received less rainfall as it showed the negative deviation in most of districts of Tamil Nadu. More wet spell and lesser dry spell weeks was observed under El Niño condition while the lesser wet spell and more dry spell was observed under La Niña conditions. Higher amount of rainfall during El Niño led to more number of wet spells under El Niño event.

Wheat yield vulnerability: relation to rainfall and suggestions for adaptation

Wheat production is of paramount importance in the region of Meknes, which is mainly produced under rainfed conditions. It is the dominant cereal, the greater proportion being the soft type. During the past few decades, rainfall flaws have caused a number of cases of droughts. These flaws have seriously affecting wheat production. The main objective of this study is the assessment of rainfall variability at monthly, seasonal and annual scales and to determine their impact on wheat yields. To reduce this impact we suggested some mechanisms of adaptation. We used monthly rainfall records for three decades and wheat yields records of fifteen years. Rainfall variability is assessed utilizing the precipitation concentration index and the variation coefficient. The association between wheat yields and cumulative rainfall amounts of different scales was calculated based on a regression model to evaluate the impact of rainfall on wheat yields. Data analysis shown moderate seasonal and irregular annual rainfall distribution. Yields fluctuated from 210 to 4500 Kg/ha with 52% of coefficient of variation. The correlation results shows that soft wheat and hard wheat are strongly correlated with the period of January to March than with the whole growing-season. While they are adversely correlated with the mid-spring. This investigation concluded that synchronizing appropriate adaptation with the period of January to March was crucial to achieving success yield of wheat.

Climate Change Impact on Rainfall: How will Threaten Wheat Yield?

Climate change has a significant impact on the environmental condition of the agricultural region. Meknes has an agrarian economy and wheat production is of paramount importance. As most arable area are under rainfed system, Meknes is one of the sensitive regions to rainfall variability and consequently to climate change. Therefore, the use of changes in rainfall is vital for detecting the influence of climate system on agricultural productivity. This article identifies rainfall temporal variability and its impact on wheat yields. We used monthly rainfall records for three decades and wheat yields records of fifteen years. Rainfall variability is assessed utilizing the precipitation concentration index and the variation coefficient. The association between wheat yields and cumulative rainfall amounts of different scales was calculated based on a regression model. The analysis shown moderate seasonal and irregular annual rainfall distribution. Yields fluctuated from 210 to 4500 Kg/ha with 52% of coefficient of variation. The correlation results shows that wheat yields are strongly correlated with rainfall of the period January to March. This investigation concluded that climate change is altering wheat yield and it is crucial to adept the necessary adaptation to challenge the risk.

Influence of rainfall duration and intensity on particulate matter removal from plant leaves

Rainfall influences removal of airborne particulate matter (PM) from leaf surfaces through a process called wash off resulting in throughfall that carries PM to the ground. The present study examined the effects of rainfall characteristics on PM wash-off mass and rate from the foliage of four broadleaf species, to investigate retention of PM pollution. In a controlled rainfall simulation experiment, rainfall intensity was set to 15, 30, and 50mmh−1, and sampling intervals for the three rainfall intensities were divided into 10, 5, and 3min, respectively. Of the plants examined, the evergreen shrub Euonymus japonicus had the greatest surface PM accumulation before rainfall (165μgcm−2), maximum wash-off during the first 2.5mm of rain (30μgcm−2), and maximum surface PM retention after rainfall (24μgcm−2). Fitting observations with the Box Lucas regression model, cumulative PM wash-off rates increased with cumulative rainfall amount, until the curves tended to become steady after rain exceeded 12.5mm. Wash off removed 51 to 70% of surface PM accumulation. As rainfall intensity increased, the duration of PM wash-off decreased, and wash-off rates were highest during the first rainfall interval. However, there was no significant difference between PM wash-off rates for rainfall intensities of 30 and 50mmh−1 in each rainfall interval. In addition, rain did not remove all PM completely, and PM retention following rainfall differed with rainfall intensity, except for Populus tomentosa.

Processes leading to deep convection and sensitivity to sea‐state representation during HyMeX IOP8 heavy precipitation event

During the first observation period of the HyMeX programme, the Mediterranean coasts of Spain were impacted by several heavy precipitating events (HPEs). The most damaging one occurred during IOP 8 resulting in cumulative rainfall amounts over 180 mm in the area of Murcia–Valencia. Numerical simulations using a high‐resolution atmospheric model provide a very realistic representation of the mesoscale convective systems (MCSs) at the origin of this HPE and of the associated low‐level conditions, consisting in two cold sectors surrounding a warm sector. This study provides a detailed analysis of the mechanisms of deep convection initiation and maintenance between 1200 UTC 28 September and 0000 UTC 29 September 2012. On the coastal mountainous area, the conditionally unstable inflow feeding the MCS is uplifted by the relief whereas at sea, a strong low‐level convergence plays the same role. At the coast, cold pools are generated and strengthened by a strong low‐level jet (LLJ) carrying cold dense air parcels from the Gulf of Lion and by evaporation and cooling under the precipitating systems. These cold pools play a key role in triggering the deep convection, either by directly uplifting the air masses or by deflecting the inflow horizontally. They largely control the localisation and distribution of the heavy precipitation at sea near Valencia. A weak barrier wind over the cold pools and a secondary cyclonic circulation result in a bending of the convergence line at sea, in agreement with radar observations.A sensitivity study to a more realistic representation of the sea state in the air–sea exchanges shows that the LLJ is decelerated by the increased sea‐surface roughness, resulting in cold pools extending further at sea and shifting the precipitation patterns 50 km offshore.

Numerical rainfall simulation with different spatial and temporal evenness by using a WRF multiphysics ensemble

Abstract. The Weather Research and Forecasting (WRF) model is used in this study to simulate six storm events in two semi-humid catchments of northern China. The six storm events are classified into four types based on the rainfall evenness in the spatial and temporal dimensions. Two microphysics, two planetary boundary layers (PBL) and three cumulus parameterizations are combined to develop an ensemble containing 16 members for rainfall generation. The WRF model performs the best for type 1 events with relatively even distributions of rainfall in both space and time. The average relative error (ARE) for the cumulative rainfall amount is 15.82 %. For the spatial rainfall simulation, the lowest root mean square error (RMSE) is found with event II (0.4007), which has the most even spatial distribution, and for the temporal simulation the lowest RMSE is found with event I (1.0218), which has the most even temporal distribution. The most difficult to reproduce are found to be the very convective storms with uneven spatiotemporal distributions (type 4 event), and the average relative error for the cumulative rainfall amounts is up to 66.37 %. The RMSE results of event III, with the most uneven spatial and temporal distribution, are 0.9688 for the spatial simulation and 2.5327 for the temporal simulation, which are much higher than the other storms. The general performance of the current WRF physical parameterizations is discussed. The Betts–Miller–Janjic (BMJ) scheme is found to be unsuitable for rainfall simulation in the study sites. For type 1, 2 and 4 storms, member 4 performs the best. For type 3 storms, members 5 and 7 are the better choice. More guidance is provided for choosing among the physical parameterizations for accurate rainfall simulations of different storm types in the study area.

A spatio-temporal evaluation of the WRF physical parameterisations for numerical rainfall simulation in semi-humid and semi-arid catchments of Northern China

Mesoscale Numerical Weather Prediction systems can provide rainfall products at high resolutions in space and time, playing an increasingly more important role in water management and flood forecasting. The Weather Research and Forecasting (WRF) model is one of the most popular mesoscale systems and has been extensively used in research and practice. However, for hydrologists, an unsolved question must be addressed before each model application in a different target area. That is, how are the most appropriate combinations of physical parameterisations from the vast WRF library selected to provide the best downscaled rainfall? In this study, the WRF model was applied with 12 designed parameterisation schemes with different combinations of physical parameterisations, including microphysics, radiation, planetary boundary layer (PBL), land-surface model (LSM) and cumulus parameterisations. The selected study areas are two semi-humid and semi-arid catchments located in the Daqinghe River basin, Northern China. The performance of WRF with different parameterisation schemes is tested for simulating eight typical 24-h storm events with different evenness in space and time. In addition to the cumulative rainfall amount, the spatial and temporal patterns of the simulated rainfall are evaluated based on a two-dimensional composed verification statistic. Among the 12 parameterisation schemes, Scheme 4 outperforms the other schemes with the best average performance in simulating rainfall totals and temporal patterns; in contrast, Scheme 6 is generally a good choice for simulations of spatial rainfall distributions. Regarding the individual parameterisations, Single-Moment 6 (WSM6), Yonsei University (YSU), Kain-Fritsch (KF) and Grell-Devenyi (GD) are better choices for microphysics, planetary boundary layers (PBL) and cumulus parameterisations, respectively, in the study area. These findings provide helpful information for WRF rainfall downscaling in semi-humid and semi-arid areas. The methodologies to design and test the combination schemes of parameterisations can also be regarded as a reference for generating ensembles in numerical rainfall predictions using the WRF model.

Surface Runoff of Pesticides from a Clay Loam Field in Sweden.

Pesticides stored at or close to the soil surface after field application can be mobilized and transported off the field when surface runoff occurs. The objective of our study was to quantify the potential pesticide losses in surface runoff from a conventionally managed agricultural field in a Swedish climate. This was achieved by measuring surface runoff volumes and concentrations in runoff of six spring-applied pesticides and autumn-applied glyphosate and its metabolite aminomethylphosphonic acid (AMPA). Measurements were performed for 3 yr both during the growing seasons and during intervening winter snowmelt periods on a clay loam field close to Uppsala. During growing seasons, surface runoff was generated on only five occasions during one 25-d period in 2012 when the infiltration capacity of the soil may have been reduced by structural degradation due to large cumulative rainfall amounts after harrowing. Concentrations in surface runoff exceeded Swedish water quality standards in all samples during this growing season for diflufenican and pirimicarb. Surface runoff was generated during three snowmelt periods during the winter of 2012-2013. All of the applied pesticides were found in snowmelt samples despite incorporation of residues by autumn plowing, degradation, and leaching into the soil profile during the period between spraying and sampling. Concentrations of glyphosate ranged from 0.12 to 7.4 μg L, and concentrations of AMPA ranged from 0 to 2.7 μg L. Our results indicate that temporal changes in hydraulic properties during the growing season and when the soil freezes during winter affect pesticide losses through surface runoff.

Revisiting storm runoff processes in the upper Blue Nile basin: The Debre Mawi watershed

There is a scientific knowledge gap in locating runoff producing areas and their spatial variation in the landscape of the Ethiopian highlands and the upper Blue Nile basin. Identification of these spatial variations and runoff generation mechanisms is needed for optimum implementation of conservation measures. In many cases poor performance of soil and water conservation practices for erosion control can be traced back to non-optimum placement. A 95ha watershed in the headwaters of the Blue Nile basin was used to investigate the runoff processes using the 2010 and 2011 monsoon, precipitation and runoff measurements made at sub-watersheds and watershed outlets. Perched water table heights and infiltration rates were also recorded. With the median infiltration rate exceeded by the rainfall intensity only 3% of the time the dominant runoff generation mechanism is found to be a saturation excess runoff process. Using the saturation excess interpretation of the Natural Resources Conservation Service Curve Number method, the seven day cumulative runoff fits better to the input as 7-day cumulative effective rainfall amount than to the rainfall intensity. In a monsoon climate where the watershed is dry at the onset of the rainfall, the saturated areas and the runoff coefficients varied in the landscape (upslope locations vs downslope locations) as the rainy season progresses and available water storage adjusts.

Variabilities in Rainfall Onset, Cessation and Length of Rainy Season for the Various Agro-Ecological Zones of Ghana

This paper examines the onset and cessation dates of the rainy season over Ghana using rain gauge data from the Ghana Meteorological Agency (GMet) over the period of 1970–2012. The onset and cessation dates were determined from cumulative curves using the number of rainy days and rainfall amount. In addition, the inter-annual variability of the onset and cessation dates for each climatic zone was assessed using wavelet analysis. A clear distinction between the rainfall characteristics and the length of the rainy season in the various climatic zones is discussed. The forest and coastal zones in the south had their rainfall onset from the second and third dekads of March. The onset dates of the transition zone were from the second dekad of March to the third dekad of April. Late onset, which starts from the second dekad of April to the first dekad of May, was associated with the savannah zone. The rainfall cessation dates in the forest zone were in the third dekad of October to the first dekad of November, and the length of the rainy season was within 225–240 days. The cessation dates of the coastal zone were within the second and third dekad of October, and the length of rainy season was within 210–220 days. Furthermore, the transition zone had cessation dates in the second to third dekad of October, and the length of the rainy season was within 170–225 days. Lastly, the savannah zone had cessation dates within the third dekad of September to the first dekad of October, and the length of rainy season was within 140–180 days. The bias in the rainfall onset, cessation and length of the rainy season was less than 10 days across the entire country, and the root mean square error (RMSE) was in the range of 5–25 days. These findings demonstrate that the onset derived from the cumulative rainfall amount and the rainy days are in consistent agreement. The wavelet power spectrum and its significant peaks showed evidence of variability in the rainfall onset and cessation dates across the country. The coastal and forest zones showed 2–8- and 2–4-year band variability in the onsets and cessations, whereas the onset and cessation variability of the transition and savannah zones were within 2–4 and 4–8 years. This result has adverse effects on rain-fed agricultural practices, disease control, water resource management, socio-economic activities and food security in Ghana.