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The US Department of Agriculture (USDA), Soil Conservation Services (SCS) rainfall-runoff model has been applied worldwide since 1954 and adopted by Malaysian government agencies. Malaysia does not have regional specific curve numbers (CN) available for the use in rainfall-runoff modelling, and therefore a SCS-CN practitioner has no option but to adopt its guideline and handbook values which are specific to the US region. The selection of CN to represent a watershed becomes subjective and even inconsistent to represent similar land cover area. In recent decades, hydrologists argue about the accuracy of the predicted runoff results from the model and challenge the validity of the key parameter, initial abstraction ratio coefficient (λ) and the use of CN. Unlike the conventional SCS-CN technique, the proposed calibration methodology in this chapter discarded the use of CN as input to the SCS model and derived statistically significant CN value of a specific region through rainfall-runoff events directly under the guide of inferential statistics. Between July and October of 2004, the derived λ was 0.015, while λ = 0.20 was rejected at alpha = 0.01 level at Melana watershed in Johor, Malaysia. Optimum CN of 88.9 was derived from the 99% confidence interval range from 87.4 to 96.6 at Melana watershed. Residual sum of square (RSS) was reduced by 79% while the runoff model of Nash–Sutcliffe was improved by 233%. The SCS rainfall-runoff model can be calibrated quickly to address urban runoff prediction challenge under rapid land use and land cover changes.

The purpose of this paper is to estimate quick and low-cost processes for surface runoff potential on the basis of natural environmental attributes.

An approach based on the natural environmental attributes and on the Cook’s method was used for maximal peak flows of surface runoff, as well as for assigning weights to the considered attributes. Used attributes are as follow: steepness, bedrock (lithology), soil (texture, genesis, thickness, and permeability coefficient), drainage density, and favorable features to surface storage.

Using natural environmental attributes from previous available studies, adapted from different scales, the authors obtain a low-cost potential surface runoff chart, which can be useful for planning, impact and hazard analysis, and decision purposes in an area without large financial resources, like small communities in developing countries. Despite the common scarcity of data in these communities, often regional basic studies of soil and bedrock are available, making this kind of analysis possible.

The highlights are quick and low-cost procedures in characterizing the natural environment for planning activities, providing the basis for further detailing, which focus on solving local problems. This approach to runoff estimation allows for the definition of the criteria, considering the potential geodynamic processes. Thus, this kind of study may be very useful for land use planning in developing countries.

The purpose of this paper is to investigate the effects of extreme weather conditions on runoff, nutrient, and soil loss from agriculture‐dominated catchments at different locations in Norway.

Four catchments have been selected to study the potential effects of climate change on runoff and nutrient loss. The catchments are part of the Agricultural Environmental Monitoring Programme in Norway (JOVA) and represent different climatological conditions, agricultural production systems/practices, and soil types. Different characteristics were calculated on the basis of existing measurements and evaluated with respect to climate change.

In four selected catchments, climate change is predicted to lead to an increase in runoff. Under similar land use and tillage methods, this will most likely lead to an increase in nutrient and soil loss. Milder winters as a consequence of climate change might lead to extreme runoff conditions and severe erosion, caused by a combination of frozen soil, snowmelt, and intense rainfall. Existing large diurnal variations in discharge have to be taken into consideration in the future design of hydrotechnical implementations. Information about the potential effects of climate change on runoff generation, the magnitude of the different hydrological flow paths, and their potential effects on nutrient and soil loss processes is necessary in choosing the right mitigation measures.

Long time series on runoff and water quality (such as those collected in small agriculture‐dominated catchments as part of the Agricultural Environmental Monitoring Programme in Norway (JOVA)) are rare, but indispensable in evaluating the potential effects of climate change on nutrient and soil loss.

An attempt is made to produce a susceptibility surface runoff hazard map for Kuwait by integrating four maps: paleodrainage; topography; vegetation cover (extracted from a Landsat image of 2001); and soil.

Local expert knowledge, weighting methods like the Delphi method and the analytical hierarchy process (AHP), and GIS techniques were used to evaluate the factors controlling surface runoff hazard in Kuwait.

The susceptibility surface runoff hazard map produced indicates that a moderate class of surface runoff hazard in Kuwait averages 45.5 percent, followed by a low class (21 percent). The very low, high and very high classes constitute about 8, 18.5 and 15 percent, respectively.

The surface hazard map obtained from this study may be presented to the authorities concerned to be used as basic data for designing runoff flood prevention and mitigation measures.

The approach adopted in this study is new to Kuwait.

This study aims to use porous concrete and mineral adsorbents (additives) for reducing the quantity and improving the quality of urban runoff.

The effects of adding mineral adsorbents and fine grains to porous concrete is tested for increasing its performance in improving the quality of urban runoff. Two levels of sand (10 and 20 per cent) and 5, 10 and 15 per cent of zeolite, perlite, LECA and pumice were added to the porous concrete. Unconfined compressive strength, hydraulic conductivity (permeability) and porosity of the porous concrete specimens were measured. Some of the best specimens were selected for testing the improvement of runoff quality. A rainfall simulator was designed and the quality of the runoff was investigated for changes in electrical conductivity (EC), total suspended solids (TSS), total dissolved solids (TDS) and chemical oxygen demand (COD).

The results of this study showed that compressive strength of the porous concrete was increased by adding fine grains to the concrete mixture. Fine grains decreased the permeability and porosity of the samples. Zeolite had the highest compressive strength. Samples having pumice own maximum permeability. Samples which had perlite, had the least compressive strength and permeability. Because of the fast flow of runoff water in the porous slab and its low thickness, sufficient time was not provided for effective functioning of the additives, and the removal percentage of the pollution parameters was low.

Porous concrete can ameliorate both quantity and quality of the urban runoff.

Rainfall–runoff relationship is one of the most complex hydrological phenomena. A conventional neural network (NN) with backpropagation algorithm has successfully modelled various non-linear hydrological processes in recent years. However, the convergence rate of the backpropagation NN is relatively slow, and solutions may trap at local minima. Therefore, a new metaheuristic algorithm named as cuckoo search optimisation was proposed to combine with the NN to model the daily rainfall–runoff relationship at Sungai Bedup Basin, Sarawak, Malaysia. Two-year rainfall–runoff data from 1997 to 1998 had been used for model training, while one-year data in 1999 was used for model validation. Input data used are current rainfall, antecedent rainfall and antecedent runoff, while the targeted output is current runoff. This novel NN model is evaluated with the coefficient of correlation (R) and the Nash–Sutcliffe coefficient (E²). Results show that cuckoo search optimisation neural network (CSONN) is able to yield R and E² to 0.99 and 0.94, respectively, for model validation with the optimal configuration of number of nests (n) = 20, initial discovery rate of alien eggs (painitial) = 0.6, hidden neuron (HN) = 100, iteration number (IN) = 1,000 and learning rate (LR) = 1 for CSONND4 model. The results revealed that the newly developed CSONN is able to simulate runoff accurately using only precipitation and runoff data.

The purpose of this paper is to investigate the application of water harvesting techniques as a sustainability measure of the cropping system for barley production in the Fa'a farming area located in the Northern part of Jordan.

Usually, the farmers plant barley to feed their animals. The climate of the area is semi‐arid to arid. Annual average rainfall in the area is not enough for the survival of barley and farmers are usually grassing barley instead of harvesting. Overgrazing and mismanagement contribute to land degradation in the area, which affect the production system in the area.

The paper investigates the runoff collection system which is framed with two different sizes in three different land uses: cultivated with barley; fallow and rangeland. Data are collected in all of five stormy events. The total soil sediment is measured for these land uses. The amount of water collected from runoff is also measured for the same areas. The ploughing against the slope with planting barley can reduce the runoff and soil sediment increasing soil moisture and reducing soil erosion. The barley production as biomass is highest using strip cropping as opposed to zero ratio control site or conventional cultivation. The plants' lengths were also higher in strip cropping ranging between 26 and 28 centimetres in the different strip cropping ratios compared to 23 centimetres in the conventional cropping system.

By using the results from this new research to such an area, surface runoff from the uncultivated land can be used to supplement the rainfall to the cultivated land. This increases the share of runoff on the cultivated land to the degree where barley can be harvested.

The purpose of this paper is to assess the scale of changes in the distribution of water and their influence on the components of the hydrological balance in two lake catchments situated in the Leczna-Wlodawa Lake District.

In order to estimate the scale of man-made modification of water distribution an analysis of published cartographic materials was used. The maps cover time-scale of over 150 years. The analysis was completed by territorial research carried out during water years 2007-2009. The elements of water balance equation were calculated on the basis of daily water levels, discharge, precipitations and lake volumes. Evaporation was calculated as the difference of balance gains and losses (runoff deficit).

The study has shown high permanent human pressure on lake-catchment systems under study, since the 50 of the nineteenth century. Naturally drainless lakes were connected to the system of surface runoff, which modified radically directions and pace of water circulation. The most pronounced hydrologic changes of the lake-catchment systems under study occurred in the 60 of the twentieth century. Human pressure on water conditions resulted in changes of water balance elements relation (increased surface inflow and outflow).

In the ecosystems with zonal watersheds, even slight modification of water distribution may lead to radical changes in the structure of lake-catchment systems’ water balance. The paper is first in polish literature that documents major water divide translocation, as well as bifurcation in the drainage area of the highest cascade lake. Man-made modifications cause natural ecosystems degradation, especially in the areas built with peat-bogs.

Recent advances in hydrological impact studies point that the response of specific catchments to climate change scenario using a single model approach is questionable. This study was aimed at investigating the impact of climate change on three river basins in China, Ethiopia and Norway using WASMOD and HBV hydrological models.

First, hydrological models' parameters were determined using current hydro‐climatic data inputs. Second, the historical time series of climatic data was adjusted according to the climate change scenarios. Third, the hydrological characteristics of the catchments under the adjusted climatic conditions were simulated using the calibrated hydrological models. Finally, comparisons of the model simulations of the current and possible future hydrological characteristics were performed. Responses were evaluated in terms of runoff, actual evapotranspiration and soil moisture change for incremental precipitation and temperature change scenarios.

From the results obtained, it can be inferred that two equally well calibrated models gave different hydrological response to hypothetical climatic scenarios. The authors' findings support the concern that climate change analysis using lumped hydrological models may lead to unreliable conclusions.

Extrapolation of driving forces (temperature and precipitation) beyond the range of parameter calibration yields unreliable response. It is beyond the scope of this study to reduce this model ambiguity, but reduction of uncertainty is a challenge for further research.

The research was conducted based on the primary time series data using the existing two hydrological models to test the magnitude differences one can expect when using different hydrological models to simulate hydrological response of climate changes in different climate zones.

Since surface runoff clogs stormwater grates, leading to deterioration of drainage capacity, and also it is difficult to complete the study with actual dimensions in experiments, a numerical simulation work was established in this study to investigate the surface runoff clogging stormwater grate patterns. The purpose of this study is to describe the mechanisms of storm grate clogging and storm well deposition for different flow rate floods and granular materials.

In the work of this study, the volume of fluid (VOF) method and the discrete element method (DEM) are used to solve the gas–liquid and particle flows. In order to solve the evolution of the gas–liquid interface during surface runoff, the VOF was used. To simulate the rain grate and set up different material particles to represent the surface floating materials, the DEM was utilized.

The research results show that the clogging distribution and clogging rate of the rainwater grate are closely related to the fluid flow velocity and the physical characteristics of the particles, and the higher the clogging rate of the rainwater grate and the higher the number of particles deposited in the rainwater well at the same surface runoff velocity, the higher the density of the clogged particles. The surface runoff velocity (0.5 m/s, 1 m/s) shows that the rapid change of particle movement state at high runoff velocity makes the particle clogging more obvious.

A multi-scale CFD-DEM approach was used to simulate the particulate motion of the road surface with different incoming runoff velocities. The innovative use of DEM to model the storm grate simulation ensures the accuracy of the traction model.