Comparing Rainfall Erosivity Estimation Methods Using Weather Radar Data for the State of Hesse (Germany)

Rainfall erosivity exhibits a high spatiotemporal variability. Rain gauges are not capable of detecting small-scale erosive rainfall events comprehensively. Nonetheless, many operational instruments for assessing soil erosion risk, such as the erosion atlas used in the state of Hesse in Germany, are still based on spatially interpolated rain gauge data and regression equations derived in the 1980s to estimate rainfall erosivity. Radar-based quantitative precipitation estimates with high spatiotemporal resolution are capable of mapping erosive rainfall comprehensively. In this study, radar climatology data with a spatiotemporal resolution of 1 km2 and 5 min are used alongside rain gauge data to compare erosivity estimation methods used in erosion control practice. The aim is to assess the impacts of methodology, climate change and input data resolution, quality and spatial extent on the R-factor of the Universal Soil Loss Equation (USLE). Our results clearly show that R-factors have increased significantly due to climate change and that current R-factor maps need to be updated by using more recent and spatially distributed rainfall data. Radar climatology data show a high potential to improve rainfall erosivity estimations, but uncertainties regarding data quality and a need for further research on data correction approaches are becoming evident.

Soil organic carbon and nutrients losses form the sloping land in the scenario of water erosion in the south of Rwanda

<p><strong>Abstract:</strong>Rwanda is located in the plateau of the central-eastern Africa nearby the equator of the Earth, known as ’The Land of a Thousand Hills’, and covers the part of the region of the Upper Nile. The sloping lands are ubiquitous across Rwanda, and the sloping farmlands account for more than 70 per cent of the sloping land resources. The soil and water losses are very severe on the sloping lands, especially on the sloping farmlands due to the farming activities and soil water erosion induced by the erosive rainfall events. Therefore, the soil erosion and soil organic carbon (SOC) and nutrient losses and the resultant soil deterioration and crop yield decline on the sloping farmlands in this country have attracted the widespread concerns. It is necessary to understand severity of the SOC and nutrient losses on the sloping farmland due soil erosion in term of launching the countermeasure to control the losses. The investigation on the SOC and nutrient losses in the sloping farmlands and the rainfall was carried out on the runoff plot with 20m long, 5m wide and gradient of 12°in Rubona, Huye District, south province of Rwanda. The cropping rotation of soybean-maize-groundnut was practiced on the plot during the monitor on soil losses from the plot. The contents of constituents of soils lost from the plot decreased in the order: SOC> total potassium (TK)>total nitrogen (TN)>total phosphorus (TP). The loss intensities of SOC from the plot varied from 383.0 kg/hm<sup>2</sup> to 1680.9 kg/hm<sup>2</sup> in the period from 2011 to 2013, 259.4 kg/hm<sup>2</sup> to 1138.5 kg/hm<sup>2</sup> for TK, 41.2 kg/hm<sup>2</sup> to 180.8 kg/hm<sup>2</sup> for TN, 9.2 kg/hm<sup>2</sup> to 40.2 kg/hm<sup>2</sup> for TP. The loss intensities of SOC, TK, TN and TP were 1262.3 kg/hm<sup>2</sup>, 99.0 kg/hm<sup>2</sup>, 99.4 kg/hm<sup>2</sup>, 35.4 kg/hm<sup>2</sup> in 2017, and 3786.8 kg/hm<sup>2</sup>, 2970.0 kg/hm<sup>2</sup>, 298.1 kg/hm<sup>2</sup> and 106.3 kg/hm<sup>2</sup> in 2018, respectively. The loss intensities of SOC and nutrients varied significantly over the years. It can be seen that the amounts of erosive rainfall have the crucial impacts on loss intensities of SOC and nutrients through analyzing the relation between loss intensities and erosive rainfall. The relations between loss intensities of SOC and nutrients and mounts of erosive rainfall can be described by exponential function. Compared with the loss intensities of SOC and nutrients on the runoff plot, the loss intensities were much less on the plots with the corresponding soil and water conservation measures such as terracing and plant hedges. Therefore, the measures of anti-erosion should be adopted on the sloping farmlands in an effort to reduce SOC and nutrient losses and keep the sustainable soil productivity in Rwanda. </p><p><strong>Keywords:</strong> SOC; nutrient; sloping farmland, Rwanda</p>

The Thresholds of Sediment-Generating Rainfall from Hillslope to Watershed Scales in the Loess Plateau, China

Obtaining practical thresholds for erosive rainfall plays a crucial role in calculating rainfall erosivity and predicting water erosion. Nevertheless, the study of thresholds on subwatershed and watershed scales remains scarce. Given this, we presented the critical rainfall that generated the outflows of subwatersheds and watersheds as the threshold of sediment-generating rainfall. On the basis of the observation of twelve nested topographical units at the Peijiamaogou watershed in the Loess Plateau of China, we fitted regression relationships between rainfall indexes (rainfall amount, maximum 30-min intensity, maximum 60-min intensity, rainfall amount multiply maximum 30-min intensity, and rainfall amount multiply maximum 60-min intensity) and the proportion of cumulative sediment yield to the total sediment yield. We determined the thresholds of sediment-generating rainfall and explored the variabilities of thresholds across different spatial scales. Moreover, the covering area proportion (CAP) with rainfall indexes higher than the thresholds was also employed as thresholds at the subwatershed and watershed scales. The thresholds of CAP for P and I30 were 50.5% and 47.6% at the subwatershed scale, while 31.0% and 30.3% at the watershed scale. The thresholds of P and I30 at the subwatershed scale were higher than those of hillslope scale, while the threshold of I30 at the watershed scale was smaller compared to the other scales. In general, I30 was viewed as the best threshold among single rainfall indexes across different spatial scales, while P was not recommended as a practical threshold. This study can improve the prediction accuracy of water erosion across different spatial scales and develop the spatial scale effect of sediment yield in the loess hilly areas.

Environmental Conditions Of Zakamensk Town (Dzhida River Basin Hotspot)

Ecological problems of Zakamensk town are associated with sand deposits that were formed as a result of mining activities of former Dzhidinsky tungstenmolybdenum plant. Sands are accumulated in large quantities and they contain dangerous concentrations of heavy metals. Desertification in an urbanized area is manifested locally, but it differs from agricultural desertification by a profound and comprehensive destructive change in the components of the environment. Maps of soils, vegetation, types of lands, as well as ecological zoning maps of Zakamensk were created. The basis for the creation of electronic maps using GIS were stock, archive and own materials, topographic maps and remote sensing data. Urbanized desertification in Zakamensk is caused by chemical contamination of sandy eluvium, the spreading of pollutants by water flows and wind currents. Erosion occurs both in the form of flat flushing and linear erosion. The most intensive is gully erosion. Quantitative parameters of temporal variability of the erosive rainfall potential for the Zakamensk town are received. The quantitative characteristics of loads of pollutants on the territory of the town are determined on the basis of the erosion-deflation models. The calculations showed that 204 tons/ha of contaminated sand annually falls into the settlement area with water-erosion flows (Pb – 3.7 tons, W – 4.3 tons). Moreover, active wind activity led to the deposition of more metals (Pb – 5.6 tons, W – 6.5 tons) in the town.

Filling the gap between plot and landscape scale – eight years of soil erosion monitoring in 14 adjacent watersheds under soil conservation at Scheyern, Southern Germany

Watershed studies are essential for erosion research because they embed real agricultural practices, heterogeneity along the flow path, and realistic field sizes and layouts. An extensive literature review covering publications from 1970 to 2018 identified a prominent lack of studies, which (i) observed watersheds that are small enough to address runoff and soil delivery of individual land uses, (ii) were considerably smaller than erosive rain cells (<400 ha), (iii) accounted for the episodic nature of erosive rainfall and soil conditions by sufficiently long monitoring time series, (iv) accounted for the topographic, pedological, agricultural and meteorological variability by measuring at high spatial and temporal resolution, (v) combined many watersheds to allow comparisons, and (vi) were made available. Here we provide such a dataset comprising 8 years of comprehensive soil erosion monitoring (e.g. agricultural management, rainfall, runoff, sediment delivery). The dataset covers 14 adjoining and partly nested watersheds (sizes 0.8 to 13.7 ha), which were cultivated following integrated (four crops) and organic farming (seven crops and grassland) practices. Drivers of soil loss and runoff in all watersheds were determined with high spatial and temporal detail (e.g., soil properties are available for 156 m2 blocks, rain data with 1 min resolution, agricultural practices and soil cover with daily resolution). The long-term runoff and especially the sediment delivery data underline the dynamic and episodic nature of associated processes, controlled by highly dynamic spatial and temporal field conditions (soil properties, management, vegetation cover). On average, the largest 10 % of events lead to 85.4 % sediment delivery for all monitored watersheds. The analysis of the Scheyern dataset clearly demonstrates the distinct need for long-term monitoring in runoff and erosion studies.

How rainfall event characteristics affect the applicability of I₃₀ as an index of intense or erosive rainfall: a brief review with proposed new rainfall index

In many fields, the intensity of rainfall events is expressed using indexes such as I30, the wettest 30-minute interval within a rainfall event. Various limitations attend this usage: I30 cannot be estimated for rainfall events shorter than 30 minutes, including many intense convective storms, and it represents a diminishing proportion of increasingly long rainfall events (representing 10 % of the duration of a 5-hour event but declining to < 2 % of the duration in a 30-hour event). These and other issues connected with I30 and related indices based on fixed clock periods (I15, I60, etc.) can be eliminated if instead, a nominated fraction of the event duration is used as an index, such as the wettest 5 % of the event duration. This index (termed EDf5) can be derived for both short and long rainfall events. Illustrative results are presented for two Australian locations having high-resolution rainfall data and contrasting rainfall climatologies, one arid and one wet tropical. The value of I30 is similar at both sites (7.7 mm h-1 and 7.9 mm h-1) and fails to differentiate between them. In contrast, the average intensity of the wettest 5 % of event durations (EDf5) at the arid site is 7.4 mm h-1, whilst at the wet tropical site, the corresponding value is 3.8 mm h-1. Thus, the EDf5 index indicates a greater concentration of rain at the arid site (i.e., intensity sustained for 5 % of event duration at the wet tropical site is lower). Results exemplify the capacity of the EDf5 index to be applied to short, intense events. The use of a fixed 30-minute clock period to describe intensity at the contrasting field locations has less discriminatory power and may be of less use in the investigation of rainfall characteristics that drive landsurface processes.

Temporal and Elevation Trend Detection of Rainfall Erosivity Density in Greece

This paper presents certain characteristics of trends in rainfall erosivity density (ED), that have not been so far investigated in depth in the current literature. Raw pluviograph data were acquired from the Greek National Bank of Hydrological and Meteorological Information for 108 stations. Precipitation time series values were cleared from noise and errors, and the ratio of missing values was computed. Erosive rainfalls were identified, their return period was determined using intensity–duration–frequency (IDF) curves and erosivity values were computed. A Monte Carlo method was utilized to assess the impact of missing values ratio to the computation of annual erosivity (R) and ED values. It was found that the R values are underestimated in a linear way, while ED is more robust against the presence of missing precipitation values. Indicatively, the R values are underestimated by 49%, when only 50% of the erosive rainfall events are used, while at the same time the estimation error of ED is 20%. Using predefined quality criteria for coverage and time length, a subset of stations was selected. Their annual ED values, as well as the samples' autocorrelation and partial autocorrelation functions were computed, in order to investigate the presence of stochastic trends. Subsequently, Kendall's Tau was used in order to yield a measure of the monotonic relationship between annual ED values and time. Finally, the hypothesis that ED values are affected by elevation was tested. In conclusion: (a) It is suggested to compute ED for the assessment of erosivity in Greece instead of the direct computation of R; (b) stationarity of ED was found for the majority of the selected stations, in contrast to reported precipitation trends for the same time period; and (c) the hypothesis that ED values are not correlated to elevation could not be rejected.