Special Issue "Water and Soil Resources Management in Agricultural Areas"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water, Agriculture and Aquaculture".

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 7738

Special Issue Editors

Prof. Dr. Qiang Fu
E-Mail Website
Guest Editor
School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin, Heilongjiang 150030, China
Interests: water-efficient irrigation; water and soil management; freeze–thaw cycle; water–heat transport; biochar; seasonally frozen areas; soil environment
Prof. Dr. Yongqiang Cao
E-Mail Website
Guest Editor
School of Geographical Sciences, Liaoning Normal University, Dalian, Liaoning, China
Interests: efficient utilization of water resources; water–food–energy nexus; hydrological forecast; risk analysis; water environment management
Dr. Tianxiao Li
E-Mail Website
Guest Editor
School of Water Conservancy & Civil Engineering, Northeast Agricultural University, Harbin, Heilongjiang, China
Interests: agricultural water and soil resources; efficient utilization; hydrological forecast; freeze–thaw cycle; water and sediment process
Prof. Dr. Mo Li
E-Mail Website
Guest Editor
School of Water Conservancy & Civil Engineering, Northeast Agricultural University, Harbin, Heilongjiang, China
Interests: water and soil allocation; optimization modelling; water–food–energy nexus; uncertainty; water cycle; soil environment

Special Issue Information

Dear Colleagues,

Water scarcity is becoming an urgent global-scale issue by virtue of a shrinking water supply and deteriorating water quality, hampering ecosystem health and socioeconomic development. This restricts the development of the agricultural sector because water resources originally used for agricultural irrigation have to be diverted to domestic, industrial, and ecological activities. This diversion will correspondingly reduce agricultural benefit and thus affect the distribution of crop cultivation. Against this backdrop, agricultural water and soil resources require effective regulation and management to promote agricultural sustainability. However, agricultural water and/or soil management (AWSM) cover a multi-scale range, e.g., crop, field, irrigated area, and watershed. AWSM is relevant to hydrological processes, energy consumption, socioeconomic development, environmental protection, and climate change. Therefore, it is an urgent need to solve the problem from multiple scale perspectives using interdisciplinary methods. Contributions to this Special Issue will encompass a broad spectrum of topics in AWSM, including but not limited to:

  • AWSM considering crop growth and social and environment aspects;
  • Hydrological processes in AWSM and related effects;
  • Optimization of agricultural water–food–energy nexus;
  • Modeling-based development for AWSM;
  • Management and assessment of AWSM;
  • Decision support system of AWSM;
  • Quantification of the various water footprints to AWSM;
  • Data mining in hydrology and agricultural water and soil-based systems.

Prof. Dr. Qiang Fu
Prof. Dr. Yongqiang Cao
Dr. Tianxiao Li
Prof. Dr. Mo Li
Guest Editors

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Keywords

  • water resources management
  • cropping pattern optimization
  • agriculture
  • water–food–energy nexus
  • water and soil allocation and planning
  • hydrological forecasting
  • water cycle and related processes
  • sustainability
  • modelling

Published Papers (12 papers)

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Research

Article
Diagnosis of Basin Eco-Hydrological Variation Based on Index Sensitivity of Similar Years: A Case Study in the Hanjiang River Basin
Water 2022, 14(12), 1931; https://doi.org/10.3390/w14121931 - 16 Jun 2022
Viewed by 381
Abstract
The variation of hydrological conditions in the basin affects the original stable state of the basin, and the change of eco-hydrological conditions also plays a decisive role in the stability of the basin. In this manuscript, Indicators of Hydrologic Alteration (IHA) was used [...] Read more.
The variation of hydrological conditions in the basin affects the original stable state of the basin, and the change of eco-hydrological conditions also plays a decisive role in the stability of the basin. In this manuscript, Indicators of Hydrologic Alteration (IHA) was used to diagnose watershed variation from the eco-hydrological perspective, and a new diagnostic method was proposed in the current study, which was the extraction method of the most relevant eco-hydrological indicators based on a similar year sensitive index and the diagnosis method of variation period. This method used the sensitivity of statistical characteristics between similar years to provide the basis for the selection of the most ecologically-relevant hydrogeological indicators (ERHIs), then selected the strong variation indicators from the most relevant eco-hydrological indicators, and finally used the strong variation indicators to diagnose the watershed variation. The runoff data (1960 to 2020) in the Ankang gauging station of the Hanjiang River were analyzed, and the results showed that the indicators of high variation were the average duration index of low discharge in a year and the minimum discharge index of one day in a year. The variation period was from 1973 to 1986. It was concluded that the diagnosis results from the perspective of eco-hydrology were consistent with the actual hydrological situation changes, and this method had certain reliability. Full article
(This article belongs to the Special Issue Water and Soil Resources Management in Agricultural Areas)
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Article
Assessing the Forecasting Accuracy of a Modified Grey Self-Memory Precipitation Model Considering Scale Effects
Water 2022, 14(10), 1647; https://doi.org/10.3390/w14101647 - 21 May 2022
Viewed by 428
Abstract
Precipitation is an important parameter in water resource management, urban flood warning systems, and hydrological analyses. Precipitation forecasting can provide a decision-making basis for relevant organizations, such as those in the agricultural sector and water conservancy departments. In this paper, a modified grey [...] Read more.
Precipitation is an important parameter in water resource management, urban flood warning systems, and hydrological analyses. Precipitation forecasting can provide a decision-making basis for relevant organizations, such as those in the agricultural sector and water conservancy departments. In this paper, a modified grey self-memory model (MGSM) was constructed by combining a self-memory function and grey theory. To verify the precision of the model in cases in which measured data are not available in the forecasting stage, a self-test method based on the scale effect in the precipitation forecasting stage was proposed. Ultimately, the model was verified based on three precipitation scales—the annual scale, the crop growth period, and the monthly scale—in the crop growth period from 1961 to 2018 in the Songnen Plain area, Heilongjiang Province. The results showed that the MGSM yielded higher fitting accuracy than the original GM(1,1) and grey self-memory models. Furthermore, the precipitation in the study area was predicted with the MSGM at the three different scales above from 2019 to 2023. The accuracy of forecasting meets the relevant requirements, and the model can be used to forecast precipitation trends at different time scales in the future. The results provide a reference for formulating scientific and rational agricultural water use strategies and guiding agricultural production practices. Full article
(This article belongs to the Special Issue Water and Soil Resources Management in Agricultural Areas)
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Article
Imputation of Ammonium Nitrogen Concentration in Groundwater Based on a Machine Learning Method
Water 2022, 14(10), 1595; https://doi.org/10.3390/w14101595 - 16 May 2022
Viewed by 534
Abstract
Ammonium is one of the main inorganic pollutants in groundwater, mainly due to agricultural, industrial and domestic pollution. Excessive ammonium can cause human health risks and environmental consequences. Its temporal and spatial distribution is affected by factors such as meteorology, hydrology, hydrogeology and [...] Read more.
Ammonium is one of the main inorganic pollutants in groundwater, mainly due to agricultural, industrial and domestic pollution. Excessive ammonium can cause human health risks and environmental consequences. Its temporal and spatial distribution is affected by factors such as meteorology, hydrology, hydrogeology and land use type. Thus, a groundwater ammonium analysis based on limited sampling points produces large uncertainties. In this study, organic matter content, groundwater depth, clay thickness, total nitrogen content (TN), cation exchange capacity (CEC), pH and land-use type were selected as potential contributing factors to establish a machine learning model for fitting the ammonium concentration. The Shapley Additive exPlanations (SHAP) method, which explains the machine learning model, was applied to identify the more significant influencing factors. Finally, the machine learning model established according to the more significant influencing factors was used to impute point data in the study area. From the results, the soil organic matter feature was found to have a substantial impact on the concentration of ammonium in the model, followed by soil pH, clay thickness and groundwater depth. The ammonium concentration generally decreased from northwest to southeast. The highest values were concentrated in the northwest and northeast. The lowest values were concentrated in the southeast, southwest and parts of the east and north. The spatial interpolation based on the machine learning imputation model established according to the influencing factors provides a reliable groundwater quality assessment and was not limited by the number and the geographical location of samplings. Full article
(This article belongs to the Special Issue Water and Soil Resources Management in Agricultural Areas)
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Article
Flood Forecasting via the Ensemble Kalman Filter Method Using Merged Satellite and Measured Soil Moisture Data
Water 2022, 14(10), 1555; https://doi.org/10.3390/w14101555 - 12 May 2022
Viewed by 441
Abstract
Flood monitoring in the Chaohe River Basin is crucial for the timely and accurate forecasting of flood flow. Hydrological models used for the simulation of hydrological processes are affected by soil moisture (SM) data and uncertain model parameters. Hence, in this study, measured [...] Read more.
Flood monitoring in the Chaohe River Basin is crucial for the timely and accurate forecasting of flood flow. Hydrological models used for the simulation of hydrological processes are affected by soil moisture (SM) data and uncertain model parameters. Hence, in this study, measured satellite-based SM data obtained from different spatial scales were merged, and the model state and parameters were updated in real time via the data assimilation method named ensemble Kalman filter. Four different assimilation settings were used for the forecasting of different floods at three hydrological stations in the Chaohe River Basin: flood forecasting without data assimilation (NA case), assimilation of runoff data (AF case), assimilation of runoff and satellite-based soil moisture data (AFWR case), and assimilation of runoff and merged soil moisture data (AFWM case). Compared with NA, the relative error (RE) of small, medium, and large floods decreased from 0.53 to 0.23, 0.35 to 0.16, and 0.34 to 0.12 in the AF case, respectively, indicating that the runoff prediction was significantly improved by the assimilation of runoff data. In the AFWR and AFWM cases, the REs of the small, medium, and large floods also decreased, indicating that the soil moisture data play important roles in the assimilation of medium and small floods. To study the factors affecting the assimilation, the changes in the parameter mean and variance and the number of set samples were analyzed. Our results have important implications for the prediction of different levels of floods and related assimilation processes. Full article
(This article belongs to the Special Issue Water and Soil Resources Management in Agricultural Areas)
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Article
Analysis of Temperature Effect on Saturated Hydraulic Conductivity of the Chinese Loess
Water 2022, 14(9), 1327; https://doi.org/10.3390/w14091327 - 19 Apr 2022
Viewed by 462
Abstract
Saturated hydraulic conductivity (Ks) is a significant basic hydraulic parameter in the field of soil science. However, it is typically used as a constant, and that will lead to some inaccurate results in numerical simulations of water movement. In this study, [...] Read more.
Saturated hydraulic conductivity (Ks) is a significant basic hydraulic parameter in the field of soil science. However, it is typically used as a constant, and that will lead to some inaccurate results in numerical simulations of water movement. In this study, a laboratory experiment was conducted to investigate the effect of temperature on Ks of Chinese loess. The results indicated that Ks had a special relationship with temperature for this soil: Ks increased in the range of temperatures (t) from 7 to 44 °C. A formula in Forest Standard of China LY/T 1218-1999 can well describe the distribution characteristics of the experimental data, but it may not apply if bulk density changes. The study improved the formula by analyzing another set of published experimental data. In the improved formula, the influence of bulk density and temperature on Ks is fully considered. The results show that the improved formula can be applied to the simulation of saturated water flow by accurately describing Ks variation with temperature and bulk density. Full article
(This article belongs to the Special Issue Water and Soil Resources Management in Agricultural Areas)
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Article
Spatiotemporal Distribution of Irrigation Water Use Efficiency from the Perspective of Water Footprints in Heilongjiang Province
Water 2022, 14(8), 1232; https://doi.org/10.3390/w14081232 - 12 Apr 2022
Viewed by 440
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Water and Soil Resources Management in Agricultural Areas)
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Article
Study on the Matching Method of Agricultural Water and Land Resources from the Perspective of Total Water Footprint
Water 2022, 14(7), 1120; https://doi.org/10.3390/w14071120 - 31 Mar 2022
Cited by 1 | Viewed by 434
Abstract
The matching status of agricultural water and land resources is a prerequisite for grain production. The influence of gray water footprint has not been paid attention to in the study of agricultural water and land resources matching based on water footprint. To measure [...] Read more.
The matching status of agricultural water and land resources is a prerequisite for grain production. The influence of gray water footprint has not been paid attention to in the study of agricultural water and land resources matching based on water footprint. To measure the matching status of agricultural water and land resources more comprehensively, the total water footprint (including blue, green and gray water footprint) and the cultivated land area was taken as the characterization parameters of water and land resources, respectively. The Gini coefficient model, and the agricultural water and land resources matching coefficient model were constructed to calculate the matching degree of agricultural water and land resources in a cold region (Heilongjiang Province) of China. Based on the amount of agricultural water consumption, the equivalent coefficient model was used to evaluate the degree of agricultural water and land resources shortage or to be developed. The result of agricultural water and land resources matching coefficient model showed that the matching degree of agricultural water and land resources in Heilongjiang Province is getting better year by year, which is consistent with the calculations determined from the Gini coefficient. The result of the equivalent coefficient method based on agricultural water consumption was consistent with the result of the Gini coefficient method based on total water footprint, which is verified that it is scientific and reasonable to take the total water footprint as the characterization parameter of water resource. The findings may provide implications for the spatial optimal allocation of regional agricultural water and land resources. Full article
(This article belongs to the Special Issue Water and Soil Resources Management in Agricultural Areas)
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Article
Study on the Spatial and Temporal Distribution of Irrigation Water Requirements for Major Crops in Shandong Province
Water 2022, 14(7), 1051; https://doi.org/10.3390/w14071051 - 27 Mar 2022
Cited by 2 | Viewed by 518
Abstract
Understanding the spatial and temporal distribution of irrigation water requirements is significant to realize the rational allocation of water resources and also serves as the basis for analyzing agricultural water-saving potential. This study refers to the standard irrigation regions in southwestern, northern, central, [...] Read more.
Understanding the spatial and temporal distribution of irrigation water requirements is significant to realize the rational allocation of water resources and also serves as the basis for analyzing agricultural water-saving potential. This study refers to the standard irrigation regions in southwestern, northern, central, southern, and eastern Shandong province. The irrigation water requirements at 20 weather stations in Shandong Province from 1968 to 2016 were calculated, and the spatial and temporal distribution characteristics were analyzed. The results indicated the following: (a) The trend of the annual irrigation water requirements for summer maize and winter wheat showed an insignificant increase in the eastern Shandong irrigation region, a significant decline in northern and southwestern Shandong irrigation regions, and an insignificant decrease in the other irrigation regions. (b) The multi-year average irrigation water requirement for summer maize generally presents a spatial distribution characteristic which is less in the southwest, more in the northeast, less in the south, and more in the north, while the spatial distribution characteristic for winter wheat is less in the southeast, more in the northwest, less in the south, and more in the north. (c) The main meteorological factors affecting the irrigation water requirements for summer maize are precipitation and sunshine duration, while relative humidity is the main factor affecting winter wheat in Shandong Province. Full article
(This article belongs to the Special Issue Water and Soil Resources Management in Agricultural Areas)
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Article
Assessment of Seasonal Drought Impact on Potato in the Northern Single Cropping Area of China
Water 2022, 14(3), 494; https://doi.org/10.3390/w14030494 - 07 Feb 2022
Viewed by 453
Abstract
Drought is one of the key limiting factors for potato yield in the northern single cropping area (NSCA) in China. To analyze the impact of drought on potato yield in the NSCA, this study first analyzed the variation of dry/wet conditions in the [...] Read more.
Drought is one of the key limiting factors for potato yield in the northern single cropping area (NSCA) in China. To analyze the impact of drought on potato yield in the NSCA, this study first analyzed the variation of dry/wet conditions in the plantable areas on a seasonal scale using the standardized precipitation evapotranspiration index (SPEI). Secondly, the changes in yield structure in the last 36 years were systematically analyzed and divided the total yield change into planting area contribution and climate yield contribution. Finally, a regression model of the seasonal drought index and contributing factors of total yield change in different administrative regions was constructed. The results showed that the main factors affecting the total potato yield of the NSCA began to change from yield to planting area in the 1990s, while the barycenter of the output structure and population moved to the southwest, with grassland being the main source; dry/wet conditions (year i) had varying degrees of effect on contributing factors (year i, year i + 1) of total yield change in different administrative regions that were not limited to the growing season; the non-overlap of high-yield area, high-adaptability area and planting area was the urgent problem to be solved for the NSCA. The results of this study can provide a scientific basis for NSCA crop management and communication with farmers, providing new ideas for sustainable production in other agricultural regions in the world. Full article
(This article belongs to the Special Issue Water and Soil Resources Management in Agricultural Areas)
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Article
The Dynamics Characteristics of Soil Water Infiltration and Capillary Rise for Saline–Sodic Soil Mixed with Sediment
Water 2022, 14(3), 481; https://doi.org/10.3390/w14030481 - 06 Feb 2022
Viewed by 568
Abstract
Yellow River sediment is the potential resource for saline–sodic soil reclamation. Experiments of one-dimensional soil columns were conducted to investigate the upward and downward soil water transportation characteristics for saline–sodic soil mixed with different sediment addition (0, 10, 20 kg/m2 in the [...] Read more.
Yellow River sediment is the potential resource for saline–sodic soil reclamation. Experiments of one-dimensional soil columns were conducted to investigate the upward and downward soil water transportation characteristics for saline–sodic soil mixed with different sediment addition (0, 10, 20 kg/m2 in the top 20 cm layer). The saturated hydraulic conductivity, ratio of macroporosity, cumulative capillary adsorption and infiltration rate all increased with the increase in sediment addition. No significant differences were detected for both the initial capillary rise rate and the initial infiltration rate for the upward and downward water transportation treatments, respectively. The average adsorption and infiltration rates showed an increasing trend with the increased sediment addition. The initial and average infiltration rates were higher than the initial capillary rise rate and average adsorption rates. The Philip model seems the optimal choice for the dynamic simulation of both upward and downward soil water transportation. The results may provide useful information for soil salinization amelioration. Full article
(This article belongs to the Special Issue Water and Soil Resources Management in Agricultural Areas)
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Article
Research on the Non-Point Source Pollution Characteristics of Important Drinking Water Sources
Water 2022, 14(2), 211; https://doi.org/10.3390/w14020211 - 12 Jan 2022
Cited by 1 | Viewed by 541
Abstract
In recent years, freshwater resource contamination by non-point source pollution has become particularly prominent in China. To control non-point source (NPS) pollution, it is important to estimate NPS pollution exports, identify sources of pollution, and analyze the pollution characteristics. As such, in this [...] Read more.
In recent years, freshwater resource contamination by non-point source pollution has become particularly prominent in China. To control non-point source (NPS) pollution, it is important to estimate NPS pollution exports, identify sources of pollution, and analyze the pollution characteristics. As such, in this study, we established the modified export coefficient model based on rainfall and terrain to investigate the pollution sources and characteristics of non-point source total nitrogen (TN) and total phosphorus (TP) throughout the Huangqian Reservoir watershed—which serves as an important potable water source for the main tributary of the lower Yellow River. The results showed that: (1) In 2018, the non-point source total nitrogen (TN) and total phosphorus (TP) loads in the Huangqian Reservoir basin were 707.09 t and 114.42 t, respectively. The contribution ratios to TN export were, from high to low, rural life (33.58%), farmland (32.68%), other land use types (20.08%), and livestock and poultry breeding (13.67%). The contribution ratios to TP export were, from high to low, rural life (61.19%), livestock and poultry breeding (21.65%), farmland (12.79%), and other land use types (4.38%). The non-point source pollution primarily originated from the rural life of the water source protection zone. (2) Non-point source TN and TP pollution loads and load intensities showed significantly different spatial distribution patterns throughout the water source protection area. Specifically, their load intensities and loads were the largest in the second-class protected zone, which is the key source area of non-point source pollution. (3) When considering whether to invest in agricultural land fertilizer control or rural domestic sewage, waste, and livestock manure pollution control, the latter is demonstrably more effective. Thus, in addition to putting low-grade control on agricultural fertilizer loss, to rapidly and effectively improve potable water quality, non-point source pollution should, to a larger extent, also be controlled through measures such as establishing household biogas digesters, introducing village sewage treatment plants, and improving the recovery rate of rural domestic garbage. The research results discussed herein provide a theoretical basis for formulating a reasonable and effective protection plan for the Huangqian Reservoir water source and can potentially be used to do the same for other similar freshwater resources. Full article
(This article belongs to the Special Issue Water and Soil Resources Management in Agricultural Areas)
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Article
Study on Health Evaluation of an Ecological Irrigation District in Helan County, China
Water 2021, 13(23), 3325; https://doi.org/10.3390/w13233325 - 23 Nov 2021
Viewed by 555
Abstract
The construction of ecological irrigation districts is of great significance to protect the Yellow River ecology and achieve sustainable development of the local ecological economy. Taking the ecological irrigation district of Helan County as the study area, a health evaluation index system of [...] Read more.
The construction of ecological irrigation districts is of great significance to protect the Yellow River ecology and achieve sustainable development of the local ecological economy. Taking the ecological irrigation district of Helan County as the study area, a health evaluation index system of the irrigation district was established, including three primary indexes of ecological environment, modernization level, and agricultural production and benefit, and 20 secondary indexes. Then, the Topsis method, entropy weight evaluation method, fuzzy pattern recognition model, and variable fuzzy model were used to evaluate the health of the Helan ecological irrigation district. In order to avoid the one-sidedness of the evaluation results of a single evaluation method, a combined evaluation method named deviation maximization combined evaluation method was used to combine each single evaluation result. The evaluation results by the combined evaluation method showed the following: (1) The ecological health of Helan irrigation district had a trend of becoming better from 2007 to 2016. (2) The grey correlation analysis showed that the soil salt content, groundwater depth, canal lining rate, ratio of efficient water-saving irrigation area, information level of the irrigation district, water productivity, agricultural unilateral aquatic output value, irrigation water consumption per mu, and coefficient of effective utilization of farmland irrigation water were closely related to the evaluation results. (3) In order to effectively improve the ecological health of Helan irrigation districts, it is necessary to reduce soil salt content and groundwater salinity, increase canal linings, promote water-saving irrigation measures, and agricultural information construction, etc. Full article
(This article belongs to the Special Issue Water and Soil Resources Management in Agricultural Areas)
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