• Editorial: artificial intelligence in hydrologyElena Volpi, Jong Suk KIM, Shaleen Jain, Sangam ShresthaWavelet-based predictor screening for statistical downscaling of precipitation and temperature using the artificial neural network methodAida Hosseini Baghanam, Ehsan Norouzi, Vahid NouraniEvaluating the long short-term memory (LSTM) network for discharge prediction under changing climate conditionsCarolina Natel de Moura, Jan Seibert, Daniel Henrique Marco DetzelThe need for training and benchmark datasets for convolutional neural networks in flood applicationsAbdou Khouakhi, Joanna Zawadzka, Ian TruckellApplication of red edge band in remote sensing extraction of surface water body: a case study based on GF-6 WFV data in arid areaZhao Lu, Daqing Wang, Zhengdong Deng, Yue Shi, Zhibin Ding, Hao Ning, Hongfei Zhao, Jiazheng Zhao, Haoli Xu, Xiaoning ZhaoApplication of the artificial intelligence approach and remotely sensed imagery for soil moisture evaluationVahid NouraniHybrid point and interval prediction approaches for drought modeling using ground-based and remote sensing dataKiyoumars Roushangar, Roghayeh Ghasempour, V. S. Ozgur Kirca, Mehmet Cüneyd DemirelStochastic modeling of artificial neural networks for real-time hydrological forecasts based on uncertainties in transfer functions and ANN weightsShiang-Jen Wu, Chih-Tsung Hsu, Che-Hao ChangApplication of temporal convolutional network for flood forecastingYuanhao Xu, Caihong Hu, Qiang Wu, Zhichao Li, Shengqi Jian, Youqian Chen

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• Editorial: artificial intelligence in hydrologyElena Volpi, Jong Suk KIM, Shaleen Jain, Sangam ShresthaWavelet-based predictor screening for statistical downscaling of precipitation and temperature using the artificial neural network methodAida Hosseini Baghanam, Ehsan Norouzi, Vahid NouraniEvaluating the long short-term memory (LSTM) network for discharge prediction under changing climate conditionsCarolina Natel de Moura, Jan Seibert, Daniel Henrique Marco DetzelThe need for training and benchmark datasets for convolutional neural networks in flood applicationsAbdou Khouakhi, Joanna Zawadzka, Ian TruckellApplication of red edge band in remote sensing extraction of surface water body: a case study based on GF-6 WFV data in arid areaZhao Lu, Daqing Wang, Zhengdong Deng, Yue Shi, Zhibin Ding, Hao Ning, Hongfei Zhao, Jiazheng Zhao, Haoli Xu, Xiaoning ZhaoApplication of the artificial intelligence approach and remotely sensed imagery for soil moisture evaluationVahid NouraniHybrid point and interval prediction approaches for drought modeling using ground-based and remote sensing dataKiyoumars Roushangar, Roghayeh Ghasempour, V. S. Ozgur Kirca, Mehmet Cüneyd DemirelStochastic modeling of artificial neural networks for real-time hydrological forecasts based on uncertainties in transfer functions and ANN weightsShiang-Jen Wu, Chih-Tsung Hsu, Che-Hao ChangApplication of temporal convolutional network for flood forecastingYuanhao Xu, Caihong Hu, Qiang Wu, Zhichao Li, Shengqi Jian, Youqian Chen

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• Editorial: artificial intelligence in hydrologyElena Volpi, Jong Suk KIM, Shaleen Jain, Sangam ShresthaWavelet-based predictor screening for statistical downscaling of precipitation and temperature using the artificial neural network methodAida Hosseini Baghanam, Ehsan Norouzi, Vahid NouraniEvaluating the long short-term memory (LSTM) network for discharge prediction under changing climate conditionsCarolina Natel de Moura, Jan Seibert, Daniel Henrique Marco DetzelThe need for training and benchmark datasets for convolutional neural networks in flood applicationsAbdou Khouakhi, Joanna Zawadzka, Ian TruckellApplication of red edge band in remote sensing extraction of surface water body: a case study based on GF-6 WFV data in arid areaZhao Lu, Daqing Wang, Zhengdong Deng, Yue Shi, Zhibin Ding, Hao Ning, Hongfei Zhao, Jiazheng Zhao, Haoli Xu, Xiaoning ZhaoApplication of the artificial intelligence approach and remotely sensed imagery for soil moisture evaluationVahid NouraniHybrid point and interval prediction approaches for drought modeling using ground-based and remote sensing dataKiyoumars Roushangar, Roghayeh Ghasempour, V. S. Ozgur Kirca, Mehmet Cüneyd DemirelStochastic modeling of artificial neural networks for real-time hydrological forecasts based on uncertainties in transfer functions and ANN weightsShiang-Jen Wu, Chih-Tsung Hsu, Che-Hao ChangApplication of temporal convolutional network for flood forecastingYuanhao Xu, Caihong Hu, Qiang Wu, Zhichao Li, Shengqi Jian, Youqian Chen

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