scholarly journals Simulation of Crop Water Demand and Consumption Considering Irrigation Effects Based on Coupled Hydrology–Crop Growth Model

2021 ◽  
Author(s):  
Yuliang Zhang ◽  
Zhiyong Wu ◽  
Vijay P. Singh ◽  
Qiong Su ◽  
Hai He ◽  
...  
Keyword(s):  
Growth Model ◽  
Water Demand ◽  
Crop Growth ◽  
Crop Water ◽  
Crop Growth Model ◽  
Crop Water Demand ◽  
Irrigation Effects

scholarly journals Implementing the nitrogen cycle into the dynamic global vegetation, hydrology, and crop growth model LPJmL (version 5.0)

2018 ◽  
Vol 11 (7) ◽  
pp. 2789-2812 ◽  
Author(s):  
Werner von Bloh ◽  
Sibyll Schaphoff ◽  
Christoph Müller ◽  
Susanne Rolinski ◽  
Katharina Waha ◽  
...  
Keyword(s):  
Growth Model ◽  
Nitrogen Cycle ◽  
Crop Productivity ◽  
Crop Growth ◽  
Limiting Factors ◽  
Full Detail ◽  
Crop Growth Model ◽  
Maintenance Respiration ◽  
Area Index ◽  
Global Vegetation

Abstract. The well-established dynamical global vegetation, hydrology, and crop growth model LPJmL is extended with a terrestrial nitrogen cycle to account for nutrient limitations. In particular, processes of soil nitrogen dynamics, plant uptake, nitrogen allocation, response of photosynthesis and maintenance respiration to varying nitrogen concentrations in plant organs, and agricultural nitrogen management are included in the model. All new model features are described in full detail and the results of a global simulation of the historic past (1901–2009) are presented for evaluation of the model performance. We find that the implementation of nitrogen limitation significantly improves the simulation of global patterns of crop productivity. Regional differences in crop productivity, which had to be calibrated via a scaling of the maximum leaf area index, can now largely be reproduced by the model, except for regions where fertilizer inputs and climate conditions are not the yield-limiting factors. Furthermore, it can be shown that land use has a strong influence on nitrogen losses, increasing leaching by 93 %.

Future Climatic Patterns and Sustainability of Current Cropping Patterns in a Water-Scarce River Basin of Eastern India 

2021 ◽  
Author(s):  
Smaranika Mahapatra ◽  
Madan Kumar Jha
Keyword(s):  
Water Demand ◽  
Agricultural Sector ◽  
Monsoon Rainfall ◽  
Baseline Period ◽  
Eastern India ◽  
Crop Water ◽  
Cropping Patterns ◽  
Water Demands ◽  
Crop Water Demand ◽  
Water Scarce

<p>Agricultural sector, being the largest consumer of water is greatly affected by climatic variability and disasters. Most parts of the world already face an enormous challenge in meeting competitive and conflicting multi-sector water demands. Climate change has further exacerbated this challenge by putting the sustainability of current cropping patterns and irrigation practices in question. For ensuring climate-resilient food production, it is crucial to examine the patterns of the projected climate and potential impacts on the agricultural sector at a basin scale. Hence, this study was carried out for an already water-scarce basin, Rushikulya River basin (RRB), located in the coastal region of eastern India. The bias-corrected NorESM2-MM general circulation model of Coupled Model Intercomparison Project-6 (CMIP6) was used in this study under four shared socioeconomic pathway (SSPs) scenarios, namely SSP126, SSP245, SSP370 and SSP585. The projected climatic parameters and crop water demands of the basin were analyzed assuming existing cropping pattern in the future. Analysis of the results reveals a significant and rapid increase in the temperature at a rate of 0.02-0.5ºC/year during 2026-2100 under all SSPs except SSP126, whereas the rainfall is expected to increase slightly during 2026-2100 as compared to the baseline period (1990-2016), especially in the far future (2076-2100) under all the SSPs. In contrast, monsoon rainfall is predicted to decrease under SSP245 and SSP370, while a slight increase in the monsoon rainfall is evident under SSP126 and SSP585. Although the rainy days will decrease slightly in the future 25-year time window, the number of heavy rainfall events is predicted to increase by two to three times. Also, retrospective analysis of rainfall and evapotranspiration suggested an existence of rainfall deficit (rainfall-evapotranspiration) in the basin throughout the year, except during July to September. The rainfall deficit in the basin during 2026-2100 is found to remain more or less same in the non-monsoon season, except for the month of October under SSP245, SSP370 and SSP585 scenarios where deficit increases by two folds. Rainfall is expected to be in surplus by 4 to 5 times higher under all SSPs except for SSP245. As to the evapotranspiration, an insignificant increasing trend is observed under future climatic condition with only 2 to 4% rise in the crop water demand compared to the baseline period. As the basin is already water stressed during most months in a year under baseline and future climatic conditions, continuing the current practice of monsoon paddy dominant cultivation in the basin will further aggravate this situation. The results of this study will be helpful in formulating sustainable irrigation plans and adaptation measures to address climate-induced water stress in the basin.</p><p><strong>Keywords:</strong> Climate change; CMIP6; SSP; Monsoon rainfall; Temperature; Crop water demand.</p>

An efficient and accurate method for obtaining regional scale rice growth conditions based on WOFOST model and satellite images

2021 ◽  
Author(s):  
Bingyu Zhao ◽  
Meiling Liu ◽  
Jiianjun Wu ◽  
Xiangnan Liu ◽  
Mengxue Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Assimilation ◽  
Growth Model ◽  
Growth Parameters ◽  
Remote Sensing Data ◽  
Growth Conditions ◽  
Crop Growth ◽  
Crop Growth Model ◽  
Parallel Method ◽  
Rice Growth

<p>It is very important to obtain regional crop growth conditions efficiently and accurately in the agricultural field. The data assimilation between crop growth model and remote sensing data is a widely used method for obtaining vegetation growth information. This study aims to present a parallel method based on graphic processing unit (GPU) to improve the efficiency of the assimilation between RS data and crop growth model to estimate rice growth parameters. Remote sensing data, Landsat and HJ-1 images were collected and the World Food Studies (WOFOST) crop growth model which has a strong flexibility was employed. To acquire continuous regional crop parameters in temporal-spatial scale, particle swarm optimization (PSO) data assimilation method was used to combine remote sensing images and WOFOST and this process is accompanied by a parallel method based on the Compute Unified Device Architecture (CUDA) platform of NVIDIA GPU. With these methods, we obtained daily rice growth parameters of Zhuzhou City, Hunan, China and compared the efficiency and precision of parallel method and non-parallel method. Results showed that the parallel program has a remarkable speedup (reaching 240 times) compared with the non-parallel program with a similar accuracy. This study indicated that the parallel implementation based on GPU was successful in improving the efficiency of the assimilation between RS data and the WOFOST model and was conducive to obtaining regional crop growth conditions efficiently and accurately.</p>

scholarly journals Coupling a land-surface model with a crop growth model to improve ET flux estimations in the Upper Ganges basin, India

2014 ◽  
Vol 18 (10) ◽  
pp. 4223-4238 ◽  
Author(s):  
G. M. Tsarouchi ◽  
W. Buytaert ◽  
A. Mijic
Keyword(s):  
Growth Model ◽  
Land Surface ◽  
Coupled Model ◽  
Crop Growth ◽  
Original Model ◽  
Surface Model ◽  
Strong Impact ◽  
Crop Growth Model ◽  
Mean Error ◽  
The Impact

Abstract. Land-Surface Models (LSMs) are tools that represent energy and water flux exchanges between land and the atmosphere. Although much progress has been made in adding detailed physical processes into these models, there is much room left for improved estimates of evapotranspiration fluxes, by including a more reasonable and accurate representation of crop dynamics. Recent studies suggest a strong land-surface–atmosphere coupling over India and since this is one of the most intensively cultivated areas in the world, the strong impact of crops on the evaporative flux cannot be neglected. In this study we dynamically couple the LSM JULES with the crop growth model InfoCrop. JULES in its current version (v3.4) does not simulate crop growth. Instead, it treats crops as natural grass, while using prescribed vegetation parameters. Such simplification might lead to modelling errors. Therefore we developed a coupled modelling scheme that simulates dynamically crop development and parametrized it for the two main crops of the study area, wheat and rice. This setup is used to examine the impact of inter-seasonal land cover changes in evapotranspiration fluxes of the Upper Ganges River basin (India). The sensitivity of JULES with regard to the dynamics of the vegetation cover is evaluated. Our results show that the model is sensitive to the changes introduced after coupling it with the crop model. Evapotranspiration fluxes, which are significantly different between the original and the coupled model, are giving an approximation of the magnitude of error to be expected in LSMs that do not include dynamic crop growth. For the wet season, in the original model, the monthly Mean Error ranges from 7.5 to 24.4 mm month−1, depending on different precipitation forcing. For the same season, in the coupled model, the monthly Mean Error's range is reduced to 5.4–11.6 mm month−1. For the dry season, in the original model, the monthly Mean Error ranges from 10 to 17 mm month−1, depending on different precipitation forcing. For the same season, in the coupled model, the monthly Mean Error's range is reduced to 2.2–3.4 mm month−1. The new modelling scheme, by offering increased accuracy of evapotranspiration estimations, is an important step towards a better understanding of the two-way crops–atmosphere interactions.

scholarly journals Estimation of rice yield by SIMRIW-RS, a model that integrates remote sensing data into a crop growth model

2017 ◽  
Vol 73 (1) ◽  
pp. 2-8 ◽  
Author(s):  
Masayasu MAKI ◽  
Kosuke SEKIGUCHI ◽  
Koki HOMMA ◽  
Yoshihiro HIROOKA ◽  
Kazuo OKI
Keyword(s):  
Remote Sensing ◽  
Growth Model ◽  
Rice Yield ◽  
Remote Sensing Data ◽  
Crop Growth ◽  
Crop Growth Model ◽  
Sensing Data

scholarly journals DEMANDA HÍDRICA DO MARACUJAZEIRO AMARELO (Passiflora edulis Sims f. flavicarpa Deg.)

Irriga ◽  
2002 ◽  
Vol 7 (3) ◽  
pp. 185-190
Author(s):  
Ana Alexandrina Gama da Silva ◽  
Antonio Evaldo Klar
Keyword(s):  
Water Demand ◽  
Crop Coefficient ◽  
Passion Fruit ◽  
Crop Water ◽  
Passiflora Edulis ◽  
Crop Water Demand ◽  
Passiflora Edulis Sims ◽  
E Mail ◽  
Fruit Formation ◽  
Yellow Passion Fruit

DEMANDA HÍDRICA DO MARACUJAZEIRO AMARELO (Passiflora edulis Sims f. flavicarpa Deg.)   Ana Alexandrina Gama da SilvaEmbrapa Tabuleiros Costeiros, CP 44, CEP 49025-040, Aracaju, SE. E-mail: [email protected] Evaldo KlarDepartamento de Engenharia Rural, Faculdade de Ciências Agronômicas, Universidade Estadual Paulista, CP 237, CEP 18603-970, Botucatu, SP. E-mail: [email protected] Científico do CNPq   1 RESUMO  Determinou-se à demanda hídrica e o coeficiente de cultivo (Kc) do maracujá amarelo (Passiflora edulis Sims f. flavicarpa Deg.), seleção Sul-Brasil, cultivado sob irrigação localizada, no município de Botucatu-SP (22o 51’ S,  48o 26’ W). A evapotranspiração máxima da cultura (ETc) e a evapotranspiração de referência (ETo) foram medidas em lisímetros de nível de lençol freático constante, durante o período de 29 de setembro de 2000 a 20 de julho de 2001. Os valores da ETc e ETo foram de 954,98 mm e  1.069,21 mm, respectivamente, durante todo o período medido. Os valores de Kc variaram de 0,42 a 1,12, com os valores máximos registrados entre 150 e 210 dias após o transplantio das mudas no campo (DAT), período correspondente aos estádios fenológicos de florescimento e formação dos frutos.  UNITERMOS: Passiflora edulis, evapotranspiração, coeficiente de cultivo (Kc).   SILVA, A.A.G. da, KLAR, A.E.  YELLOW PASSION FRUIT (Passiflora edulis Sims f. flavicarpa Deg.) CROP: WATER DEMAND.   2 ABSTRACT  Crop water demand and crop water coefficient (Kc = ETc/ETo) of yellow passion fruit were evaluated in constant level lysimeters under drip irrigation from September 21, 2000 to July 31, 2001 in Botucatu-SP. The maximum crop water demand (ETc) and the Reference Evapotranspiration (ETo), measured by lysimeters, were 954.98 mm and 1,069.21 mm, respectively, during all period measured. The values of Kc varied from 0.42 to 1.12  with maximum values registered from 150 to 210 days following transplanting during flowering and fruit formation  phases.  KEYWORDS: Passiflora edulis, evapotranspiration, crop coefficient (Kc). 

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