In this research, the rate of vertical infiltration was evaluated and compared using cylinder infiltrometer method to determine the coefficients of 5 infiltration models, called Kostiakov,-Green- Ampt, Horton, Soil Conservation Service (SCS) and Philip. In 82 regions, in addition to agrology profile, soil physics properties and required parameters, infiltration was also performed 3 times by using cylinder infiltrometer. Infiltration parameters (such as time cumulative infiltration, infiltration rate, and average infiltration rate) were estimated by using above mentioned infiltration models and compared to measured amounts. The model with the most explanation coefficient (R2) and the least variance (S2) were introduced as the best model. The study of infiltration on 3 types of soil texture as clay, loam and clay loam showed that Kostiakov was the most suitable model for estimating cumulative infiltration and infiltration rate in all conditions. By increasing the duration of infiltration test, results showed that the coefficients of Kostiakov model had more fluctuation in comparison to other models and using the coefficients of Horton and Kostiakov models which were the basis of experimental data in a short duration had a considerable error for estimating cumulative infiltration in a long duration. So, it was found that Philip and SCS models were more suitable in a long duration.

BACKGROUND AND OBJECTIVES: Peak flow in watershed is important in designing and controlling soil erosion, as well as assessing the potential water yield. It also serves as a basis for assessing and managing the risk of environmental damage. However, there is no accurate information on peak flow to ensure sustainable management and conservation of Wuno Sub-Watershed in Palu Watershed which serves as a buffer for the capital of Central Sulawesi Province. Therefore, this study aimed to assess and determine the potential runoff and peak flows in watershed using soil conservation service-curve number.METHODS: Soil conservation service-curve number method was calculated to analyze rainfall from runoff as a function of cumulative rainfall, land use, soil type, and humidity. This method was developed by the United States Soil Conservation Service in 1972 and applied in this study with due consideration for several variables, including (a) land use classification and intensity for settlements, rice fields, plantations, rivers, etc., (b) basic physical conditions of the area such as rainfall and hydrology, as well as (c) classes of soil hydrology significantly influencing carbon-nitrogen value.FINDINGS: The result showed that carbón-nitrogen values for all types of land use or cover were in normal conditions from 5 to 25 years. Moreover, carbón-nitrogen range was observed to have significantly large quantitative consequences on direct runoff. The trend showed the need for precision and effectiveness in planning watershed management and conservation. Soil conservation service also had a positive influence on land use, specifically runoff, as observed in carbón-nitrogen values for return periods of 2, 5, 25, and 100 years. However, several other factors were identified to influence land use such as land cover and soil texture.CONCLUSION: Soil Conservation Service presented an analysis of how land use affected runoff, specifically with a focus on carbon-nitrogen values. Land use was not only affected by carbon-nitrogen values but other factors such as land cover and geomorphometric properties. The trend showed the need for a more comprehensive exploration of soil conservation service-curve number method in accurately predicting runoff patterns in sub-watershed areas to ensure effective and sustainable management and conservation practices. 

Runoff assessment and estimation are crucial for watershed management as it provides information that is needed to expedite the course of watershed planning and development. The most commonly used model due to its simplicity and versatility in runoff estimation is the soil conservation service curve number developed by the United States Department of Agriculture. The study estimates the surface runoff of Upper Benue watershed using a geospatial based soil conservation service curve number model. Datasets utilized for this purpose are; Rainfall, land use, digital elevation model and FAO-Soil. The soil and land use data were intersected to create the curve number grid and database. The curve number grid combined with the mean annual rainfall data from 1990 – 2017 was used to estimate runoff. The result revealed that 61. 5% of rainfall was direct runoff while tree/plant cover and soil retained 38. 5% of the rainfall. The average curve number for the normal condition was calculated to be 80. 1 while the dry and wet season was 59. 6, and 93. 2 respectively. The average runoff volume for 27 years was estimated to be 69, 887. 43mm3. A correlation coefficient of 0. 79 was found for the relationship between rainfall and runoff. The research highlights the importance of geospatial technique when integrated with soil conservation service curve number to estimate runoff conditions in Upper Benue Watershed.

Water infiltration is one of the most important properties of soil that plays an important role in watershed management. The main purpose of this study was to estimate the coefficients of different equations of water infiltration into soil, including Philip, Kostyakov, Kostyakov-Louise, Horton, and SCS to estimate the infiltration rate and potential for runoff in long-duration rainfall in two land uses (rangeland and agricultural) and three soil textures (loam, clay loam, and silty clay loam). These models were fitted to the measured infiltration data to estimate the model parameters and find a suitable model for this region. After estimating the parameters, the infiltration rates for 2, 4 and 24 hours were calculated using the infiltration rate equations of each model. For this purpose, the infiltration data were obtained by double rings method from 16 point of different regions in the basin. The parameters of these models were then obtained, using least square optimization method. In order to evaluate the accuracy of the models, the coefficient of determination (R2), Nash Sutcliffe (NSE) efficiency, root mean square error (RMSE) and mean error (ME) were calculated. Comparisons of the mean of evaluation statistics using the Tukey method showed that the method of estimating cumulative infiltration in the Kostyakov-Louise model had a more-stable trend compared to other models and was evaluated as the best in most soil texture classes and land uses. Means comparisons showed that despite the differences between the models in estimating the cumulative infiltration, the differences between the models in estimating the infiltration rate were not significant and were in the same group. Regardless of the model used, soil texture and land use are the two main factors affecting the final infiltration rate. According to the results, the rate of infiltration with time in agricultural use has significant changes, such that, in this use, it was initially high and decreased sharply with increasing time from 2 hours to 24 hours. In order to reduce the weakening effects of agricultural activities on soil quality and to increase the infiltration rate in long-duration rainfall and reduce runoff, management activities such as expansion of conservation agriculture, no-tillage, and minimum tillage farming operations will play a very effective role.

Locating the occurrence of flood has been very difficult using common and traditional methods. And most of the time leads to errors. The soil conservation service (SCS) of the U.S has developed a method for runoff estimation due to the accuracy of the SCS method, in this study, is used to estimate the risk of floods of SCS-CN method. purpose of this study, to estimate the risk of floods is using SCS-CN. In this method, due to the hydrological groups of soil and slope area, was obtained curve number or CN. Average CN shows number 87 in this basin. Therefore, using climatological stations, the average rainfall estimated 304 mm. Results showed that due to the loss of vegetation, expansion of the city from the south, land use change and the form basin is to be Stretched, in the southern part of the basin,  the probability of flooding is greater than the rest of the basin.

Extended Abstract Background: Soil erosion, a significant form of land degradation, poses severe challenges to humanity in different ecosystems. It serves as a comprehensive index for evaluating the development and sustainability of land management programs. Assessing the status and spatial extent of soil erosion has become crucial in developing countries. Biological management, a recommended and effective means of controlling soil erosion in the early stages of all processes, offers a practical solution. Biological methods, such as minimum tillage operations and limited intervention in nature, prove to be more cost-effective and efficient than structural measures. Despite these advantages, biological measures have not received adequate attention in soil erosion control. This research addresses this gap by applying biological management in the Kilanbar Watershed (Kermanshah Province, Iran), demonstrating its effectiveness and cost-efficiency. Methods: The layers of elevation from sea level, aspect, and slope steepness were prepared and combined in the geographic information system (GIS) software to prepare 38 land units. In the Kilanbar Watershed, 14 land units with the ability to perform biological management measures were extracted based on the expert and technical opinions of the watershed manager and considering different bases to improve the performance and decision-making of the units with an area of less than 300 ha. The Kilanbar Watershed is located in Ravansar City, west of Kermanshah Province. The study area is approximately 10798 ha. The highest and lowest elevation points of the watershed are 2183 and 1388 m above mean sea level, respectively. The mean annual precipitation, temperature, and relative humidity are 533 mm, 11.4 °C, and 45.1%, respectively. The status of soil erosion in each land unit was completed based on the scoring of the BLM form based on the visual and expert opinions, and a map of the erosion pattern was prepared in the land units. Ambrotropic and hyetographs were drawn using the 30-year precipitation and temperature data of the Ravansar synoptic station to determine the periods of drought and wet conditions and to identify suitable plants with the characteristics of the region. A climatic–agricultural map was prepared and integrated into the GIS using meteorological station data (temperature, precipitation, evaporation, and transpiration), and plant species were selected according to ecological expectations for watershed biological measures. Results: According to the BLM form results, one and eight land units are in partial and low erosion conditions, respectively, and five other land units are in medium erosion conditions. According to the erosion pattern map, the majority of the studied area, about 70% of the watershed, is in a low and medium erosion state, which naturally confirms the high ability to use appropriate biological measures to control soil erosion. According to ambrothermic and hyetograph measurements, June to September were dry months, and precipitation changes were more significant than temperature changes from October to May. According to the climatic–agricultural map, the region is divided into five classes. Class 4 (4819.3 ha) and Class 1 (364.83 ha) had the largest and smallest areas, respectively. Finally, the zoning of suitable rangeland species in the watershed showed that rangeland species of Asteragalus ascendes, Avena fatua, Picnomon sp., Achillea millefolium, Bromus tomentellus, and Hordum blubosum dominantly covered the region. Based on the study results, appropriate plant species were introduced for the studied watershed. Accordingly, conservation and reclamation measures were recommended to improve land productivity and ecological conditions and avoid land use changes for the study area. The essential measures include vegetation in rangeland ecosystems aiming at preventing the role of the canopy cover from directly impacting raindrops on the soil surface, increasing water infiltration in the soil, stabilizing soil aggregates due to roots extension, increasing grazing capacity and livestock production, and increasing its efficiency and productivity with time. Conclusion: The findings of this study hold significant potential for the Kilanbar Watershed. The proposed biological erosion measures, tailored to the ecosystem's unique conditions, are effective, low-cost, and environmentally compatible. They offer a sustainable solution for managing soil and water resources in various ecosystems. Implementing these measures can significantly reduce soil erosion in the watershed, particularly in areas with low to moderate erosion status. This research is an essential initiative in applying biological erosion measures in the Kilanbar Watershed, demonstrating that soil erosion can be effectively and practically controlled in approximately 67% of the watershed through biological methods in the critical land-use areas of rangelands and agriculture. It is important to note that applying biological erosion measures requires comprehensive and integrated investigations, considering the different parts of the ecosystem. With these findings, the proposed approach in this research can be extended to other watersheds across the country, particularly those with slight to moderate erosion status, while maintaining the principle of comprehensiveness and respecting the unique conditions of each watershed.

Soil conservation service-curve number (SCS-CN) method is one of the most employed methods for computing discharge as well as surface runoff from watersheds. Recent studies show that this much-used method is susceptible to difference in curve number. As a result, much caution is recommended in its application. In this research the above-mentioned method was used and it was found that the asymptotic method would give a better SCS Table method for determining curve number. Results also reveal least peak-flood differences between observed and calculated discharge in the asymptotic method. The discharge while using SCS Table method in different antecedent moisture conditions shows a larger difference with the observed discharge.