The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydr...The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydrology and water resources which usually consist of three steps： （1） use of general circulation models （GCMs） to provide future global climate scenarios under the effect of increasing greenhouse gases, （2） use of downscaling techniques （both nested regional climate models, RCMs, and statistical methods） for ＂downscaling＂ the GCM output to the scales compatible with hydrological models, and （3） use of hydrologic models to simulate the effects of climate change on hydrological regimes at various scales. Great progress has been achieved in all three steps during the past few years, however, large uncertainties still exist in every stage of such study. This paper first reviews the present achievements in this field and then discusses the challenges for future studies of the hydrological impacts of climate change.展开更多
The Swiss Agency for Development and Cooperation (SDC) has funded the Rural Water and Sanitation Support Programme (RWSSP) that has increased the access to public water supply throughout Europe’s youngest state—Kos...The Swiss Agency for Development and Cooperation (SDC) has funded the Rural Water and Sanitation Support Programme (RWSSP) that has increased the access to public water supply throughout Europe’s youngest state—Kosovo—in the past ten years. The Programme, implemented by Dorsch International Consultants GmbH and Community Development Initiatives has, among other activities, implemented groundwater protection methods. Nevertheless, groundwater protection remains a challenge in Kosovo. The water law describes that water source protection is similar to German rules, yet modelling-based planning of water source protection zones remains challenging. In the present study, the development of the hydrogeological and the mathematical groundwater model for the technical delineation of the well head protection area for the Ferizaj well fields under limited data availability is described in detail. The study shows that even when not all data are available, it is possible and necessary to use mathematical groundwater models to delineate well head protection areas.展开更多
An integrated method that implements multivariate statistical analysis and ML methods to evaluate groundwater quality of the shallow aquifers of the Djerid and Kebili district,Southern Tunisia,was adopted.An evaluatio...An integrated method that implements multivariate statistical analysis and ML methods to evaluate groundwater quality of the shallow aquifers of the Djerid and Kebili district,Southern Tunisia,was adopted.An evaluation of their suitability for irrigation and/or drinking purposes is necessary.A comprehensive hydrochemical assessment of 52 samples with entropy weighted water quality index(EWQI)was also proposed.Eleven water parameters were calculated to ascertain the potential use of those resources in irrigation and drinking.Multivariate analysis showed two main components with Dim1(variance=62.3%)and Dim.2(variance=22%),due to the bicarbonate,dissolution,and evaporation and the intrusion of drainage water.The evaluation of water quality has been carried out using EWQI model.The calculated EWQI for the Djerid and Kebili waters(i.e.,52 samples)varied between 7.5 and 152.62,indicating a range of 145.12.A mean of 79.12 was lower than the median(88.47).From the calculation of EWQI,only 14 samples are not suitable for irrigation because of their poor to extremely poor quality(26.92%).The bivariate plot showed high correlation for EWQI~TH(r=0.93),EWQI~SAR(r=0.87),indicating that water quality depended on those parameters.Diff erent ML algorithms were successfully applied for the water quality classifi cation.Our results indicated high prediction accuracy(SVM>LDA>ANN>kNN)and perfect classifi cation for kNN,LDA and Naive Bayes.For the purposes of developing the prediction models,the dataset was divided into two groups:training(80%)and testing(20%).To evaluate the models’performance,RMSE,MSE,MAE and R^(2) metrics were used.kNN(R^(2)=0.9359,MAE=6.49,MSE=79.00)and LDA(accuracy=97.56%;kappa=96.21%)achieved high accuracy.Moreover,linear regression indicated high correlation for both training(R^(2)=0.9727)and testing data(0.9890).This well confi rmed the validity of LDA algorithm in predicting water quality.Cross validation showed a high accuracy(92.31%),high sensitivity(89.47%)and high specifi city(95%).These fi ndings are fundamentally important for an integrated water resource management in a larger context of sustainable development of the Kebili district.展开更多
文摘The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydrology and water resources which usually consist of three steps： （1） use of general circulation models （GCMs） to provide future global climate scenarios under the effect of increasing greenhouse gases, （2） use of downscaling techniques （both nested regional climate models, RCMs, and statistical methods） for ＂downscaling＂ the GCM output to the scales compatible with hydrological models, and （3） use of hydrologic models to simulate the effects of climate change on hydrological regimes at various scales. Great progress has been achieved in all three steps during the past few years, however, large uncertainties still exist in every stage of such study. This paper first reviews the present achievements in this field and then discusses the challenges for future studies of the hydrological impacts of climate change.
文摘The Swiss Agency for Development and Cooperation (SDC) has funded the Rural Water and Sanitation Support Programme (RWSSP) that has increased the access to public water supply throughout Europe’s youngest state—Kosovo—in the past ten years. The Programme, implemented by Dorsch International Consultants GmbH and Community Development Initiatives has, among other activities, implemented groundwater protection methods. Nevertheless, groundwater protection remains a challenge in Kosovo. The water law describes that water source protection is similar to German rules, yet modelling-based planning of water source protection zones remains challenging. In the present study, the development of the hydrogeological and the mathematical groundwater model for the technical delineation of the well head protection area for the Ferizaj well fields under limited data availability is described in detail. The study shows that even when not all data are available, it is possible and necessary to use mathematical groundwater models to delineate well head protection areas.
文摘An integrated method that implements multivariate statistical analysis and ML methods to evaluate groundwater quality of the shallow aquifers of the Djerid and Kebili district,Southern Tunisia,was adopted.An evaluation of their suitability for irrigation and/or drinking purposes is necessary.A comprehensive hydrochemical assessment of 52 samples with entropy weighted water quality index(EWQI)was also proposed.Eleven water parameters were calculated to ascertain the potential use of those resources in irrigation and drinking.Multivariate analysis showed two main components with Dim1(variance=62.3%)and Dim.2(variance=22%),due to the bicarbonate,dissolution,and evaporation and the intrusion of drainage water.The evaluation of water quality has been carried out using EWQI model.The calculated EWQI for the Djerid and Kebili waters(i.e.,52 samples)varied between 7.5 and 152.62,indicating a range of 145.12.A mean of 79.12 was lower than the median(88.47).From the calculation of EWQI,only 14 samples are not suitable for irrigation because of their poor to extremely poor quality(26.92%).The bivariate plot showed high correlation for EWQI~TH(r=0.93),EWQI~SAR(r=0.87),indicating that water quality depended on those parameters.Diff erent ML algorithms were successfully applied for the water quality classifi cation.Our results indicated high prediction accuracy(SVM>LDA>ANN>kNN)and perfect classifi cation for kNN,LDA and Naive Bayes.For the purposes of developing the prediction models,the dataset was divided into two groups:training(80%)and testing(20%).To evaluate the models’performance,RMSE,MSE,MAE and R^(2) metrics were used.kNN(R^(2)=0.9359,MAE=6.49,MSE=79.00)and LDA(accuracy=97.56%;kappa=96.21%)achieved high accuracy.Moreover,linear regression indicated high correlation for both training(R^(2)=0.9727)and testing data(0.9890).This well confi rmed the validity of LDA algorithm in predicting water quality.Cross validation showed a high accuracy(92.31%),high sensitivity(89.47%)and high specifi city(95%).These fi ndings are fundamentally important for an integrated water resource management in a larger context of sustainable development of the Kebili district.
