Spatiotemporal Distribution of Irrigation Water Use Efficiency from the Perspective of Water Footprints in Heilongjiang Province

Abstract

Water footprints can reflect the sources and utilities of water resources. Introducing the water footprint theory to evaluate irrigation water use efficiency can reflect agricultural water consumption more scientifically and accurately. This study analyzes the variation trends of the blue, green and gray water footprints of grains in different regions of Heilongjiang Province and selects the grain-sowing area, total agricultural machinery power, grain blue water footprint and green water footprints and absolute fertilizer amount as input indexes and the agricultural gross product and gray water footprint of grain as output indexes. A slacks-based measure–data envelopment analysis (SBM-DEA) model is used to estimate the irrigation water use efficiencies of 11 cities in Heilongjiang Province, analyze the corresponding spatiotemporal distribution and further decompose and calculate the irrigation water use efficiencies of the five economically underdeveloped second-level cities. The results suggest that the spatial distribution of the grain water footprint in Heilongjiang Province reflects coexisting areas of excess and scarcity. The irrigation water use efficiency showed a steady and slow downward trend from 2008 to 2018. The irrigation water use efficiency reflected significant spatial differences in Heilongjiang Province, with a pattern of high values in the southwest and low values in the northeast; these differences have gradually narrowed. The average irrigation water use efficiency in Heilongjiang Province was 0.821 and the irrigation water efficiencies of Harbin, Qiqihar and Jixi were at the forefront of the province. Jiamusi, Hegang, Shuangyashan, Yichun, and Mudanjiang are the five cities with below-provincial-average irrigation water use efficiencies. The irrigation water use efficiency of Heilongjiang Province mainly depends on the pure technical efficiency. In the future, technical inputs should be improved on the basis of optimizing the agricultural production layout, focusing on improving the pure technical efficiency. The research results obtained herein can provide a theoretical basis for agricultural water management in Heilongjiang Province.

Evaluasi Efisiensi Penggunaan Sumber Daya Air dalam Irigasi Pertanian: Studi Kasus di Wilayah Kabupaten Cianjur

“…Studi ini menemukan bahwa efisiensi penggunaan air irigasi menunjukkan tren penurunan yang stabil dan lambat dari tahun 2008 hingga 2018, dan terdapat perbedaan spasial yang signifikan di Provinsi Heilongjiang, dengan pola nilai yang tinggi di bagian barat daya dan nilai yang rendah di bagian timur laut. Studi ini menyarankan agar rencana harus diformulasikan sesuai dengan kondisi lokal ketika meningkatkan AWUE di daerah kering dan semi-kering (Liu et al, 2022). They achieve the best air and light performance and create the air and light that keeps the alfalfa in the air with such a high air and light transmission that the alfalfa and air are significantly higher than you need please Note that this is not the case for P1 and P3.…”

“…Metode ini diusulkan untuk mengatasi keterbatasan efisiensi penggunaan air klasik (Koc, 2022;Sutrisno et al, 2016). Model analisis pengukuran-data envelopment (SBM-DEA) -Metode ini memperkirakan efisiensi penggunaan air irigasi di berbagai daerah dan kota dengan memilih indeks input seperti area penaburan biji-bijian, jumlah tenaga mesin pertanian, jejak air biru biji-bijian dan jejak air hijau, dan jumlah pupuk absolut, dan indeks output seperti produk bruto pertanian dan jejak air abu-abu biji-bijian (Liu et al, 2022).…”

Mapping Irrigated Areas in China Using a Synergy Approach

“…First, in Gansu, Guangdong, Guizhou, Hainan, Heilongjiang, Hubei, Liaoning, Ningxia Hui, Shanxi, Xinjiang, Xizang and Yunnan provinces, there is a net increase in irrigated cropland because the expansion in the irrigated area was much larger than the contraction. The largest growth took place in Heilongjiang, which is the largest grain-producing area in China [38].…”

Regional differences and dynamic evolution of agricultural water resources utilization efficiency in China

“…There are fuzzy comprehensive evaluation method [ 7 , 8 ], analytic hierarchy process [ 8 , 9 ], stochastic frontier method and data envelopment analysis (DEA) [ 6 , 10 – 14 ] in the evaluation method of agricultural water resource utilization efficiency. With the deepening of DEA research, the use of DEA method to measure the utilization efficiency of agricultural water resources has gradually changed from the original standard efficiency DEA model to the super efficiency DEA model [ 15 – 17 ], from only expected output model to include undesirable output [ 18 , 19 ], and SBM model can consider the relaxation variable problem [ 20 , 21 ], which has more advantages in efficiency measurement, so it has been more widely used [ 11 , 14 – 17 , 20 , 22 , 23 ]. Most of the economic studies on agricultural water resource utilization efficiency are analyzed from the influencing factors of efficiency changes [ 14 – 16 , 24 – 26 ].…”

“…When studying the utilization efficiency of agricultural water resources, many studies focus on the irrigation water use efficiency and regional distribution of the planting industry [1][2][3][4][5], and put forward reasonable suggestions, such as optimizing irrigation technology and developing water-saving agriculture [5,6]. There are fuzzy comprehensive evaluation method [7,8], analytic hierarchy process [8,9], stochastic frontier method and data envelopment analysis (DEA) [6,[10][11][12][13][14] in the evaluation method of agricultural water resource utilization efficiency. With the deepening of DEA research, the use of DEA method to measure the utilization efficiency of agricultural water resources has gradually changed from the original standard efficiency DEA model to the super efficiency DEA model [15][16][17], from only expected output model to include undesirable output [18,19], and SBM model can consider the relaxation variable problem [20,21], which has more advantages in efficiency measurement, so it has been more widely used [11, 14-17, 20, 22, 23].…”