SWAT manual calibration and parameters sensitivity analysis in a semi-arid watershed in North-western Morocco

Being a laborious approach, manual calibration of hydrologic model in a semi-arid context requires in-depth knowledge of the watershed and as much as possible field input data to obtain reliable simulations. In this study, manual calibration and relative sensitivity analysis approaches of the SWAT model (Soil and Water Assessment Tool) were applied for water balance in a 1993 km² watershed (on the R’dom river) located in North-western Morocco. The watershed is located in a semi-arid area dominated by agro-forestry activities. The objectives of this study were (i) to perform a local sensitivity analysis of the SWAT model taking into consideration the watershed characteristics and (ii) to implement a detailed methodology of manual calibration and validation of the model in a semi-arid context. Sensitivity analysis has been carried out on 12 different SWAT input parameters, and has revealed that 4 input parameters only were the most influential ones on flow components of the R’dom watershed. Model manual calibration was conducted along 2006 and 2007 by comparing measured and predicted monthly and daily discharges and taking Nash-Sutcliffe coefficient (NSE), determination coefficient (R ²), and percent bias (PBIAS) as goodness-of-fit indicators. Validation has been performed by the same approach through 2008 and 2009 period. All final NSE values were above 0.5, R ² values exceeded 0.7, and PBIAS lower than 25% demonstrating satisfactory model performances over the study watershed conditions. The SWAT model set-up with measured input data, manually calibrated and validated, reflects well the real hydrologic processes occurring in the R’dom watershed and can be used to assess current and future conditions and to evaluate alternative management practices.     

Use of SWAT to determine the effects of climate and land use changes on streamflow and sediment concentration in the Purna River basin,India

A semi-distributed, physically based, basin-scale Soil and Water Assessment Tool (SWAT) model was developed to determine the key factors that influence streamflow and sediment concentration in Purna river basin in India and to determine the potential impacts of future climate and land use changes on these factors. A SWAT domain with a Geographical Information System (GIS) was utilized for simulating and determining monthly streamflow and sediment concentration for the period 1980–2005 with a calibration period of 1980–1994 and validation period of 1995 to 2005. Additionally, a sequential uncertainty fitting (SUFI-2) method within SWAT-CUP was used for calibration and validation purpose. The overall performance of the SWAT model was assessed using the coefficient of determination (R²) and Nash–Sutcliffe efficiency parameter (E_NS) for both calibration and validation. For the calibration period, the R² and E_NS values were determined to be 0.91 and 0.91, respectively. For the validation period, the R² and E_NS were determined to be 0.83 and 0.82, respectively. The model performed equally well with observed sediment data in the basin, with the R² and E_NS determined to be 0.80 and 0.75 for the calibration period and 0.75 and 0.65 for the validation, respectively. The projected precipitation and temperature show an increasing trend compared to the baseline condition. The study indicates that SWAT is capable of simulating long-term hydrological processes in the Purna river basin.     

Evaluation of the SWAT model for water balance study of a mountainous snowfed river basin of Nepal

In this study, a semi-distributed hydrologic model Soil and Water Assessment Tool (SWAT) has been employed for the Karnali River basin, Nepal to test its applicability for hydrological simulation. Further, model was evaluated to carry out the water balance study of the basin and to determine the snowmelt contribution in the river flow. Snowmelt Runoff Model (SRM) was also used to compare the snowmelt runoff simulated from the SWAT model. The statistical results show that performance of the SWAT model in the Karnali River basin is quite good (p-factor = 0.88 and 0.88, for daily calibration and validation, respectively; r-factor = 0.76 and 0.71, for daily calibration and validation, respectively). Baseflow alpha factor (ALPHA_BF) was found most sensitive parameter for the flow simulation. The study revealed that the average annual runoff volume available at the basin outlet is about 47.16 billion cubic metre out of which about 12% of runoff volume is contributed by the snowmelt runoff. About 25% of annual precipitation seems to be lost as evapotranspiration. The results revealed that both the models, SWAT and SRM, can be efficiently applied in the mountainous river basins of Nepal for planning and management of water resources.     

Determination of water balance equation components in irrigated agricultural watersheds using SWAT and MODFLOW models : A case study of Samalqan plain in Iran

Increasing water demands,especially in arid and semi-arid regions,continuously exacerbate groundwater as the only reliable water resources in these regions.Samalqan watershed,Iran,is a groundwater-based irrigation watershed,so that increased aquifer extraction,has caused serious groundwater depletion.So that the catchment consists of surface water,the management of these resources is essential in order to increase the groundwater recharge.Due to the existence of rivers,the low thickness of the alluvial sediments,groundwater level fluctuations and high uncertainty in the calculation of hydrodynamic coefficients in the watershed,the SWAT and MODFLOW models were used to assess the impact of irrigation return flow on groundwater recharge and the hydrological components of the basin.For this purpose,the irrigation operation tool in the SWAT model was utilized to determine the fixed amounts and time of irrigation for each HRU(Hydrological Response Unit)on the specified day.Since the study area has pressing challenges related to water deficit and sparsely gauged,therefore,this investigation looks actual for regional scale analysis.Model evaluation criteria,RMSE and NRMSE for the simulated groundwater level were 1.8 m and 1.1%respectively.Also,the simulation of surface water flow at the basin outlet,provided satisfactory prediction(R²=0.92,NSE=0.85).Results showed that,the irrigation has affected the surface and groundwater interactions in the watershed,where agriculture heavily depends on irrigation.Annually 11.64 Mm3 water entered to the aquifer by surface recharge(precipitation,irrigation),transmission loss from river and recharge wells 5.8 Mm3 and ground water boundary flow(annually 20.5 Mm³).Water output in the watershed included ground water extraction and groundwater return flow(annually 46.4 Mm³)and ground water boundary flow(annually 0.68 Mm³).Overally,the groundwater storage has decreased by 9.14 Mm3 annually in Samalqan aquifer.This method can be applied to simulate the effects of surface water fluxes to groundwater recharge and river-aquifer interaction for areas with stressed aquifers where interaction between surface and groundwater cannot be easily assessed.     

Simulation of nitrogen and phosphorus loads in the Dongjiang River basin in South China using SWAT

Population growth, urbanization, and intensified agriculture have resulted in mobilization of nitrogen and phosphorus, which is the main cause of river water quality deterioration. Environmental regulation has expedited the necessity for agricultural producers to design and implement more environmentally suitable practices. Therefore, there is a need to identify critical nutrients and their loss/transport potential. Watershed model can be used to better understand the relationship between land use activities/management and hydrologic processes/water quality changes that occur within a watershed. The objective of the study is to test the performance of the SWAT model and the feasibility of using this model as a simulator of water flow and nitrogen and phosphorus yields over the Dongjiang River basin in South China. Spatial data layers of land slope, soil type, and land use were combined with geographic information system (GIS) to aid in creating model inputs. The observed streamflow and sediment at Boluo station in the Dongjiang River basin were used to calibrate and validate the model. Time series plots and statistical measures were used to verify model predictions. Predicted values generally matched well with the observed values during calibration and validation (R ²≥0.6 and Nash-Suttcliffe Efficiency ≥0.5) except for underestimation of sediment peaks and overestimation of sediment valleys at Boluo. This study shows that SWAT is able to predict streamflow, sediment generation, and nutrients transport with satisfactory results.     

Determination of areas vulnerable to pollution in a karstic river basin in Turkey via a decision support system based on DRASTIC,SWAT and isotopes analysis

Determination of areas vulnerable to water pollution in river basins helps to generate appropriate water management protection plans. This study aims to define areas vulnerable to pollutants in a data-scarce karstic river basin in Turkey by using a holistic approach integrating the Soil and Water Assessment Tool (SWAT), the DRASTIC framework, and selected isotopes within a decision support system based on a geographic information system to delineate vulnerable areas. DRASTIC was used to show groundwater vulnerability to pollutants. The concentrations of isotopes ¹⁸O, ²H, and ³H in groundwater were used to define the vulnerable areas of the karst region. SWAT was utilized to show watershed vulnerability to pollutants in shallow aquifers. The recharge rate parameter in DRASTIC was obtained from SWAT. This methodological approach was applied to the Yuvacık Dam Basin in Kocaeli, part of the Marmara River Basin, as it is a good example of a karstic watershed. According to this study, each approach provides different vulnerabilities when applied separately. The final map obtained from the integrated approach shows that drinking water supplies in the northeast and northwest parts of the basin are highly vulnerable to pollution. All the karst spring catchments and areas near the basin outlet are highly vulnerable. Moreover, across all water samples taken across the basin, those exhibiting the highest concentrations in nitrate were all found in the areas mapped as highly vulnerable. The methodology was validated by analyzing nitrate concentration in 22 groundwater and surface-water samples.

     

Parameters optimization based on the combination of localization and auto-calibration of SWAT model in a small watershed in Chinese Loess Plateau

This study simulated the watershed flow and sediment responses based on calibration of the SWAT model in the semi-arid Chinese Loess Plateau (LP) where soil erosion intensively occurs. After the model’s initiation and manual modification, a 7-year inconsecutively observed flow and sediment data from 1984 to 1990 was used to analyze the model’s application in the selected watershed called AJW in the Chinese LP region. The model procedure included sensitivity analysis, parameter calibration and model validation. The best parameter set was finally determined based on the combination of parameter localization and auto-calibration. Then the model was assessed for its accuracy based on the NSE estimation, resulting in 0.77 and 0.67 for calibration and 0.46 and 0.32 for validation on simulations for flow and sediment, respectively, which is a moderately satisfactory accuracy among the applications of the SWAT model. Annual watershed assessment on flow and sediment with the calibrated SWAT model resulted in a multiyear averaged annual runoff coefficient of about 2.7% and an erosion modulus of 797 t/(km²·a⁻¹) in the AJW, indicating a beneficial consequence from the implementation of the historical soil and water conservations.     

Runoff and sediment yield modeling using SWAT model: case of Wadi Hatab basin,central Tunisia

This study presents an application of the model Soil and Water Assessment Tool (SWAT) to simulate daily and monthly water flow and sediment fluxes in the Wadi Hatab watershed (2200 km²) located in central Tunisia. The study basin is characterized by a significant climatic contrast, abrupt topography, and soil fragility, resulting thereby in flash floods and important water erosion rates. This alarming situation requires urgent interventions in order to preserve water and soil resources, implying the need for a decision tool for proper integrated management of the watershed. The model was calibrated and validated based on a comparison of simulated and observed flow rates at the basin outlet (hydrometric station Khanguet Zazia), during the periods 1987–1988 and 1989–1990, respectively. The comparison was based not only on visual inspection of the agreement between observed and simulated time series, but also on statistical parameters. Indeed, for the daily time step application, the Nash—Sutcliffe efficiency (NSE) values were 0.52 and 0.61, and the coefficient of determination (R²) was 0.54 and 0.61 for calibration and validation, respectively. As for the monthly time-step application, the obtained NSE values were 0.67 and 0.89 while R² values were 0.83 and 0.87 for calibration and validation, respectively. This clearly shows the reasonably good agreement between simulated and observed flow rates. In terms of erosion, the model gave sediment yield values ??of 1.15 and 5.37 t/ha/year during the periods of calibration and validation, respectively.     

Analysis of the dynamical instability of several multiple stars with weak hierarchy

The dynamical stability of 16 multiple stars is analyzed using Monte Carlo simulations with allowance for the errors in the observational data. The analysis was carried out by varying the uncertainties in the initial observational data. Six different stability criteria were considered, and the dynamical evolution was studied using numerical simulations. Eleven of the systems are probably stable, whereas five systems (HD 40887, HD 136176, HD 150680, HD 217675, and HD 222326) are probably unstable (the probability that they are unstable is 0.94 or more accordingt o the results of forward and backward simulations over intervals of 10⁶ yr). The results of the simulations were most consistent with the criteria of Mardling-Aarseth (the correlation coefficient between the probabilities of disruption inferred from the stability criterion and numerical integration was r = 0.998), Valtonen-Karttunen (r = 0.998), and Eggleton-Kiseleva (r = 0.997). In about 92–93% of all cases, these criteria yield results that are consistent with the numerical simulations. These criteria also yield high disruption probabilities for the unstable systems. Scenarios for the formation of such systems are discussed: temporary capture of a field star by a close binary, perturbation of a stable multiple system by a massive field object, and disruption of small stellar groups or clusters. The probabilities that these scenarios are realized are analyzed.     

Geospatial approach in mapping soil erodibility using CartoDEM – A case study in hilly watershed of Lower Himalayan Range

Soil erodibility is one of the most important factors used in spatial soil erosion risk assessment. Soil information derived from soil map is used to generate soil erodibility factor map. Soil maps are not available at appropriate scale. In general, soil maps at small scale are used in deriving soil erodibility map that largely generalized spatial variability and it largely ignores the spatial variability since soil map units are discrete polygons. The present study was attempted to generate soil erodibilty map using terrain indices derived from DTM and surface soil sample data. Soil variability in the hilly landscape is largely controlled by topography represented by DTM. The CartoDEM (30 m) was used to derive terrain indices such as terrain wetness index (TWI), stream power index (SPI), sediment transport index (STI) and slope parameters. A total of 95 surface soil samples were collected to compute soil erodibility factor (K) values. The K values ranged from 0.23 to 0.81 t ha^?1R^?1 in the watershed. Correlation analysis among K-factor and terrain parameters showed highest correlation of soil erodibilty with TWI (r ²= 0.561) followed by slope (r ²= 0.33). A multiple linear regression model was developed to derive soil erodibilty using terrain parameters. A set of 20 soil sample points were used to assess the accuracy of the model. The coefficient of determination (r ²) and RMSE were computed to be 0.76 and 0.07 t ha^?1R^?1 respectively. The proposed methodology is quite useful in generating soil erodibilty factor map using digital elevation model (DEM) for any hilly terrain areas. The equation/model need to be established for the particular hilly terrain under the study. The developed model was used to generate spatial soil erodibility factor (K) map of the watershed in the lower Himalayan range.     

Uncertainty assessment of the multilayer perceptron (MLP) neural network model with implementation of the novel hybrid MLP-FFA method for prediction of biochemical oxygen demand and dissolved oxygen: a case study of Langat River

Accurate prediction of the chemical constituents in major river systems is a necessary task for water quality management, aquatic life well-being and the overall healthcare planning of river systems. In this study, the capability of a newly proposed hybrid forecasting model based on the firefly algorithm (FFA) as a metaheuristic optimizer, integrated with the multilayer perceptron (MLP-FFA), is investigated for the prediction of monthly water quality in Langat River basin, Malaysia. The predictive ability of the MLP-FFA model is assessed against the MLP-based model. To validate the proposed MLP-FFA model, monthly water quality data over a 10-year duration (2001–2010) for two different hydrological stations (1L04 and 1L05) provided by the Irrigation and Drainage Ministry of Malaysia are used to predict the biochemical oxygen demand (BOD) and dissolved oxygen (DO). The input variables are the chemical oxygen demand (COD), total phosphate (PO₄), total solids, potassium (K), sodium (Na), chloride (Cl), electrical conductivity (EC), pH and ammonia nitrogen (NH₄-N). The proposed hybrid model is then evaluated in accordance with statistical metrics such as the correlation coefficient (r), root-mean-square error, % root-mean-square error and Willmott’s index of agreement. Analysis of the results shows that MLP-FFA outperforms the equivalent MLP model. Also, in this research, the uncertainty of a MLP neural network model is analyzed in relation to the predictive ability of the MLP model. To assess the uncertainties within the MLP model, the percentage of observed data bracketed by 95 percent predicted uncertainties (95PPU) and the band width of 95 percent confidence intervals (d-factors) are selected. The effect of input variables on BOD and DO prediction is also investigated through sensitivity analysis. The obtained values bracketed by 95PPU show about 77.7%, 72.2% of data for BOD and 72.2%, 91.6% of data for DO related to the 1L04 and 1L05 stations, respectively. The d-factors have a value of 1.648, 2.269 for BOD and 1.892, 3.480 for DO related to the 1L04 and 1L05 stations, respectively. Based on the values in both stations for the 95PPU and d-factor, it is concluded that the neural network model has an acceptably low degree of uncertainty applied for BOD and DO simulations. The findings of this study can have important implications for error assessment in artificial intelligence-based predictive models applied for water resources management and the assessment of the overall health in major river systems.     

Satellite-based rainfall estimation and discharge measurement of Middle Indus River,Pakistan

The impacts of floods and droughts are intensified by climate change, lack of preparedness, and coordination. The average rainfall in study area is ranging from 200 to 400 mm per year. Rain gauge generally provides very accurate measurement of point rain rates and the amounts of rainfall but due to scarcity of the gauge locations provides very general information of the area on regional scale. Recognizing these practical limitations, it is essential to use remote sensing techniques for measuring the quantity of rainfall in the Middle Indus. In this research, Tropical Rainfall Measuring Mission (TRMM) estimation can be used as a proxy for the magnitude of rainfall estimates from classical methods (rain gauge), quantity, and its spatial distribution for Middle Indus river basin. In order to use TRMM satellite data for discharge measurement, its accuracy is determined by statistically comparing it with in situ gauged data on daily and monthly bases. The daily R ² value (0.42) is significantly lower than monthly R ² value (0.82), probably due to the time of summation of TRMM 3-hourly precipitation data into daily estimates. Daily TRMM data from 2003 to 2012 was used as input forcing in Soil and Water Assessment Tool (SWAT) hydrological model along with other input parameters. The calibration and validation results of SWAT model give R ² = 0.72 and 0.73 and Nash-Sutcliffe coefficient of efficiency = 0.69 and 0.65, respectively. Daily and monthly comparison graphs are generated on the basis of model discharge output and observed data.     

Evaluating the impact of management scenarios and land use changes on annual surface runoff and sediment yield using the GeoWEPP: a case study from the Lighvanchai watershed,Iran

This study was undertaken to evaluate land use change impact and management scenarios on annual average surface runoff (SR) and sediment yield (SY) using the GeoWEPP tool in the Lighvanchai watershed (located in northwestern Iran). Following a sensitivity analysis, the WEPP model was calibrated (2005–2007) and validated (2008–2010) against monthly observed SY and SR. The coefficient of determination (R ²), Nash–Sutcliffe efficiency (NSE), mean bias error (MBE), and root-mean-square error (RMSE) were applied to quantitatively evaluate the WEPP model. The results indicate a satisfactory model performance with R ² > 0.80 and NSE > 0.60. Therefore, the model for current land use (scenario 1) was run for a 30-year time period (1982–2011). The annual average of SR and sediment load were predicted as 93,584 m³/year and 4340 ton/year, respectively. To reduce the annual average surface runoff and sediment yield at the watershed scale, the second scenario (alfalfa cultivation with suitable tillage) and the third scenario (grassland development) as two management scenarios of land use changes were defined by identifying the critical hillslopes. The rate of SR and sediment load in the second scenario were 42,096 m³/year and 429 ton/year, respectively. For the third scenario, the model predictions were 30,239 m³/year and 226 ton/year, respectively. Compared to the first scenario, the reduction rates in annual average of sediment load were about 90 and 94%, respectively. Moreover, for the second and third management scenarios, the reduction rates in annual average of SR were about 55 and 67%, respectively.     

Land-use-mediated <Emphasis Type="Italic">Escherichia coli</Emphasis> concentrations in a contemporary Appalachian watershed

A high-spatial resolution study design was used to investigate the relationship between land use practices, stream physicochemistry, hydroclimate, and stream Escherichia (E) coli concentrations in a mixed-land-use watershed in the Appalachian region. Stream samples were collected daily from six monitoring sites and analyzed for total E. coli counts using an enzyme metabolism indicator method. Statistical comparison of E. coli concentration time series showed significant (p?<?0.05) differences between study sites. Although highest average E. coli concentrations were observed at two agricultural sites (534 and 582 colony-forming counts (CFU) per 100 mL, respectively), highest total loadings were observed within the receiving stream, with values increasing downstream (2?×?10¹² and 4.2?×?10¹² study total CFU for bracketed upstream and downstream sites, respectively). No single physical variable displayed a significant correlation (p?<?0.05) with observed E. coli concentration at every site. However, sites displayed different patterns of significant correlations (p?<?0.05) between E. coli concentration and both physicochemical (e.g. pH, dissolved oxygen saturation) and hydroclimate variables (e.g. streamflow and precipitation). Percent agricultural land cover was the only land use category that showed significant (p?<?0.04) correlation with study average E. coli concentrations, thereby emphasizing the importance of land use practices to stream pathogen regimes. Results validate the analytical method and provide high-resolution, detailed, quantitative characterizations of stream E. coli regimes, thereby supplying land and water resource managers with science-based information to advance management decisions and improve public health.     

Quantifying land use influences on event-based flow frequency,timing, magnitude,and rate of change in an urbanizing watershed of the central USA

There is a need for research that advances understanding of flow alterations in contemporary watersheds where natural and anthropogenic interactions can confound mitigation efforts. Event-based flow frequency, timing, magnitude, and rate of change were quantified at five-site nested gauging sites in a representative mixed-land-use watershed of the central USA. Statistically independent storms were paired by site (n = 111 × 5 sites) to test for significant differences in event-based rainfall and flow response variables (n = 17) between gauging sites. Increased frequency of small peak flow events (i.e., 64 more events less than 4.0 m³ s^?1) was observed at the rural–urban interface of the watershed. Differences in flow response were apparent during drier periods when small rainfall events resulted in increased flow response at urban sites in the lower reaches. Relationships between rainfall and peak flow were stronger with decreased pasture/crop land use and increased urban land use by approximately 20%. Event-based total rainfall explained 40–68% of the variance in peak flow (p < 0.001). Coefficients of determination (r²) were negatively correlated with pasture/crop land use (r² = 0.92; p = 0.007; n = 5) and positively correlated with urban land use (r² = 0.90; p = 0.008; n = 5). Significant differences in flow metrics were observed between rural and urban sites (p < 0.05; n = 111) that were not explained by differences in rainfall variables and drainage area. An urban influence on flow timing was observed using median time lag to peak centroid and time of maximum precipitation to peak flow. Results highlight the need to establish manageable flow targets in rapidly urbanizing mixed-land-use watersheds.     

Predicting saturated hydraulic conductivity using particle swarm optimization and genetic algorithm

Soil saturated hydraulic conductivity (K_s) is considered as soil basic hydraulic property, and its precision estimation is a key element in modeling water flow and solute transport processes both in the saturated and vadose zones. Although some predictive methods (e.g., pedotransfer functions, PTFs) have been proposed to indirectly predict K_s, the accuracy of these methods still needs to be improved. In this study, some easily available soil properties (e.g., particle size distribution, organic carbon, calcium carbonate content, electrical conductivity, and soil bulk density) are employed as input variables to predict K_s using a fuzzy inference system (FIS) trained by two different optimization techniques: particle swarm optimization (PSO) and genetic algorithm (GA). To verify the derived FIS, 113 soil samples were taken, and their required physical properties were measured (113 sample points?×?7 factors?=?791 input data). The initial FIS is compared with two methods: FIS trained by PSO (PSO-FIS) and FIS trained by GA (GA-FIS). Based on experimental results, all three methods are compared according to some evaluation criteria including correlation coefficient (r), modeling efficiency (EF), coefficient of determination (CD), root mean square error (RMSE), and maximum error (ME) statistics. The results showed that the PSO-FIS model achieved a higher level of modeling efficiency and coefficient of determination (R²) in comparison with the initial FIS and the GA-FIS model. EF and R² values obtained by the developed PSO-FIS model were 0.69 and 0.72, whereas they were 0.63 and 0.54 for the GA-FIS model. Moreover, the results of ME and RMSE indices showed that the PSO-FIS model can estimate soil saturated hydraulic conductivity more accurate than the GA-FIS model with ME?=?10.4 versus 11.5 and RMSE?=?5.2 versus 5.5 for PSO-FIS and GA-FIS, respectively.     

Evaluating the impacts of watershed management on runoff storage and peak flow in Gav-Darreh watershed,Kurdistan, Iran

Recently, water and soil resource competition and environmental degradation due to inadequate management practices have been increased and pose difficult problems for resource managers. Numerous watershed practices currently being implemented for runoff storage and flood control purposes have improved hydrologic conditions in watersheds and enhanced the establishment of riparian vegetation. The assessment of proposed management options increases management efficiency. The purpose of this study is to assess the impact of watershed managements on runoff storage and peak flow, and determine the land use and cover dynamics that it has induced in Gav-Darreh watershed, Kurdistan, Iran. The watershed area is 6.27 km² which has been subjected to non-structural and structural measures. The implemented management practices and its impact on land use and cover were assessed by integrating field observation and geographic information systems (GIS). The data were used to derive the volume of retained water and determine reduction in peak flow. The hydrology of the watershed was modeled using the Hydrologic Engineering Center–Hydrologic Modeling System (HEC–HMS) model, and watershed changes were quantified through field work. Actual storms were used to calibrate and validate HEC–HMS rainfall–runoff model. The calibrated HEC–HMS model was used to simulate pre- and post-management conditions in the watershed. The results derived from field observation and HEC–HMS model showed that the practices had significant impacts on the runoff storage and peak flow reduction.     

The morphological characteristics of gully systems and watersheds in Dry-Hot Valley,SW China

Gully systems and watersheds are geomorphic units with clear boundaries that are relatively independent of basin landscapes and play an important role in natural geography. In order to explore the morphological characteristics of gully systems and watersheds in the Dry-Hot Valley [South West (SW) China], gullies are interpreted from online Google images with high resolution and watersheds are extracted from digital elevation model at a scale of 1:50,000. The results show that: (1) There are 17,382 gullies (with a total area of 1141.66 km²) and 42 watersheds in the study area. (2) The average gully density of the study area (D) is 4.29 km/km², gully frequency (F) is 14.39 gullies/km², the branching ratio (B) is 5.13, the length ratio (L) is 3.12, and the coefficient of the main and tributary gullies (M) is 0.06. The degree of gully erosion is strong to extremely strong, the main development intensity of gully erosion ranges from intense to moderate, and the type of gully system is tributary. (3) The watershed areas (A) are between 0.39 and 96.43 km², the relief ratio (R) is from 0.10 to 0.19, the circularity ratio (C) is from 0.30 to 0.83, the texture ratio (T) is from 0.82 to 39.35, and the dominant geomorphological texture type is fine. (4) There is a quantitative relationship between F and D:F?=?0.624D² (R?=0.84) and T is closely related to D, F, M (R²?>?0.7). A, R and C are related to M (R²?>?0.5). The development of gully systems is the result of coupling effects between multiple factors. In this area, the degree of erosion and the condition of the main and tributary gullies can be controlled by the degree of topographic breakage in the watershed, which provides some theoretical basis for the evaluation of gully erosion by the latter. In addition, the scale, relief, and shape have a significant impact on the locations of the main and tributary gullies. For tributary gullies, attention should be paid to the interception and control of runoff and sediment in the small confluence branches in order to prevent gully expansion and head advance. These features can inform the development of targeted measures for the control of soil erosion.     

Halo density profiles and baryon physics

The radial dependence of the pseudo phase-space density, ρ(r)/σ ³(r) is studied. We find that the pseudo phase-space density for halos consisting both of dark matter and baryons is approximately a power-law only down to 0.1% of the virial radius while it has a non-power law behavior below the quoted scale, with inner profiles changing with mass. Halos consisting just of dark matter, as the one in dark matter only simulations, are characterized by an approximately power-law behavior. The results argue against universality of the pseudo phase-space density, when the baryons effect are included, and as a consequence argue against universality of density profiles constituted by dark matter and baryons as also discussed in [1].     

Spatiotemporal characteristics of earthquake disaster losses in China from 1993 to 2016

The present study analyzes the runoff response during extreme rain events over the basin of Subarnarekha River in India using soil and water assessment tool (SWAT). The SWAT model is configured for the Subarnarekha River basin with 32 sub-basins. Three gauging stations in the basin (viz., Adityapur, Jamshedpur and Ghatshila) were selected to assess the model performance. Daily stream flow data are taken from Central Water Commission, India—Water Resources Information System. Calibration and validation of the model were performed using the soil and water assessment tool-calibration uncertainty programs (SWAT-CUPs) with sequential uncertainty fitting (SUFI-2) algorithm. The model was run for the period from 1982 to 2011 with a calibration period from 1982 to 1997 and a validation period from 1998 to 2011. The sensitivity of basin parameters has been analyzed in order to improve the runoff simulation efficiency of the model. The study concluded that the model performed well in Ghatshila gauging station with a Nash–Sutcliffe efficiency (NSE) of 0.68 during calibration and 0.62 during validation at daily scale. The model, thus calibrated and validated, was then applied to evaluate the extreme monsoon rain events in recent years. Five extreme events were identified in Jamshedpur and Ghatshila sub-basins of Subarnarekha River basin. The simulation results were found to be good for the extreme events with the NSE of 0.89 at Jamshedpur and 0.96 at Ghatshila gauging stations. The findings of this study can be useful in runoff simulation and flood forecasting for extreme rainfall events in Subarnarekha River basin.