RAINFALL EROSION INDICES FOR CANADA EAST OF THE ROCKY MOUNTAINS

1983 ◽  
Vol 63 (2) ◽  
pp. 271-280 ◽  
Author(s):  
G. J. WALL ◽  
J. GREUEL ◽  
W. T. DICKINSON
Keyword(s):  
Rocky Mountains ◽  
Water Conservation ◽  
Soil Loss ◽  
Distribution Patterns ◽  
Seasonal Distribution ◽  
Annual Rainfall ◽  
Rainfall Runoff ◽  
Runoff Factor ◽  
Rainfall Erosion

The use of the universal soil loss equation in Canada to estimate soil loss potential for soil and water conservation planning purposes has been limited by the lack of published rainfall erosion indices and by the arduous procedure generally accepted for determination of these indices. This study was conducted to develop and test relatively simple methods to develop annual rainfall erosion indices and associated seasonal distribution patterns. An approach to the determination of a rainfall-runoff factor to accommodate the effect of winter conditions has also been included. The relatively simple techniques for estimating average annual rainfall erosion indices and seasonal distribution patterns of rainfall erosion have been found to yield comparable values to those determined by more tedious methods. These erosion indices and associated distribution patterns have proven useful for the development of a first approximation of rainfall erosion maps for Canadian locations east of the Rocky Mountains. Key words: Rainfall erosion indices, USLE

scholarly journals Assessment of Soil Loss Rates in Asreh Watershed (North Jordan Badia) Using RUSLE and GIS

2021 ◽  
Vol 12 (1) ◽  
pp. 10-16
Author(s):  
Saad M. AlAyyash ◽  
Keyword(s):  
Soil Loss ◽  
Loss Rate ◽  
Rainwater Harvesting ◽  
Annual Rainfall ◽  
Physical Factors ◽  
Rainfall Erosivity ◽  
Water Harvesting ◽  
Rainfall Runoff ◽  
Semi Arid ◽  
Soil Loss Rate

In arid lands, rainwater harvesting can play an important role in making more water available since most of the rainfall runoff evaporates. If rainwater can be collected, it will form a useful resource. Jordan is classified as one of the poorest countries regarding water resources with an arid and semi-arid climate. For these limited and vital sources of water, good estimation of rainfall runoff quantity and quality can enhance the sustainability of water harvesting projects. The hydrologic estimations of runoff quantities and qualities are essential, and several techniques to achieve that exist. Revised Universal Soil Loss Equation (RUSLE) is one of the widely used techniques to assess the soil erosion due to runoff, by assessing other physical factors that affect the soil loss. RUSLE combined five parameters to identify the soil loss rate: rainfall erosivity, topographic, soil erodibility, vegetation cover and management, and land management. Based on RUSLE results, areas are classified as a highly soil loss rate if the annual rates exceeded 20 tons per hectare. The Asreh watershed is a 196 km2 area that is mostly wasted land and receives an annual rainfall between 50 and 300 mm per year. The RUSLE equation inputs parameters for the study area are found and the equation is applied for the watershed. Results of RUSLE application on the Asreh watershed showed that the average annual soil loss rate is about 7.8 tons per hectare, about 73% of the area are classified as low soil loss rate with less than 10 tons per hectare per year, and only 13% of the area is classified as a high soil loss rate of more than 20 tons per hectare per year.

scholarly journals Estimation of soil loss rate using the USLE model for Agewmariayam Watershed, northern Ethiopia

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Gebrehana Girmay ◽  
Awdenegest Moges ◽  
Alemayehu Muluneh
Keyword(s):  
Water Conservation ◽  
Soil Loss ◽  
Loss Rate ◽  
Sub Saharan Africa ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Northern Ethiopia ◽  
Spatial Risk ◽  
Soil Loss Rate ◽  
Loss Rates

Abstract Background Soil erosion and nutrient depletion threaten food security and the sustainability of agricultural production in sub-Saharan Africa. Estimating soil loss and identifying hotspot areas support combating soil degradation. The aim of this paper is to estimate the soil loss rate and identify hotspot areas using USLE model in the Agewmariam watershed, northern Ethiopia. Methods Rainfall erosivity factor was determined from annual rainfall, soil erodibility factor from soil data, slope length and gradient factor were generated from DEM, cover factor and conservation practice factor obtained from land use cover map. Finally, the parameters were integrated with ArcGIS tools to estimate soil loss rates of the study watershed. Results Mean annual soil loss rates were estimated to be between 0 and 897 t ha−1 year−1 on flatter and steeper slopes, respectively. The total annual soil loss was 51,403.13 tons from the watershed and the annual soil loss rate of the study area was 25 t ha−1 year−1. More than 33% of the study areas were above tolerable soil loss rate (11 t ha−1 year−1). The spatial risk categorization rate was 67.2% severe (> 51 t ha−1 year−1), 5.4% very high (31–50 t ha−1 year−1), 5.8% high (19–30 t ha−1 year−1), 3.2% moderate (12–18 t ha−1 year−1) and 18.3% slight (0–11 t ha−1 year−1). Conclusion The results showed that the severity of erosion occurred on the steep slope cultivation, absence of conservation measures, and sparse nature of the vegetation cover. This area required immediate action of soil and water conservation which accounts for about 33.5% of the total watershed.

scholarly journals Estimating RUSLE’s rainfall factor in the part of Italy with a Mediterranean rainfall regime

2004 ◽  
Vol 8 (1) ◽  
pp. 103-107 ◽  
Author(s):  
N. Diodato
Keyword(s):  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Critical Examination ◽  
Rainfall Regime ◽  
Rainfall Erosivity ◽  
Rainfall Runoff ◽  
Erosion Index ◽  
Index Rainfall ◽  
Soil Loss Equation

Abstract. The computation of the erosion index (EI), which is basic to the determination of the rainfall-runoff erosivity factor R of the Revised Universal Soil Loss Equation (RUSLE), is tedious and time-consuming and requires a continuous record of rainfall intensity. In this study, a power equation(r2 = 0.867) involving annual erosion index (EI30-annual) in the Mediterranean part of Italy is obtained. Data from 12 raingauge stations are used to derive and then test a regional relationship for estimating the erosion index from only three rainfall parameters. Erosivity rainfall data derived from 5 additional stations are used for validation and critical examination. The empirical procedures give results which compare satisfactorily with relationships calibrated elsewhere. Keywords: erosion index, rainfall, erosivity, Revised Universal Soil Loss Equation

scholarly journals Runoff and soil loss responses of cultivated land managed with graded soil bunds of different ages in the Upper Blue Nile basin, Ethiopia

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Mengie Belayneh ◽  
Teshome Yirgu ◽  
Dereje Tsegaye
Keyword(s):  
Water Conservation ◽  
Soil Loss ◽  
Formation Rate ◽  
Summer Rainfall ◽  
Sediment Concentration ◽  
Annual Rainfall ◽  
Runoff Coefficient ◽  
Wide Range ◽  
Gumara Watershed ◽  
Runoff And Soil Loss

Abstract Background In view of a wide range of on-site and off-site impacts of soil erosion, different soil and water conservation measures have been implemented mainly over the last two decades in the Gumara watershed and Ethiopia at large. But their effects have not been sufficiently documented, and maintenance of structures received very little attention. This study investigated the effectiveness of graded soil bunds of zero and 11 years of age in reducing runoff and soil loss. Six hydrologically isolated experimental runoff plots (three treatments × two replicates) were prepared to observe rainfall, runoff, and sediment concentrations in the 2019 summer rainfall season (covering approximately 70% of the annual rainfall). Results Newly constructed soil bunds reduced runoff by 34.94 and 25.56% compared to the old and non-treated counterparts, respectively. Similarly, 59.6 and 48.3% soil loss reductions were observed. The amount of soil loss in non-treated plots was twice that from the new plots and even 1.6 times higher than that from the old-graded soil bund treatments. The rate of soil loss in the new- and old-graded soil bund-treated and non-treated plots was 23.5, 45.6, and 58.1 t ha−1 year−1, respectively. However, the effectiveness of the old soil bunds was much lower (only − 12.6 and − 21.7% in runoff and soil loss, respectively) than its new equivalent. Graded soil bunds, in its new form, reduced runoff, runoff coefficient, and soil loss significantly (P < 0.05). Regardless of the treatments, from the start of the rainy season to the end, runoff and runoff coefficient showed an increase, but sediment concentration decreased. Newly constructed soil bund is the most effective in reducing runoff and soil loss. Conclusion Graded soil bunds reduced runoff and soil loss significantly, but the rate even in the treated plots was very high when compared to both the soil loss tolerance (1–6 t ha−1 year−1) and formation rate (10–14 t ha−1 year−1) estimated for the area. Hence, these structures need to be supported by other measures such as grass strips, agro-forestry, and percolation ditches, for better results. Besides, regular maintenance by either removing sediments from bund furrows or increasing the bund height is recommended for sustained reduction of runoff and soil loss.

scholarly journals Intra-Storm Pattern Recognition through Fuzzy Clustering

Hydrology ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 57
Author(s):  
Konstantinos Vantas ◽  
Epaminondas Sidiropoulos
Keyword(s):  
Fuzzy Clustering ◽  
A Priori ◽  
Temporal Distribution ◽  
Distribution Patterns ◽  
Rainfall Data ◽  
Rainfall Runoff ◽  
Domain Specific ◽  
Runoff Modeling ◽  
National Bank ◽  
Rainfall Patterns

The identification and recognition of temporal rainfall patterns is important and useful not only for climatological studies, but mainly for supporting rainfall–runoff modeling and water resources management. Clustering techniques applied to rainfall data provide meaningful ways for producing concise and inclusive pattern classifications. In this paper, a timeseries of rainfall data coming from the Greek National Bank of Hydrological and Meteorological Information are delineated to independent rainstorms and subjected to cluster analysis, in order to identify and extract representative patterns. The computational process is a custom-developed, domain-specific algorithm that produces temporal rainfall patterns using common characteristics from the data via fuzzy clustering in which (a) every storm may belong to more than one cluster, allowing for some equivocation in the data, (b) the number of the clusters is not assumed known a priori but is determined solely from the data and, finally, (c) intra-storm and seasonal temporal distribution patterns are produced. Traditional classification methods include prior empirical knowledge, while the proposed method is fully unsupervised, not presupposing any external elements and giving results superior to the former.

scholarly journals Torrential Flood Water Management: Rainwater Harvesting through Relation Based Dam Suitability Analysis and Quantification of Erosion Potential

2021 ◽  
Vol 10 (1) ◽  
pp. 27
Author(s):  
Bilal Ahmad Munir ◽  
Sajid Rashid Ahmad ◽  
Raja Rehan
Keyword(s):  
Sediment Yield ◽  
Soil Loss ◽  
Rainwater Harvesting ◽  
Suitability Analysis ◽  
Valley Bottom ◽  
The North ◽  
Roughness Index ◽  
Dam Site ◽  
Very High

In this study, a relation-based dam suitability analysis (RDSA) technique is developed to identify the most suitable sites for dams. The methodology focused on a group of the most important parameters/indicators (stream order, terrain roughness index, slope, multiresolution valley bottom flatness index, closed depression, valley depth, and downslope gradient difference) and their relation to the dam wall and reservoir suitability. Quantitative assessment results in an elevation-area-capacity (EAC) curve substantiating the capacity determination of selected sites. The methodology also incorporates the estimation of soil erosion (SE) using the Revised Universal Soil Loss Equation (RUSLE) model and sediment yield at the selected dam sites. The RDSA technique identifies two suitable dam sites (A and B) with a maximum collective capacity of approximately 1202 million m3. The RDSA technique was validated with the existing dam, Gomal-Zam, in the north of Sanghar catchment, where RDSA classified the Gomal-Zam Dam in a very high suitability class. The SE estimates show an average of 75 t-ha−1y−1 of soil loss occurs in the study area. The result shows approximately 298,073 and 318,000 tons of annual average sediment yield (SY) will feed the dam A and B respectively. The SE-based sediment yield substantiates the approximate life of Dam-A and Dam-B to be 87 and 90 years, respectively. The approach is dynamic and can be applied for any other location globally for dam site selection and SE estimation.

scholarly journals Performance Evaluation of a Two-Parameters Monthly Rainfall-Runoff Model in the Southern Basin of Thailand

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1226
Author(s):  
Pakorn Ditthakit ◽  
Sirimon Pinthong ◽  
Nureehan Salaeh ◽  
Fadilah Binnui ◽  
Laksanara Khwanchum ◽  
...  
Keyword(s):  
Exchange Rate ◽  
Rainfall Runoff ◽  
Management Planning ◽  
Runoff Variation ◽  
Groundwater Exchange ◽  
Monthly Runoff ◽  
Rainfall Runoff Model ◽  
Two Parameters ◽  
Runoff Model

Accurate monthly runoff estimation is crucial in water resources management, planning, and development, preventing and reducing water-related problems, such as flooding and droughts. This article evaluates the monthly hydrological rainfall-runoff model’s performance, the GR2M model, in Thailand’s southern basins. The GR2M model requires only two parameters: production store (X1) and groundwater exchange rate (X2). Moreover, no prior research has been reported on its application in this region. The 37 runoff stations, which are located in three sub-watersheds of Thailand’s southern region, namely; Thale Sap Songkhla, Peninsular-East Coast, and Peninsular-West Coast, were selected as study cases. The available monthly hydrological data of runoff, rainfall, air temperature from the Royal Irrigation Department (RID) and the Thai Meteorological Department (TMD) were collected and analyzed. The Thornthwaite method was utilized for the determination of evapotranspiration. The model’s performance was conducted using three statistical indices: Nash–Sutcliffe Efficiency (NSE), Correlation Coefficient (r), and Overall Index (OI). The model’s calibration results for 37 runoff stations gave the average NSE, r, and OI of 0.657, 0.825, and 0.757, respectively. Moreover, the NSE, r, and OI values for the model’s verification were 0.472, 0.750, and 0.639, respectively. Hence, the GR2M model was qualified and reliable to apply for determining monthly runoff variation in this region. The spatial distribution of production store (X1) and groundwater exchange rate (X2) values was conducted using the IDW method. It was susceptible to the X1, and X2 values of approximately more than 0.90, gave the higher model’s performance.

scholarly journals Modelling monthly runoff generation processes following land use changes: groundwater–surface runoff interactions

2004 ◽  
Vol 8 (5) ◽  
pp. 903-922 ◽  
Author(s):  
M. Bari ◽  
K. R. J. Smettem
Keyword(s):  
Land Use ◽  
Water Balance ◽  
Surface Runoff ◽  
Land Use Changes ◽  
Annual Rainfall ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
Mean Annual Rainfall ◽  
Monthly Runoff ◽  
Stream Bed

Abstract. A conceptual water balance model is presented to represent changes in monthly water balance following land use changes. Monthly rainfall–runoff, groundwater and soil moisture data from four experimental catchments in Western Australia have been analysed. Two of these catchments, "Ernies" (control, fully forested) and "Lemon" (54% cleared) are in a zone of mean annual rainfall of 725 mm, while "Salmon" (control, fully forested) and "Wights" (100% cleared) are in a zone with mean annual rainfall of 1125 mm. At the Salmon forested control catchment, streamflow comprises surface runoff, base flow and interflow components. In the Wights catchment, cleared of native forest for pasture development, all three components increased, groundwater levels rose significantly and stream zone saturated area increased from 1% to 15% of the catchment area. It took seven years after clearing for the rainfall–runoff generation process to stabilise in 1984. At the Ernies forested control catchment, the permanent groundwater system is 20 m below the stream bed and so does not contribute to streamflow. Following partial clearing of forest in the Lemon catchment, groundwater rose steadily and reached the stream bed by 1987. The streamflow increased in two phases: (i) immediately after clearing due to reduced evapotranspiration, and (ii) through an increase in the groundwater-induced stream zone saturated area after 1987. After analysing all the data available, a conceptual monthly model was created, comprising four inter-connecting stores: (i) an upper zone unsaturated store, (ii) a transient stream zone store, (ii) a lower zone unsaturated store and (iv) a saturated groundwater store. Data such as rooting depth, Leaf Area Index, soil porosity, profile thickness, depth to groundwater, stream length and surface slope were incorporated into the model as a priori defined attributes. The catchment average values for different stores were determined through matching observed and predicted monthly hydrographs. The observed and predicted monthly runoff for all catchments matched well with coefficients of determination (R2) ranging from 0.68 to 0.87. Predictions were relatively poor for: (i) the Ernies catchment (lowest rainfall, forested), and (ii) months with very high flows. Overall, the predicted mean annual streamflow was within ±8% of the observed values. Keywords: monthly streamflow, land use change, conceptual model, data-based approach, groundwater

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