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[Display omitted] • Soil loss from the furrows under rainfall is a result of interaction between interrill and rill erosion processes. • Dryland Furrow Soil Erosion (DFSE) is introduced as a new form of water erosion. • DFSE is affected by soil particle size distribution, structure, organic matter and permeability. • Soil particle size distribution is the most factor determining the DFSE in rainfed lands. Soil erosion by water is the most serious form of land degradation in dry farming lands of semi-arid regions where tillage are mostly done up and down slope which accelerate water erosion processes in the soil. Cultivated furrows are similar to rills and transport soil particles detached by interrill and rill processes during heavy rainfalls. Soil loss from the furrows is an interaction of interrill and rill erosion processes. This can be introduced as dryland furrow soil erosion (DFSE). There is limited information on the factors influencing the DFSE in semi-arid regions. A laboratory experiment was set up for ten dominant soil textures (clay loam, sandy loam, sandy clay loam, loam, loamy sand, sandy clay, silty clay loam, silty clay, silt loam and clay) in erosion flume (60 cm wide and 400 cm long) under simulated rainfalls with 50 mm h−1 for 60 min. Thirty DFSE and soil properties data were randomly divided to two groups consist of twenty data for modeling DFSE and ten data for validation of the model. The DFSE values varied from 0.014 g m−2 s−1 to 0.092 g m−2 s−1 with an average of 0.054 g m−2 s−1. The DFSE was negatively correlated with sand (r = -0.95), organic matter (r = -0.59), MWD of water-stable aggregates (r = -0.49) and infiltration rate (r = -0.46) and positively correlated with silt (r = 0.71), clay (r = 0.72), dispersible clay (r = 0.77). Multiple linear regression analysis using twenty data showed that the DFSE is related to silt and clay content (R2 = 0.92, p < 0.001). Evaluation of the model showed that the developed model has lower error with a mean absolute error of 9.11 % and a model efficiency of 0.92. Therefore, the model can be reliably used for predicting the DFSE in the similar areas in soil and rainfalls in semi-arid regions. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is believed to be an impressive factor in hydrological process, agricultural productivity, and monitoring dangerous outcomes of climate changes. The present study aimed to monitor and recognize the pattern of spatial and temporal variation of SMAP soil moisture in five subcatchments of Simineh-Zarrineh catchment in northwest of Iran from 2015 to 2017. Precipitation data of 35 meteorological stations and 287 soil moisture points were derived from the SMAP and used to monitor SM variations in the time scale. The results indicated that the SM variations are subject to precipitation variations throughout the monthly scale in the catchment. In all the seasons of this period, SM was found to have a decreasing trend from north to south of the catchment. On the contrary, no such constant pattern was observed from east to west. Oscillation SM patterns in this period were completely coordinated with the precipitation pattern. The determination coefficient between monthly SMAP soil moisture and precipitation for each subcatchment was 0.9, 0.83, 0.7, 0.84, and 0.71 for Bokan, Saqqez, Takab, Saeinqaleh, and Miandoab subcatchments, respectively. Spatial variability of standard deviation for SM values was used to find the amount of deviation from the average value during dry and wet seasons. The results revealed that in the seasonal scale, northwestern (0.067 to 0.069 cm³.cm³) and eastern parts (0.057 to 0.061 cm³.cm³) of the study area had higher values of the SM standard deviations in autumn. Additionally, according to the findings, a high value of standard deviation was observed in autumn because of irregular precipitation events and fluctuation of the temperature. [ABSTRACT FROM AUTHOR]

Soil moisture is an influential parameter in land surface hydrology and precise soil moisture data that can help researcher to realize the climate changes and land-atmosphere interactions. A initial struggle for the utilize of soil moisture data from satellite sensors is their reliability. It is important to appraise the dependability of those data before they can be regularly used at a global or local scale. In this study, the satellite soil moisture data was evaluated from the Soil Moisture Active/Passive (SMAP) over Simineh-Zarrineh Catchment in Bokan region, NW of Iran. A total of 287 soil samples as ground-based observations in the time period of 03 April to 03 December 2017 were taken for SMAP data validation. Results showed that the satellite data and in situ observation has a good correlation, with a mean correlation (r) value of 0.63 in total. This correlation level showed that, commonly, the SMAP soil moisture products over Simineh-Zarrineh Catchment (Bokan) have great quality, and it would be valuable for versatile utilization, including monitoring of land surface, weather prediction, modeling of hydrological process, soil loess monitoring, and climate studies. The results reveal that the remotely sensed data demonstrate the good correlation with in situ observation across the dry land with mean correlation (r) values of 0.67 throughout the time period. Particularly, SMAP soil moisture reveal a constant structure for obtain the spatial distribution of surface soil moisture. Additional researches are necessary for well realizing the SMAP data. [ABSTRACT FROM AUTHOR]

Interrill erodibility can be affected by soil aggregates, especially by those aggregate size classes that are dominant in the soil. In the Water erosion Prediction Project (WEPP) model, interrill soil erodibility (K i ) is estimated using very fine sand content. Despite that some studies have indicated an effect of aggregate stability on the K i , information on the relationship between the aggregate size class and K i and factors controlling it, particularly in semi-arid region is limited. This study was conducted to determine the variation of K i for different aggregate size classes under various rainfall intensities and evaluation of the WEPP model in estimating the K i for different aggregate fractions. Five aggregate size classes (0.25–2, 2–4.75, 4.75–5.6, 5.6–9.75 mm, and 9.75–12.7 mm) were separated from a sandy clay loam soil sampled in an agricultural land and put in laboratory flumes of 100 cm × 50 cm. The flumes were placed on a 9% slope and exposed to ten sequential rainfall simulations varying from 10 to 60 mm h −1 for 30 min. The K i of each aggregate size classes was determined using the interrill sediment delivery rate and compared this with the values estimated using WEPP. All physicochemical properties were also determined in the aggregate size classes. Organic matter content in the aggregate size classes was very low (0.65–0.73%) and didn't show strong relationships with the aggregate stability and hydraulic conductivity, whereas clay was major factor controlling determining these properties for the different aggregate fractions. Significant differences were found among the aggregate size classes in clay content ( P  < 0.05), aggregate stability measured using both wet-sieving method ( P  < 0.05) and water drop test method P  < 0.05, saturated hydraulic conductivity (K s ), and measured K i ( P  < 0.05). The measured K i was about 34 and 90 times bigger than the estimated K i for the fine aggregates and coarse aggregates, respectively. The fine aggregates showed higher susceptibility to interrill detachment with increasing rainfall intensity as compared with the coarse aggregates. Significant decrease was observed in the measured K i with increasing the aggregate size which was associated with increases in clay content, aggregate stability and K s . The stability of aggregates against raindrop impact (CND) was an important indicator describing the effect of aggregate size on the interrill erodibility in semi-arid soils. Therefore, this indicator can be taken into account as a soil structure measure to develop a proper equation for estimating interrill erodibility (K i ) for agricultural lands. The minimum use of tillage practices is essential to prevent aggregate breakdown and control interrill erosion in semi-arid regions. [ABSTRACT FROM AUTHOR]

There is a strong need to develop a simple method for rapid estimation of erodibility using readily available data. In this study, soil erodibility was measured using eleven soil textures at the plot scale (60 cm × 80 cm) on a slope of 9% in a semi-arid region. A total of 110 soil erosion experiments were conducted using ten simulated rainfalls (50 mm h − 1 for 30 min). A regression model was developed based on silt and clay content (R 2 = 0.82, p < 0.001) and was applied to estimate erodibility for 231 soils in the textural triangle. Kriging was used to spatial interpolate erodibility using these data to unknown soils on the textural triangle. A soil erodibility triangle was developed using kriging technique and its accuracy was evaluated using seven other soils. The technique showed a 5.4% error and allowed the prediction of soil erodibility in semi-arid areas by using the soil erodibility triangle. [ABSTRACT FROM AUTHOR]