Evaluation of Pavement Runoff and Driving Safety on Highway Curve Segment

Runoff depth distribution on the concave and circular curve sections is obtained from a two-dimensional numerical simulating model in order to analyze the temporal and spatial variation of the pavement runoff on the curve section. The two-dimensional model verified by the field data can depict the alignment of pavement more accurately as compared to the empirical equation and a one-dimensional model. The runoff on the concave section and circular curve section is compared for the free water drainage and centerline drainage. Results show that a two-dimensional model is essential for the analysis of the centerline drainage. The runoff depth can be controlled by a reasonable curb height and location interval. The drainage type affects the variation of the runoff depth on the nearside lane, and the maximum water depth can be up to more than 80 mm on the concave section and nearly 60 mm on the circular curve section under centerline drainage. Besides the existing hydroplaning results, the runoff depth difference of the wheel trace should be considered to evaluate driving safety. Sideslip will occur when the depth difference becomes more than 6 mm under condition that the runoff depth is less than the tread depth (7 mm). When the runoff depth is more than the tread depth, sideslip will occur once the depth difference exceeds 4 mm.

Hydrological impacts of climate and land-use change on flow regime variations in upper Indus basin

Investigating the effects of climate and land-use changes on surface runoff is critical for water resources management. The majority of studies focused on projected climate change effects on surface runoff, while neglecting future land-use change. Therefore, the main aim of this article is to discriminate the impacts of projected climate and land-use changes on surface runoff using the Soil and Water Assessment Tool (SWAT) through the lens of the Upper Indus Basin, Pakistan. Future scenarios of the land-use and climate changes are predicted using cellular automata artificial neural network and four bias-corrected general circulation models, respectively. The historical record (2000–2013) was divided into the calibration period (2000–2008) and the validation period (2009–2013). The simulated results demonstrated that the SWAT model performed well. The results obtained from 2000 to 2013 show that climate change (61.61%) has a higher influence on river runoff than land-use change (38.39%). Both climate and land-use changes are predicted to increase future runoff depth in this basin. The influence of climate change (12.76–25.92%) is greater than land-use change (0.37–1.1%). Global weather data has good applicability for simulating hydrological responses in the region where conventional gauges are unavailable. The study discusses that both climate and land-use changes impact runoff depth and concluded some suggestions for water resources managers to bring water environment sustainability.

A Study Case on Estimation of Soil Loss and Sediment Yield in Curtin University, Malaysia

Because of human activities, soil erosion has been one of the most concerning issues in Malaysia in the past decades. This study aimed to estimate the amount of soil loss and sediment yield at Curtin University, Malaysia by using the Revised Universal Soil Loss Equation (RUSLE) and the Modified Universal Soil Loss Equation (MUSLE), respectively. The parameters of RUSLE include rainfall erosivity factor (R), soil erodibility factor (K), slope length factor (L), slope steepness factor (S), cover-management factor (C) and support practice factor (P). The rainfall data (10 years) from the Sarawak Meteorological Department was used to determine the R-factor. The K-factor was determined by sieve analysis, hydrometer analysis, the Standard Proctor Test (SPT), and organic content testing. The L-and S-factors were performed by measuring on site and using Google Earth. The C-and P-factors were based on the ground surface cover condition (bare soil in this study). In the MUSLE, the runoff factor comprises V and Qp, while the other parameters are the same as in the RUSLE. The runoff depth, V, is equivalent to the rainfall intensity. Rainfall intensities were recorded by using a rain gauge. The highest rainfall intensity was used for runoff depth. The Rational method has been utilized to calculate Qp. The amount of soil loss estimated was 119.97 tons/ha/year and the sediment yield amount estimated was 0.76 ton/storm event in Curtin University, Malaysia.

Responses of Runoff and Soil Loss on Slopes to Land Use Management and Rainfall Characteristics in Northern China

Soil conservation measures are widely used to control soil erosion and sediment loss; however, their proper usage relies on a deep understanding of the responses of runoff and sediment loss to land management and rainfall characteristics. In the present study, a long-term (2014–2020) monitored dataset derived from ten runoff plots in the upstream catchment of the Miyun Reservoir in Beijing, China, was used to study runoff and sediment loss responses to land use management and rainfall characteristics. The study results show that plots with no soil conservation measures had the highest runoff depth of 75 mm and suffered the highest sediment loss, at a rate of 3200 t km−2 yr−1. The terraced and vegetated plots generated lower runoff depths, with soil loss rates less than 213.0 t km−2 yr−1. With the exception of the contour tillage plots on steep slopes, the vegetation and engineering measures can efficiently reduce runoff and sediment loss, with both runoff and sediment reduction efficiencies higher than 76%. Statistical analyses indicate that, on the plots of bare soil and cultivation without soil conservation measures, runoff and sediment loss were mainly affected by the maximum 30 min rainfall intensity. However, on the plots with soil conservation measures, they were mainly determined by rainfall amount and duration. The sediment loss rate can be well fitted with the runoff depth using a power function. Based on the analyses, water-saving soil conservation measures are recommended for the study area. In addition, the size of terraces should be reconsidered on gentle slopes, and the coverage of forest, shrubs, and grass on slopes should be reduced, thus allowing for more surface runoff generation to ensure drinking water safety. In general, for the study area, soil conservation measures are required on the bare soil and cultivated slopes.

Runoff assessment by Storm water management model (SWMM)- A new approach

The present study investigated the storm wise runoff collected in farm pond with the runoff estimated by Storm Water Management Model (SWMM) and Soil Conservation Service (SCS-CN) models. The SWMM and SCS-CN models estimated runoff depth storm wise. The runoff depths correspond to the catchment area given the runoff volume from the catchment. The runoff depth estimated from the Storm Water Management Model and Soil Conservation Service model was compared against the depth of runoff estimated from the Water balance model. For small rainfall depths, the runoff estimated from the Storm Water Management Model was at par with the actual runoff volume stored at the pond. It is necessary to know the watershed runoff contribution to the river or streams due to rainfall in order to determine environmental risk or flood potential. In larger rainfall depth, the runoff volume estimated from the SWMM model was less than the stored runoff volume at Farm Pond. The Soil Conservation Service Model gave better results for larger rainfall depth compared to Storm Water Management Model. SWMM was able to simulate runoff depth for small rainfall depths of 2mm. The peak runoff depths were produced by rainfall depths of 35.5mm. Initial abstractions of the study area for antecedent moisture content i.e. AMC I, AMCII and AMCIII are 53.2, 23.91 and 10.43mm, respectively. The comparison showed that both SWMM and SCS-CN models gave better runoff quantification results.

Rainfall-Runoff Modeling Using NRCS-CN method and GIS approach

Rainfall-Runoff modeling is a hydrological modeling which is extremely important for water resources planning, development, and management. In this paper, Natural Resource Conservation Service-Curve Number (NRCS-CN) method along with Geographical Information System (GIS) approach was used to evaluate the runoff resulting from the rainfall of four stations, namely, Bilodra, Kathlal, Navavas and Rellawada of Sabarmati River basin. The rainfall data were taken for 10 years (2005-2014). The curve number which is the function of land use, soil and antecedent moisture condition (AMC) was generated in GIS platform. The CN value generated for AMC- I, II and III were 57.29, 75.39 and 87.77 respectively. Using NRCS-CN method, runoff depth was calculated for all the four stations. The runoff depth calculated with respect to the rainfall for Bilodra, Kathlal, Navavas and Rellawada shows a good correlation of 0.96. The computed runoff was compared with the observed runoff which depicted a good correlation of 0.73, 0.70, 0.76 and 0.65 for the four stations. This method results in speedy and precise estimation of runoff from a watershed.

Simulating glacier mass balance in the cross-border Poiqu/Bhotekoshi Basin, China and Nepal

To assess the change of glacier mass balance (GMB) in the Poiqu/Bhotekoshi basin in the context of global warming, this study applied a conceptual Hydrologiska Bryans Vattenbalansavdelning (HBV) hydrological model to quantify the GMB in the area. The HBV model was trained and validated based on in-situ hydro meteorological data from 10 weather stations in the basin. The dataset, which consists of the daily observations for both rainfall and air temperature, was partitioned into two decades, 1988–1998 and 1999–2008 for calibration and validation, respectively. The calibrated model was adopted to restore the daily runoff depth and then estimate the annual changes of GMB in Poiqu/Bhotekoshi basin over the period of 1988–2008. Results show that the Nash–Sutcliffe efficiency coefficient (Reff) of the daily runoff depth simulation after the runoff calibration process was above 0.802. Therefore, the simulated values of the HBV model are reliable and can be used to estimate the GMB of Himalayan cross-border glacial mountain basins with huge elevation difference, and provide scientific data support for water resources management. Furthermore, the result demonstrated a slow year-by-year rise of snow water equivalent because of global warming, and it highly correlates with the soil moisture, the spring temperature and the summer precipitation.

Decomposition and Attribution Analysis of Runoff Alteration of the Dongting Lake in China

The runoff process in the Dongting Lake has been influenced by climate change and human activities in recent decades. To manage the Dongting Lake efficiently and exploit water resources properly under the background of water shortage, it is desired to detect the factors of runoff change in the Dongting Lake. Hydro-meteorological data from 1961 to 2019 are analyzed to reveal the climate change and runoff alteration of the Dongting Lake comprehensively. Mutation test is used to detect the change points of runoff depth series, finding that 1984 and 2005 are change points and therefore 1961–1983, 1984–2004, and 2005–2019 are regarded as baseline period (BP), period 1 (P1), and period 2 (P2), respectively. Eight methods are used to quantitatively assess the relative contribution of human activities and climate change on runoff variation. It reveals that climate change especially precipitation change plays the dominant role (climate change makes runoff depth increase 70.14–121.51 mm, human activities make runoff depth decrease 51.98–103.35 mm) in runoff alteration in P1 while human activities play a prime role (account for 88.47–93.17%) in P2. Human activities such as reservoir construction, water consumption, and land-use (land-cover) change may be the main factors that influence the runoff in the Dongting Lake in P2. According to the sensitivity analysis, runoff in the Dongting Lake is more sensitive to climate change in P2 compared with that in P1, and no matter in P1 or P2, runoff is more sensitive to change in precipitation than the change in potential evapotranspiration. Combined with climate forecast, the results of sensitivity analysis can be used to estimate runoff change caused by climate change in the future.

DETERMINANT PLUVIOMETRIC CHARACTERISTICS OF SEDIMENT TRANSPORT IN A CATCHMENT WITH THINNED VEGETATION IN THE TROPICAL SEMIARID

ABSTRACT Knowing determinant factors of erosive process is essential to adopt soil conservationist and loss-mitigation measures. Therefore, the objective of this work was to assess the correlation between rainfall characteristics and sediment transport in the Semiarid region of Brazil. The study was conducted at the Iguatu Experimental Basin in the state of Ceará, Brazil, in a watershed with area of 1.15 ha. The vegetation was thinned by removal of plants with diameters below 10 cm, and the area remained with an arboreous cover of 60%. The following variables were evaluated from 2012 to 2016: rainfall depth (mm), rainfall duration (hours), maximum rainfall intensity in 5, 10, 15, 20, 30, 45, and 60 minutes (mm h-1), mean rainfall intensity (mm h-1), rainfall depth in the previous 5 days (mm), runoff depth (mm), and transported sediment (kg ha-1). The records showed 158 rainfall events, 27 with surface runoff and 24 with sediment transport. The correlations were investigated by multivariate analysis of principal components (PC). The model explained 84% of total variance with four PC-PC1, PC2, PC3, and PC4 were formed, respectively, for disaggregating power of rainfall on soil particles, represented by the rainfall intensities; soil water content; runoff depth and sediment transport; and rainfall duration and interval between rainfalls. The highest factorial weight was found for the maximum intensity in 20 minutes, indicating the need for further hydrological studies focused on this variable at basin scale in areas of the Semiarid region of Brazil subjected to thinning of the vegetation.