Ước lượng lượng nước rút từ ống dẫn bằng phương pháp mềm kết hợp sóng trong điều kiện khí hậu đồng nhất và không đồng nhất

Springer Science and Business Media LLC - Tập 25 - Trang 5283-5314 - 2022
Sarvin Zamanzad-Ghavidel1,2, Sina Fazeli3, Sevda Mozaffari4, Reza Sobhani2, Mohammad Azamathulla Hazi5, Alireza Emadi2
1Daneshvaran Omran-Ab Consulting Engineers, Urmia, Iran
2Department of Water Engineering, Sari Agricultural Sciences and, Natural Resources University, Sari, Iran
3Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, Faculty of Agriculture Engineering and Technology, University of Tehran, Tehran, Iran
4Department of Water Engineering, Urmia University, Urmia, Iran
5Department of Civil and Environmental Engineering, University of the West Indies, St. Augustine, Trinidad and Tobago

Tóm tắt

Do biến đổi khí hậu và sự suy giảm nguồn tài nguyên nước mặt gần đây, tài nguyên nước ngầm, đặc biệt là nước ống dẫn, có vai trò đặc biệt quan trọng để đáp ứng các yêu cầu khác nhau của con người ở các vùng khô hạn và bán khô hạn. Với mục tiêu ước lượng lượng nước rút từ ống dẫn (AWW) cho các mục đích nông nghiệp, nghiên cứu hiện tại được thực hiện ở các khu vực Golpayegan và Kashan của Iran; được phân loại trong các vùng khí hậu không đồng nhất và đồng nhất với tình trạng thiếu nước. Các biến AWW được ước lượng dựa trên bốn kịch bản bao gồm (1) đặc điểm địa phương của ống dẫn, (2) thủy văn, (3) sử dụng đất, và (4) kịch bản kết hợp. Các biến [(Độ sâu giếng mẹ (MWD), chiều dài kênh ống dẫn (ACL)), (lưu lượng tối thiểu (QMin), lưu lượng tối đa (QMax)), và (Diện tích canh tác (CA), Diện tích vườn (OA))] liên quan đến kịch bản đầu tiên đến kịch bản thứ ba, tương ứng. Việc ước lượng AWW được thực hiện thông qua các phương pháp Soft-computing (SC) đơn lẻ và kết hợp sóng (W-hybrid với khử nhiễu), bao gồm mạng nơ-ron nhân tạo (ANNs), Wavelet-ANN (WANNs), hệ thống suy diễn mờ thích ứng (ANFIS), Wavelet-ANFIS (WANFIS), lập trình biểu thức gen (GEP), và Wavelet-GEP (WGEP). Hiệu quả của mô hình WGEP với các đặc điểm kết hợp của các biến MWD, ACL, QMin, QMax, CA và OA được khuyến nghị là mô hình tốt nhất để ước lượng các biến AWW không bị ảnh hưởng bởi điều kiện khí hậu. Với việc tăng mức độ phân rã trong phương pháp sóng và giảm nhiễu, hiệu suất của các mô hình ước lượng AWW đã tăng lên. Ngoài ra, các phát hiện cho thấy rằng việc thực hiện phương pháp đề xuất trong các khí hậu đồng nhất có thể có hiệu suất cao hơn so với khí hậu không đồng nhất. Giá trị RMSE đạt được cho yếu tố kết hợp của các mô hình WGEP lần lượt là 23.249 và 17.227 (×103 m3), cho ước lượng AWW ở Golpayegan và Kashan. Hiệu suất của WGEP rất xuất sắc (R > 0.920) trong việc ước lượng AWW ở cả hai loại khí hậu cho các mức cực đại. Việc trừu tượng hóa công thức toán học của các mô hình GEP và WGEP là một phần trong nghiên cứu tìm ra các ảnh hưởng sâu sắc từ việc thực hiện các chính sách liên quan đến Quản lý Tài nguyên Nước Tích hợp để bảo vệ sự hủy hoại của ống dẫn do tiêu thụ quá mức.

Từ khóa

#biến đổi khí hậu #nguồn nước ngầm #ống dẫn #ước lượng AWW #phương pháp mềm kết hợp sóng #mô hình WGEP

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