RESPONSE FUNCTIONS OF CROPS YIELD TO SOIL MOISTURE STRESS1

: A methodology for determining an optimal irrigation policy to obtain maximum economic yield of crops is presented. The method is based on an empirical response function, relating crop yield to soil moisture stress in different stages of plant growth. The function was developed from data obtained in field experiments on several crops and may be useful in determining when and how much to irrigate. Additionally, a mathematical expression is derived from that function which estimates the economic loss if irrigation is not applied in the opportune moment.     

PERCOLATE WATER AND BROMIDE MOVEMENT IN THE ROOT ZONE OF EFFLUENT IRRIGATION SITES1

ABSTRACT: A bromide tracer was used to evaluate percolate water and ion movement in the upper 1.2 m of soil at a proposed sewage effluent irrigation site located in the Missouri Ozarks. Two plots representing Doniphan silt loam and Crider silt loam soils were sprinkler irrigated with local ground water at a rate of 7.62 cm/week from June through August 1976. Soil water potential, percent soil moisture by volume, and background levels of bromide in soil water, ground water, and precipitation were measured at the study plots. Bromide exchange properties and saturated hydraulic conductivity of the soils were determined in the laboratory. During two selected time periods, irrigation water, was spiked with NaBr (5.0 mg/l Br). Bromide movement through the upper profile was quantified by soil water samples and post-sampling neutron activation analysis. Soil moisture was near saturatin in both soils when the Br tracer was applied. Bromide concentrations above background levels (0.023 mg/l Br, Doniphan silt loam and 0.016 mg/l Br, Crider silt loam) were detected within 2.60 hours at 0.9 m in the Doniphan soil and within 3.75 hours at that depth in the Crider soil. The rate of Br movement in the profile was greater in both soils than the measured saturated hydraulic conductivity, Bromide concentrations above background levels were present in soil water from the study plots for a minimum of 21 days after irrigation with the Br tracer.     

IMPACTS OF RECREATION ON RIPARIAN SOILS AND VEGETATION1

ABSTRACT: The seemingly magnetic attraction of water resources for recreation has direct implications for proximate land resources which are needed to provide access and support facilities. This paper reviews and synthesizes the literature dealing with the impacts of recreation use on riparian soils and vegetation. Part one of the paper sets forth the major negative impacts of recreation use on soils and vegetation. A seven-step soil impact cycle is identified, beginning with the scuffing away of leaf litter and other organic material and working through the soil erosion and sedimentation process. Four major kinds of impacts of recreation use on vegetation are then outlined, and the‘Vicious circle” relationship between impacts on soil and vegetation is demonstrated through a Soil/Vegetation Impact Diagram. Part two identifies several spatial and temporal patterns of environmental impact caused by recreation use. The node and linkage pattern of recreation use, campground and trail expansion, ground cover response and succession, rates of soil compaction, and resource response to various intensities of recreation use are important aspects. The final part of the paper deals with measuring environmental impacts caused by recreation use. Management implications of the research findings are considered throughout the paper.     

SOIL MOISTURE PREDICTION USING SUPPORT VECTOR MACHINES1

ABSTRACT: Herein, a recently developed methodology, Support Vector Machines (SVMs), is presented and applied to the challenge of soil moisture prediction. Support Vector Machines are derived from statistical learning theory and can be used to predict a quantity forward in time based on training that uses past data, hence providing a statistically sound approach to solving inverse problems. The principal strength of SVMs lies in the fact that they employ Structural Risk Minimization (SRM) instead of Empirical Risk Minimization (ERM). The SVMs formulate a quadratic optimization problem that ensures a global optimum, which makes them superior to traditional learning algorithms such as Artificial Neural Networks (ANNs). The resulting model is sparse and not characterized by the “curse of dimensionality.” Soil moisture distribution and variation is helpful in predicting and understanding various hydrologic processes, including weather changes, energy and moisture fluxes, drought, irrigation scheduling, and rainfall/runoff generation. Soil moisture and meteorological data are used to generate SVM predictions for four and seven days ahead. Predictions show good agreement with actual soil moisture measurements. Results from the SVM modeling are compared with predictions obtained from ANN models and show that SVM models performed better for soil moisture forecasting than ANN models.     

SYSTEM ECONOMIC RESPONSE TO WATER QUANTITY AND QUALITY - FUNDAMENTAL CONSIDERATIONS1

The relationship between water quantity, water quality, and system economic response to permutations of these variables on any given water use, and the allocation of water among competing uses is outlined by means of a conceptual model. The effect of the quantity-quality variable mix on a given use is called the “intensive effect,” and the allocation mix on the total system is the “extensive effect.” The elements of the model are best described by the partial sketch of the flow diagram, outlined below in terms of symbols.     

MEASURED AND CREAMS-PREDICTED NITROGEN LOSSES FROM TOMATO AND CORN MANAGEMENT SYSTEMS1

Nitrogen runoff and leaching losses from two tomato and four corn field plots were compared to model predictions by CREAMS, a field-scale model for Chemicals, Runoff, and Erosion from Agricultural Management Systems. The tomato treatments were (1) trickle irrigation with one-half of applied N at preplant and one-half of applied N through the trickle irrigation system and (2) overhead sprinkler irrigation with one-half of applied N at preplant and one-half of applied N in two equal sidedressings. The corn treatments consisted of multiple N applications, minimum tillage, and “conventional” management. Soil type appeared to influence the ability of CREAMS to predict seasonal trends and treatment influences. Model predictions for N losses from tomato and corn treatments that were located on sandy soils often disagreed with measured values. Treatment influences and seasonal trends for N losses from corn treatments that were located on a higher clay content soil were more satisfactorily predicted by CREAMS. Even though model input parameter estimation and measurement techniques may be imperfect, the simulation ability of CREAMS for predicting N leaching losses from systems on deep sands probably needs to be improved. Sensitivity analyses indicated that annual NC₃^?-N leaching loss predictions were either minimally or not affected by changes in saturated hydraulic conductivity. Input estimations of the fraction of soil pore space filled at field capacity and soil organic matter were inversely related to annual NO₃^?-N leaching losses, while potential mineralizable N was directly related to yearly N leaching losses.     

On the Relationship Between Mean and Variance of Soil Moisture Fields1

Abstract: The objective of this work was to explain an apparent contradiction in the literature related to the relationship between mean and variance (or standard deviation) of soil moisture fields. Some studies found an increase in soil moisture variance with decreasing mean soil moisture, while others showed a decrease. The evidence of maximum variance in the mid‐range of mean soil moisture was also reported in the literature. In this paper, we focus on the effects of spatial variability of soil texture on the relationship between variance and mean of soil moisture during soil dry‐down processes. Soil texture influences soil moisture mean and variance through its direct effects on evaporation and drainage, which are two main factors controlling soil drying. A differential equation describing soil moisture dry down is proposed and studied. Our study shows that as mean soil moisture is greater than a threshold, variance increases with decreasing mean soil moisture. If mean soil moisture is less than the threshold, variance decreases with decreasing mean soil moisture. The threshold depends on soil texture and is between the field capacity and the wilting point. The soil moisture dry‐down equation is also applied to explain the apparent contradiction with regard to the relationship between mean and variance of soil moisture fields reported in the literature.     

ANNOYANCE AND COMMUNITY NOISE: PSYCHOPHYSICAL MODEL OF DOSE – RESPONSE RELATIONSHIPS

There is a paucity of theory pertaining to social surveys of annoyance and community noise. A new psychophysical model addresses data concerning resident annoyance in sites exposed to various maximum noise levels and different numbers of noise events. The best fits of this model point to the relevance of response variance for understanding the results obtained with category response scales. The argument identifies a number of psychological and physical variables that may influence annoyance reactions to community noise. Most importantly, the model suggests that the truncation inherent in category scales biases the responses, and that response variability may be critical in determining the detailed shape of the dose–response function. Regulatory decisions concerning annoyance and community noise should be more valid when based on a deeper understanding of the theoretical basis of the empirical data.     

ROLE OF IRRIGATION WATER IN AGRICULTURAL PRODUCTION: SOME RESOURCE USE ISSUES1

ABSTRACT: A partial production function for corn that considers the time and amount of water applications is determined. Examples are worked out by using data on site specific parameters for nine soil sites in the Great Plains Region repesenting various combinations of water holding capacity, pan evaporation, and average rainfall. It is found that soils with a low water holding capacity are more water and energy intensive in crop production and thus more vulnerable to fluctuations in net returns due to declining water tables or energy shortages. Despite this, farmers of low water holding capacity soils are likely to opt for irrigation. This points to the existence of a necessary, but sufficient, condition for socially inefficient use of ground water resources. This calls to question the property right concept in water created through the appropriation doctrine and the “law of capture.” This paper indicates the type of analysis that must be undertaken in order to make appropriate changes in laws governing water use.     

PREDICTABILITY OF SURFACE WATER POLLUTION LOADING IN PENNSYLVANIA USING WATERSHED‐BASED LANDSCAPE MEASUREMENTS1

ABSTRACT: We formally evaluated the relationship between landscape characteristics and surface water quality in the state of Pennsylvania (USA) by regressing two different types of pollutant responses on landscape variables that were measured for whole watersheds. One response was the monthly exported mass of nitrogen estimated from field measurements, while the other response was a GIS‐modeled pollution potential index. Regression models were built by the stepwise selection protocol, choosing an optimal set of landscape predictors. After factoring out the effect of physiography, the dominant predictors were the proportion of “annual herbaceous” land and “total herbaceous” land for the nitrogen loading and pollution potential index, respectively. The strength of these single predictors is encouraging because the marginal land cover proportions are the simplest landscape measurements to obtain once a land cover map is in hand; however, the optimal set of predictors also included several measurements of spatial pattern. Thus, for watersheds at this general hierarchical scale, gross landscape pattern may be an important influence on instream pollution loading. Overall, there is strong evidence that using landscape measurements alone, obtained solely from remotely sensed data, can explain most of the water quality variability (R²= approx. 0.75) within these watersheds.     

Carbon dioxide flux as affected by tillage and irrigation in soil converted from perennial forages to annual crops

Among greenhouse gases, carbon dioxide (CO(2)) is one of the most significant contributors to regional and global warming as well as climatic change. A field study was conducted to (i) determine the effect of soil characteristics resulting from changes in soil management practices on CO(2) flux from the soil surface to the atmosphere in transitional land from perennial forages to annual crops, and (ii) develop empirical relationships that predict CO(2) flux from soil temperature and soil water content. The CO(2) flux, soil temperature (T(s)), volumetric soil water content (theta(v)) were measured every 1-2 weeks in no-till (NT) and conventional till (CT) malt barley and undisturbed soil grass-alfalfa (UGA) systems in a Lihen sandy loam soil (sandy, mixed, frigid Entic Haplustoll) under irrigated and non-irrigated conditions in western North Dakota. Soil air-filled porosity (epsilon) was calculated from total soil porosity and theta(v) measurements. Significant differences in CO(2) fluxes between land management practices (irrigation and tillage) were observed on some measurement dates. Higher CO(2) fluxes were detected in CT plots than in NT and UGA treatments immediately after rainfall or irrigation. Soil CO(2) fluxes increased with increasing soil moisture (R(2)=0.15, P<0.01) while an exponential relationship was found between CO(2) emission and T(s) (R(2)=0.59). Using a stepwise regression analysis procedure, a significant multiple regression equation was developed between CO(2) flux and theta(v), T(s) (CO(2) [Formula: see text] ; R(2)=0.68, P0.01). Not surprisingly, soil temperature was a driving factor in the equation, which accounted for approximately 59% in variation of CO(2) flux. It was concluded that less intensive tillage, such as no-till or strip tillage, along with careful irrigation management will reduce soil CO(2) evolution from land being converted from perennial forages to annual crops.     

SATELLITE MICROWAVE OBSERVATIONS OF SOIL MOISTURE VARIATIONS1

ABSTRACT: Results from studies in the Illinois-Indiana and Texas-Oklahoma areas indicate that satellite microwave observations at the 1.55 cm wavelength are responsive to relative moisture variations in the near surface layer of the soil. Because significant vegetation cover absorbs the 1.55 cm microwave emission from the soil, the target area must be predominately bare soil or low density vegetation cover for meaningful measurements to result. The 25 km resolution of the satellite sensor limits application of the microwave techniques to large areas such as watersheds or agricultural districts rather than individual fields. In general, at 1.55 cm. there is an inverse relationship between microwave brightness temperature and changes in soil moisture levels (as indicated by antecedent rainfall) in agricultural regions before the planting of crops or during the early growing season when vegetation cover is sparse. Even early season observations should be of great value in deciding on the time and type of crop planting and for initial irrigation scheduling when the root zone is still in close proximity to the surface.     

PREDICTIVE ASSESSMENT OF SEVERITY OF AGRICULTURAL DROUGHTS BASED ON AGRO-CLIMATIC FACTORS1

ABSTRACT: Past historical evidence indicates that droughts have had great impacts on human life. Drought (or scarcity of water) is assessed based on two key factors, namely, the estimated water demand, and the expected water supply. The formulation of these key factors for a region largely depends on the agro-climatic and economic conditions. Consideration of one such key factor is the relationship between the crop yield and water deficit in the assessment and prediction of agricultural droughts. The varying nature of this relationship from crop to crop adds to the complexity of agricultural drought analysis. To overcome this difficulty in analyzing agricultural droughts of a region, it is adequate to consider and place emphasis on a single crop (i.e., an index crop) grown homogeneously over the major area of the region. From one year to another year, the pattern of water requirement during the growing season of an index crop is rather stationary, and the water supply in arid and semi-arid area is mainly from seasonal random precipitation. In a region, grain yield of the index crop and, in turn, assessment of the severity of drought can reasonably be predicted as a function of the time of crop sowing and the distribution of rainfall, provided that temporal and spatial effects of other contributing factors (crop variety, soil fertility status, crop disease, pest control, cultivation practices etc.) on grain yield are considered to be uniformly distributed (i.e., stable). A predictive method of assessing agricultural droughts in an arid area of western India is presented. The major crop (Pearl Millet) of this region is grown from. July through September. The formulation of the proposed predictive method inherently implies that the grain yield of the main crop is a reliable indicator of agricultural drought. In the development of this predictive relationship (i.e., a regression type model) a number of potential yet simple variables affecting the grain yield in the region were investigated. The soil moisture index, although generally considered significant compared to the simple variables, has been found to account for insignificant variation in the grain yield. Results of our investigations suggest that it would be advisable to exclude the soil moisture index variable from the model. The proposed regression model can be used in the prediction of grain yield of the main crop several months ahead of crop harvesting operations and, in turn, the assessment of agricultural drought severity as mild, moderate, or severe. Such an assessment is expected to be helpful to planners for arranging appropriate measures to effectively combat agricultural drought situations.     

APPLICATION OF AN INTEGRATED BASIN-SCALE HYDROLOGIC MODEL TO SIMULATE SURFACE-WATER AND GROUND-WATER INTERACTIONS1

ABSTRACT: Hydrologic models have become an indispensable tool for studying processes and water management in watersheds. A physically-based, distributed-parameter model, Basin-Scale Hydro-logic Model (BSIIM), has been developed to simulate the hydrologic response of large drainage basins. The model formulation is based on equations describing water movement both on the surface and in the subsurface. The model incorporates detailed information on climate, digital elevation, and soil moisture budget, as well as surface-water and ground-water systems. This model has been applied to the Big Darby Creek Watershed, Ohio in a 28-year simulation of rainfall-runoff processes. Unknown coefficients for controlling runoff, storativity, hydraulic conductivity, and streambed permeability are determined by a trial-and-error calibration. The performance of model calibration and predictive capability of the model was evaluated based on the correlation between simulated and observed daily stream discharges. Discrepancies between observed and simulated results exist because of limited precipitation data and simplifying assumptions related to soil, land use, and geology.     

POTENTIAL,ACTUAL, AND EQUILIBRIUM EVAPOTRANSPIRATION IN A WHEAT FIELD 1

ABSTRACT: This paper examines the relationship between both potential (E*) and nonpotential evapotranspiration and equilibrium evapotranspiration (EQ) in an irrigated wheat field in southcentral Alberta, Canada. The control exercised by surface wetness and root reservoir moisture content in determining the value of the Priestley-Taylor constant a is explored. Also investigated is the relationship between a and the vapor flux fraction ET/(R-G) where ET is the actual evapotranspiration, R the net radiation, and G the soil heat flux. It is shown that evapotranspiration occurred at the potential rate (E*) when the available soil moisture (ASM) within the root zone was ≥3 percent. a varied from 0.84 for a dry soil to 1.49 for a saturated soil. The mean a for E* was 1.24. Surface wetness sustained evapotranspiration at the potential rate when such wetting exceeded 2mm d^?1 following a period of prolonged drawdown of soil moisture, α and ET/(R-G) were positively correlated and this correlation strengthened with increasing soil moisture for constant values of the energy partitioning factor s+γ/s where s is the slope of the saturation humidity-temperature curve and γ is the psychrometric constant. ET=EQ when ETI(R-G) lay within the range of 0.59 to 0.82 corresponding to Bowen ratio (β) values of 0.22 and 0.69, respectively.     

ECONOMIC EVALUATION OF ON-FARM WATER MANAGEMENT PROJECTS1

ABSTRACT: During the last three decades, developing countries have invested enormous amounts of resources (running into billions of dollars) in the development of large surface irrigation systems. Investment funds were largely spent on the development of the main systems such as dams, canals and distributaries. Very little attention and resources have been spent on the development of below-the-outlet subsystems, in spite of very low levels of water use efficiency due to lack of proper land leveling, high water losses in field channels, and skewed distribution of available water among farmers served by individual water courses. This state of affairs has resulted in a lack of confidence on the part of most farmers in the reliability of surface irrigation systems to deliver water on time and in adequate quantities which, in turn, has resulted in farmers using below optimum levels of all other complementary inputs except labor. Realizing the importance of improving water use efficiency, both the domestic governments and donor agencies are increasingly paying serious attention to these problems. On-Farm Water Management (OFWM) as a strategy to improve water use efficiency and consequently agricultural production in many developing countries has been currently receiving very wide and vigorous consideration among economists, water management experts, policymakers, and donor agencies. A judicious use of the newly allocated funds of OFWM projects obviously needs proper evaluation procedures so that money could be allocated for the most deserving purposes and projects. In particular, recently, private profitability calculations due to public investments in OFWM activities have received attention from economists and decision makers in developing countries’governments and in donor agencies are very much interested in knowing the impacts of their investments in OFWM activities on farmers’income and welfare. However, the evaluation procedures commonly used in empirical studies, using a production function approach, seem to be at variance and sometimes inconsistent with proper comparative-static procedures. Thus, the primary objective of this paper is to develop consistent procedures for evaluating the impacts created by OFWM investments on farmers’income and resource use. In this context, the paper examines the critical relationship between the market price of the agricultural output and production function parameters which are affected by the OFWM investments.     

In situ measurement of soil moisture and pore-water pressures in an ‘incipient’ landslide: Lake Tutira,New Zealand

The immediate cost of shallow regolith landslides in New Zealand has been estimated to exceed US$33M annually. Since the majority of these landslides occur during prolonged wet conditions, or intense rainstorms, moisture conditions are a critical control. The nature, dynamics, and character of soil moisture conditions, and the piezometric response to rainfall, have been recorded within an ‘incipient’ landslide for more than 5 years. The study site, on pastoral hill country within the Lake Tutira catchment in northern Hawkes Bay, is typical of large areas of New Zealand episodically affected by extensive landsliding. Detailed continuous measurements show that both the soil moisture and piezometric response within the regolith are highly storm- and site-specific. The development of positive pore pressures is infrequent; they form only during intense rainstorms, and persist for a short time. The hydraulic response of the soil is primarily a function of storm characteristics, but this response can be modified by antecedent moisture conditions, topographic position, and heterogeneity of soil properties.     

SPATIAL DISTRIBUTION OF POINT SOIL MOISTURE ESTIMATES USING LANDSAT TM DATA AND FUZZY-C CLASSIFICATION1

ABSTRACT: Many hydrologic models have input data requirements that are difficult to satisfy for all but a few well-instrumented, experimental watersheds. In this study, point soil moisture in a mountain watershed with various types of vegetative cover was modeled using a generalized regression model. Information on sur-ficial characteristics of the watershed was obtained by applying fuzzy set theory to a database consisting of only satellite and a digital elevation model (DEM). The fuzzy-c algorithm separated the watershed into distinguishable classes and provided regression coefficients for each ground pixel. The regression model used the coefficients to estimate distributed soil moisture over the entire watershed. A soil moisture accounting model was used to resolve temporal differences between measurements at prototypical measurement sites and validation sites. The results were reasonably accurate for all classes in the watershed. The spatial distribution of soil moisture estimates corresponded accurately with soil moisture measurements at validation sites on the watershed. It was concluded that use of the regression model to distribute soil moisture from a specified number of points can be combined with satellite and DEM information to provide a reasonable estimation of the spatial distribution of soil moisture for a watershed.     

BIOECONOMIC ANALYSIS OF SELECTED CONSERVATION PRACTICES ON SOIL EROSION AND FRESHWATER FISHERIES1

ABSTRACT: Farmers can generate environmental benefits (improved water quality and fisheries and wildlife habitat), but they may not be able to quantify them. Furthermore, farmers may reduce their incomes from managing lands to produce these positive externalities but receive little monetary compensation in return. This study simulated the relationship between agricultural practices, water quality, fish responses to suspended sediment and farm income within two small watersheds, one of a cool water stream and one of a warm water stream. Using the Agricultural Drainage and Pesticide Transport (ADAPT) model, this study related best management practices (BMPs) to calculated instream suspended sediment concentrations by estimating sediment delivery, runoff, base flow, and streambank erosion to quantify the effects of suspended sediment exposure on fish communities. By implementing selected BMPs in each watershed, annual net farm income declined $18,000 to $28,000 (1 to 3 percent) from previous levels. “Lethal” fish events from suspended sediments in the cool water watershed decreased by 60 percent as conservation tillage and riparian buffers increased. Despite reducing suspended sediments by 25 percent, BMPs in the warm water watershed did not reduce the negative response of the fisheries. Differences in responses (physical and biological) between watersheds highlight potential gains in economic efficiency by targeting BMPs or by offering performance based “green payments.”