Function Of Rainfall Research Articles

Use of The Zero Run-Off System to Minimaze of Surface Run Off on Cacao Land

The decline quality of land of cocoa plantations mainly due to erosion by run off. The application of the Zero Run-off system can reduce rill erosion by eliminating surface runoff. The study was conducted to get the dimensions and layout of the system of Zero Run-Off is effective in improving infiltration so there is no runoff. Dimensions of the system is designed using the water balance approach, where all runoff accommodated in the zero Run- off system then infiltrated. Surface runoff calculated by the method of the Soil Conservation Service (SCS). Potential rate of water inflow into the soil is a function of the saturated hydraulic conductivity of the soil and the surface area of the system. Soil hydraulic conductivity is determined by the falling head method. Dimensions of the system known through a simulation model based on the physical condition data of field using a dynamic model. The simulation results show that the dimensions of the system are required to enter the entire runoff into the ground in the form of infiltration is a function of rainfall, catchment area and the soil saturated hydraulic conductivity. Using this data, the dimensions and position of the systems zero run-off can be determined accurately. For the conditions of research sites, the whole wet surface area of the system at 5 x 106 mm2 per m2. With a broad measure of the volume of water present in the systems of 0 to 0.0000055 m3, so that the system depths of 1,000 mm, then there is no runoff occurs.

Climate change and food security in EAC region: a panel data analysis

PurposeThis study aims to analyze the impact of global climate change on food security in the East African Community (EAC) region, using panel data analysis for five countries, over 2000-2014.Design/methodology/approachThe determinants of food security are expressed as a function of rainfall, temperature, land area under cereal production, and population size. The paper used pooled fixed effects to estimate the relationship among these variables.FindingsFindings show that food security in EAC is adversely affected by temperature. However, precipitation and increasing areas cultivated with cereal crops will be beneficial to ensure everyone's food security.Originality/valueActions for mitigating global warming are important for EAC to consolidate the region’s economic, political and social development/stability.

Tropical tree cover in a heterogeneous environment: A reaction-diffusion model.

Observed bimodal tree cover distributions at particular environmental conditions and theoretical models indicate that some areas in the tropics can be in either of the alternative stable vegetation states forest or savanna. However, when including spatial interaction in nonspatial differential equation models of a bistable quantity, only the state with the lowest potential energy remains stable. Our recent reaction-diffusion model of Amazonian tree cover confirmed this and was able to reproduce the observed spatial distribution of forest versus savanna satisfactorily when forced by heterogeneous environmental and anthropogenic variables, even though bistability was underestimated. These conclusions were solely based on simulation results for one set of parameters. Here, we perform an analytical and numerical analysis of the model. We derive the Maxwell point (MP) of the homogeneous reaction-diffusion equation without savanna trees as a function of rainfall and human impact and show that the front between forest and nonforest settles at this point as long as savanna tree cover near the front remains sufficiently low. For parameters resulting in higher savanna tree cover near the front, we also find irregular forest-savanna cycles and woodland-savanna bistability, which can both explain the remaining observed bimodality.

A Generalized Analytical Solution for Preferential Infiltration and Wetting

Core Ideas New model simulates relative infiltration and wetting depth due to preferential flow. Solution normalizes parameters to account for soil properties and initial conditions. Preferential flow estimations match closely with dual‐permeability HYDRUS‐1D results. Preferential flow wetting depths decrease as volume of macropore domains increase. Model provides new insight into preferential flow dynamics during rainfall events. Macropores induce preferential flow in many soils, creating the need for parsimonious solutions to describe nonequilibrium infiltration and wetting processes. This study applied the Green–Ampt infiltration model within a dual‐domain framework to distinguish water movement through the soil matrix vs. through macropores. Using a nondimensional parameter set to generalize the results, the developed equations enabled estimates of infiltration and depth of wetting due to preferential flow during constant‐intensity rain. The analysis revealed that infiltration partitioning varies with time, with flow regimes changing at time of ponding of the matrix and again at time of ponding in the macropores. The results also showed that the fraction of infiltration due to preferential flow increases as a function of rainfall and relative volume of the macropore domain. Conversely, macropore volume has an inverse relationship with wetting depth: all other factors being equal, infiltration due to preferential flow becomes proportionally greater than matrix infiltration as macropore volume decreases. Finally, the proposed infiltration and wetting equations were compared with numerical simulations of the Richards equation for dual‐permeability soils. The analytical solutions closely approximated the numerical results, with root mean square deviation values ≤0.15 and simulated wetting depths within 35% of one another, even as modeled times to ponding varied by 5 to 80%. Altogether, the theoretical framework developed in this study provides new insight into preferential flow dynamics during rainfall events.

Grass competition overwhelms effects of herbivores and precipitation on early tree establishment in Serengeti

Abstract Savanna ecosystems span a diverse range of climates, edaphic conditions, and disturbance regimes, the complexity of which has stimulated long‐standing interest in the mechanisms that maintain tree–grass coexistence. One hypothesis suggests that tree establishment is strongly limited by one or several demographic bottlenecks at early stages of the tree life cycle. A major impediment to testing this hypothesis is the lack of data on the relative strengths of different bottlenecks across key environmental gradients. To identify demographic bottlenecks that limit early tree establishment (0–18 months), we conducted a series of transplant experiments with two savanna trees species (Acacia robusta and Acacia tortilis) across a natural rainfall and soil fertility gradient in the Serengeti ecosystem, Tanzania. We tested the interactive effects of precipitation, herbivory, seed scarification, grass competition, water limitation, and tree species identity on two key life stages: germination and early seedling survival (0–2 months), and juvenile seedling survival (2–18 months). Germination and early seedling survival increased as a function of rainfall, in the absence of herbivores and when seeds were scarified. Juvenile seedling survival, in contrast, decreased with rainfall but increased in the absence of herbivores. Grass removal had the single strongest (positive) effect on juvenile seedling survival of any treatment. Soil moisture monitoring and grass‐addition treatments revealed that grasses negatively affected seedlings in ways that were not necessarily linked to soil moisture. A demographic model combining all effects across early life stages showed that the strength of grass competition on juvenile seedling survival was the key factor limiting early tree establishment. While rainfall had an unexpected opposing effect on the two life stages, the net effect of mean annual precipitation on early tree establishment was positive. Synthesis. Successful tree establishment in Serengeti is maximized by a seemingly unlikely sequence of events: (a) scarification of seeds by browsers, (b) heavy rainfall to promote germination, (c) intensive grazing (but absence of browsers), and (d) dry conditions during juvenile seedling growth (>2 months) to reduce competition with grasses. By considering a wide suite of conditions and their interactions, our experimental results are relevant to ongoing debates about savanna vegetation dynamics and structural shifts in tree:grass ratios.

Impact of Boreal Summer Intraseasonal Oscillation on Rainfall Extremes in Southeastern China and its Predictability in CFSv2

AbstractThe boreal summer intraseasonal oscillation (BSISO) is one of the dominant modes of intraseasonal variability of the tropical climate system, which has prominent northward propagation extending much further from the equator. The impacts of BSISO on extreme rainfall in eastern China were studied using the BSISO indices and daily rainfall data in China. We revealed that the responses of extreme rainfall to BSISO activity in eastern China are not spatially uniform. Under the influences of BSISO1, the probability‐distribution functions of rainfall in two southeastern China subregions: South China and Yangtze River Valley significantly skew toward larger values, respectively, in phases 4 and 8, and phases 3 and 4 with the probability of 90th extremes increased by 35–45% relative to May–August rainfall probability‐distribution function, showing southward propagation with the speed of 1.96°/phase. Under the BSISO2, the probability of the 90th extremes increased more than 40% in South China and Yangtze River Valley, respectively, during phases 4–5 and phases 6–7, showing northward propagation with a speed of 2.75°/phase. Physical analysis showed that the increased probability of extreme rainfall is associated with intensifying moisture convergence and upward moisture transport during BSISO active phases. The hindcasts from the Climate Forecast System version 2 have been used to evaluate the modulations of BSISO on extreme rainfall and associated predictability. It was shown that the Climate Forecast System version well reproduces the modulations of BSISO on extreme rainfall within 2 weeks. These results demonstrate the feasibility to develop medium‐to‐extended‐range probabilistic forecasts of extreme rainfall for southeastern China.

How will East African maize yields respond to climate change and can agricultural development mitigate this response?

We analyze the response of Kenyan maize yields to near-term climate change and explore potential mitigation options. We model county level yields as a function of rainfall and temperature during a period of increased regional warming and drying (1989–2008). We then do a counter factual analysis by comparing existing maize yields from 2000 to 2008 to what yields might have been if observed warming and drying trends had not occurred. We also examine maize yields based on projected 2026–2040 climate trends. Without the observed warming and drying trends, Eastern Kenya would have had an 8% increase in maize yields, which in turn would have led to a net production increase of 500,000 metric tons. In Western Kenya, the magnitude of change is higher but the relative changes in predicted values are smaller. If warming and drying trends continue, we expect future maize yields to decline by 11% in Eastern Kenya (vs. 7% in Western Kenya). We also examine whether these future losses might be offset through agricultural development. For that analysis, we use a household panel dataset (2000, 2005) with measurements of individual farm plot yields, inputs, and outputs. We find that under a scenario of aggressive adoption of hybrid seeds and fertilizer usage coupled with warming and drying trends, yields in Western Kenya might increase by 6% while those in Eastern Kenya could increase by 14%. This increase in yields might be larger if there is a corresponding increase in usage of drought-tolerant hybrids. However, wide prediction intervals across models highlight the uncertainty in these outcomes and scenarios.

Modeling response of runoff and evapotranspiration for predicting water table depth in arid region using dynamic recurrent neural network

The investigation of the dynamic response of aquifer to rainfall with variation of the atmospheric conditions is a key issue for groundwater resource management. A data-driven dynamic recurrent neural network approach, based on multi-objective optimization is used here to forecast groundwater levels as a function of rainfall, temperature, humidity, runoff and evapotranspiration data. Recurrent Neural Network (RNN) with variable transfer functions like tangential sigmoidal, purelin and logarithmic sigmoidal are used to compute the relative performance of the model. The results demonstrate the transition behavior due to changing evapotranspiration and runoff. Statistical and graphical indicators are used to compare the results. The statistical indicators used in this work are Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R2). From the results, evapotranspiration loss and run off are the influencing parameters which affect the depth to water table in the ground water reservoir. It is observed that calculated losses due to evapotranspiration are comparatively less during high precipitation in the Rengali province. Results of R2 suggest that inclusion of evapotranspiration and runoff in different scenario improves the model efficiency in predicting water table depth.

The Impact of Income Distribution and Agricultural Credit Facilities on Rural-Urban Migration

The Impact of Income Distribution and Agricultural Credit Facilities on Rural-Urban Migration

Topography reconstruction of eroding landscapes – A case study from a hummocky ground moraine (CarboZALF-D)

Erosion processes, aggravated by human activity, have a large impact on the spatial variation of soil and topographic properties. Knowledge of the topography prior to human-induced erosion (paleotopography) in naturally stable landscapes is valuable for identifying vulnerable landscape positions and is required as starting point for erosion modelling exercises. However, developing accurate reconstructions of paleotopography provide a major challenge for geomorphologists. Here, we present a set of paleotopographies for a closed kettle hole catchment in north-east Germany (4ha), obtained through different reconstruction approaches. Current soil and colluvium thickness, estimated from a dataset of 264 soil descriptions using Ordinary Kriging, were used as input for a mass balance, or were compared with a set of undisturbed soil thicknesses to estimate the amount of erosion. The performance of the different approaches was assessed with cross-validation and the count of mispredicted eroded, depositional or stable landscape positions.The paleotopographic reconstruction approach based on the average thickness of undisturbed soils in the study area showed the best performance. This thickness (1.00m) is comparable to the average undisturbed soil thickness in the region and in line with global correlations of soil thickness as a function of rainfall and initial CaCO3 content. The performance of the different approaches depended more on mispredictions of landscape position due to the assumption of a spatially constant initial soil depth than on small variations in this depth. To conclude, we mention several methodological and practical points of attention for future topography reconstruction studies, concerning data quality and availability, spatial configuration of data and other processes affecting topography.

Analyzing the Mara River Basin Behaviour through Rainfall-Runoff Modeling

Hydrological models are considered as necessary tools for water and environmental resource management. However, modelling poorly gauged watersheds has been a challenge to hydrologists and hydraulic engineers. Research done recently has shown the potential to overcome this challenge through incorporating satellite based hydrological and meteorological data in the measured data. This paper presents results for a study that used the semi-distributed conceptual HBV Light Model to model the rainfall-runoff in the Mara River Basin, Kenya. The model simulates runoff as a function of rainfall. It is built on the basis established between satellite observed and in-situ rainfall, evaporation, temperature and the measured runoff. The model’s performance and reliability were evaluated over two sub-catchments namely: Nyangores and Amala in the Mara River Basin using the Nash-Sutcliffe Efficiency which the model referred to as Reff and the coefficient of determination (R2). The Reff for Nyangores and Amala during the calibration and (validation) period were 0.65 (0.68) and 0.59 (0.62) respectively. The model showed good flow simulations particularly during the recession flows, in the Nyangores sub-catchment whereas it simulated poorly the short term fluctuations of the high-flow for Amala sub-catchment. Results from this study can be used by water resources managers to make informed decision on planning and management of water resources.

Host genus and rainfall drive the population dynamics of a vascular epiphyte

AbstractVascular epiphytes constitute up to 25% of tropical plant diversity and play an important role in providing food, water, and shelter to many organisms. However, the factors that drive their population dynamics, including the influence of their host plants (phorophytes) and of climatic factors, are still poorly understood. We provide the first test of whether host tree genus can affect population dynamics of an epiphytic species, and assess the interactive effects of host tree and rainfall. We carried out a five‐year study of the demography of >1000 plants of the endemic bromeliad, Tillandsia macdougallii L. B. Sm, growing on pine and oak trees in a Mexican montane forest. We tested for differences in vital rates and used integral projection models to test whether these scaled up to differences in long‐term population growth rates between the two host genera and as a function of rainfall. T. macdougallii survival and growth were higher on pines than on oaks for larger plants but not for seedlings. The probability of producing capsules was higher for T. macdougallii on oaks than on pines. Increasing dry season rainfall was significantly correlated with increased survival of individuals, but not of ramets, growing on both oaks and pines. The probability of clonal reproduction increased significantly with increasing dry season rainfall for T. macdougallii growing on oaks, but not on pines. Projected long‐term population growth rates, λ, for T. macdougallii on pines were higher than on oaks. Lambda increased steeply as a function of dry season rainfall for T. macdougallii populations on both host tree genera, but the increase was steeper for populations on oaks, likely because the former are deciduous. Our results show that host tree genus can affect the long‐term dynamics of epiphyte populations and suggest that these effects may depend on rainfall. The high sensitivity of this species to changes in dry season rainfall suggests that a better understanding of how rainfall may drive vascular epiphyte populations will be critical for understanding the effects of climate change on species persistence.

Observations and analytical modeling of freshwater and rainwater lenses in coastal dune systems

Observations are reported on (i) groundwater recharge rates under various types of vegetation as measured with megalysimeters in the dunes, (ii) freshwater lenses along the Dutch North Sea coast in the early 1900s, and (iii) rainwater lenses that develop on top of laterally migrating, artificially recharged riverwater. Subsequently analytical methods are presented to estimate annual natural groundwater recharge as function of rainfall and vegetation, and to calculate the size, shape and transition zone of freshwater lenses on saline groundwater and rainwater lenses on infiltrated riverwater. An empirical correction factor, based on the hydraulic resistance of an aquitard within the freshwater lens, is proposed to account for the frequently observed reduction of the Ghyben-Herzberg ratio of 40. This factor raises the groundwater table, reduces the depth of the fresh/salt interface and increases the lens formation time. The suite of methods offers a tool box for knowledge based water management of dune systems, by rapidly predicting: (i) more or less autonomous changes due to sealevel rise, climate change and vegetation development; and (ii) the potential (side) effects of interventions. Knowing what happened or will happen to the fresh water lens or a rainwater lens is important, because changes impact on important natural habitat parameters such as salinity, depth to groundwater table, decalcification rate (and thus on pH, Ca/Al, PO4, NH4) and nutrient availability, and on drinking water supply. The analytical models are applied to predict effects of sealevel rise, coastal progradation, vegetation changes, and increased temperature of coastal air and river water to be infiltrated.

Practical Method for Estimating Time-Dependent Corrosion Depth of Uncoated Carbon Steel Plates under Various Atmospheric Environmental Conditions Using Fe/Ag Galvanic Couple Corrosion Sensor

In this research, an evaluation method for the time-dependent corrosion depth of uncoated structural steel plates using an Fe/Ag galvanic couple atmospheric corrosion monitoring (ACM)-type sensor was proposed. This method was focused on environments with and without effects of rainfall and airborne sea salt. Atmospheric exposure tests were carried out on the uncoated carbon steel plates in four sites in which the environments varied widely as a function of rainfall and airborne sea salt. In addition to this, the corrosive environments of the skyward-and groundward-facing surfaces of the plates were monitored using the ACM sensors.

Stochastic modelling of the hydraulic performance of an onsite rainwater harvesting system in Mediterranean climate

The performance of onsite rainwater harvesting (RWH) system in Mediterranean climate was assessed. A stochastic model quantifying the necessary storage, as a function of rainfall (frequency, depth), roof area, residents’ number, specific water use (toilet flushing, laundry) and the required efficiency was developed. Two performance indicators were calculated: water saving efficiency (RSE) – proportion of water used supplied by the RWH system; and rainwater use efficiency (RUE) – proportion of rainwater actually used. The maximum storage capacity and WSE decreased with increasing number of residents for a given roof area, and with an increasing roof area for constant number of residents. For variable storage volume, RUE increased with increasing storage capacity and reached a maximum with an increase in residents’ number and a decrease in the roof area. The model enables to determine WSE and RUE for specific storage volumes or to determine the desired WSE and calculate the necessary storage.

Statistical model for economic damage from pluvial floods in Japan using rainfall data and socioeconomic parameters

Abstract. The assessment of flood risk is important for policymakers to evaluate damage and for disaster preparation. Large population densities and high property concentration make cities more vulnerable to floods and having higher absolute damage per year. A number of major cities in the world suffer from flood inundation damage every year. In Japan, approximately USD 1 billion in damage occurs annually due to pluvial floods only. The amount of damage was typically large in large cities, but regions with lower population density tended to have more damage per capita. Our statistical approach gives the probability of damage following every daily rainfall event and thereby the annual damage as a function of rainfall, population density, topographical slope and gross domestic product. Our results for Japan show reasonable agreement with area-averaged annual damage for the period 1993–2009. We report a damage occurrence probability function and a damage cost function for pluvial flood damage, which makes this method flexible for use in future scenarios and also capable of being expanded to different regions.

Quantifying spatiotemporal drivers of environmental heterogeneity in Kruger National Park, South Africa

Environmental heterogeneity is considered an important mechanism of biodiversity. How environmental heterogeneity is characterised by the compositional, structural and functional variation of biotic and abiotic components is a central research theme in conservation. We explore how environmental heterogeneity relates to the underlying physical landscape template and how that relationship changes over space and time. We examine how, in some areas, environmental heterogeneity may also be driven by dynamic ecological processes, and how this relates to patterns of plant species richness. We use local geographically weighted regression to spatially partition environmental heterogeneity, measured as Landsat spectral variance, into the portion explained by stable physical landscape properties (R2) and the portion unexplained (1−R2) which we term landscape complexity. We explore how this relationship varies spatially and temporally as a function of dynamic ecological processes such as rainfall and season in Kruger National Park, as well as plant species richness at landscape scales. The significance and direction of relationships varied over space and time and as a function of rainfall and season. R2 values generally decreased in higher rainfall summer months and revealed patterns describing the importance of known stable factors relative to unknown dynamic factors. Landscape complexity (1−R2) explained over 70 % of variation in species richness. Rainfall and seasonality are important drivers of environmental heterogeneity. The spatial arrangement and magnitude of model agreement helped disentangle the relative influence of the physical landscape template on environmental heterogeneity. Given the high correlation with species richness, landscape complexity provides complementary guidance to biodiversity research and monitoring prioritization.

Washoff of Residual Photosystem II Herbicides from Sugar Cane Trash under a Rainfall Simulator.

Herbicides are often applied to crop residues, but their fate has not been well studied. We measured herbicide washoff from sugar cane trash during simulated rainfall, at 1, 8, and 40 days after spraying (DAS), to provide insight into herbicide fate and for use in modeling. Herbicides included are commonly used in the sugar industry, either in Australia or in Brazil. Concentrations of all herbicides and applied Br tracer in washoff declined exponentially over time. The rate of washoff during rainfall declined with increasing DAS. Cumulative washoff as a function of rainfall was similar for most herbicides, although the most soluble herbicides did have more rapid washoff. Some but not all herbicides became more resistant to washoff with increasing DAS. Of the total mass washed off, 80% washed off in the first 30 mm (∼40 min) of rainfall for most herbicides. Little herbicide remained on the trash after rainfall, implying nearly complete washoff.

Modeling of river flow rate as a function of rainfall and temperature using response surface methodology based on historical time series

In the present paper we propose a new model of monthly river flow rate as a simple nonlinear function of air temperature and rainfall. Response surface methodology is used to analyze the observed monthly flow rates from 1950 to 1990 for Great Morava River, as the largest domestic river in Serbia. Obtained results indicate significant linear and quadratic effect of both individual factors, while two-factor interactions show significantly smaller influence, indicating occurrence of maximum flow rate for low temperature and high rainfall regime. Statistical reliability of the proposed model is verified by internal and external validation, the latter of which included comparison of predicted and observed values from 1991 to 2012. It is shown that predicted flow rates exhibit a similar statistical pattern as observed ones, with a satisfying value of Nash–Sutcliffe coefficient (NSE = 0.73), although the derived model cannot capture well the highest flow rates. Obtained results further indicate the sequence of residuals represents random time series, which is confirmed by appropriate test statistics and surrogate data testing. The advantage of using the derived model for hydrological simulations in river basins instead of existing ones lies in its explicit mathematical form, making it suitable for quick and reliable estimation and prediction of monthly flow rates.

An Integrated Geomechanical Investigation, Multi-Parameter Monitoring and Analyses of Babadağ-Gündoğdu Creep-like Landslide

A creep-like landslide in the Gundogdu district of Babadag town in Denizli (Turkey), where about 2000 people lived within the damaged houses, has been moving with a velocity of 4–14 cm/year since 1940s. Field observations and monitoring together with geomechanical laboratory tests were carried out to investigate the causative factors of the landslide. These studies were conducted as a part of an international research project performed by Turkish and Japanese scientists since 2000. Long-term monitoring stations established involved measurements of meteorological parameters, displacements, acoustic emission counts, variations in groundwater table, borehole strain measurement, in situ permeability and infiltration characteristics of the slope forming materials, and vibrations induced by weaving machines during their operation. Geomechanical properties of the sandstone and marl, which form the unstable slope, were determined from laboratory tests. In addition to the use of conventional 2-D equilibrium method of analyses, a new approach for modelling the long-term creep-like behaviour of the landslide body, based on discrete finite element method, was also proposed and used to analyse the landslide. It was found that the sliding mass has been involving several zones of weakness (interface) between the sandstone and marl layers through in situ monitoring. The monitoring data of pipe strain, groundwater level fluctuation and rainfall, and AE data showed that slope movement accelerated during and after rainy seasons. It was obtained that the proposed numerical method based on discrete finite element method (DFEM), which considers the softening and hardening of stiffness of the weakness zone as a function of rainfall and, is capable of simulating creep-like behaviour of the landslide. Disaster and Emergency Management Authority of Turkey also considered the results of this research and the landslide area was designated as a Natural Disaster Area and the people living in the unstable part of the town were re-settled at a new area.