States Soil Conservation Service Research Articles

MAXIMUM FLOW STUDY BY THE HYDROGRAM METHOD FOR A WATERSHED IN THE SOUTH OF SANTA CATARINA, BRAZIL

Knowing the maximum flow and its return period is extremely important for safely dimension hydraulic projects for flood prediction and control and also water erosion prediction. Thus, this study aimed to evaluate Capivari river watershed maximum flow, located in south of Santa Catarina, that has a flooding history. The method used was The United States Soil Conservation Service (SCS) Triangular Unit Hydrogram method (current Natural Resources Conservation Service), and, for effective rainfall, the US Curve Number (SCS-CN) method is used. To estimate the maximum flow in the watershed, three background moisture scenarios (CNI, CNII and CNIII) and six empirical equations proposed for rural watersheds were adopted to calculate the concentration time. To evaluate the observed upstream flow, a 34-years historical series was used, measured at the São Martinho downstream fluviometric station (code 84598002), located in the outlet section of the study watershed. The results showed that the maximum flows estimated by the SCS-CN method for the conditions of CNII and CNIII had greater differences (-198% and -287%) compared to the observed flow. The smallest differences were verified for the CNI condition for all the analyzed return periods (2, 5, 10, 15, 20, 25, 50 and 100). Also, it was observed that, the longer is the return period, smaller the difference among the maximum observed and estimated flows, and, the smallest was verified for the 50-year period, indicating that this is the most appropriate for studies of extreme events in the study watershed.

Time distribution of heavy rainfall events in south west of Iran

Accurate knowledge of rainfall time distribution is a fundamental issue in many Meteorological-Hydrological studies such as using the information of the surface runoff in the design of the hydraulic structures, flood control and risk management, and river engineering studies. Since the main largest dams of Iran are in the south-west of the country (i.e. South Zagros), this research investigates the temporal rainfall distribution based on an analytical numerical method to increase the accuracy of hydrological studies in Iran. The United States Soil Conservation Service (SCS) estimated the temporal rainfall distribution in various forms. Hydrology studies usually utilize the same distribution functions in other areas of the world including Iran due to the lack of sufficient observation data. However, we first used Weather Research Forecasting (WRF) model to achieve the simulated rainfall results of the selected storms on south west of Iran in this research. Then, a three-parametric Logistic function was fitted to the rainfall data in order to compute the temporal rainfall distribution. The domain of the WRF model is 30.5N–34N and 47.5E–52.5E with a resolution of 0.08 degree in latitude and longitude. We selected 35 heavy storms based on the observed rainfall data set to simulate with the WRF Model. Storm events were scrutinized independently from each other and the best analytical three-parametric logistic function was fitted for each grid point. The results show that the value of the coefficient a of the logistic function, which indicates rainfall intensity, varies from the minimum of 0.14 to the maximum of 0.7. Furthermore, the values of the coefficient Bof the logistic function, which indicates rain delay of grid points from start time of rainfall, vary from 1.6 in south-west and east to more than 8 in north and central parts of the studied area. In addition, values of rainfall intensities are lower in south west of IRAN than those of observed or proposed by the SCS values in the US.

Comparison between the United States Soil Conservation Service (SCS) and the two models commonly used for estimating rainfall-runoff in south-eastern Botswana

The United States Soil Conservation Service (SCS) curve number method is used to estimate rainfall runoff from three sub-watersheds in South-Eastern Botswana. This approach uses the NASA Endeavour Shuttle Radar Topography Mission (SRTM) DEMs, digital soil data from the Botswana Ministry of Agriculture, rainfall data from the Department of Meteorological Services and land-use data derived from Landsat ETM+ imagery. Runoff predicted from the SCS method is compared with the runoff calculated using the Pitman and Monash models and the gauged runoff. The Thagale River system watershed produces a mean annual volume of 7.2 Mm3 while the Notwane and Metsimotlhabe runoff volumes are 19.9 Mm3 and 17.8 Mm3 respectively. The SCS Model is found to be either over- or under-estimating the mean annual runoff volumes found using the other two models. It is concluded that more mean annual runoff volumes should be established for the whole country using the three models and a correlation analysis made in order to determine the superior model. The SCS Model uses a lot of Earth Observation (EO) and other data found in different government departments, hence this encourages collaboration. It is further observed that the SCS Model is quick to produce results, does not require stream gauging and can also easily be updated as the land use/land cover changes. Water SA Vol 32(1)pp:29-36

Drainage Investment and Wetlands Loss: an Analysis of the National Resources Inventory Data

The United States Soil Conservation Service (SCS) conducts a survey for the purpose of establishing an agricultural land use database. This survey is called the National Resources Inventory (NRI) database. The complex NRI land classification system, in conjunction with the quantitative information gathered by the survey, has numerous applications. The current paper uses the wetland area data gathered by the NRI in 1982 and 1987 to examine empirically the factors that generate wetland loss in the United States. The cross-section regression models listed here use the quantity of wetlands, the stock of drainage capital, the realty value of farmland and drainage costs to explain most of the cross-state variation in wetland loss rates. Wetlands preservation efforts by federal agencies assume that pecuniary economic factors play a decisive role in wetland drainage. The empirical models tested in the present paper validate this assumption.