Soil erosion modelling: A bibliometric analysis.

Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication's CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper.

Finding Possible Weakness in the Runoff Simulation Experiments to Assess Rill Erosion Changes without Non-Intermittent Surveying Capabilities.

The Terrestrial Photogrammetry Scanner (TEPHOS) offers the possibility to precisely monitor linear erosion features using the Structure from Motion (SfM) technique. This is a static, multi-camera array and dynamically moves the digital videoframe camera designed to obtain 3-D models of rills before and after the runoff experiments. The main goals were to (1) obtain better insight into the rills; (2) reduce the technical gaps generated during the runoff experiments using only one camera; (3) enable the visual location of eroded, transported and accumulated material. In this study, we obtained a mean error for all pictures reaching up to 0.00433 pixels and every single one of them was under 0.15 pixel. So, we obtained an error of about 1/10th of the maximum possible resolution. A conservative value for the overall accuracy was one pixel, which means that, in our case, the accuracy was 0.0625 mm. The point density, in our example, reached 29,484,888 pts/m². It became possible to get a glimpse of the hotspots of sidewall failure and rill-bed incision. We conclude that the combination of both approaches-rill experiment and 3D models-will make easy under laboratory conditions to describe the soil erosion processes accurately in a mathematical-physical way.

Automotive Radar in a UAV to Assess Earth Surface Processes and Land Responses.

The use of unmanned aerial vehicles (UAVs) in earth science research has drastically increased during the last decade. The reason being innumerable advantages to detecting and monitoring various environmental processes before and after certain events such as rain, wind, flood, etc. or to assess the current status of specific landforms such as gullies, rills, or ravines. The UAV equipped sensors are a key part to success. Besides commonly used sensors such as cameras, radar sensors are another possibility. They are less known for this application, but already well established in research. A vast number of research projects use professional radars, but they are expensive and difficult to handle. Therefore, the use of low-cost radar sensors is becoming more relevant. In this article, to make the usage of radar simpler and more efficient, we developed with automotive radar technology. We introduce basic radar techniques and present two radar sensors with their specifications. To record the radar data, we developed a system with an integrated camera and sensors. The weight of the whole system is about 315 g for the small radar and 450 g for the large one. The whole system was integrated into a UAV and test flights were performed. After that, several flights were carried out, to verify the system with both radar sensors. Thereby, the records provide an insight into the radar data. We demonstrated that the recording system works and the radar sensors are suitable for the usage in a UAV and future earth science research because of its autonomy, precision, and lightweight.

Evaluation of soil erosion and sediment deposition rates by the 137Cs fingerprinting technique at different hillslope positions on a catchment.

Assessment of the variation of soil erosion and sediment mobilization at different hillslope positions using the 137Cs tracing technique has been carried out for the Dapotou closed watershed, a representative depression in the karst gabin basin in Southwest China. The results showed that the annual soil erosion rates in the shoulders, backslopes, and footslopes were 0.87, 0.35 and 0.49 cm year-1, respectively, while the soil sediment deposition rate in the depression bottom was 2.68 cm year-1. The average annual soil erosion modulus of the complete hillslope was 632 t km-2year-1, which confirmed the seriousness of erosion according to the gradation of the karst soil erosion standards. For the whole catchment, the sediment delivery ratio was estimated as 0.82. To identify which factor could play the most important role in influencing the estimates using 137Cs, a linear correlation and principal component analysis were conducted. The results showed that 137Cs concentrations at different soil depths of the different hillslope positions were significantly correlated with soil organic matter and total nitrogen (P < 0.05). As this watershed is a typical karst geomorphological type, these findings are expected to provide data support for larger watershed soil erosion management and ecological restoration in fragile karst ecosystems.

Detailed assessment of spatial and temporal variations in river channel changes and meander evolution as a preliminary work for effective floodplain management. The example of Sajó River, Hungary.

The quasi-natural meandering type of alluvial rivers is quite unusual in Central European watersheds. The lack of extensive regulation allows such rivers to shift along their floodplain and cause erosion of natural and agricultural lands. Description of channel morphometric parameters over decadal timescales allows a better understanding of such river systems like Sajó River (Slovakia-Hungary) where no preliminary work is available regarding channel dynamics. In addition, to just describing the geomorphic processes, the environmental management implications of these meandering rivers need to be investigated as well. Thus, this study represents a bend-scale morphological analysis on the 124 km long section of the Sajó River in the Hungarian territory in eight different periods between 1952 and 2011. Archive aerial imagery, orthophotographs and topographical maps were organized into a database, then GIS-based analyses were performed to quantify the rate and extent of channel shifts, bend development and the area of erosion/accretion. On the bend scale, we have calculated several morphometric parameters (bend length, chord, amplitude, the radius of curvature) to quantify the evolutionary trajectory of reaches. Hydrological time series data were evaluated to reveal its possible role in the processes. Based on the available GIS-data of natural elements and anthropogenic intervention, we delineated 12 different reaches showing similar characteristics, from which six reaches were defined as natural. According to the morphometric parameters of the natural reaches, channel widths became narrower and the planform became more concentrated spatially in most of the reaches while the overall sinuosity of almost all natural reaches increased. Although artificial cutoffs mainly reduced the reach complexity, in some cases, they have accelerated the bend development downstream in the following few years. Erosion and accretion activity were higher in the periods when the discharge was higher than the effective discharge but its effect became less apparent in the second half of the investigated time period. By 1980, major artificial cutoffs and bank protection works were carried out that could have an impact in reducing the potential channel shifting. Based on our results, we propose a possible preservation and some modifications along the Hungarian part of the Sajó River reaches to be carried out by the local river management authorities. We conclude that this study provides a detailed demonstration of the Sajó River morphodymanics which can be used for further land planning to avoid harmful consequences of recent bank erosion processes not only along the Sajó River, but other similar rivers in Europe.

A comparison of different solarisation systems and their impacts on soil thermal characteristics-an application in cultivated soils close to Baghdad, a highly populated city in Iraq.

Solarisation application by mulching the soil with a polyethene plastic film has a significant influence on soil thermal characteristics (TCs), which, in turn, show a strong impact on soil energy balance and agricultural productivity. In countries like Iraq with highly populated cities, such as Baghdad, that need large quantities of agriproducts, this kind of clean energy should play a key role in sustainable agricultural production. However, little is known about the effects of different soil solarisation systems in specific cultivated fields for this country characterised by an arid climate and silty clay soils. Therefore, an experimental study was conducted to investigate changes in soil TCs under different soil solarisation systems (black and clear plastics) at three different soil depths in a two-factor factorial design. Also, both the black and clear plastic plots were compared with a control (without mulch) plot treatment. Three different soil TCs were assessed, namely soil thermal flux (qℎ), soil thermal conductivity (k), and soil volumetric heat capacity (Cv). The results of this study indicated that the soil solarisation application had a significant influence on soil TCs. Soil qℎ decreased with increasing soil depth, while k and Cv exhibited an opposite trend. The black plastic mulch treatment produced higher soil qℎ, k, and Cv values than both the clear plastic and the control treatments. Moreover, high diurnal variability of the TCs was also registered, and the clear plastic conserved a higher temperature than the black one during the night hours. During daylight, the black mulch reached a maximum temperature of 70 °C. It is recommended that more research should be conducted to get new insights on the interplay of the different seasons, and different crops and soil types.

Monitoring and assessment of seasonal land cover changes using remote sensing: a 30-year (1987-2016) case study of Hamoun Wetland, Iran.

The availability of Landsat data allows improving the monitoring and assessment of large-scale areas with land cover changes in rapid developing regions. Thus, we pretend to show a combined methodology to assess land cover changes (LCCs) in the Hamoun Wetland region (Iran) over a period of 30-year (1987-2016) and to quantify seasonal and decadal landscape and land use variabilities. Using the pixel-based change detection (PBCD) and the post-classification comparison (PCC), four land cover classes were compared among spring, summer, and fall seasons. Our findings showed for the water class a higher correlation between spring and summer (R2 = 0.94) than fall and spring (R2 = 0.58) seasons. Before 2000, ~ 50% of the total area was covered by bare soil and 40% by water. However, after 2000, more than 70% of wetland was transformed into bare soils. The results of the long-term monitoring period showed that fall season was the most representative time to show the inter-annual variability of LCCs monitoring and the least affected by seasonal-scale climatic variations. In the Hamoun Wetland region, land cover was highly controlled by changes in surface water, which in turn responded to both climatic and anthropogenic impacts. We were able to divide the water budget monitoring into three different ecological regimes: (1) a period of high water level, which sustained healthy extensive plant life, and approximately 40% of the total surface water was retained until the end of the hydrological year; (2) a period of drought during high evaporation rates was observed, and a mean wetland surface of about 85% was characterized by bare land; and (3) a recovery period in which water levels were overall rising, but they are not maintained from year to year. After a spring flood, in 2006 and 2013, grassland reached the highest extensions, covering till more than 20% of the region, and the dynamics of the ecosystem were affected by the differences in moisture. The Hamoun wetland region served as an important example and demonstration of the feedbacks between land cover and land uses, particularly as pertaining to water resources available to a rapidly expanding population.

Assessment of temporal and spatial water quality in international Gomishan Lagoon, Iran, using multivariate analysis.

Coastal lagoon ecosystems are vulnerable to eutrophication, which leads to the accumulation of nutrients from the surrounding watershed over the long term. However, there is a lack of information about methods that could accurate quantify this problem in rapidly developed countries. Therefore, various statistical methods such as cluster analysis (CA), principal component analysis (PCA), partial least square (PLS), principal component regression (PCR), and ordinary least squares regression (OLS) were used in this study to estimate total organic matter content in sediments (TOM) using other parameters such as temperature, dissolved oxygen (DO), pH, electrical conductivity (EC), nitrite (NO2), nitrate (NO3), biological oxygen demand (BOD), phosphate (PO4), total phosphorus (TP), salinity, and water depth along a 3-km transect in the Gomishan Lagoon (Iran). Results indicated that nutrient concentration and the dissolved oxygen gradient were the most significant parameters in the lagoon water quality heterogeneity. Additionally, anoxia at the bottom of the lagoon in sediments and re-suspension of the sediments were the main factors affecting internal nutrient loading. To validate the models, R2, RMSECV, and RPDCV were used. The PLS model was stronger than the other models. Also, classification analysis of the Gomishan Lagoon identified two hydrological zones: (i) a North Zone characterized by higher water exchange, higher dissolved oxygen and lower salinity and nutrients, and (ii) a Central and South Zone with high residence time, higher nutrient concentrations, lower dissolved oxygen, and higher salinity. A recommendation for the management of coastal lagoons, specifically the Gomishan Lagoon, to decrease or eliminate nutrient loadings is discussed and should be transferred to policy makers, the scientific community, and local inhabitants.

Evaluating temporal sand drift potential trends in the Sistan region, Southeast Iran.

The Sistan region in Southeastern Iran is one of the world's most sensitive areas when it comes to sandstorms and wind erosion. One of the most influential factors in interpreting sandstorms is sand drift potential (DP), which is directly related to wind speed. Accurately, monitoring this phenomenon is still being determined, considering various temporal scales. Therefore, the main aim of this research is to analyze the trend of DP on monthly and annual scales. Our results showed that monthly variations of DP reached the highest and lowest values in July (609 VU) and January (47 VU), respectively. Blowing sand predominantly moved southeast, and the directional index fluctuated from 0.88 to 0.94. The annual DP was measured equal to 2700 VU, signifying a relatively high value when compared to other arid regions worldwide. The trend analysis results obtained from the Mann-Kendall test revealed both positive trends during the period 1987-2001 and negative ones from 2002 to 2016). However, the positive trend was found statistically insignificant. Furthermore, Sen's slope test results demonstrated that a negative trend could be observed with a steeper slope during July, September, and August, while a positive trend could be observed with a steeper pitch during November, December, and June. We recommend that land managers and stakeholders involved in controlling blowing sand using biological and physical methods should consider these trends in the Sistan region. Implementing nature-based solutions or control strategies should focus on these temporal sequences.

Land-use changes and precipitation cycles to understand hydrodynamic responses in semiarid Mediterranean karstic watersheds.

Non-planned agricultural land abandonment is affecting natural hydrological processes. This is especially relevant in vulnerable arid karstic watersheds, where water resources are scarce but vital for sustaining natural ecosystems and human settlements. However, studies assessing the spatiotemporal evolution of the hydrological responses considering land-use changes and precipitation cycles for long periods are rare in karstic environments. In this research, we selected a representative karstic watershed in a Mediterranean semiarid domain, since in this belt, karst environments are prone to land degradation processes due to human impacts. Geographic Information Systems-based tools and hydrological modeling considering daily time steps were combined with temporal analysis of climate variables (wavelet analysis) to demonstrate possible interactions and vulnerable responses. Observed daily flow data were used to calibrate/validate these hydrological models by applying statistic indicators such as the NSE efficiency and a self-developed index (the ANSE index). This new index could enhance goodness-of-fit measurements obtained with traditional statistics during the model optimization. We hypothesize that this is key to adding new inputs to this research line. Our results revealed that: i) changes in the type of sclerophyllous vegetation (Quercus calliprinos, ilex, rotundifolia, suber, etc.) from 81.5% during the initial stage (1990) to natural grasslands by 81.6% (2018); and, ii) decreases in agricultural areas (crops) by approximately 60% and their transformation into coniferous forests, rock outcrops, sparsely natural grasslands, etc. in the same period. Consequently, increases in the curve number (CN) rates were identified as a result of land abandonment. As a result, an increase in peak flow events jointly with a relevant decrease of the average flow rates (water scarcity) in the watershed was predicted by the HEC-HMS model and verified through the observed data. This research provides useful information about the effects of anthropogenic changes in the hydrodynamic behaviour of karstic watersheds and water resource impacts, especially key in water-scarce areas that depict important hazards for the water supply of related populations and natural ecosystems.

Replacing chemical fertilizers with organic and biological ones in transition to organic farming systems in saffron (Crocus sativus) cultivation.

To evaluate the response of saffron to animal manure, and biological and chemical fertilizer in an arid climate, an experiment was performed as split plots based on a randomized complete blocks design with three replications during three consecutive crop growth seasons (2015-2018) at the Research Farm of University of Gonabad, Iran. The experimental treatments included application (60 t ha-1) and non-application (control) of manure as the main plot and the use of biosulfur (5 kg ha-1), biophosphate (3 L ha-1), nitroxin (3 L ha-1), chemical fertilizer (150, 100, and 100 kg ha-1 of urea, triple superphosphate, and potassium sulfate, respectively), and no fertilizer application (control) as the sub-plot. The results showed a highly significant response of the quantitative traits of saffron to the application of manure, which increased the leaf, flower, and corm indices of saffron by a mean of 15.1-35.7% than control. The interaction effect of manure with biological and chemical fertilizers for leaf, flower, and weeds indices of saffron was significant. There was no significant difference between the interaction treatments of manure and chemical fertilizer with nitroxin and biophosphorus fertilizers in most of the mentioned traits in the three experiment years. The simultaneous application of these fertilizers increased the average by about 60, 105, 135, 110, 165, and 55% of the leaf dry weight, the number of flowers, fresh flower yield, dry flower yield, dry stigma yield, and weed dry weight of saffron, respectively as compared to control. There was no significant difference between the chemical fertilizer with nitroxin or biophosphate in terms of the effect on the traits related to saffron corm so the use of these fertilizers, as compared to control, increased replacement corm weight, replacement corm size, and bud number per corm by, respectively, about 35, 60, and 40% on average. The chemical and biological fertilizers improved the content of crocin, picrocrocin, and safranal of saffron stigma. The best results were obtained from the use of chemical fertilizers, although no significant difference was observed between this treatment and the nitroxin and biophosphate treatments. Overall, the results of this three-year experiment show a very high response of the saffron plant to the simultaneous use of manure and biological fertilizers and, therefore, it is possible to replace chemical fertilizers with organic and biological fertilizers in saffron cultivation to implement organic agriculture and achieve acceptable quantitative and qualitative yields in areas similar to the experiment location.

Designing grazing susceptibility to land degradation index (GSLDI) in hilly areas.

Evaluation of grazing impacts on land degradation processes is a difficult task due to the heterogeneity and complex interacting factors involved. In this paper, we designed a new methodology based on a predictive index of grazing susceptibility to land degradation index (GSLDI) built on artificial intelligence to assess land degradation susceptibility in areas affected by small ruminants (SRs) of sheep and goats grazing. The data for model training, validation, and testing consisted of sampling points (erosion and no-erosion) taken from aerial imagery. Seventeen environmental factors (e.g., derivatives of the digital elevation model, small ruminants' stock), and 55 subsequent attributes (e.g., classes/features) were assigned to each sampling point. The impact of SRs stock density on the land degradation process has been evaluated and estimated with two extreme SRs' density scenarios: absence (no stock), and double density (overstocking). We applied the GSLDI methodology to the Curvature Subcarpathians, a region that experiences the highest erosion rates in Romania, and found that SRs grazing is not the major contributor to land degradation, accounting for only 4.6%. This methodology could be replicated in other steep slope grazing areas as a tool to assess and predict susceptible to land degradation, and to establish common strategies for sustainable land-use practices.

Assessing previous land-vegetation productivity relationships on mountainous areas hosting coming Winter Olympics Games in 2022.

In order to prevent land degradation in areas before hosting big events such as the Winter Olympic Games (WOG), developing strategic vegetation restoration plans is key. To evaluate four experimental areas with different degrees of human impacts located in the Chongli District, northern Hebei Province, China, where the coming WOG 2022 will take considering: i) the feedback mechanisms between vegetation and soil in the process of future vegetation restoration; ii) the vegetation productivity of land in different land-use types; iii) the management mode considering the sustainable development as the primary goal. To achieve these goals, we applied a minimum soil data set (MDS) to screen the most relevant indicators (soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), available phosphorus (AP), available potassium (AK), available nitrogen (AN), soil bulk density (BD), soil porosity (SP), pH, clay, silt, sand and gravel), and the nonlinear scoring method to establish a soil quality index (SQI). For this purpose, 400 soil samples (0-20 cm depth), the total biomass of one natural grassland (NG) and abandoned farmland (AF), and the growing stock of natural secondary forest (NF) and a larch plantation (LP). The results showed that the SQI can be established based on TN, silt, TP and gravel. Under LP and AF land-use type, vegetation showing a poor effect on the improvement of soil quality (SQIs were significantly lower than the NF and NG). It was also observed that above 1700 m, the growing stock of artificial vegetation exceeds the range of vegetation productivity (about 165 m3·h-1) that the land can carry under the LP. We concluded that the main reason is the excessive depletion of N and P after human impacts. On the other hand, the SQI of NF and NG were higher, which is due to the significant improvement of soil quality by the conservation of the vegetation, so that no longer limited by the spatial distribution law, also showing higher vegetation productivity of land at different altitudes. This demonstrates that it is key to develop effective restoration plans considering the soil-vegetation relationship status of the NF and NG land-use types in this area in the territories used by the activities of the WOG 2022.

Impact of Climate Change on Eye Diseases and Associated Economical Costs.

Climate change generates negative impacts on human health. However, little is known about specific impacts on eye diseases, especially in arid and semi-arid areas where increases in air temperatures are expected. Therefore, the main goals of this research are: (i) to highlight the association between common eye diseases and environmental factors; and (ii) to analyze, through the available literature, the health expenditure involved in combating these diseases and the savings from mitigating the environmental factors that aggravate them. Mixed methods were used to assess the cross-variables (environmental factors, eye diseases, health costs). Considering Southern Spain as an example, our results showed that areas with similar climatic conditions could increase eye diseases due to a sustained increase in temperatures and torrential rains, among other factors. We highlight that an increase in eye diseases in Southern Spain is conditioned by the effects of climate change by up to 36.5%; the economic burden of the main eye diseases, extrapolated to the rest of the country, would represent an annual burden of 0.7% of Spain's Gross Domestic Product. In conclusion, the increase in eye diseases has a strong economic and social impact that could be reduced with proper management of the effects of climate change. We propose a new concept: disease sink, defined as any climate change mitigation action which reduces the incidence or morbidity of disease.

Evaluation of multi-hazard map produced using MaxEnt machine learning technique.

Natural hazards are diverse and uneven in time and space, therefore, understanding its complexity is key to save human lives and conserve natural ecosystems. Reducing the outputs obtained after each modelling analysis is key to present the results for stakeholders, land managers and policymakers. So, the main goal of this survey was to present a method to synthesize three natural hazards in one multi-hazard map and its evaluation for hazard management and land use planning. To test this methodology, we took as study area the Gorganrood Watershed, located in the Golestan Province (Iran). First, an inventory map of three different types of hazards including flood, landslides, and gullies was prepared using field surveys and different official reports. To generate the susceptibility maps, a total of 17 geo-environmental factors were selected as predictors using the MaxEnt (Maximum Entropy) machine learning technique. The accuracy of the predictive models was evaluated by drawing receiver operating characteristic-ROC curves and calculating the area under the ROC curve-AUCROC. The MaxEnt model not only implemented superbly in the degree of fitting, but also obtained significant results in predictive performance. Variables importance of the three studied types of hazards showed that river density, distance from streams, and elevation were the most important factors for flood, respectively. Lithological units, elevation, and annual mean rainfall were relevant for detecting landslides. On the other hand, annual mean rainfall, elevation, and lithological units were used for gully erosion mapping in this study area. Finally, by combining the flood, landslides, and gully erosion susceptibility maps, an integrated multi-hazard map was created. The results demonstrated that 60% of the area is subjected to hazards, reaching a proportion of landslides up to 21.2% in the whole territory. We conclude that using this type of multi-hazard map may be a useful tool for local administrators to identify areas susceptible to hazards at large scales as we demonstrated in this research.

CMIP5 climate projections and RUSLE-based soil erosion assessment in the central part of Iran.

Soil erosion (SE) and climate change are closely related to environmental challenges that influence human wellbeing. However, the potential impacts of both processes in semi-arid areas are difficult to be predicted because of atmospheric variations and non-sustainable land use management. Thus, models can be employed to estimate the potential effects of different climatic scenarios on environmental and human interactions. In this research, we present a novel study where changes in soil erosion by water in the central part of Iran under current and future climate scenarios are analyzed using the Climate Model Intercomparison Project-5 (CMIP5) under three Representative Concentration Pathway-RCP 2.6, 4.5 and 8.5 scenarios. Results showed that the estimated annual rate of SE in the study area in 2005, 2010, 2015 and 2019 averaged approximately 12.8 t ha-1 y-1. The rangeland areas registered the highest soil erosion values, especially in RCP2.6 and RCP8.5 for 2070 with overall values of 4.25 t ha-1 y-1 and 4.1 t ha-1 y-1, respectively. They were followed by agriculture fields with 1.31 t ha-1 y-1 and 1.33 t ha-1 y-1. The lowest results were located in the residential areas with 0.61 t ha-1 y-1 and 0.63 t ha-1 y-1 in RCP2.6 and RCP8.5 for 2070, respectively. In contrast, RCP4.5 showed that the total soil erosion could experience a decrease in rangelands by - 0.24 t ha-1 y-1 (2050), and - 0.18 t ha-1 y-1 (2070) or a slight increase in the other land uses. We conclude that this study provides new insights for policymakers and stakeholders to develop appropriate strategies to achieve sustainable land resources planning in semi-arid areas that could be affected by future and unforeseen climate change scenarios.

Impact of roof rain water harvesting of runoff capture and household consumption.

In recent years, the occurrence of floods is one of the most important challenges facing in Hamadan city. In the absence/inefficiency of urban drainage systems, rainwater harvesting (RWH) systems as low-impact development (LID) methods can be considered as a measure to reduce the floods. In this study, three scenarios concerning the RWH from the roof surfaces are studied to evaluate the type of the harvested water on reducing flooding. In the first scenario, which indicates the current situation in the studied area, it is indicated that there is no harvest of the roof surfaces in the studied area. The second scenario is about the use of water harvested from the roof surfaces for household purposes. The third scenario also refers to the use of harvested water for irrigation of gardens. The simulation results of these three scenarios using the Soil Conservation Service (SCS) method in the Hydrologic Modeling System (HEC-HMS) model reveal that if the second scenario is implemented, the runoff volume decreases from 28 to 12% for the return period from 2 to 100 years. However, in the third scenario, this reduction in runoff volume will be 48 and 27% for return periods of 2 to 100 years, respectively. Therefore, the results of this study indicate that the use of harvested water can also affect the reduction on runoff volume.

Prediction of factors affecting activation of soil erosion by mathematical modeling at pedon scale under laboratory conditions.

Soil degradation due to erosion is a significant worldwide problem at different spatial (from pedon to watershed) and temporal scales. All stages and factors in the erosion process must be detected and evaluated to reduce this environmental issue and protect existing fertile soils and natural ecosystems. Laboratory studies using rainfall simulators allow single factors and interactive effects to be investigated under controlled conditions during extreme rainfall events. In this study, three main factors (rainfall intensity, inclination, and rainfall duration) were assessed to obtain empirical data for modeling water erosion during single rainfall events. Each factor was divided into three levels (- 1, 0, + 1), which were applied in different combinations using a rainfall simulator on beds (6 × 1 m) filled with soil from a study plot located in the arid Sistan region, Iran. The rainfall duration levels tested were 3, 5, and 7 min, the rainfall intensity levels were 30, 60, and 90 mm/h, and the inclination levels were 5, 15, and 25%. The results showed that the highest rainfall intensity tested (90 mm/h) for the longest duration (7 min) caused the highest runoff (62 mm3/s) and soil loss (1580 g/m2/h). Based on the empirical results, a quadratic function was the best mathematical model (R2 = 0.90) for predicting runoff (Q) and soil loss. Single-factor analysis revealed that rainfall intensity was more influential for runoff production than changes in time and inclination, while rainfall duration was the most influential single factor for soil loss. Modeling and three-dimensional depictions of the data revealed that sediment production was high and runoff production lower at the beginning of the experiment, but this trend was reversed over time as the soil became saturated. These results indicate that avoiding the initial stage of erosion is critical, so all soil protection measures should be taken to reduce the impact at this stage. The final stages of erosion appeared too complicated to be modeled, because different factors showed differing effects on erosion.

Effect of Wheat Straw as a Cover Crop on the Chlorophyll, Seed, and Oilseed Yield of Trigonella foeunm graecum L under Water Deficiency and Weed Competition.

The effects of water stress on fenugreek crops are well documented. However, little is known about how these plants respond to water deficits under a soil-mulching system when the surface is protected. Therefore, the current research aims to demonstrate the possibility of reducing the impact of water stress and weed competition on the fenugreek crop through the use of wheat residues as a cover crop on the soil surface. A field experiment was carried out during the winter season (2016-2017) using a split-plot design arrangement with three replicates. The experiments included four levels of water deficit, which consisted of a 40% depletion treatment as a control plot, and 50%, 60%, and 70% depletion from the field capacity (DFC) for the other studied fields. The subplot division consisted of mulching the soil with wheat residues. The results demonstrated that soil-mulching systems and a water deficit are able to impact the fenugreek yield of seed and oil. Additionally, soil mulching led to a decrease in weed density and biomass, chlorophyll content, and biological yield. Although high water deficit (70% DFC) led to yield and growth reduction, the use of wheat residue as a cover crop moderated the effect of a strong water deficit on plants and showed clear reduction of weed growth. Therefore, the results suggest that soil mulching can mitigate the adverse effects of water deficit by conserving soil moisture and decreasing weeds, which can be considered an acclimation mechanism under water-deficit conditions to avoid yield loss. Moreover, the allelopathic effects of wheat residue were observed on fenugreek crops subjected to irrigation after depleting 40% soil water moisture, but these effects disappeared within 90 days of sowing. We conclude that these results can help future agricultural planning and systems in order to increase productivity, reduce irrigation costs, and conserve soil quality.

GIS-based groundwater potential mapping in Shahroud plain, Iran. A comparison among statistical (bivariate and multivariate), data mining and MCDM approaches.

In arid and semi-arid areas, groundwater resource is one of the most important water sources by the humankind. Knowledge of groundwater distribution over space, associated flow and basic exploitation measures can play a significant role in planning sustainable development, especially in arid and semi-arid areas. Groundwater potential mapping (GWPM) fits in this context as the tool used to predict the spatial distribution of groundwater. In this research we tested four GIS-based models for GWPM, consisting of: i) random forest (RF); ii) weight of evidence (WoE); iii) binary logistic regression (BLR); and iv) technique for order preference by similarity to ideal solution (TOPSIS) multi-criteria. The Shahroud plain located in Iran, was selected to research the water scarcity and over-exploitation of groundwater resources over the past 20 years. In this research, using Iranian Department of Water Resources Management data, and extensive field surveys, 122 groundwater well data with high potential yield of ≥11 m3 h-1 were selected for GWPM. Specifically, we generated four different models selecting 70% (n = 85) of the wells and validated the resulting GWP maps upon the complementary 30% (n = 37).A total of fifteen ground water conditioning factors to explain the groundwater well distribution over the Shahroud plain were selected. From the Advanced Land Observing Satellite (ALOS), a DEM (30 m resolution) was extracted to calculate a set of morphometric properties which were combined with thematic ones such as land use/land cover (LU/LC) and Soil Type (ST). Results show that in RF (LU/LC), LR (ST), and AHP (Slope) are the most relevant contributors to groundwater occurrence. After that, using the natural break method, final maps were divided into five susceptibility classes of very low, low, moderate, high, and very high. The accuracy of models was ultimately tested using prediction rate (validation data), success rate (training data) and the seed cell area index (SCAI) indicators. Results of validation show that BLR with prediction rate of 0.905 (90.5%) and success rate of 0.918 (91.8%) had higher accuracy than WoE, RF and TOPSIS models with respective prediction rates of 0.885, 0.873 and 0.870 (88.5%, 87.3%, and 87%) and success rate of 0.900, 0.889, and 0.881 (90%, 88.9%, and 88.1%). SCAI results show that all models have acceptable classification accuracy although BLR outperformed the other models in terms of accuracy. Results show that the combination of remote sensing (RS) data and geographic information system (GIS) with new approaches can be used as a powerful tool in GWPM in arid and semi-arid areas. The results of this investigation introduced a potential novel methodology that could be used by decision-makers for the sustainable management of ground water resources.