Rainfall Depth Research Articles

Curva número para estimativa do escoamento superficial em pavimento de concreto intertravado

ABSTRACT Curve Number (CN) values estimating from rainfall-runoff data is an attractive topic in hydrology. However, CN values are lacking for Interlocking Concrete Pavement (ICP) material, mainly when seated over bare soil (not over a permeable pavement structure). Here, we compute CN values for the ICP seated over clayey soil using measured rainfall and infiltration capacity data. We estimated runoff ( Q) using 32 events of 24-hour rainfall depth ( P 24) and an infiltration model, assuming a hortonian runoff process. To estimate the CN for each P 24 event, we used the rainfall-runoff incremental approach. Overall, we obtained CN values ranging from 52 to 63. The best CN values to estimate Q were equal to 52.2 ( R M S E = 9.09 mm and R 2 = 0.03) and 60.1 ( R M S E = 1.45 mm and R 2 = 0.97), considering natural- and rank-ordered P 24- Q data, respectively. Our results indicate that it is more suitable to use the initial abstraction ratio ( λ) equal to 0.20 for the ICP material. The findings provide a better understanding of the rainfall-runoff process in ICP and help improve the design of stormwater drainage systems.

The Recent Droughts of 2019/20 in Southern Africa and Its Teleconnection with ENSO Events

This study is motivated to highlight the variability of recent drought hotspots in the region of southern Africa in terms of the seasonal and annual rainfall regimes and their possible spatial linkage with the 1950-2020 seasonal El Niño/Southern Oscillation (ENSO). Some evidence is found on possible links between the occurrence of drought hotspots in the region in terms of seasonal and mean annual runoff and warm ENSO events. This was revealed by the existence of a strong and nearly-strong positive linear correlation between Seasonal and annual rainfall depths and the warm seasonal ENSO indices explained by the southern oscillation index represented by the sea level pressure (SLP) anomalies data obtained from the National Oceanographic and Aeronautics Administration (NOAA). Considering the entire southern African region, 41% of the surface areas exhibit moderate (r > 0.25) and strong (r > 0.5) correlation coefficients in terms of the December to February quarter rainfall and ENSO indices. Above 50% confidence interval in the correlation between seasonal rainfall and ENSO during DJF quarters is found in 74% of the surface area of the region of southern Africa. The high confidence interval of the positive correlation coefficients is an indication that substantial variance of precipitation during ENSO years is accounted for by the warm ENSO events. The areas with pronounced lower rainfalls and droughts associated with ENSO activity in the region include larger and some pockets of various countries in southern Africa, including but not limited to Angola, Botswana, Lesotho, Namibia, Zambia, Zimbabwe, South Africa and Mozambique. The recent drought events of 2019/2020, and previously in 2015/16 in this region with wider regional impacts can be explained by the ENSO phenomena.

Impact of Climate Change on Runoff Prediction in Ogbese River Watershed

Increased rainfall amounts are projected in the humid southern parts of Nigeria due to climate change. The consequence of higher rainfall in future years would result to higher peak runoffs and flood stages in streams in these parts. The focus of this study is to simulate peak runoff at the outlet of Ogbese river watershed for future years of 2030, 2040, 2050 and 2060. Local twenty years (2000-2019) historical rainfall depths were used to statically downscale General Circulation Model outputs in the future for RCP 4.5 climate scenario. Downscaled rainfall depths were inputted in HEC-HMS model version 4.2 for rainfall-runoff simulation. The watershed was delineated with DEM in ArcGIS while four land use and land cover classifications were extracted with QGIS. Maximum rainfall depths projected in years 2030, 2040, 2050 and 2060 were 38.5mm/hr, 39mm/hr, 42mm/hr and 46mm/hr respectively. Peak runoff discharge simulated for RCP 4.5 climate scenario in years 2030, 2040, 2050 and 2060 are 1771m3/s, 1826 m3/s, 1897 m3/s and 2200 m3/s respectively. This represents 24.2% increase peak discharge between 2030 and 2060. Land area delineated for the catchment is 1946.2 km2. The LULC classification areas for urban area, forest, rock outcrop and bare land are 81.59 km2, 1721.84 km2, 146.27 km2 and 4.11 km2 respectively. The soil types are sandy clay loam (92.51 %), sandy loam (6.84 %), and clay (0.65 %). Curve Number and Initial abstraction parameter values are 70.27 and 2.89 respectively. Keywords- Climate change, GCM, HEC-HMS , Ogbese river, Peak runoff

TREND DETECTION OF AVERAGE ANNUAL RAINFALL AND TEMPERATURE IN SULAYMANIYAH GOVERNORATE, IRAQ

Change in the magnitudes of temperature and rainfall temporally and spatially can be observed, on both regional and global scales, so detecting the trend of their changes is essential to fit the management plans of hydrological, agricultural, and other water-related activities. In this study, the trend of annual temperature and annual rainfall magnitudes within Sulaymaniyah Governorate have been investigated by using the Mann–Kendall trend test and Sen’s slope estimator. The recorded data at five stations namely Sulaymaniyah, Dukan, Halabja, Penjwen, and Chamchamal stations across Sulaymaniyah Governorate have been studied. The results showed that the positive increasing trend appeared in the annual temperature values of the data of Sulaymaniyah, Dukan, Penjwen, and Chamchamal stations, while Halbja station didn’t reveals any trend in its annual temperature values. Regarding the trend of annual magnitudes of rainfall, the results showed that the trend didn’t appears in the rainfall magnitudes of all of the studied stations, based on the calculated value of (Z), the trend has not appeared in average annual rainfall depth in all of the studied stations at the significant level of 95%, however by taking the p-values, slightly trend toward negative was observed in Sulaymaniyah Station, while moderately trend toward negative and positive increase has appeared in Halabja and Chamchamal stations respectively, but at Dukan and Penjwen Stations, the trend has not appeared in the average annual rainfall.

Rainfall-runoff characteristics and their threshold behaviors on a karst hillslope in a peak-cluster depression region

Water balance characteristics and rainfall-runoff relationships of karst slope, are poorly understood worldwide, even though karst landscapes occupy 10–15% the planet’s land surface. Dynamic hydrological responses were monitored for 43 rainfall events on a karst slope in southwest China over two years (2018–2019). The responses included surface, subsurface, and epikarst seepage runoff (abbreviated as SR, SSR, and ESR, respectively) and soil water content at different depths (10 cm, 30 cm, and the soil-epikarst interface) in twelve plots (5 m× 20 m, total 1200 m2). Results showed that: (1) The hillslope-scale SR, SSR, and ESR coefficients were 2.2% (0.4%–5.2%), 3.8% (0.2%–12.4%), and 31.2% (0.6%–89.1), respectively. SR and SSR were relatively rare and of short duration, while ESR was a crucial component of the karst hillslope water balance and its duration was longer, demonstrating the critical role of epikarst zone in regulating flow functions such as water storage and release; (2) Soil depth exerted the greatest direct effect on SR, which increased as soil deepened. Factors controlling the rainfall-SSR response were difficult to identify. They require other geophysical exploration methods; (3) Threshold-like runoff responses to rainfall inputs were observed on karst slope, and the rainfall depth (P) runoff initiation thresholds for SR and SSR were 36±2 mm and 43±7 mm, respectively. The strength of the threshold-like input–output relationships was slightly greater when the P + ASI (antecedent soil water content index) was used as the hydrological input variable rather than without consideration of ASI. The differing shapes of nonlinear hydrological behaviours, such as the ‘hockey stick’, ‘heaviside’ function, or the sigmoid function were detected in karst slope. This suggests karst hydrological system complexity. Threshold values should be determined according to the shapes of nonlinear hydrological behaviours. These results extend the understanding of karst hydrological processes.

Impact of climate change on groundwater recharge in the lake Manyara catchment, Tanzania

Groundwater account for about 60 to 80% of water supply to the population of Tanzania's semi-arid regions for domestic and agriculture uses. Despite the importance of groundwater resource in semi-arid areas, limited information exists on the recharge amount and potential recharge zones in Tanzania in the context of climate change which could result in unsustainable withdrawals. This study aimed to estimate the potential impact of climate change on groundwater recharge and identify potential recharge zones in the Lake Manyara catchment using Water and Energy Transfer between Soil, Plants and Atmosphere under the quasi-steady State (WetSpass) model. The WetSpass model was setup and calibrated using hydro-meteorological data (rainfall, temperature, wind speed, potential evapotranspiration, and groundwater depth) and biophysical data (soil, land use, topography, and slope). Simulated rainfall, temperature and potential evapotranspiration from an ensemble of four CORDEX-Africa regional climate models for the period 2021–2050 under the Representative Concentration Pathway (RCP 8.5) scenario (hereafter referred as business-as-usual scenario) were used as input in the WetSpass model for the climate change impact assessment. WetSpass model calibration using the water balance equation showed a coefficient of determination (R2) value of 0.9 and Root-Mean-Square Error (RMSE) of 0.49 mm/yr between the simulated and calculated recharge. It was determined that the mean annual recharge of 53.9 mm/year (149 MCM/year) for the period 1989–2018 would increase by 7.9% in the future (2021–2050) under the business-as-usual climate scenario, due to the increase in rainfall. Seasonality and spatial differences in recharge amount were observed, with recharge projected to increase in the dry season and at areas that receive high amount of rainfall. Potential recharge zones in the catchment were found mostly around the northern part near Ngorongoro, the south-western part, and around Mbulu region. Findings from this study would help policymakers, and local stakeholders in planning and management of the groundwater resources for sustainable development.

Integrating Tank Model and adsorption/desorption characteristics of filter media to simulate outflow water quantity and quality of a bioretention basin: A case study of biochar-based bioretention basin

Reliable approaches for accurately assessing the performance of stormwater treatment systems is essential for their effective design, including filter media selection which can be a significant constituent in stormwater treatment systems. This study presents an innovative modelling approach integrating the Tank Model with the adsorption-desorption characteristics of the filter media. The resulting modelling approach was applied to simulate a field-scale bioretention basin where biochar was used as filter media with over ten years of rainfall records. The resulting outflow and overflow volumes were compared with observed data for calibration. The Stormwater Treatment Tank Model (STTM) was validated using the Leave-One-Out-Cross-Validation (LOOCV) method. The simulation outcomes include water outflow and overflow (quantity) from the bioretention basin as well as outflow water quality represented by three heavy metals (Pb, Cu, and Zn). The modelling approach developed was found to be capable of accurately simulating outflow and overflow volumes, with outlet water quantity being significantly influenced by the total rainfall depth. The modeling results also suggested that a sole treatment system would not be adequate, particularly for large rainfall events (>100 mm) and a treatment train would be more effective. Simulating long-term (over ten years) pollutant removal performance in the bioretention basin indicated that heavy metals outflow event mean concentration (EMCs) values calculated using simulated results of 30% biochar application rate generated the best pollutant removal with consistent values (2.7 μg/L, 3.0 μg/L, 17.2 μg/L for Pb, Cu, and Zn, respectively). These results confirm that the modelling approach is reliable for assessing long-term treatment performance, as well as a robust tool able to contribute to more effective treatment system design, particularly filter media selection and evaluation.

The Comparison of Erosion Rates in Grassland, Teak Forest, Crops Land, and Gliricidia Forest Plantation in Wanagama Edu Forest

<p class='Els-Abstract-text'>Wanagama forest is an integral part of a nearby village. This forest is left unprotected, so local people can easily enter the forest area to take non-timber forest products, including cropland and grass. The increasing demand for grass for feeding the cattle in Wanagama resulted in a larger area of grassland. Therefore, it is highly important to review and measure the erosion rate of the grassland compared to other land uses. This research aims to measure the erosion rates of four land uses and determine the correlation between rainfall and erosion at those four land uses: grassland, teak forest, crops land, and Gliricidia forest plantation. In measuring the erosion rates, this research uses four plots of 22 x 4 meters established at those four land uses. Each plot has two drums at the outlet. We took the erosion samples at every single rainfall event. To investigate the rainfall, there were two ombrometers installed in the field. The results show that the grassland has the lowest erosion rate (0.45 tons/ha) compared to a teak forest (0.5 tons/ha), crops land (0.84 tons/ha), and Gliricidia plantation forest (1.66 tons/ha). The rainfall has a positive coefficient correlation to erosion; the lowest was in grassland (r = 0.723), followed by teak forest (r = 0.828), Gliricidia (r = 0.830), and Crops land (0.873). The higher the rainfall depth will result in the higher erosion rate at the four land uses.

A Cox Process with State-Dependent Exponential Pulses to Model Rainfall

A point process model based on a class of Cox processes is developed to analyse precipitation data at a point location. The model is constructed using state-dependent exponential pulses that are governed by an unobserved underlying Markov chain. The mathematical formulation of the model where both the arrival rate of the rain cells and the initial pulse depth are determined by the Markov chain is presented. Second-order properties of the rainfall depth process are derived and utilised in model assessment. A method of moment estimation is employed in model fitting. The proposed model is used to analyse 69 years of sub-hourly rainfall data from Germany and 15 years of English rainfall data. The results of the analysis using variants of the proposed model with fixed pulse lifetime and variable pulse duration are presented. The performance of the proposed model, in reproducing second-moment characteristics of the rainfall, is compared with that of two stochastic models where one has exponential pulses and the other has rectangular pulses. The proposed model is found to capture most of the empirical rainfall properties well and outperform the two alternative models considered in our analysis.

Design, Development and Implementation of Real Time Canal and Weather Monitoring Devices

In the present study, canal depth, velocity and weather monitoring sensors are designed and implemented in the field irrigation laboratory, Aditya Engineering College, Surampalem, Andhra Pradesh, India. The depth sensor which is used in this project is HC-SR04 sensor and the velocity sensor is YF-S403. A method of data acquisition and transmission based on ThingSpeak IOT is proposed. To record weather data (i.e., temperature, humidity, rainfall depth and wind speed) DHT11 sensor, ultrasonic sensor and IR sensors are used. The purpose of this project is to evaluate the performance of real time canal and weather monitoring devices. A structure of real time weather monitoring devices based on sensors and ThingSpeak IOT, a design was developed to realize the independent operation of sensors and wireless data transmission can help in minimizing the error in data collection. Arduino UNO is connected with canal depth and velocity sensor to generate the output, similarly NodeMCU is connected with weather monitoring device. The results revealed that observed sensor data showed good results when compared/calibrated with the existing conventional measurement system. In order to decrease the time and to get accurate value, it is recommended to consider the sensors for the proper use and to access weather data easily. The developed device worked satisfactorily with minimum or no errors.

Effect of Time-Resolution of Rainfall Data on Trend Estimation for Annual Maximum Depths with a Duration of 24 Hours

The main challenge of this paper is to demonstrate that one of the most frequently conducted analyses in the climate change field could be affected by significant errors, due to the use of rainfall data characterized by coarse time-resolution. In fact, in the scientific literature, there are many studies to verify the possible impacts of climate change on extreme rainfall, and particularly on annual maximum rainfall depths, Hd, characterized by duration d equal to 24 h, due to the significant length of the corresponding series. Typically, these studies do not specify the temporal aggregation, ta, of the rainfall data on which maxima rely, although it is well known that the use of rainfall data with coarse ta can lead to significant underestimates of Hd. The effect of ta on the estimation of trends in annual maximum depths with d = 24 h, Hd=24 h, over the last 100 years is examined. We have used a published series of Hd=24 h derived by long-term historical rainfall observations with various temporal aggregations, due to the progress of recording systems through time, at 39 representative meteorological stations located in an inland region of Central Italy. Then, by using a recently developed mathematical relation between average underestimation error and the ratio ta/d, each Hd=24 h value has been corrected. Successively, commonly used climatic trend tests based on different approaches, including least-squares linear trend analysis, Mann–Kendall, and Sen’s method, have been applied to the “uncorrected” and “corrected” series. The results show that the underestimation of Hd=24 h values with coarse ta plays a significant role in the analysis of the effects of climatic change on extreme rainfalls. Specifically, the correction of the Hd=24 h values can change the sign of the trend from positive to negative. Furthermore, it has been observed that the innovative Sen’s method (based on a graphical approach) is less sensitive to corrections of the Hd values than the least-squares linear trend and the Mann–Kendall method. In any case, the analysis of Hd series containing potentially underestimated values, especially when d = 24 h, can lead to misleading results. Therefore, before conducting any trend analysis, Hd values determined from rainfall data characterized by coarse temporal resolution should always be corrected.

Method for assessing the impact of rainfall depth on the stormwater volume in a sanitary sewage network

Sanitary sewage network is relatively rarely considered as the cause of urban floods. Its hydraulic overload can result not only in flooding, but also sanitary contamination of subcatchments. Stormwater is the main reason for this overload. In contrast to the stormwater or combined sewer system, these waters infiltrate into the network in an uncontrolled way, through ventilation holes of covers or structural faults and lack of tightness of manholes. Part of stormwater infiltrates into the soil, where it leaks into pipelines. This greatly hinders assessing the quantity of stormwater influent into the sanitary sewer system. Standard methods of finding correlation between rainfall and the intensity of stormwater flow are ineffective. This is confirmed, i.a. by the studies performed in an existing network, presented in this paper. Only when residuals analysis was performed using the ARIMA and ARIMAX methods, the authors were able to develop a mathematical model enabling to assess the influence of rainfall depth on the stormwater effluent from the sewage network. Owing to the possibility of using the rainfall depth forecasts, the developed mathematical model enables to prepare the local water and sewerage companies for the occurrence of urban floods as well as hydraulic overload of wastewater treatment plants.

Calibration of Spatial Rain Scanner using Rainfall Depth of Rain Gauges

A spatial rain scanner has been developed based on a marine radar to satisfy the demand for spatial rain information for hydrological applications. Since the coverage of the rain scanner is 44 km in radius, it is necessary to expand the coverage by installing it in two sites that intersect each other performing a radar network. For this purpose, the first rain scanner has been installed at the Center for Atmospheric Science and Technology (PSTA) in Bandung and the second one at the Space and Atmospheric Observation Center (BPAA) Tanjungsari in Sumedang. This paper focuses on the calibration of radar observations with rainfall data from 7 rain gauges installed in Bandung area and its surroundings. The calibration method calculates rainfall depth (three parameters) instead of only the intensity of rainfall. The data period used for this research is from March to November 2020. The rain scanners have better rainfall events detection over basin area, such as Dayeuh Kolot and Cidurian, than over highland area, such as Lembang. Two calibration methods are used, and the results show that the calibration by calculating three parameters (accumulated reflectivity, duration, and intensity) in the linear model is able to measure rainfall estimation better than using a linear model with one parameter (accumulated reflectivity) for rainfall depth more than 10 mm. Rainfall estimation calculation using scheme 1 tends to underestimate while scheme 2 tends to overestimate.

THE EFFECT OF TREE CANOPY STRUCTURE ON SPATIAL RAINFALL REDISTRIBUTION DURING POST-ERUPTION RECOVERY OF MOUNT MERAPI, JAVA ISLAND

The tree canopy around Merapi Volcano, Yogyakarta, Indonesia, has a unique structure. The frequency of volcanic eruptions influences the uniqueness of the structure, as it is a response to volcanic ash and rainfall characteristics. This research was conducted on eight species that have different canopy structures. In contrast to the trees canopy that was not affected by eruptions, the tree canopy around the Volcano has more dynamic canopy surface characteristics during the recovery period. The redistribution of rainfall in the tree canopy was traced by calculating unit area discharge and droplets' probability in each canopy structure segment. The results of empirical throughfall calculation and throughfall direct observation were tested using ANOVA. Most of the throughfall occurs simultaneously under the canopy during rain with a depth of 3.5 - 72.5 mm or intensity of 10 - 20 mm/hour (observed = 58% and empirical = 57%). The existing range of rainfall intensity or rainfall depth shows that the process of redistribution of rainfall in the canopy has time constraints and canopy storage capacity constrain. The canopy surface characteristics have a more significant effect than the canopy structure on the redistribution of rainfall. The canopy surface serves as a sheet of rainfall concentration to the next section. The important canopy surface structure parameters to rainfall concentration are leaves characteristics, branches stiffness, and crown density. Knowledge of the tree canopy's rainfall flow distribution process will help manage conservation-based rehabilitation activities in areas prone to volcanic disasters.

Combined effects of rainfall and flow depth on the resistance characteristics of sheet flow on gentle slopes

Rainfall and sheet flow (SF) on gentle slopes always appear concurrently. However, the combined effects of rainfall and flow depth on SF resistance are still unclear for gentle slopes. In this study, two sets of experiments, namely, upstream inflow with rainfall and upstream inflow only, were conducted to investigate the resistance characteristics of SF on a flat and smooth flume with three gentle slopes (3°, 5° and 7°). The experimental results indicated that in the tests with upstream inflow only, the Darcy–Weisbach resistance (f) and Manning coefficient (n) decreased following a power function with increasing flow depth. When the Reynolds number (Re) was less than 1070, the n and f of the SF in the upstream inflow alone decreased with increasing Re following the power function. Both the n and f of the SF increased with increasing rainfall intensity for the upstream inflow with the rainfall tests. The rainfall significantly affected the f and n of the SF in the low Re zone (Re < 1070), inflow discharge (<0.06 m2 min−1) and flow energy for all inflow with rainfall cases. Under the conditions of upstream inflow with rainfall, both the f and n of the SF decreased with the increase in the ratio between the flow depth and median raindrop diameter (H/D50) in the power function. This result indicated that a deeper flow could dissipate more raindrop energy. In addition, empirical equations among Re, hydraulic slope and H/D50 were established to predict the n and f of the SF for upstream inflow with rainfall tests. This study will be helpful in understanding the combined effects of rainfall and flow depth on SF and could provide a scientific basis for improving hydrological and soil erosion models.

Failure Mechanism of Weak Rock Slopes considering Hydrological Conditions

Landslides frequently occur on cutting slopes with weak rock during the rainy season. An understanding of the failure mechanism is essential for designers to adopt effective measures to mitigate potential impacts caused by landslides. Based on an enormous number of highway slope practices in Guangdong Province, China, this paper presents a whole train of numerical investigations on the hydraulic response and stability of weak rock slopes subject to a subtropical climate where the average annual rainfall is approximately 1,800 – 2,000 mm. This study explored a different failure mechanism of three different types of weak rock slopes in a modeling approach. A physics-based slope model coupled with a hydrological model is used to simulate the factor of safety and porewater pressure development of unsaturated slopes with various rock masses under diverse rainfall scenarios. The input parameters were determined from the rainfall intensity–duration–frequency (IDF) curves of regional hydrological conditions to comprehensively consider the impact of rainfall. The general suction range of rock masses was acquired using three hydraulic characteristic curves associated with sandstone, siltstone, and mudstone. Furthermore, the failure models of weak rock slopes under different rainfall conditions were assessed. Based on the theory of regional hydrology, a unified rainfall and intensity-duration threshold for different weak rock slopes was established. The results indicate that both siltstone and mudstone slopes are more sensitive to long-term rainfall than short-term rainstorms. However, the sandstone slope appears to be unstable under regional rainfall conditions of 40-year return periods. This also proves that the instability mode of the siltstone slope exhibits a retrogressive type in which the sliding surface of the slope increases with an increase in rainfall duration. Translational shallow landslides occurred in the transient saturation zone of the sandstone slope, and the depth of the failure plane was independent of rainfall patterns and duration. This study revealed the instability mechanism and provided a robust early warning measure for weak rock slopes by fusing engineering geology and regional hydraulics, providing insightful information for mitigating potential landslide disasters. The proposed model can also be used to predict the possible infiltration depth of rainfall and the spatial location of the sliding surface, prior to construction to assess whether slope stabilization and reinforcement measures are needed.

Forecasting river basin yield using information of large-scale coupled atmospheric–oceanic circulation and local outgoing longwave radiation

ABSTRACT Global and local climate parameters influence the distribution of precipitation over continents. The spatio-temporal distribution of rainfall and the depth of rainfall over a river basin influence the river basin yield. This study deals with the prediction of the river basin scale yield of the ‘Upper Bhima River basin’ from the Maharashtra State of India. The information on large-scale circulation patterns El Nino-Southern Oscillation (ENSO), Equatorial Indian Ocean Oscillation (EQUINOO) index, Multivariate ENSO Index (MEI), and local meteorological input viz. Outgoing longwave radiation (OLR) has been used to predict the river basin scale yield. The Artificial Intelligence (AI) tool – Genetic Programming (GP) – is used for developing prediction models. Ten different combinations of input variables are attempted for the development of monthly river basin yield models to arrive at the best input variable combination for the best predictions with varying lead times. Also, three combinations of input variables were tested for the prediction of ‘Seasonal Yield’. The findings of this research work indicate that GP-derived monthly River Basin Scale Yield forecasting models are successful in the prediction of yield with a correlation coefficient of 0.83. The seasonal yields could be predicted with a correlation coefficient of 0.75.

Characterizing the effects of dry antecedent soil moisture conditions, channel transmission losses, and variable precipitation on peak flow scaling

Peak discharge to drainage area relationships are widely applied engineering solutions for design flood estimation in ungauged basins. In this study we investigated the effects of antecedent moisture conditions (AMC), rainfall duration, and channel transmission losses on discharge-drainage area power law scaling relationships. The spatial organization of peak discharges were evaluated through coupled surface-subsurface physics based numerical modeling. We take advantage past research and the detailed flexibility of HydroGeoSphere, the numerical modeling platform, to systematically vary AMC and rainfall depths evolving the current understanding of the effects on discharge-drainage area relationships. Channel network dynamics in the Beaver Creek watershed dominated the location of a scale break, or the location where the log-log linear relationship between peak discharge and drainage area is best described by two or more slopes. Single peaked hydrographs and high-quality power law scaling relationships resulted from wet AMC conditions or high precipitation depths. As we reduced the AMC, under low rainfall depths, the hillslope response diverged from the channel response, providing an unorganized system response no longer fitting the power law scaling relationship. Additionally, when initializing the system under losing stream conditions, where the stream channel is assumed unsaturated, a single peaked response ensued whereby the channel and hillslope responded in unison. This study adds to our current understanding of the physical basis of the variability of the scaling structure of peak discharges that is observed in single rainfall-runoff events by investigating the spatial organization of peak discharges under exceedingly dry antecedent soil moisture conditions.

Trends in monthly and annual streamflow related to rainfall and land use at the Atlantic rainforest biome

Understanding trends in rainfall and streamflow over time are essential for water resources planning and management. This study analyzed trends in the streamflow of the Itapemirim river basin (IRB) in Southeastern Brazil and to relate these trends with changes that occurred in rainfall and land use (from 1969 to 2018). Accumulated rainfall decreased in the dry period. In October (considered the beginning of the hydrological year), rainfall amounts decreased in all sub-basins and suggested a shift of the beginning of the rainy period to November. Increasing rainfall was only observed for December and only in the west and northwest portion of the IRB. Average monthly streamflow showed a downward trend and followed downward trends in rainfall depth from the same month or the immediately previous one. Decreases of 25–40% in minimum streamflow occurred in most sub-basins and dated mainly from the 1990's. There was an increasing trend in maximum streamflow of 28–48% in the Braço Norte Direito River and in the Itapemirim River.

A Simplified Model for Predicting the Effectiveness of Bioswale’s Control on Stormwater Runoff from Roadways

Bioswales are commonly constructed along roadways to control stormwater runoff. Many factors can affect the performance of a bioswale such as the size of the bioswale and its associated drainage area, rainfall characteristics, site conditions, soil properties, and deterioration of the bioswale’s condition over usage. Transportation agencies and engineering communities need a reliable and convenient method for predicting the effectiveness of bioswale. Although available software tools can be used to model and analyze design options, input values for a large number of variables and highly skilled modelers are required to handle these sophisticated modeling tools. The objective of this study was to develop a simplified and easy-to-use mathematical model for predicting the effectiveness of bioswales through empirical predictions of stormwater runoff as a function of four key parameters: area ratio (bioswale surface area to its drainage service area), rainfall depth, rainfall intensity, and sediment accumulation (build-up) on bioswale’s surface area. A PCSWMM model was developed to simulate the physical conditions of a field-scale bioswale. This PCSWMM tool was also used to simulate an idealized (conceptual) catchment model that represents common highway geometries and characteristics. A total of 72 scenarios were simulated on various combinations of the four studied parameters: area ratio (9%, 13%); rainfall depth (2.54, 5.08, 7.62, 10.16 cm); rainfall intensity (2.54, 5.08, 10.16 cm/h); and sediment accumulation (0, 0.25, 1.78 cm). Half of the total scenarios (i.e., 36 scenarios) were used to develop a new simplified mathematical model, and the other 36 scenarios were used to calibrate and validate this newly developed model. The analysis revealed a reasonable correlation (R2 = 0.967) between modelled predictions and PCSWMM-simulated results, indicating the newly developed mathematical model can serve as an adequate alternative for simulating bioswales’ performance for stormwater runoff control.