On-farm rainwater and crop management for improving productivity of rainfed areas

Scarcity of water is a critical limitation to adoption of modern technology for increasing productivity of traditional rainfed rice growing areas of eastern Madhya Pradesh, India. The shortage of water results from uneven distribution of rains, significant gaps between rain events and field water losses rather than from low seasonal or annual rainfall totals. A feasible strategy to alleviate this limitation is to harvest excess rainwater in a farm pond during the wet season and use the conserved water for crop production in both wet (as insurance against drought) and dry seasons by adopting suitable crop and cropping systems. The results of water balance in a 1.05 ha field, on which a farm pond was built using 0.09 ha area, showed that 28–37% of seasonal rainfall was available as surface runoff from microcatchment (0.66 ha growing soybean, peanut and pigeonpea) for collection in the pond. This was sufficient for saving rice in a 0.30 ha area (in the lower side of the field) from drought stress, and for establishment of chickpea and mustard (in 0.90 ha) in the post-rainy season after harvest of rainy season crops. Soybean, peanut and pigeonpea, grown in the microcatchment during the rainy season, utilized respectively 371–726, 364–733 and 535–920 mm water in evapotranspiration (E,) and deep percolation (P). Rice grown below the pond required 28–317 mm water in different seasons to save the crop from in-season drought stress which commonly occurred during vegetative and reproductive stages. Water requirement (E, + P) of rice was 816–1342 mm in different seasons. Residual soil moisture after rainy season soybean, peanut and rice was sufficient (172–203 mm) to support post rainy season crops of chickpea and mustard. However, the losses of moisture from the soil surface layer after harvest of rainy season crops were rapid (7–23 mm), which necessitated a light irrigation (21–45 mm) for establishment of chickpea and mustard in the post-rainy season. The water balance results of soybean-mustard, peanut-mustard and peanut-chickpea were near identical to soybean-chickpea cropping. Similarly the water balance of rice-mustard was identical to Corresponding author. rice-chickpea in the vertisols. Soybean-mustard and rice-chickpea were the suitable and economical cropping systems for the microcatchment and service area of the farm pond.     

Calibration and validation of SALTMED model under dry and wet year conditions using chickpea field data from Southern Portugal

The SALTMED model is one of the few available generic models that can be used to simulate crop growth with an integrated approach that accounts for water, crop, soil, and field management. It is a physically based model using the well-known water and solute transport, evapotranspiration, and water uptake equations. In this paper, the model simulated chickpea growth under different irrigation regimes and a Mediterranean climate. Five different chickpea varieties were studied under irrigation regimes ranging from rainfed to 100 % crop water requirements, in a dry and a wet year. The calibration of the model using one of the chickpea varieties was sufficient for simulating the other varieties, not requiring a specific calibration for each individual chickpea variety. The results of calibration and validation of the SALTMED model showed that the model can simulate very accurately soil moisture content, grain yield, and total dry biomass of different chickpea varieties, in both wet and dry years. This new version of the SALTMED model (v. 3.02.09) has more features and possibilities than the previous versions, providing academics and professionals with a very good tool to manage water, soil, and crops.     

Evapotranspiration and seed yield of field grown soybean under deficit irrigation conditions

Evapotranspiration was measured for a reference crop, rye grass (Lolium prerenne) and soybean (Glycine max L. Merril) grown over two seasons in 2000 and 2001 at Tal Amara Research Station, Lebanon, using drainage and weighing lysimeters. Climatic data from the field weather station were recorded daily. Within the experimental plots, irrigation was withheld at full bloom, R2 stage (S1 treatment), at seed enlargement, R5 stage (S2 treatment) and at mature seeds, R7 stage (S3 treatment). Further, a control (C) was fully-irrigated throughout the growing period.Average crop evapotranspiration (ETc) as measured by the drainage lysimeters in 2000 totaled 800 mm for a total growing period of 140 days. However, when ETc was measured by the weighing lysimeter in 2001, it was 725 mm during a growing period of 138 days. Average crop coefficients (K_c) were computed for different growth stages for the two growing periods by dividing the measured crop evapotranspiration (ETc) by the corresponding measured reference evapotranspiration (ETo-rye grass). K_c values ranged from 0.62 at V10 stage (10th node on the main stem beginning with the unifoliolate node) to 1.0 at pod initiation, then to 0.81 at mature pods.Growth parameters, leaf area index (LAI) and dry matter accumulation, have been shown to be sensitive to water stress caused by the deficit irrigations. However, growth parameters were found to compensate for water stress at early stages, while at seed maturity the compensation ability was decreased.Plants of the lysimeters produced average aboveground biomass and seed yield of 8.1 and 3.5 t ha⁻¹, respectively. However, in the well-irrigated field treatment, aboveground biomass and seed yield averaged 7.3 and 3.2 t ha⁻¹, respectively. Deficit irrigation at R2 stage reduced aboveground biomass and seed yield by 16 and 4%, respectively, while deficit irrigation at R5 stage reduced these two parameters by 6 and 28%, respectively, with comparison to the control. The significant decrease in biomass at R2 stage due to water deficit may be attributed to a pronounced reduction in the number of vegetative nodes. However, limited irrigation at this stage did not reduce significantly (P < 0.01) neither seed number nor seed weight, while at R5 stage these two parameters were reduced by 20 and 10%, respectively, with comparison to the control. Results showed also that deficit irrigation at R7 stage (S3) was more profitable than irrigation deficit at any other crop phenology and did not cause significant reductions either in seed number or seed weight.     

Performance measure for improving irrigation management

A measure to evaluate performance in irrigation systems is analyzed using the mean square prediction error concept. In the context of irrigation system management, the term error means the deviation of actual performance from a reference performance. The measure assesses performance in terms of the management objectives of adequacy and dependability of water delivery and an equitable distribution among various water users. It provides an understanding of the management capacity to schedule and distribute water in an irrigation system. Application of the performance measure is demonstrated by evaluating performance of an irrigation system in the Northwest Frontier Province of Pakistan.     

Development of a simple potato growth model for use in crop-pest management

A simple whole-plant level potato growth model was developed that accumulates and partitions dry matter into four state variables—leaves, stems, roots and tubers. Daily growth is computed from a function of the total solar radiation, the proportion of total radiation intercepted by the crop, temperature and soil water status. Dry matter is partitioned using modified Michaelis-Menten equations. At initialization, the seed piece size, plant and row spacing, and the values for the dry matter partitioning parameters are required. After initialization, the inputs required are the daily minimum and maximum temperatures and the daily soil water potential. Daily site-specific, seasonal radiation is presently estimated from a sine function. Model parameterization and output plotted against field data are presented for two cultivars, each planted a total of three times in two seasons. The model is intended for use in analyzing the dynamics of yield under variable pest pressures and environmental conditions. Model sensitivity, behavior and use in relation to modeling yield loss due to pests are discussed.     

Logistic model application for prediction of maize yield under water and nitrogen management

Simulation of crop yield allows better planning and efficient management under different environmental inputs such as water and nitrogen application. However, most of the models are complicated and difficult to understand. Furthermore, input data are not readily available. The objectives of this investigation were to use logistic equation to quantify the influence of seasonal water and nitrogen application on maize biomass accumulation and grain yield and to develop empirical models for prediction of maize biomass and grain yield. Logistic equations were fitted to dray matter (DM) yield at different times in the growing season at different irrigation water and nitrogen levels. The parameters of the logistic equations were then fitted to irrigation water and nitrogen as empirical functions. Further, the harvest index (HI) was related to the applied water and nitrogen as another empirical model. The empirical logistic models were used to estimate the DM and grain yield based on data from another experiment in the same area. Results indicated that the empirical models predicted the DM yield during the growing season with an acceptable accuracy, but dry matter (DM) prediction at harvest was very good. The grain yield also was predicted with a very good accuracy. It is concluded that logistic equation along with the presented empirical models for prediction of constants in logistic equation and HI are appropriate for accurate prediction of DM and grain yield of maize at the study region.     

Representation of rainfed valley ricefields using a soil-water balance model

Soil-water conditions for ricefields located in valleys in micro-catchments are simulated using a daily soil-water balance model. The crop is primarily rainfed but there is also limited irrigation water. The simulation covers a complete year and includes features such as rainfall, irrigation releases, runoff from uplands, actual evaporation and evapotranspiration, percolation losses through the bed and bunds of the ricefield, standing water in the field and overflows from the ricefield. A specific location in Sri Lanka is selected to illustrate the approach. The impacts of different conditions are explored including alternative irrigation releases, increased losses through the bed and bunds of the ricefield and a lower overflow from the ricefield. Simulations indicate that ricefields which are towards the valley sides have an increased inflow due to runoff from adjacent uplands; this can lead to improved rice yields. However, reducing heights of the bunds to half the original value results in substantial overflows during periods of high rainfall while the number of days without submergence almost doubles. This uncomplicated model is consistent with the limited field data and information available; it provides a realistic representation of the important processes and indicates why poor crop yields often occur.     

Water use and water use efficiency of sweet corn under different weather conditions and soil moisture regimes

Plant growth and development are influenced by weather conditions that also affect water use (WU) and water use efficiency (WUE) and ultimately, yield. The overall goal of this study was to determine the impact of weather and soil moisture conditions on WU and WUE of sweet corn (Zea mays L. var rugosa). An experiment consisting on three planting dates was conducted in 2006 at The University of Georgia, USA. A sweet corn genotype sh2 was planted on March 27 under irrigated and rainfed conditions and on April 10 and 25 under irrigated conditions only. Soil moisture was monitored using PR2 probes. Rainfall and irrigation were recorded with rain gauges installed in the experimental area while other weather variables were recorded with an automatic weather station located nearby. A water balance was used to obtain the crop's daily evapotranspiration (ETc). WUE was calculated as the ratio of fresh and dry matter ear yield and cumulative ETc. The potential soil moisture deficit (Dp) approach was used to determine the crop's moisture stress. Results were analyzed using a single degree freedom contrast, linear regression, and the least significant difference. WU and WUE of sweet corn were both markedly affected by the intra-seasonal weather variability and Dp. For both variables, significant (p < 0.05) differences were found between planting dates under irrigated conditions and between the irrigated and rainfed treatments. WU was as high as 268 mm for the April 10 planting date under irrigated conditions and as low as 122 mm for the March 27 planting date under rainfed conditions. The maximum soil moisture deficit was reached at the milky kernel stage and was as high as 343 mm for the March 27 planting date under rainfed conditions and as low as 260 mm for the April 10 planting date under irrigated conditions. Further work should focus on the impact of the intra-seasonal weather variability and soil moisture conditions during different crop stages to determine critical periods that affect yield.     

Overestimation of soybean crop transpiration by sap flow measurements under field conditions in Central Portugal

Direct measurements of the xylem sap flow by the stem heat balance technique can be a valuable aid for determining the irrigation demand of field crops. In the present study, soybean (Glycine max (L.) Merr.) sap flow was evaluated under well-watered and water-stressed conditions using Dynamax SGA10 sap flow gauges. Solar radiation was measured continuously throughout the growing season. Soil water content was measured before and after each irrigation. There was a close relationship between solar radiation and xylem sap flow. The water flux in the soybean stems responded realistically to changes in the soil water content. However, the absolute values of sap flow were highly questionable. Calculating crop transpiration from sap flow measurements, the results were up to 4 times as high as calculated transpiration from soil moisture data and simulated transpiration using the locally calibrated soybean crop growth model SOYGRO. A sensitivity analysis of the stem heat balance technique gave no indications of technique or input errors. The gauge design was possibly not appropriate for the outdoor installation on soybeans.     

不同土地利用条件下土壤质量综合评价方法

针对传统的土壤质量评价方法难以满足现代农业发展的现状,提出了一种土壤质量指数法(SQI)综合评价土壤质量,旨在为农业生产、农产品产地选址、农业环境保护等提供理论支撑和参考依据。将方法在北京市郊区7种土地利用方式（粮田、林地、湿地、荒地、果园、菜地、草地）上进行了应用,并与常规方法进行了对比,结果表明：采用隶属度模型评价土壤肥力,肥力高低顺序为：湿地＞菜地＞粮田＞林地＞果园＞荒地＞草地;采用内梅罗污染指数评价了重金属污染状况,污染程度高低顺序为：湿地＞菜地＞荒地＞果园＞林地＞粮田＞草地;采用SQI指数评价土壤综合质量,其综合质量的高低顺序为：湿地＞粮田＞菜地＞果园＞林地＞荒地＞草地。此外还对评价模型的适用范围、评价结果的划分等一系列关键问题进行了探讨,得出：SQI指数评价方法的应用及结果的划分涵盖了不同的土地利用方式的农用地,体现了各种土壤属性的差异和变异特性,评价结果可实现土壤综合质量定性和定量化,能够反映土壤的关键信息,符合农业生产需要。     

Optimization model of an irrigation reservoir for water allocation and crop planning under various weather conditions

This paper develops a non-linear programming optimization model with an integrated soil water balance, to determine the optimal reservoir release policies, the irrigation allocation to multiple crops and the optimal cropping pattern in irrigated agriculture. Decision variables are the cultivated area and the water allocated to each crop. The objective function of the model maximizes the total farm income, which is based on crop–water production functions, production cost and crop prices. The proposed model is solved using the simulated annealing (SA) global optimization stochastic search algorithm in combination with the stochastic gradient descent algorithm. The rainfall, evapotranspiration and inflow are considered to be stochastic and the model is run for expected values of the above parameters corresponding to different probability of exceedence. By combining various probability levels of rainfall, evapotranspiration and inflow, four weather conditions are distinguished. The model takes into account an irrigation time interval in each growth stage and gives the optimal distribution of area, the water to each crop and the total farm income. The outputs of this model were compared with the results obtained from the model in which the only decision variables are cultivated areas. The model was applied on data from a planned reservoir on the Havrias River in Northern Greece, is sufficiently general and has great potential to be applicable as a decision support tool for cropping patterns of an irrigated area and irrigation scheduling.     

An inexact two-stage water management model for planning agricultural irrigation under uncertainty

In this study, an inexact two-stage water management (ITWM) model is developed for planning agricultural irrigation in the Zhangweinan River Basin, China. The ITWM model is derived from the incorporation of interval-parameter programming (IPP) within a two-stage stochastic programming (TSP) framework. It can reflect not only uncertainties expressed as probability distributions but also interval numbers. Moreover, it can provide an effective linkage between conflicting economic benefits and the associated penalties attributed to the violation of the predefined policies. Four decision scenarios associated with different water-resources management policies are examined. Targeted incomes, recourse costs, and net system benefits under different scenarios are analyzed, which indicates that different policies for agricultural irrigation targets correspond to different water shortages and surplus, and thus lead to varied system benefit and system-failure risk. The results are valuable for supporting the adjustment or justification of the existing irrigation patterns and identify a desired water-allocation plan for agricultural irrigation under uncertainty.     

The use of soybean leaflet angle data for irrigation scheduling

Summary The feasibility of scheduling soybean [Glycine max (L.) Merr.] irrigation by using terminal leaflet angle data was evaluated by simultaneously measuring the angles to the horizontal of the uppermost terminal leaflet and soil moisture contents on plots with different soil moisture regimes during and following a drying cycle. Severe water stress was avoided. The percentage of leaflets with an angle greater than or equal to 45 degrees correlated significantly with both water content in the top 0.45 m of soil and the ET/Epan ratio.     

Evaluation of the Penman-Monteith model for estimating soybean evapotranspiration

The Penman-Monteith model with a variable surface canopy resistance (r_cv) was evaluated to estimate hourly and daily crop evapotranspiration (ET_c) over a soybean canopy for different soil water status and atmospheric conditions. The hourly values of r_cv were computed as a function of environmental variables (air temperature, vapor pressure deficit, net radiation) and a normalized soil water factor (F), which varies between 0 (wilting point, _WP) and 1 (field capacity, _FC). The performance of the Penman-Monteith model (ET_PM) was evaluated using hourly and daily values of ET_c obtained from the combined aerodynamic method (ET_R). On an hourly basis, the overall standard error of estimate (SEE) and the absolute relative error (ARE) were 0.06 mm h^–1 (41 W m^–2) and 4.2%, respectively. On a daily basis, the SEE was 0.47 mm day^–1 and the ARE was 2.5%. The largest disagreements between ET_PM and ET_R were observed, on the hourly scale, under the combined influence of windy and dry atmospheric conditions. However, this did not affect daily estimates, since nighttime underestimations cancelled out daytime overestimations. Thus, daily performances of the Penman-Monteith model were good under soil water contents ranging from 0.31 to 0.2 (_FC and _WP being 0.33 and 0.17, respectively) and LAI ranging from 0.3 to 4.0. For this validation period, calculated values of r_cv and F ranged between 44 s m^–1 and 551 s m^–1 and between 0.19 and 0.88, respectively.Communicated by R. Evans     

Economic instruments for improving water use efficiency: theory and practice

The paper discusses the problem of water scarcity and the need to improve efficiency and sustainability through the use of market-based mechanisms. It outlines the theoretical basis of the argument, discusses difficulties in practical application, and points to the need to develop best-practice guidelines for different circumstances.     

Simulation of water harvesting potential in rainfed ricelands using water balance model

Using daily water balance simulation in rainfed ricelands, the study estimates the probable supplemental irrigation (SI) requirement to meet the water deficits during the reproductive stage of rice and surface runoff (SR) generated that can be harvested in OFR for meeting the aforesaid SI. Value of SI of rice during reproductive stage at 25% probability of exceedence (PE) was found to be 144 mm, neglecting distribution and application losses. Water harvesting potential of the study area indicates that at 50% PE, 85% of SI of rice can be met from the SR generated from the ricelands and stored in OFR. Rest amount of SI can be met from the direct conservation of rainfall in a lined OFR of 2 m depth with 1:1 side slope occupying 9% ricelands. Economic analysis of OFR irrigation system reveals that OFR of 9% ricelands gives net profit (NP) of Indian Rupees (Rs.) 13445 (US $295.49) for 1 ha sown with dry seeded rainfed upland rice with benefit–cost ratio (BCR) of 1.25. Values of NP and BCR indicate that investment in OFR irrigation system is profitable in the study region.     

Description and evaluation of the rice growth model ORYZA2000 under nitrogen-limited conditions

Various crop growth simulation models exist for rice but thorough validation and evaluation reports are scarce. We present the model ORYZA2000, which simulates the growth and development of rice under conditions of potential production and water and nitrogen limitations. The model was evaluated against a data set of five field experiments with irrigated rice performed at IRRI between 1991 and 1993, with nitrogen levels varying from 0 to 400 kg ha⁻¹ in different splits and timings of application. We compared simulated and measured leaf area index (LAI) and biomass of leaves, stems, panicles, and total aboveground biomass by graphics; by the slope, intercept, and adjusted coefficient of correlation; by Student’s t test of means; and by absolute and normalized root mean square errors (RMSE). On average, RMSE was 690–1280 kg ha⁻¹ for total biomass, 350–380 kg ha⁻¹ for leaf biomass, 460–790 kg ha⁻¹ for stem biomass, and 380–580 kg ha⁻¹ for panicle biomass. Yield was simulated with an RMSE of 840–850 kg ha⁻¹ and a normalized RMSE of 11–13%. For these crop variables, normalized RMSE values were 65–84% higher than the typical coefficients of variation associated with their measurements. Simulated LAI generally exceeded measured values, especially at low levels of nitrogen application. We can use ORYZA2000 to support N field experiments and investigate optimum N application regimes with quantified errors of simulation. The developed database and quantitative goodness-of-fit parameters serve as references for future model improvements.     

大豆振兴背景下吉林省大豆供给反应研究——基于Nerlove模型的实证分析

大豆振兴背景下,大豆成为吉林省农业结构调整的关键作物.本文利用19852019年吉林省大豆相关数据,通过建立Nerlove模型对大豆供给反应进行分析,得出吉林省大豆短期供给价格弹性为0.23,而长期供给价格弹性为0.39,表明大豆供给对价格反应较为迟缓,缺乏弹性.测得预期价格调整系数为0.72,调整时滞为1.39,表明...     

Usefulness and limitations of decision support systems for improving irrigation scheme management

SIMIS (the FAO Scheme Irrigation Management Information System) is a decision support system that integrates tools and performance indicators to facilitate the planning and management of irrigation schemes. The authors used SIMIS to compute performance indicators in an irrigation scheme in Southern Spain that were used to identify distribution system constraints affecting the flexibility of water deliveries and to identify scheme sectors where deliveries could not meet the predicted crop water demands. Applying SIMIS, the authors and the irrigation scheme manager evaluated measures to overcome the constraints for future irrigation campaigns, and to refine the water orders made every 2 weeks to the basin authority. On the other hand, SIMIS presented limitations to the evaluation of on-demand delivery schedules. To overcome these limitations, an external model, developed outside SIMIS, showed that the current distribution network of the scheme has the capacity to deliver water on-demand only if a slight water deficit is accepted during the peak demand period. The analysis showed that by relaxing the stringency of the quality of operation of on-demand systems, rotation systems may be transformed into on-demand systems without changing their structures. This analysis could also be done using Clément's hypothesis, but doing so resulted in overestimates of the quality of operation and of the relative irrigation supply.     

Seasonal water use by winter wheat grown under shallow water table conditions

Techniques for estimating seasonal water use from soil profile water depletion frequently do not account for flux below the root zone. A method using tensiometers for obtaining evapotranspiration losses from the root zone and water movement below it is discussed. Soil water flux below the root zone is approached by a sequence of pseudo steady state solutions of the flow equation. Upward soil water flux contributed 36 to 73% to the total water requirement of winter wheat (Triticum aestivum L.) whereas soil water depletion accounted for 11 to 19% only. Water use efficiency with one irrigation during an early stage of plant development is greater than with no or three irrigations. This is the result of both decrease of resistance due to soil moistening and better root development. Tensiometer readings were also interpreted to estimate root zones, water table depths and soil moisture contents. Methods described in this paper can be used in determining seasonal water use by growing crops, replacing or supplementing lysimeter or meteorology approaches to this problem.