Your search found 4 records
1 Yu, B.; Shang, S. 2020. Estimating growing season evapotranspiration and transpiration of major crops over a large irrigation district from HJ-1A/1B data using a remote sensing-based dual source evapotranspiration model. Remote Sensing, 12(5):865. (Special issue: Remote Sensing in Agricultural Hydrology and Water Resources Modeling) [doi: https://doi.org/10.3390/rs12050865]
Crops ; Evapotranspiration ; Plant growth ; Irrigation water ; Remote sensing ; Satellite imagery ; Water balance ; Maize ; Sunflowers ; Models ; Normalized difference vegetation index / China / Inner Mongolia Autonomous Region / Hetao Irrigation District / Dengkou / Hangjinhouqi / Linhe / Wuyuan
(Location: IWMI HQ Call no: e-copy only Record No: H049725)
(6.10 MB) (6.10 MB)
Crop evapotranspiration (ET) is the largest water consumer of agriculture water in an irrigation district. Remote sensing (RS) technique has provided an effective way to map regional ET using various RS-based ET models over the past several decades. To map growing season ET of different crops and partition ET into evaporation (E) and transpiration (T) at regional scale, appropriate ET models should be further integrated with crop distribution maps in different years and crop growing seasons determined for each crop pixel. In this study, a hybrid dual-source scheme and trapezoid framework-based ET Model (HTEM) fed with HJ-1A/1B data was applied in Hetao Irrigation District (HID) of China from 2009 to 2015 to map crop growing season ET and T at 30 m resolution. The HTEM model with HJ-1A/1B data performed well in estimating ET in HID, and the finer spatial resolution of model input data can improve the estimation accuracy of ET. Combined with the annual crop planting map identified in previous study, and crop growing seasons determined from fitted Normalized Difference Vegetation Index (NDVI) curves for crop pixels, the spatial and temporal variations of growing season ET and T of major crops (maize and sunflower) were examined. The results indicate that ET and T of maize and sunflower reach their minimum values in the southwest HID with smaller crop planting density, and reach their maximum values in northwest HID with higher crop planting density. Over the study period with a decreasing trend of available irrigation water, ET and T in maize and sunflower growing seasons show decreasing trends, while ratios of T/ET show increasing trends, which implies that the adverse effect of decreased irrigation water diversion on crop growth is diminished due to the favorable portioning of E and T in cropland of HID. In addition, the calculation results of crop coefficients show that there is water stress to crop growth in the study area. The present results are helpful to better understand the spatial pattern of crop water consumption and water stress of different crops during crop growing season, and provide the basis for optimizing the spatial distribution of crop planting with less water consumption and more crop yield.
2 Zhang, X.; Guo, P.; Guo, W.; Gong, J.; Luo, B. 2021. Optimization towards sustainable development in shallow groundwater area and risk analysis. Agricultural Water Management, 258:107225. (Online first) [doi: https://doi.org/10.1016/j.agwat.2021.107225]
Groundwater table ; Sustainable development ; Risk analysis ; Sustainable agriculture ; Agricultural development ; Crop production ; Water stress ; Water use efficiency ; Water allocation ; Water supply ; Soil water content ; Soil salinization ; Crop yield ; Energy consumption ; Uncertainty / China / Inner Mongolia Autonomous Region / Hetao Irrigation District / Yellow River
(Location: IWMI HQ Call no: e-copy only Record No: H050705)
(3.86 MB)
The projected increasing food demand in the coming decades will require substantial water and energy resources. Practical approaches are expected to propose to realize enhancing crop production while towards sustainable development in shallow groundwater area. This study integrates a process-based model, multi-objectives, and fuzzy theory into optimization model to optimize crops water allocation pattern under uncertainties of water diversion and groundwater. The process-based model considers the water exchange between soil and groundwater, water stress and salt stress on crops, and ground water level changes. The multi-objectives defined in this study balances the conflicts of maximizing crop production, maximizing water use efficiency, and minimizing energy consumption. The uncertain amount of water diversion and groundwater is presented as fuzzy numbers. The optimized water allocation pattern of 3 crops in 12 water supply response units in Hetao Irrigation District show that the crop yield does not necessarily reach to the highest potential value, though wheat and maize are allocated more water than sunflower and have larger possibility to reach high crop yield. Significant energy investment is needed for extracting and purifying groundwater to ensure relatively high crop production at the case of possible low available water. Uncertainties of water diversion and groundwater will cause a greater range of ground water level in wheat field, a high risk of water stress in sunflower field and a high risk of very severe salinization in wheat field. The different changing directions of three sub-objectives demonstrate that optimal water allocation has no uniform rule but changes with available water.
3 Zhang, R.; Wu, J.; Yang, Y.; Peng, X.; Li, C.; Zhao, Q. 2022. A method to determine optimum ecological groundwater table depth in semi-arid areas. Ecological Indicators, 139:108915. [doi: https://doi.org/10.1016/j.ecolind.2022.108915]
Groundwater table ; Water depth ; Indicators ; Ecological factors ; Semiarid zones ; Models ; Normalized difference vegetation index ; Uncertainty ; Remote sensing ; Soil water content ; Populus / China / Inner Mongolia / Hetao Irrigation District
(Location: IWMI HQ Call no: e-copy only Record No: H051128)
https://www.sciencedirect.com/science/article/pii/S1470160X22003867/pdfft?md5=99831de53fd285ba271967a2781724db&pid=1-s2.0-S1470160X22003867-main.pdf
https://vlibrary.iwmi.org/pdf/H051128.pdf
https://vlibrary.iwmi.org/pdf/H051128.pdf
(9.24 MB) (9.24 MB)
Groundwater depth (GWD) is an important factor to sustain the ecological integrity of some ecosystems and is often used as an indicator of environmental quality in dry areas. Single-scale data gained from quadrat surveys is always used to establish a relationship with GWD to determine the optimum GWD. However, the randomness and uncertainty in single-scale data may result in insufficient reliability of results. To overcome this shortage, multiple growth indicators of poplar trees (Populus euphratica) in Hetao Irrigation District, including average crown width (ACW), tree height, diameter at breast height (DBH), mean ring spacing (MRC), and normalized difference vegetation index (NDVI), were acquired by field sampling and remote sensing. These indicators were used to establish relationships with the GWD by considering spatial and temporal variation to identify the optimum GWD. The cloud model was introduced and its three digital features derived from optimum groundwater depth data (expectation: Ex, entropy: En, and super-entropy: He) were calculated to construct the reverse cloud models W (Ex, En, He) for describing ecological GWD to determine the optimum ecological GWD in semi-arid areas. The results show that the optimum GWD range was 1.60–2.20 m. The cloud models obtained on spatial and temporal scales were WS (2.01, 0.07, 0.04) and WT (1.78, 0.10, 0.02), respectively. The resulting comprehensive cloud model WC (1.87, 0.14, 0.03) exhibited better variability, so 1.87 m was taken as the optimum GWD for poplars. This method can determine the regional ecological groundwater level more accurately and effectively, and provide evaluation indicators for the management of regional groundwater.
4 Wen, Y.; Wan, H.; Shang, S.; Rahman, K. U. 2022. A monthly distributed agro-hydrological model for irrigation district in arid region with shallow groundwater table. Journal of Hydrology, 609:127746. [doi: https://doi.org/10.1016/j.jhydrol.2022.127746]
Irrigation water ; Groundwater table ; Hydrological modelling ; Arid zones ; Evapotranspiration ; Drainage systems ; Irrigation canals ; Water balance ; Precipitation ; Soil water ; Groundwater flow ; Irrigated land ; Salinity ; Farmland ; Soil texture ; Land use mapping ; Remote sensing / China / Inner Mongolia / Hetao Irrigation District / Yellow River
(Location: IWMI HQ Call no: e-copy only Record No: H051126)
(14.10 MB)
Agro-hydrological processes in arid irrigation districts mainly include precipitation, water diversion, irrigation, drainage, evapotranspiration (ET), and soil water and groundwater flow, which interact with each other and are controlled by complex natural and anthropogenic drivers. To better understand the agro-hydrological processes in arid irrigation districts with shallow groundwater table, we developed a novel monthly distributed agro-hydrological model for irrigation districts (DAHMID) based on the concepts of canal command area (CCA) and sub-drainage command area (SDCA). The DAHMID model is driven by meteorology, irrigation, and evapotranspiration (ET) estimated by remote sensing-based ET model, and considers soil water and groundwater balances in both irrigated and non-irrigated lands and interior drainage between them. The model was applied to Hetao Irrigation District (HID), the largest irrigation district in arid region of China with a total irrigated area of 0.68 million ha. The DAHMID model was calibrated with groundwater table depth measurements in 13 CCAs of HID from 2008 to 2010, and validated from 2012 to 2013. Results depicted that the root mean square errors (RMSEs), normalized RMSEs (NRMSEs), Nash-Sutcliffe efficiency coefficients (NSEs), and coefficients of determination (r2) of groundwater table depth in both irrigated and non-irrigated lands for all CCAs were in the ranges of 0.19–0.34 m, 0.10–0.25, 0.30–0.82, and 0.68–0.91, respectively. The simulation results from 2008 to 2014 indicated that interior drainage from irrigated land to non-irrigated land is an important approach of drainage in HID, which is about 14.3% of total irrigation water diversion and 34.9% more than the drainage through ditches. The interior drainage process is basically similar to irrigation and ditch drainage processes, all reaching their peaks in May and October. ET is the major water consumption in HID, which is about 95% of total irrigation water diversion and precipitation in average. The net capillary rise of irrigated land is significantly less than that of non-irrigated land due to the impact of irrigation infiltration. The DAHMID model has less parameters and requires less inputs, and can be better applied to continuous simulation of agro-hydrological processes in irrigation districts in medium and long periods with satisfactory simulation accuracy.
Powered by DB/Text WebPublisher, from
