Nash Criterion Research Articles

Modeling dissolved organic carbon in inland waters using an unmanned aerial vehicles-borne hyperspectral camera

Remote sensing can provide an alternative solution to quantify Dissolved Organic Carbon (DOC) in inland waters. Sensors embedded on Unmanned Aerial Vehicles (UAV) and satellites that can capture the DOC have already shown good relationships between DOC and the Colored Dissolved Organic Matter absorption (aCDOM.) coefficients in specific spectral regions. However, since the signal recorded by the sensors is reflectance-based, DOC estimates accuracy decreases when inverting the aCDOM. coefficients to reflectance. Thus, the main objective is to study the potential of a UAV-borne hyperspectral camera to retrieve the DOC in inland waters and to develop reflectance-based models using UAV and satellite (Landsat-8 OLI and Sentinel-2 MSI) data. Ensemble based systems (EBS) were favored in this study. The EBSUAV calibration results showed that six spectral regions (543.5, 564.5, 580.5, 609.5, 660, and 684 nm) are sensitive to DOC in waters. The EBSUAV test results showed a good concordance between measured and estimated DOC with an R2 = Nash-criterion (NASH) = 0.86, and RMSE (Root Mean Squares Error) = 0.68 mg C/L. The EBSSAT test results also showed a strong concordance between measured and estimated DOC with R2 = NASH = 0.92 and RMSE = 0.74 mg C/L. The spatial distribution of DOC estimates showed no dependency to other optically active elements. Nevertheless, estimates were sensitive to haze and sun glint.

The effect of landuse dynamics on water balance components in the Upper Oum Er Rabia Basin, Morocco

The Upper Oum Er-Rbia Basin (UOERB) has been facing significant land use/land cover change and urban sprawl dynamics in recent years, in addition to significant climatic variability leading to disruption of precipitation intensity and quantity. Our approach is to identify the morphometric characteristics of the study region and monitor changes in land use and land cover by analyzing Landsat images. These factors form the input parameters for the HEC-HMS (Hydrologic Engineering Center - Hydrologic Modeling System) hydrological model for simulating daily historical hydro-climatic events. The classification of Landsat images shows that the Upper Oum Er-Rbia Basin has experienced significant landuse dynamics over the past 30 years, resulting in disrupted rainfall and recurrent flooding events. Overall, the hydrological simulation shows good agreement between observed and simulated flow hydrographs, with Nash criteria between 0.6 and 0.8. This knowledge enables us to better estimate the return flows in the catchment area, and to take appropriate action in terms of hydraulic management and development in the Upper Oum Er-Rbia Basin.

Rainfall-flow Modeling Using a Global Conceptual Model: Case of the Beni Bahdel Watershed (Northwest of Algeria)

Rainfall-flow modeling remains necessary, even essential, to understand the dynamics of a watershed and to solve problems related to the disruption of hydrological regimes. It has been proven effective by providing solutions to many water-related problems, such as sizing and management of structures, and flood forecasting. Global hydrological models can simulate the transformation of rainfall data into flows on natural basins for many practical applications in the field of water resource management. Our study aims to evaluate the reliability of one of these models, that of Rural Engineering 'GR' at three time steps: annual (GR1A), monthly (GR2M), and daily (GR4J), which will be applied to the Beni Bahdel watershed with an area of 1040 km², one of the sub-basins of Northwestern Algeria. The input parameters are precipitation and potential evapotranspiration (PET), and the output parameters are flows. The results obtained, both in calibration and validations, are encouraging, where the evaluation criteria taken into consideration, namely the Nash criterion and the correlation coefficient, exceeded 70% and 0.80 respectively. The study could be a decision-making tool for the simulation of flows, and be very useful for future hydraulic developments in the study area.

Nghiên cứu ảnh hưởng của công trình tới trường sóng, trường dòng chảy khu vực Cửa Tùng – Quảng Trị bằng mô hình số

For many years, Cua Tung area has suffered from the effects of rising water and waves, especially during storms. That situation leads to changes in water environment and coastal erosion, directly affecting people's lives and properties; affect the development of tourism, economy - society. The presence of the works here has led to a change in the hydrodynamic regime (waves, currents) and negatively affects the coast and water environment. Confirmed results show that wave height and flow rate are 73.6% and 55.2% according to Nash criteria, at a satisfactory level or higher. Before and after two constructions, the Southern Embankment and the North Embankment of Cua Tung, have shown a clear change in wave regime and flow, causing the waves to be strengthened and causing severe coastal erosion important. The author has proposed a breakwater construction measure off Cua Tung beach, through simulations, it has been shown that the breakwater has a great effect on breaking waves and protecting the coast. Wave height has decreased markedly at the rear of the breakwater. In addition, the barrier dyke also causes the sediment moving from the shore to the sea to be deposited inside the dyke and in the middle of the dyke there is a gap where the offshore sediment enters. The research results contribute to the assessment of the current status of the coastal zone and serve as a basis for ensuring the stability of the water environment, minimizing coastal erosion in order to develop tourism and promote socio-economic development.

(Digital Presentation) Evaluation of Two Methods of Bias Correction of Precipitations on Improvement of Hydrological Simulation:Case of Chiffa Basin-Northern Algeria-

This work aim to assess the “basic-quantile”and“gamma-mapping” bias correction methods in order to improve hydrological simulations of the Chiffa watershed. The results are provided by the conceptual rainfall-runoff GR2M model in the R environment, coupled with the outputs of rainfall data simulations from the RCA4 model of CORDEX-AFRICA forced by two global circulation models (MPI-ESM-LR and CRNM-CM5) under two Representative Concentration Pathways (RCP) RCP4.5 and RCP 8.5 .The validation of GR2M hydrological model on the Chiffa basin using Nash criteria made it possible to simulate future flows over the period 2074-2099. The results showed that the future flows simulated from raw rainfall data are not in adequacy with the evolution of future rainfall simulations whereas the flows simulated from the corrected rainfall data shown better results, which highlights the importance of bias correction for hydrological impact studies. Finally, the regional climate models simulate a 9% decrease in winter, and a 6% increase in spring under RCP4.5 by the end of the 21st century Figure 1

Quantitative Study of the Effect of Water Content on Soil Texture Parameters and Organic Matter Using Proximal Visible—Near Infrared Spectroscopy

Continuous monitoring of soil quality is a challenging task in agricultural activity. To meet this need, scientists have succeeded in developing a quick and inexpensive method to characterize soil properties. Thus, spectroscopy has become a promising method for quantifying soil parameters. However, this method remains sensitive to several factors such as water content (WC). The present study aims to quantify the effect of WC on the estimation of soil texture parameters (sand, silt, and clay) and organic matter (OM) using spectroscopy. Reflectance measurements in the laboratory on 68 soil samples were performed by varying the WC in each sample. The analysis revealed a significant influence of WC on spectra acquired from visible to near infrared (V/NIR) spectroscopy data and that spectra can be divided into two classes. To quantify the effect of WC, calibration/validation steps were performed on soil texture parameters and OM with and without taking WC into account. Calibration was performed using the partial least square regression algorithm, and the validation was assessed using four statistical evaluation indices (R2, Nash criterion (Nash), root-mean-square error (RMSE), and BIAS). Results showed a systematic increase in the accuracy of all studied soil particles when the WC is considered. Clay and OM were less influenced, while silt and sand were much more influenced by the WC. The study also highlighted that estimates of soil texture parameters using V/NIR data achieved relatively higher levels of accuracy (R2 > 0.80 and Nash > 0.80) than OM estimation (R2 = 0.83 and Nash = 0.78).

Estimation of fish assessment index based on ensemble artificial neural network for aquatic ecosystem in South Korea

Fish assessment index (FAI) is commonly used to perform ecological health assessments of fish communities in rivers. However, the estimation of this index is difficult, considering the complexity of relationships among water quality, water quantity, and hydrologic properties. In this study, we propose an ensemble artificial neural network (EANN) based on various hydrological and environmental variables, and their correlation, to improve the FAI estimation for the ecological health assessment of streams and water resource management. The optimal input variables of the model were determined through correlation analyses. These values were used to train the ANN model using the Levenberg-Marquardt algorithm. The EANN model was structured with varying number of neurons and ensemble sizes. This model provides better generalization and model performance than the single ANN model for estimation. The proposed model was applied to 143 monitoring sites across Han, Nakdong, Geum, Yeongsan, and Seomjin rivers in South Korea. The 5- and 10-fold cross-validation approaches were used to evaluate the results of the model based on the Nash criterion, relative root mean squared error, and relative mean bias. For performance comparison, support vector machine (SVM) was used as the other feasible alternative because this method shows good performance in regression analysis and solves problems mathematically, unlike other machine learning algorithms. The results indicate that EANN is suitable for solving large complex problems and provides better FAI estimates than the SVM, which can be used to manage ecological conditions.

Gaussian Process Regression-Based Structural Response Model and Its Application to Regional Damage Assessment

Seismic activities are serious disasters that induce natural hazards resulting in an incalculable amount of damage to properties and millions of deaths. Typically, seismic risk assessment can be performed by means of structural damage information computed based on the maximum displacement of the structure. In this study, machine learning models based on GPR are developed in order to estimate the maximum displacement of the structures from seismic activities and then used to construct fragility curves as an application. During construction of the models, 13 features of seismic waves are considered, and six wave features are selected to establish the seismic models with the correlation analysis normalizing the variables with the peak ground acceleration. Two models for six-floor and 13-floor buildings are developed, and a sensitivity analysis is performed to identify the relationship between prediction accuracy and sampling size. A 10-fold cross-validation method is used to evaluate the model performance, using the R-squared, root mean squared error, Nash criterion, and mean bias. Results of the six-parameter-based model apparently indicate a similar performance to that of the 13-parameter-based model for the two types of buildings. The model for the six-floor building affords a steadily enhanced performance by increasing the sampling size, while the model for the 13-floor building shows a significantly improved performance with a sampling size of over 200. The results indicate that the heighted structure requires a larger sampling size because it has more degrees of freedom that can influence the model performance. Finally, the proposed models are successfully constructed to estimate the maximum displacement, and applied to obtain fragility curves with various performance levels. Then, the regional seismic damage is assessed in Gyeonjgu city of South Korea as an application of the developed models. The damage assessment with the fragility curve provides the structural response from the seismic activities, which can assist in minimizing damage.

INFLUENCE OF THE SIDE VENTILATION ON THE DURABILITY OF THE FUNCTIONING OF DRYING BEDS WITH NON-SATURATED FLOW IN TREATEMENT OF SEPTIC TANK SLUDGE

The non-saturated Flow Drying Beds allow efficient treatment of septic tank sludge. However, they are vulnerable to clogging. To ensure the sustainability of this technology, through an additional supply of oxygen from the lateral surface, a flow model coupled with the variation of the biofilm has been developed. The calibration, validation and comparison of the simulated and experimental results were made from the NASH criterion. The simulations focused on two types of reactors. A reactor with pores on its side surface is called a ventilated reactor (VR). The second is then called an unventilated reactor (UVR). The results show that the maximum applicable organic load is 43.3 mgO2 / cm2 / d at the UVR level and 51.8 mgO2 / cm2 / d at the VR level. In addition, the reduction in free flow porosity is 93.33% at the UVR level and 81% at the AR level. In addition, the results show that when the hydraulic head is less than 5 cm / d, the COD removal efficiency is 96.19% at the UVR level and 95.64% at the VR level. But, when the load is greater than 5 cm / d, the yield is 92.65% at the level of the UVR and of 94.95% at the level of the VR. Thus, in the context of a large-scale operation, lateral ventilation is essential. It guarantees good purification efficiency, slows down internal clogging of beds and accelerates its reversibility when it occurs.

Future climatic and hydrologic changes estimated by bias-adjusted regional climate model outputs of the Cordex-Africa project: case of the Tafna basin (North-Western Africa)

This study investigates climatic and hydrologic changes of the Tafna basin, by using ten outputs of precipitation and temperature from RCMs of the Cordex-Africa project. Different methods of bias-correction (LS, LOCI, DM and VS) are compared to correct the bias of precipitation and temperature datasets to observations. The suitable method, DM, reduces the bias to 1.27 mm for precipitation and 0.06 and 0.7°C for minimum/maximum temperature, respectively. The bias-corrected precipitation and temperature datasets are introduced into the SWAT model, calibrated and validated on the Tafna basin with good Nash criteria (NSEoutlet = 0.83). The discharge is over or under-estimated without bias-correction of RCM outputs, which highlights the necessity of applying bias-correction before using RCM outputs from Cordex-Africa for hydrological applications. The results show that the precipitation and discharge decreases, and temperature increases are more important with RCP 8.5 than with RCP 4.5, especially in the last decades of the 21st century.

Future climatic and hydrologic changes estimated by bias-adjusted regional climate model outputs of the Cordex-Africa project: case of the Tafna basin (North-Western Africa)

This study investigates climatic and hydrologic changes of the Tafna basin, by using ten outputs of precipitation and temperature from RCMs of the Cordex-Africa project. Different methods of bias-correction (LS, LOCI, DM and VS) are compared to correct the bias of precipitation and temperature datasets to observations. The suitable method, DM, reduces the bias to 1.27 mm for precipitation and 0.06 and 0.7°C for minimum/maximum temperature, respectively. The bias-corrected precipitation and temperature datasets are introduced into the SWAT model, calibrated and validated on the Tafna basin with good Nash criteria (NSEoutlet = 0.83). The discharge is over or under-estimated without bias-correction of RCM outputs, which highlights the necessity of applying bias-correction before using RCM outputs from Cordex-Africa for hydrological applications. The results show that the precipitation and discharge decreases, and temperature increases are more important with RCP 8.5 than with RCP 4.5, especially in the last decades of the 21st century.

Hydropluviometric variability in non-Sahelian West Africa: case of the Koliba/Corubal River Basin (Guinea and Guinea-Bissau)

Abstract. The Koliba/Corubal River watershed is poorly documented due to the hydrometric measurements shutdown and gaps in the very short hydropluviometric timeseries. The purpose of this study is to analyze the variability of rainfall in the Basin, by simulating flows using the GR2M rain-flow model and extending the discharge timeseries. From the regional vector method, the rainfall timeseries were homogenized, and the gaps filled by the estimated values. The rank correlation and Pettitt test on annual rainfall amounts (1924–2015) indicate breaks in 1958, 1967 and 1969, leading to rainfall deficits ranging from 9.7 % to 20.2 %. For some stations, the segmentation method shows a recovery of rainfall towards the end of the 1980s (Gaoual, Mali) and the early 2000s (Gabu). The analysis of the temporal distribution of the Monthly Rainfall Coefficients shows an improvement of the contributions of a few months during the period after rupture. From a hydrological point of view, the correlation between the mean annual rainfall and the runoff has allowed to extend the flow timeseries. The mean monthly rainfall calculated using the inverse square of distance method, the Potential Evapotranspiration, and the flow rates were used to calibrate and validate the model to determine the parameters that better transform rainfall in flow. The values of the Nash criteria close to 100 have made it possible to extend the monthly flow data from Koliba/Corubal to Gaoual, Cade and Tche-Tche until 2015.

Calibration and Validation of the SWAT Model on the Watershed of Bafing River, Main Upstream Tributary of Senegal River: Checking for the Influence of the Period of Study

Management of reservoir water resources requires the knowledge of flow inputs in this reservoir. Hydrological rainfall-runoff model is used for this purpose. There are several types of hydrological model according the description of the hydrological processes: black-box models, conceptual models, deterministic physical based model. SWAT is a semi-distributed hydrological model designed for water quality and quantity. This versatile tool has been used all around the world to assess and manage water resources. The main objective of the paper is to calibrate and validate the SWAT model on the watershed of Bafing located between 10°30' and 12°30' north latitude and between 12°30' and 9°30' west longitude to assess climate change on this river flows. A DEM with a resolution of 12.5 m × 12.5 m, the daily average flows and the daily observed precipitations on the period 1979-1986 (long period) are used as inputs for the calibration, while precipitations for the period 1988-1994 are used for the validation. The sensitivity analysis was done to detect the most determining coefficients during the calibration step. It shows that 19 parameters are required. Then, the effect of the period on the parameters calibration is checked by considering first the whole period of study and then each year of the period of study. The Nash criterion was used to compare the calculated and the observed hygrographs in each case. The results showed that the longer is the period of calibration, the more accurate is the Nash criterion. The calibration per year gave a best Nash criterion except for a single year. During the validation, the parameters calculated on the long period lead to the best Nash criterion. The values of the Nash criterion calibration and validation are very suitable. These results of calibration can be used to study the long-term evolution of flow at Senegal River on Bafing Makana.

STUDI PENGEMBANGAN MODEL HIDROGRAF SATUAN SISTETIS SNYDER UNTUK SUNGAI –SUNGAI DI SULAWESI SELATAN

This study aims to analyze the parameters that influence the Snyder synthetic unit hydrograph method. The study was conducted on 11 watersheds in South Sulawesi Province, 8 watersheds for modeling and 3 other watersheds for reliability testing (model verification). With rainfall data, the discharge data and watershed characteristics obtained from each watershed were analyzed for parameters that affected the hydrograph breakdown of the Snyder HSS method. Then compared to the hydrograph of the observation unit which was analyzed by the Collins method. After calibration was done with the NASH criteria obtained Peak Time (Tp) = 97.996%; Peak Discharge (Qp) = 98.331% and Basic Time (Tb) = 99.700%. The curved delineation of the hydrograph uses the auxiliary point W, which gives the result of volume deviation, namely: 7.980%, 9.227%; 6.855%; 4.966%; 10.972% and 9.843% are relatively small when compared to the model using Alexejeyev Arch with deviations: 22.362%; 29.991%; 26,319%; 19.602%; 29,786% and 17,633%.

Use of the Inverse Slope Method for the Characterization of Geometry of Basement Aquifers: Case of the Department of Bouna (Ivory Coast)

The inverse slope method (ISM) was used to interpret electric sounding data to determine the geoelectric parameters of the alteration zones (continuous media) and rocky environments (discontinuous environments) of the Bouna Department. Having both qualitative and quantitative interpretation, the inverse slope method (ISM) has the ability to determine the different geoelectric layers while characterizing their resistivities and true thicknesses. In the Bouna department, this method allowed us to count a maximum of four (4) geoelectric layers with a total thickness ranging from 12.99 m to 24.66 m. The alteration thicknesses calculated by the ISM in comparison with those measured in the boreholes showed a linear agreement of the coefficient of determination R2 = 0.8269 with the support of the Nash criterion which showed that this method gave thicknesses of alteration close to 76.76% of that obtained during the drillings.

Comparing available rainfall gridded datasets for West Africa and the impact on rainfall-runoff modelling results, the case of Burkina-Faso

Monthly rainfall data in Burkina-Faso, West Africa, over a period of 77 years are extracted from three different gridded data sets, available either on the web : CRU (Climatic Research Unit, Norwich, UK), SIEREM (HydroSciences Montpellier, France), or from the National Meteorological Center of Burkina-Faso. With a view to modelling the runoff-rainfall relationship at the monthly time step, these data are used at the 0.5°*0.5° scale. Despite mean, minimum, standard deviation and inter-annual variability being very similar for the period 1922 to 1998, the three gridded data sets used show an important spatial variability of values with time, and some differences are observed which lead to significantly different runoff-rainfall simulations. Comparison of the rainfall grids has shown that differences between the precipitation grids are more pronounced during years when the rainfall is lower; this also applies to areas where the rainfall is lower. The three different rainfall grids produce differences in mean rainfall of 4 to 11%, depending on the grids that are compared. While these results are obviously specific to the station networks and interpolation method used, they provide an indication of the differences that can arise. It is recommended that as many stations as possible are used to better assess areal rainfall. These biases have a strong influence on the results of the runoff-rainfall modelling (using the GR2M conceptual model) : the Nash criteria show differences of about 20% and calculated flow of 30% to 40%. This study illustrates the levels of uncertainty when using available rainfall gridded data sets, for rainfall-runoff studies in West African developing countries, which is important in the context of predicting water resources for the future from the GCM outputs for the 21st century.

The assessment of soil erosion risk, sediment yield and their controlling factors on a large scale: Example of Morocco

We combined the RUSLE model with a calibrated sediment delivery ratio SDR to obtain a simulated suspended sediment yield, which is compared with the observed ones founded in 42 catchments of the biggest and important dams of Morocco. The comparison allowed us to understand areas where the model can give suitable results and also understand the factors controlling the suspended sediment yield. The analysis of the long-term observed values of sedimentation in all selected reservoirs in Morocco shows an annual mean Sediment Yield (SY) of 1.51 million m3 with a standard deviation of 2.09 million m3·year−1. A very strong positive relationship was determined between sedimentation in reservoirs and the corresponding drainage area (R2 = 0.77); reservoirs with high sediment yield are those characterized by large drainage areas. We converted the sediment yield values into Suspended Sediment Yield (SSY) (t·ha−1·year−1) in order to better understand its spatial distribution all over the studied watersheds. The average founded is 6.40 t ha−1·yr−1, with the highest values observed in the North of the country dominated by friable lithology and landslides. The application of the RUSLE model in the country of Morocco, reveals a mean soil erosion of 5.06 t ha−1·yr−1 and a good correlation with slope length and steepness (r = 0.78). The model underestimates soil erosion in hard lithology and steep slopes, whereas overestimates it in friable lithology. Excluding the case of lithology influence, the combination RUSLE/SDR gives a very strong correlation with the observed SSY (r = 0.78) with a good model prediction according to Nash criterion (Nash = 0.61).

Daily rainfall-runoff modelling by neural networks in semi-arid zone: case of Wadi Ouahrane’s basin

This research work will allow checking efficiency of formal neural networks for flows’ modelling of wadi Ouahrane’s basin from rainfall-runoff relation which is non-linear. Two models of neural networks were optimized through supervised learning and compared in order to achieve this goal, the first model with input rain, and the second one with rain and input ETP. These neuronal models were compared with another overall model, the GR4j model. Then, it has been optimized and compared with the three first models, a third model of neural network with rain, ETP and soil moisture (calculated by the model GR4j) input. The neuronal models were optimized with algorithm of Levenberg Marquarld (LM), while the GR4j model was optimized with SCE-UA method. The Nash criterion (%) and the correlation coefficient of Pearson (R) allowed appreciating performances of these models.

Optimal Nash tuning rules for robust PID controllers

In this paper, we propose tuning rules for one degree-of-freedom proportional-integral-derivative controllers, by considering important aspects such as the trade-off in the performance in the servo and regulation operation modes and the control system robustness by constraining the maximum sensitivity peak. The different conflicting objectives are dealt with by using a multi-objective optimization algorithm to generate the trade-off optimal solutions. In this context, a simple tuning rule is determined by using the Nash solutions as a multi-criteria decision making technique. The Nash criteria is shown to provide convenient trade-off solutions for the controller tuning problem. Illustrative simulation examples show the effectiveness of the method.

Application of the L-moments approach to the analysis of regional flood frequency in Northern Algeria

Algeria is periodically affected by severe and repeated flooding. Flood hazard studies require the estimation of extreme flood flows. To predict and estimate the characteristics of maximum flows, knowledge of their distribution law is essential. The L-moments method was used to determine homogeneous regions and the appropriate distribution for these regions. Three homogeneous regions were delineated. This technique produced a Pearson type III distribution for the coastal region and the Tell Atlas and a Pareto distribution for the steppe regions and high plateaus of Eastern and Western Algeria. To estimate maximum flow at ungauged sites for different return periods, the 'index-flood' method was used. An empirical formula was developed that uses the average annual maximum flow as a function of catchment area and the average slope of the main channel to estimate maximum flow at any point on the Oued. The coefficient of determination and the Nash criterion, for the three regions, are superiors to 88% and 83% respectively. The root mean squared error, for the three regions, is less than 12%. These values show the robustness of the developed models.