Measurement and simulation of water table management effects on groundwater quality

The goal of this study was to investigate the effect of various water-table management (WTM) practices on corn growth and yield and agricultural chemical concentrations in shallow groundwater. Field experiments were conducted for three years (1989-91) at the research sites near Ames and Ankeny. Water-table depths of 0.3, 0.6, and 0.9 m were maintained in field lysimeters at the Ames site, and variable water-table depths were maintained in a subirrigation field at the Ankeny site;Photosynthesis measurements were made regularly during the growing season, and yield data were collected at harvest. In 1989, a relatively dry year, photosynthesis rates were higher at shallow water-table depths than at deep water-table depths. In 1990, a very wet year, photosynthesis rates were not significantly different for water-table depths between 0.3 and 0.9 m, but rates decreased significantly for water-table depths shallower than 0.3 m. Water-table effects on photosynthetic water-use efficiency (PWUE) were highly significant in both dry and wet seasons. Corn yields increased with increasing water-table depths. Net radiation, leaf-air temperature differential, transpiration rate, stomatal conductance, and crop water stress index (CWSI) were strongly related to WTM practice during vegetative and flowering stages of corn growth. Results indicate that plant physiological parameters and CWSI could be used to develop the best WTM practices for corn growth in the humid region;Concentrations of NO[subscript]3-N in groundwater changed with WTM practices. The lowest NO[subscript]3-N concentrations were observed when water-table depths were maintained at 0.2 and 0.3 m from the soil surface. NO[subscript]3-N concentrations in groundwater also decreased with increased soil depth. Results showed that NO[subscript]3-N concentrations in groundwater could be significantly reduced by maintaining shallow water-table depths;Atrazine and alachlor concentrations in groundwater were significantly reduced by maintaining shallow WTD. Atrazine concentrations were higher than those of alachlor. Alachlor was not detected in many samples, however, atrazine was detected in all samples. Pesticide concentrations in groundwater decreased with soil depth and time. A subsurface water quality model ADAPT (Agricultural Drainage And Pesticide Transport) for the water table management system was used to simulate atrazine and alachlor concentrations in groundwater at various soil depths during the corn growing seasons of 1989 to 1991. Predicted values of atrazine and alachlor concentrations decreased with shallow water-table depths as was found from observed values. Observed and predicted results were compared and a good agreement was found between observed and predicted values

Estimation of watershed-scale hydraulic conductivity for two watershed sites using GFLOW

D. Goswami1, P. K. Kalita2, E. Mehnert3(1. S.W. Florida Research and Education Center, University of Florida, Immokalee, FL 34142;2. University of Illinois, 1304 W. Pennsylvania Avenue, Urbana, IL 61801;3. Illinois State Geological Survey, 615 E. Peabody Drive, Champaign, IL 61801) Abstract: For hydrologic and water quality studies, proper estimation of the hydraulic conductivity of the study site is very important.  The hydraulic conductivity values determined in the laboratory are usually lower than those observed in the field. Hydraulic conductivity increases with measurement scale.  This increase with larger scale is the result of spatial heterogeneities and is described as scaling-up of hydraulic conductivity.  Field and laboratory experiments to determine hydraulic conductivity values for large areas are expensive and time consuming.  Modeling may be a practical option to estimate hydraulic conductivity when the study area is large.  GFLOW, which is an analytical element model, was used to estimate the hydraulic conductivity values for two watershed sites in Illinois, namely the Big Ditch watershed and the Upper Embarras River watershed.  For each site, heads in shallow observation wells and stream discharge were used to calibrate the model.  The calibrated hydraulic conductivity values for the Big Ditch and Upper Embarras River watersheds were 4.05E-04 and 4.86E-04 m/s, respectively.  For watershed-scale studies, the hydraulic conductivity values estimated by the model might be acceptable.Keywords: GFLOW, model calibration, hydraulic conductivity, measurement scale, USA Citation: Goswami D, P.K. Kalita, and E. Mehnert.  Estimation of watershed-scale hydraulic conductivity for two watershed sites using GFLOW.  Agric Eng Int: CIGR Journal, 2010, 12(2): 7-13.  &nbsp

Adaptation Strategies for Climate Variability in the High Rainfall Zone of India, Assam

The NICRA project is being implemented in two villages viz., Chamua (since 2010–2011) and Ganakdalani (since 2012–2013 till 2016–2017), which are situated in the west of Lakhimpur district of North Bank Plains Zone of Assam. Chamua village is situated in Kherajkhat Mauza (Taluka), which is 45 km away from North Lakhimpur, the headquarter of district Lakhimpur. On the other hand, Ganakdoloni is situated at Dhalpur Mauza, situated 60 km away from North Lakhimpur and 15 km away from the local township Narayanpur. During 2017–2018 four villages viz., Jakaipelua, Borbali, Borkhet, and Nogaya were adopted under the project. Analysis of long-term rainfall data confirmed the significant decreasing trend of annual as well as monsoonal rainfall in both the Brahmaputra and Barak basins of Assam, India. Variability of rainfall has been increasing in terms of the increased frequency of high-intensity rains and the reduced number of rainy days, leading to localized flash floods and the occurrence of multiple dry spells. Mean season-wise rainfall 2011–2021 indicates long dry periods during the winter season, leading to prolonged dry spells affecting crop growth. About 69% of total rainfall (average annual rainfall of Assam is 2000 mm) is received during the monsoon season, resulting in flash floods leading to crop damage. Out of 12 years of investigation, 10 years are deficit years, resulting in crop stress both during the monsoon and post-monsoon period. Preparation and implementation of real-time crop contingencies are important in responding to weather aberrations in different strategies like preparedness, real-time response, etc. Identification of various adaptation strategies, including climate-resilient crops and cultivars, rainwater harvesting and recycling, efficient energy management through farm mechanization, dissemination of weather information, and weather-based agro-advisories to farmers in a real-time basis, is important adaptation technologies for building climate-resilient agriculture. The study showed that adaption of climate-resilient crop and cropping system and use of harvested rainwater resulted in a 12 to 30% increase in yield observed by the cultivation of high-yielding rice varieties (HYVs) (Ranjit, Gitesh, Mahsuri, etc.) when sown in time (before 15th June) over late sowing conditions (after 20th June). In the case of early season drought, replacement of long duration traditional varieties with short duration HYV and life-saving irrigation using harvested rainwater increased yield by about 59% (short duration var. Dishang) over non-irrigated fields. In case of mid-season and terminal drought, application of an additional dose of 22 kg ha−1 MOP at maximum tillering to grain growth period an increase in yield of about 33% (Ranjit), 32% (Gitesh), 64% (Shraboni), and 57.5% (Mulagabharu) has been observed over farmers’ practice. In highly flood-affected areas under lowland situations replacement of submergence tolerant varieties (Jalashree and Jalkuwari) with traditional deepwater rice varieties resulted in reduced crop loss due to the genetic trait of the deepwater rice, which can withstand water logging for a long period. With an increase in the level of mechanization through the use of machinery available in the custom hiring center the human and animal hour requirement for paddy cultivation was reduced from 795 to 350 hrha−1 and 353 to 23 hrha−1, respectively. Alternate land use in terms of low-cost poly house, vermicompost production, and mushroom cultivation also resulted in nutritional security and generation of higher income for the farmer

Assessment of Climatic Parameters for Future Climate Change in a Major Agricultural State in India

The change in future climate will have a prominent impact on crop production and water requirement. Crop production is directly related to climatic variables. Temperature, solar radiation, wind, precipitation, CO2 concentration and other climatic variables dictate crop yield. This study, based on long-term historical data, investigates the patterns and changes in climatic variables (precipitation, temperature, and solar radiation) that would most significantly affect the future crop production in many parts of the world, and especially in India, where most farmers depend on rainfall for rice production. Statistical analyses—box and whisker plot, mean absolute error, Taylor diagram, double mass curve, Mann–Kendall trend test, and projected climate change—were used to assess the significance of the climatic factors for the purpose of agricultural modeling. Large variability in precipitation may cause the flash floods and affect the farming, and at the same time, increase in temperature from baseline period will lead to high water requirement by crops, and may cause drought if rainfall does not occur. Decrease in solar radiation will affect crop growth and development, and thus, would hamper the crop production. The results of this study would be useful in identifying the negative issues arising from climate change in future agricultural practices in Bihar, India. Furthermore, the results can also help in developing management strategies to combat the climate change impact on crop production

Assessment of Different Frameworks for Addressing Climate Change Impact on Crop Production and Water Requirement

Various methodologies are used to estimate the impact of changing climatic factors, such as precipitation, temperature, and solar radiation, on crop production and water demand. In this study, the changes in rice yield, water demand, and crop phenology were estimated with varying CO2 concentration and an ensemble of general circulation models (GCMs), using a decision support system for agrotechnology transfer (DSSAT), a crop growth model. The measured CO2 concentration of 400 ppm from the Keeling curve, was used as the default CO2 concentration to estimate yield, water demand, and phenology. These outputs, obtained with the default concentration, were compared with the results from climate change scenarios’ concentrations. Further, the outputs corresponding to the ensembled GCMs’ climate data were obtained, and the results were compared with the ensembled crop model outputs simulated with each GCM. The yield was found to increase with the increase in CO2 concentration up to a certain threshold, whereas water demand and phenology were observed to decrease with the increase in CO2 concentration. The two approaches of the ensemble technique to obtain final outputs from DSSAT results did not show a large difference in the predictions

Predicting the Water Requirement for Rice Production as Affected by Projected Climate Change in Bihar, India

Climate change is a well-known phenomenon all over the globe. The influence of projected climate change on agricultural production, either positive or negative, can be assessed for various locations. The present study was conducted to investigate the impact of projected climate change on rice’s production, water demand and phenology for the state of Bihar, India. Furthermore, this study assessed the irrigation water requirement to increase the rice production by 60%, for the existing current climate scenario and all the four IPCC climate change scenarios (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5) by the 2050s (2050–2059). Various management practices were used as adaptation methods to analyze the requirement of irrigation water for a 60% increase in rice production. The climate data obtained from the four General Circulation Models (GCMs) (bcc_csm1.1, csiro_mk3_6_0, ipsl_cm5a_mr and miroc_miroc5) were used in the crop growth model, with the Decision Support System for Agrotechnology Transfer (DSSAT) used to simulate the rice yield, phenological days and water demand under all four climate change scenarios. The results obtained from the CERES-Rice model in the DSSAT, corresponding to all four GCMs, were ensembled together to obtain the overall change in yield, phenology and water demand for 10 years of interval from 2020 to 2059. We investigated several strategies: increasing the rice’s yield by 60% with current agronomic practice; increasing the yield by 60% with conservation agricultural practice; and increasing the rice yield by 30% with current agronomic practice as well as with conservation agricultural practices (assuming that the other 30% increase in yield would be achieved by reducing post-harvest losses by 30%). The average increase in precipitation between 2020 and 2059 was observed to be 5.23%, 13.96%, 9.30% and 9.29%, respectively, for RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5. The decrease in yield during the 2050s, from the baseline period (1980–2004), was observed to be 2.94%, 3.87%, 4.02% and 5.84% for RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5, respectively. The irrigation requirement was predicted to increase by a range of 39% to 45% for a 60% increase in yield using the current agronomic practice in current climate scenario and by 2050s with all the four climate change scenarios from the baseline period (1980–2004). We found that if we combine both conservation agriculture and removal of 30% of the post-harvest losses, the irrigation requirement would be reduced by 26% (45 to 19%), 20% (44 to 24%), 21% (43 to 22%), 22% (39 to 17%) and 20% (41 to 21%) with current climate scenario, RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 conditions, respectively. This combination of conservation practices suggests that the irrigation water requirement can be reduced by a large percentage, even if we produce 60% more food under the projected climate change conditions

Soil, water, and nutrient losses from management alternatives for degraded pasture in Brazilian Atlantic Rainforest biome

The objective of this study was to evaluate sediment, water and nutrient losses from different pasture managements in the Atlantic Rainforest biome. A field study was carried out in Alegre Espiríto Santo, Brazil, on a Xanthic Ferralsol cultivated with braquiaria (Brachiaria brizantha). The six pasture managements studied were: control (CON), chisel (CHI), fertilizer (FER), burned (BUR), plowing and harrowing (PH), and integrated crop-livestock (iCL). Runoff and sediment samples were collected and analyzed for calcium (Ca), magnesium (Mg), potassium (K), phosphorus (P) and organic carbon contents. Soil physical attributes and above and below biomass were also evaluated. The results indicated that higher water loss was observed for iCL (129.90 mm) and CON (123.25 mm) managements, and the sediment losses were higher for CON (10.24 t ha− 1) and BUR (5.20 t ha− 1) managements when compared to the other managements. Majority of the nutrients losses occurred in dissolved fraction (99% of Ca, 99% of Mg, 96% of K, and 65% of P), whereas a significant fraction of organic carbon (80%) loss occurred in a particulate form. Except for P, other nutrients (Ca, Mg and K) and organic carbon losses were higher in coarse sediment compared to fine sediment. The greater losses of sediment, organic carbon, and nutrients were observed for CON followed by BUR management (p < 0.05). Our findings indicated that the traditional pasture management adopted in the Atlantic Rainforest needs to be rethought and burned management should be avoided. Based on the water, soil, and nutrient losses from various practices, to reduce pasture degradation, farmers should adopt edaphic practices by applying lime and fertilize to improve pasture growth and soil cover, and reducing soil erosion in the hilly Brazilian Atlantic Rainforest biom

Climate Risk Management at Farmer’s Field through Adaptation Strategies for Resource-Poor Farmers of Assam, Northeast India

Farmers in Assam's North Bank Plains Zone are generally resource-poor and have limited adaptation ability; rainfall anomalies make the Zone's rainfed agriculture very sensitive, risky, and unprofitable. Participatory on-farm trials involving 25 farmers (5 from each village) representing different land situations for evaluating various adaptive strategies on rice-based cropping systems were conducted from 2011 to 2020. Ten years of rainfall data (2011-2021) are evaluated in connection to dry spells and their effects on rainfed rice-based farming systems. The village receives 2848.5 mm of annual rainfall, with distribution patterns of 25%, 67%, 5.0%, and 3% during the pre-monsoon, monsoon, post-monsoon, and winter seasons, respectively. Among the years under study, it has been observed that during 2010, 2015, 2016, 2017 and 2020, the district received excess annual rainfall and deficit in 2011, 2012, 2013, 2014, 2018, 2019 and 2021,respectively. The current studies were designed with two primary strategic components in mind viz., Real-time Contingency Planning (RTCP) and Preparedness. Interventions under the RTCP were designed to deal with delayed monsoon onset, early-season drought, mid-season dryspell, and terminal drought in winter rice and rabi crops. Preparedness includes changes in cropping pattern, in situ and ex situ rainwater management systems, alternate land use under low-cost polyhouse, mushroom cultivation, vermicompost production, fodder bank and village seed bank to cope with weather aberrations. An increase in yield of HYV rice varieties Ranjit (33%), Mahsuri (12.3%) and Gitesh (32%) was observed when sowing was done before 15 June over late sowing conditions. An increase in yield of 21.73 % and 44.60%. 58.67% as compared to farmers' Practice during 2013-14, 2014-15, and 2016-17 respectively, has been observed. The performance of double cropping systems recorded the highest B: C ratio of 2.03 and 1.75 in winter rice + rapeseed followed by winter rice + potato sequence as compared to mono-cropping of winter rice