Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part I: A Review of Metrics and Adjoint Methods

Irrigation management consists of many components. In this work we review and recommend rainfall forecast performance metrics and adjoint methodologies for the use of predictive weather data within the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE estimates crop water uses to optimize irrigation scheduling. WISE and its components, input requirements, and related software design issues are discussed. The use of predictive weather allows WISE to consider economic opportunity‐costs of decisions to defer water application if rainfall is forecast. These capabilities require an assessment of the system uncertainties and use of weather prediction performance probabilities. Rainfall forecasts and verification performance metrics are reviewed. In addition, model data assimilation methods and adjoint sensitivity concepts are introduced. These assimilation methods make use of observational uncertainties and can link performance metrics to space and time considerations. We conclude with implementation guidance, summaries of available data sources, and recommend a novel adjoint method to address the complex physical linkages and model sensitivities between space and time within the irrigation scheduling physics as a function of soil depth. Such tool improvements can then be used to improve water management decision performance to better conserve and utilize limited water resources for productive use. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

Multi-Criteria Decision Analysis of Treated Wastewater Use for Agriculture in Water Deficit Regions1

Al-Juaidi, Ahmed E., Jagath J. Kaluarachchi, and Ungtae Kim, 2010. Multi-Criteria Decision Analysis of Treated Wastewater Use for Agriculture in Water Deficit Regions. Journal of the American Water Resources Association (JAWRA) 46(2):395-411. DOI: 10.1111/j.1752-1688.2009.00409.x Abstract: Coastal regions such as the Gaza Strip of Palestine with limited freshwater supply suffer significantly due to the rapid depletion of water levels, seawater intrusion, and increased water demands. In such regions, use of treated wastewater (TWW) is a viable option if public health issues are addressed. The goal of this paper is to address the use of TWW in agriculture while considering net benefit, economic efficiency of water use (EEWU), environmental goals, and public health risks. The proposed methodology considers public health risk assessment and multi-criteria decision analysis to assess the beneficial use of TWW in agriculture. The methodology was demonstrated for the Gaza Strip. The health risk assessment suggests that increasing the elapsed time between irrigation and consumption and switching from surface to sprinkler and drip irrigation are practical measures to reduce public health risks. The optimization and decision analyses show that proper allocation of freshwater and TWW and distribution of land area by crop type can significantly increase the net benefit and EEWU. In most cases, net benefit increased by 44%, groundwater use reduced 29% while increasing the EEWU by threefold compared with the existing conditions. The multi-criteria decision analysis with weighted goal programming can develop flexible management options that considers a given decision-maker preference. When groundwater abstraction for agriculture reduced from 57 to 36 Mm³ as per decision analysis, the corresponding area below mean sea level decreased by 58% indicating significant aquifer recovery.     

Planning Agricultural Water Resources System Associated With Fuzzy and Random Features1

Li, Y.P. and G.H. Huang, 2011. Planning Agricultural Water Resources System Associated With Fuzzy and Random Features. Journal of the American Water Resources Association (JAWRA) 47(4):841‐860. DOI: 10.1111/j.1752‐1688.2011.00558.x Abstract: More and more regions where demand outstrips water resources availability have suffered from chronic severe shortages. It is particularly aggravated for agricultural irrigation systems where more water is necessary to support the rapidly increasing population and speedily developing economy. In this study, a two‐stage fuzzy‐stochastic programming (TFSP) method is developed for planning agricultural water resources management system in more efficient and sustainable ways. The developed method can address uncertain parameters described as probability distributions and fuzzy sets. It can also be used for analyzing various policy scenarios that are associated with different levels of economic consequences since penalties are exercised with recourse actions against any infeasibility. The developed method is applied to agricultural water‐resources management planning of the Zhangweinan River Basin, China. Solutions under various α‐cut levels and fuzzy dominance indices can be generated by solving a series of deterministic submodels, which can help determine optimized crop‐target values that could hedge appropriately against future available water levels. The results are helpful for water resources managers in not only making decisions of crop irrigation but also gaining insight into the tradeoffs between economic objective and system‐failure risk.     

Simulating the Impacts of Irrigation Levels on Soybean Production in Texas High Plains to Manage Diminishing Groundwater Levels

There is an increasing need to strategize and plan irrigation systems under varied climatic conditions to support efficient irrigation practices while maintaining and improving the sustainability of groundwater systems. This study was undertaken to simulate the growth and production of soybean [Glycine max (L.)] under different irrigation scenarios. The objectives of this study were to calibrate and validate the CROPGRO‐Soybean model under Texas High Plains’ (THP) climatic conditions and to apply the calibrated model to simulate the impacts of different irrigation levels and triggers on soybean production. The methodology involved combining short‐term experimental data with long‐term historical weather data (1951–2012), and use of mechanistic crop growth simulation algorithms to determine optimum irrigation management strategies. Irrigation was scheduled based on five different plant extractable water levels (irrigation threshold [ITHR]) set at 20%, 35%, 50%, 65%, and 80%. The calibrated model was able to satisfactorily reproduce measured leaf area index, biomass, and evapotranspiration for soybean, indicating it can be used for investigating different strategies for irrigating soybean in the THP. Calculations of crop water productivity for biomass and yield along with irrigation water use efficiency indicated soybean can be irrigated at ITHR set at 50% or 65% with minimal yield loss as compared to 80% ITHR, thus conserving water and contributing toward lower groundwater withdrawals. Editor's note: This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

辽西易旱区集雨灌溉山地大棚技术

通过雨水径流的集蓄储存可解决水源问题，发展山地蔬菜大棚。结果表明：一个70m^3的水窖集水在配以渗灌技术的条件下可以满足333m^2的大棚生育期用水需求，与传统畦灌相比节水53.4%，且效益可观，达20万元／hm^2，使干旱贫瘠的山地一跃成为发展高效农业的园田，为辽西易旱区坡地高效利用开辟了一条新途径。     

Climate Change Impacts on Irrigation Water Needs in the jaguaribe River Basin1

Gondim, Rubens S., Marco A.H. de Castro, Aline de H.N. Maia, Sílvio R.M. Evangelista, and Sérgio C. de F. Fuck, Jr., 2012. Climate Change Impacts on Irrigation Water Needs in the Jaguaribe River Basin. Journal of the American Water Resources Association (JAWRA) 48(2): 355‐365. DOI: 10.1111/j.1752‐1688.2011.00620.x Abstract: Climate change is conceptually referred to as a modification to the average of climate variables and their natural variability, due to both natural and anthropogenic driving forces, such as greenhouse gas emissions. Climate change potentially impacts rainfall, temperature, and air humidity, which have relationship with plant evapotranspiration and consequently to irrigation water needs (IWN). The purpose of this research is to assess climate change impacts on irrigation water demand, based on climatic impacts stemming from future greenhouse gas emission scenarios. The study area includes eight municipalities in the Jaguaribe River Basin, located in the Ceará State of semiarid northeast Brazil. The FAO Penman‐Monteith method is used for the calculation of a reference evapotranspiration with limited climatic data. IWN projections are calculated using bias‐corrected climate projections for monthly rainfall and surface temperature derived from the United Kingdom’s Hadley Centre Regional Climate Model simulations. The increase in the average IWN is projected to be 7.9 and 9.1% over the period 2025‐2055 for the A2 and B2 scenarios, respectively with respect to 1961‐1990 baseline.     

IDW‐Plus: An ArcGIS Toolset for Calculating Spatially Explicit Watershed Attributes for Survey Sites

Watershed characteristics such as land‐use and land‐cover affect stream condition at multiple scales, but it is widely accepted that conditions in close proximity to the stream or survey site tend to have a stronger influence. Although spatially weighted watershed metrics have existed for years, nonspatial lumped landscape metrics (i.e., areal mean or percentage) are still widely used because relatively few technical skills are needed to implement them. The Inverse Distance Weighted Percent Land Use for Streams (IDW‐Plus) custom ArcGIS toolset provides the functionality to efficiently calculate six spatially explicit watershed metrics which account for the Euclidean or flow length distance to the stream or outlet, as well as the probability for overland runoff. These include four distance‐weighted metrics, those being inverse Euclidean distance to the stream or outlet, and the inverse flow length to the stream or outlet. Two tools are also included to generate hydrologically active (i.e., runoff potential), inverse flow length to the stream or outlet metrics. We demonstrate the tools using real data from Southeast Queensland, Australia. We also provide detailed instructions, so readers can recreate the examples themselves before applying the tools to their own data.     

Deficit Irrigation Management of Maize in the High Plains Aquifer Region: A Review

Irrigated agriculture is a major economic contributor of the High Plains Region and it primarily relies on the High Plains Aquifer as a source of water. Over time, areas of the High Plains Aquifer have experienced drawdowns limiting its ability to supply sufficient water to sustain fully irrigated crop production. This among other reasons, including variable climatic factors and differences in state water policy, has resulted in some areas adopting and practicing deficit irrigation management. Considerable research has been conducted across the High Plains Aquifer region to identify locally appropriate deficit irrigation strategies. This review summarizes and discusses research conducted in Nebraska, Colorado, Kansas, and Texas, as well as highlights areas for future research. Editor's note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

WATER MANAGEMENT AND N,P LOSSES FROM PADDY FIELDS IN SOUTHERN KOREA1

ABSTRACT: Assessment and control of nutrient losses from paddy fields is important to protect water quality of lakes and streams in Korea. A four‐year field study was carried out to investigate water management practices and losses of nitrogen (N) and phosphorus (P) in rice paddy irrigation fields in southern Korea. The amount and water quality of rainfall, irrigation, surface drainage, and infiltration were measured and analyzed to estimate inputs and losses of N and P. The observed irrigation amount surpassed consumptive use, and approximately 52 to 69 percent of inflow (precipitation plus irrigation) was lost to surface drainage. Field data showed that significant amounts of irrigation water and rainfall were not effectively used for rice paddy culture. Water quality data indicated that drainage from paddy fields could degrade the recipient water environment. The nutrient balance indicated that significant amounts of nutrients (29.5 percent of total N and 8.6 percent of total P compared to input) were lost through surface drainage. Furthermore, up to half the nutrient losses occurred during nonstorm periods. The study results indicate that inadequate water management influences N and P losses during both storm and nonstorm periods. Proper water management is required to reduce nutrient losses through surface drainage from paddy fields; this includes such measures as minimum irrigation, effective use of rainfall, adoption of proper drainage outlet structures, and minimized forced surface drainage.     

Effects of Lawn Maintenance on Nutrient Losses Via Overland Flow During Natural Rainfall Events1

Spence, Porchè L., Deanna L. Osmond, Wesley Childres, Joshua L. Heitman, and Wayne P. Robarge, 2012. Effects of Lawn Maintenance on Nutrient Losses Via Overland Flow During Natural Rainfall Events. Journal of the American Water Resources Association (JAWRA) 48(5): 909‐924. DOI: 10.1111/j.1752‐1688.2012.00658.x Abstract: A sampling system was used to evaluate the effect of residential lawn management on nutrient losses via overland flow generated during natural rainfall events from three residential landscapes: a high maintenance fescue lawn (HMFL), a low maintenance fescue lawn (LMFL), and a mixed forested residential landscape (FRL). A sampling system was located in designated areas within each landscape such that 100% of the runoff follows natural flow paths to the outlet ports and collects in sterile Nalgene^® B³ media bags (Thermo Fisher Scientific, Rochester, NY). A rainfall event was defined as producing ≥2.54 mm of water. A total of 87 rainfall events occurred during a 20‐month monitoring period. The total runoff volume collected from the LMFL was higher than from the HMFL and FRL, but on average <1% of the total rainfall was collected from the three landscapes. Mean nitrate concentrations from each lawn did not exceed 0.6 mg N/l. Nutrient unit area losses from the HMFL, LMFL, and FRL were 1,000 times less than fertilizer and throughfall inputs, which were due to the presence of well‐structured soils (low bulk densities) with high infiltration rates. This study demonstrated that the frequency of runoff, total runoff volumes, and nutrient losses during natural rainfall events are lower from highly maintained (i.e., irrigation, fertilizer application, and reseeding) densely uniform manicured lawns than low maintenance lawns and forested residential landscapes.     

RUNOFF IMPOUNDMENT FOR SUPPLEMENTAL IRRIGATION IN TEXAS1

ABSTRACT: The current increase in the demand for water by municipal, industrial, and other users is likely to result in approximately one-third less water being available for agricultural use in Texas by the year 2000. As water supplies diminish, the rainfall excess needs to be used more efficiently. Large amounts of runoff occur in the eastern part of Texas that could be collected in small impoundments and utilized for crop production. Farmers in water-surplus basins or subbasins can apply for a permit to divert surface water into small on-farm impoundments to be used for supplemental irrigation. The costs for runoff collection and two supplemental irrigations, which amount to a total of 4 in./yr., are estimated to be approximately $60/acre/year. Depending upon the crop produced, the estimated increase in gross income from supplemental irrigation ranges from about $80 to more than $100 per acre annually.     

The Effects of Irrigation and Climate on the High Plains Aquifer: A County‐Level Econometric Analysis

The High Plains Aquifer (HPA) underlies parts of eight states and 208 counties in the central area of the United States (U.S.). This region produces more than 9% of U.S. crops sales and relies on the aquifer for irrigation. However, these withdrawals have diminished the stock of water in the aquifer. In this paper, we investigate the aggregate county‐level effect on the HPA of groundwater withdrawal for irrigation, of climate variables, and of energy price changes. We merge economic theory and hydrological characteristics to jointly estimate equations describing irrigation behavior and a generalized water balance equation for the HPA. Our simple water balance model predicts, at average values for irrigation and precipitation, an HPA‐wide average decrease in the groundwater table of 0.47 feet per year, compared to 0.48 feet per year observed on average across the HPA during this 1985–2005 period. The observed distribution and predicted change across counties is in the (?3.22, 1.59) and (?2.24, 0.60) feet per year range, respectively. The estimated impact of irrigation is to decrease the water table by an average of 1.24 feet per year, whereas rainfall recharges the level by an average of 0.76 feet per year. Relative to the past several decades, if groundwater use is unconstrained, groundwater depletion would increase 50% in a scenario where precipitation falls by 25% and the number of degree days above 36°C doubles. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

THE MILWAUKEE POLLUTION CASE - IMPLICATIONS FOR WATER RESOURCES PLANNING1

ABSTRACT: The Illinois v. Milwaukee Federal District Court decision is the most far reaching application yet of the federal common law of nuisance to interstate water pollution conflicts. Although a Federal Appelate Court recently rescinded part of the district court decision, Milwaukee must still upgrade its metropolitan sewage system to a level beyond that required by federal and state regulations. The improvements must be completed with or without federal aid. The case points out the apparent inability of the Clean Water Act, the most comprehensive federal legislation affecting the nation's water quality, to deal with certain interstate water quality conflicts. The Milwaukee decision could set a precedent for similar settlements elsewhere which may in turn affect the U.S. Environmental Protection Agency's water quality clean up program. A more integrated, ecosystem conscious approach to management of shared water resources (e.g., the Great Lakes) would help reduce the need for court decisions like Illinois v. Milwaukee.     

IRRIGATION PLANNING BASED ON WATER DEFICITS1

ABSTRACT: The deliberate underwatering of a larger land area, as practiced in Southern Asia, has provided impetus for a systematic investigation into the effects of designing projects for crop water deficits on Benefit-Cost performance. The study began with the derivation, from published experimental results, of functions relating ultimate crop yield to the magnitude and timing of water deficits, i.e., of the productivity of irrigation water. To obtain the net benefit of the project, the relation between the harvested area and output and the on-farm production costs was then suggested. The cost of supplying the irrigation water to the proposed area and of distributing and applying it to the field was determined, thus completing the Benefit-Cost equation. A computer simulation model was then established to search for the irrigation project design capacity and area to maximize the net present value in the Benefit-Cost analysis for the development proposed.     

BASIN SCALE WATER MANAGEMENT AND FORECASTING USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: Water scarcity in the Sevier River Basin in south‐central Utah has led water managers to seek advanced techniques for identifying optimal forecasting and management measures. To more efficiently use the limited quantity of water in the basin, better methods for control and forecasting are imperative. Basin scale management requires advanced forecasts of the availability of water. Information about long term water availability is important for decision making in terms of how much land to plant and what crops to grow; advanced daily predictions of streamflows and hydraulic characteristics of irrigation canals are of importance for managing water delivery and reservoir releases; and hourly forecasts of flows in tributary streams to account for diurnal fluctuations are vital to more precisely meet the day‐to‐day expectations of downstream farmers. A priori streamflow information and exogenous climate data have been used to predict future streamflows and required reservoir releases at different timescales. Data on snow water equivalent, sea surface temperatures, temperature, total solar radiation, and precipitation are fused by applying artificial neural networks to enhance long term and real time basin scale water management information. This approach has not previously been used in water resources management at the basin‐scale and could be valuable to water users in semi‐arid areas to more efficiently utilize and manage scarce water resources.     

Characterization of Storm Flow Dynamics of Headwater Streams in the South Carolina Lower Coastal Plain1

Epps, Thomas H., Daniel R. Hitchcock, Anand D. Jayakaran, Drake R. Loflin, Thomas M. Williams, and Devendra M. Amatya, 2012. Characterization of Storm Flow Dynamics of Headwater Streams in the South Carolina Lower Coastal Plain. Journal of the American Water Resources Association (JAWRA) 1‐14. DOI: 10.1111/jawr.12000 Abstract: Hydrologic monitoring was conducted in two first‐order lower coastal plain watersheds in South Carolina, United States, a region with increasing growth and land use change. Storm events over a three‐year period were analyzed for direct runoff coefficients (ROC) and the total storm response (TSR) as percent rainfall. ROC calculations utilized an empirical hydrograph separation method that partitioned total streamflow into sustained base flow and direct runoff components. ROC ratios ranged from 0 to 0.32 on the Upper Debidue Creek (UDC) watershed and 0 to 0.57 on Watershed 80 (WS80); TSR results ranged from 0 to 0.93 at UDC and 0.01 to 0.74 at WS80. Variability in event runoff generation was attributed to seasonal trends in water table elevation fluctuation as regulated by evapotranspiration. Groundwater elevation breakpoints for each watershed were identified based on antecedent water table elevation, streamflow, ROCs, and TSRs. These thresholds represent the groundwater elevation above which event runoff generation increased sharply in response to rainfall. For effective coastal land use decision making, baseline watershed hydrology must be understood to serve as a benchmark for management goals, based on both seasonal and event‐based surface and groundwater interactions.     

Irrigation Water Allocation Using an Inexact Two‐Stage Quadratic Programming with Fuzzy Input under Climate Change

Agricultural irrigation accounts for nearly 70% of the total water use around the world. Uncertainties and climate change together exacerbate the complexity of optimal allocation of water resources for irrigation. An interval‐fuzzy two‐stage stochastic quadratic programming model is developed for determining the plans for water allocation for irrigation with maximum benefits. The model is shown to be applicable when inputs are expressed as discrete, fuzzy or random. In order to reflect the effect of marginal utility on benefit and cost, the model can also deal with nonlinearities in the objective function. Results from applying the model to a case study in the middle reaches of the Heihe River basin, China, show schemes for water allocation for irrigation of different crops in every month of the crop growth period under various flow levels are effective for achieving high economic benefits. Different climate change scenarios are used to analyze the impact of changing water requirement and water availability on irrigation water allocation. The proposed model can aid the decision maker in formulating desired irrigation water management policies in the wake of uncertainties and changing environment.     

Simulating Soil Water Content,Evapotranspiration, and Yield of Variably Irrigated Grain Sorghum Using AquaCrop

Use of models to simulate crop production has become important in optimizing irrigation management in arid and semiarid regions. However, applicability and performance of these models differ across regions, due to differences in environmental and management factors. The AquaCrop model was used to simulate soil water content (SWC), evapotranspiration (ET), and yield for grain sorghum under different irrigation regimes and dryland conditions at two sites in Central and Southern High Plains. Prediction error (P_e), estimated as the difference between simulated and measured divided by measured, for SWC ranged from ?17% to 4% in fully irrigated, ?3% to ?10% in limited irrigated, and ?16% to 25% in dryland treatments. The P_e within ±4%, ?5%, and ?17% to 24% were attained for seasonal ET under fully irrigated, limited irrigated, and dryland conditions, respectively. P_e values for grain yield were within those previously reported and ranged from ?10% to 12%, ?12% to 7%, and 9% to 17% for fully irrigated, limited irrigated and dryland conditions, respectively. Overall performance of the AquaCrop model showed it could be used as an effective tool for evaluating the impacts of variable crop and irrigation managements on the production of grain sorghum in the study area. Finally, the application of the model in the study area revealed planting date has a significant impact on sorghum yield and irrigation requirements, but the impact of planting density was negligible. Editor's note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation1

Young, Charles A., Marisa I. Escobar‐Arias, Martha Fernandes, Brian Joyce, Michael Kiparsky, Jeffrey F. Mount, Vishal K. Mehta, David Purkey, Joshua H. Viers, and David Yates, 2009. Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation. Journal of the American Water Resources Association (JAWRA) 45(6):1409‐1423. Abstract: The rainfall‐runoff model presented in this study represents the hydrology of 15 major watersheds of the Sierra Nevada in California as the backbone of a planning tool for water resources analysis including climate change studies. Our model implementation documents potential changes in hydrologic metrics such as snowpack and the initiation of snowmelt at a finer resolution than previous studies, in accordance with the needs of watershed‐level planning decisions. Calibration was performed with a sequence of steps focusing sequentially on parameters of land cover, snow accumulation and melt, and water capacity and hydraulic conductivity of soil horizons. An assessment of the calibrated streamflows using goodness of fit statistics indicate that the model robustly represents major features of weekly average flows of the historical 1980‐2001 time series. Runs of the model for climate warming scenarios with fixed increases of 2°C, 4°C, and 6°C for the spatial domain were used to analyze changes in snow accumulation and runoff timing. The results indicated a reduction in snowmelt volume that was largest in the 1,750‐2,750 m elevation range. In addition, the runoff center of mass shifted to earlier dates and this shift was non‐uniformly distributed throughout the Sierra Nevada. Because the hydrologic model presented here is nested within a water resources planning system, future research can focus on the management and adaptation of the water resources system in the context of climate change.     

Rain Water Harvesting in Bermuda1

Rowe, Mark P., 2011. Rain Water Harvesting in Bermuda. Journal of the American Water Resources Association (JAWRA) 47(6):1219–1227. DOI: 10.1111/j.1752‐1688.2011.00563.x Abstract: Roof‐top rain water harvesting is mandated by law for all buildings in Bermuda and is the primary source of water for domestic supply. The average rate at which rain water is harvested at the typical house with four occupants is, however, insufficient to meet average demand. While just over one‐third of households have access to supplementary water either from mains pipelines or private wells, the majority rely on deliveries from water “truckers” (tankers) to augment their rain water supply. Assuming a reasonably constant daily demand, there is a linear relationship between the “maximum optimum capacity” of a water storage tank and the size of the rain water catchment area, which depends on the characteristics of the rainfall at a given geographic location. A simple spreadsheet model was developed to simulate tank storage levels for various combinations of catchment area, tank capacity, and demand, with an input of actual daily rainfall data for a study period of nearly three years. It was found that for typical cycles of rainfall surpluses and deficits in Bermuda, the tank capacity which there is no benefit in exceeding — the “optimum maximum capacity”— is 0.37 m³ of storage capacity per 1 m² of catchment area. Furthermore, it was concluded that many domestic water storage tanks in Bermuda are larger than necessary, especially so where there is a significant imbalance between rain water supply and demand.