Irrigated lands assessment for water management: Technique test

A procedure for estimating irrigated land using full frame LANDSAT imagery was demonstrated. Relatively inexpensive interpretation of multidate LANDSAT photographic enlargements was used to produce a map of irrigated land in California. The LANDSAT and ground maps were then linked by regression equations to enable precise estimation of irrigated land area by county, basin, and statewide. Land irrigated at least once in California in 1979 was estimated to be 9.86 million acres, with an expected error of less than 1.75% at the 99% level of confidence. To achieve the same level of error with a ground-only sample would have required 3 to 5 times as many ground sample units statewide. A procedure for relatively inexpensive computer classification of LANDSAT digital data to irrigated land categories was also developed. This procedure is based on ratios of MSS band 7 and 5, and gave good results for several counties in the Central Valley

A digital global map of irrigated areas : an update for Asia

The Land and Water Development Division of the Food and Agriculture Organization of the United Nations and the Johann Wolfgang Goethe University, Frankfurt am Main, Germany, are cooperating in the development of a global irrigation-mapping facility. This report describes an update of the Digital Global Map of Irrigated Areas for the continent of Asia. For this update, an inventory of subnational irrigation statistics for the continent was compiled. The reference year for the statistics is 2000. Adding up the irrigated areas per country as documented in the report gives a total of 188.5 million ha for the entire continent. The total number of subnational units used in the inventory is 4 428. In order to distribute the irrigation statistics per subnational unit, digital spatial data layers and printed maps were used. Irrigation maps were derived from project reports, irrigation subsector studies, and books related to irrigation and drainage. These maps were digitized and compared with satellite images of many regions. In areas without spatial information on irrigated areas, additional information was used to locate areas where irrigation is likely, such as land-cover and land-use maps that indicate agricultural areas or areas with crops that are usually grown under irrigation. Contents 1. Working Report I: Generation of a map of administrative units compatible with statistics used to update the Digital Global Map of Irrigated Areas in Asia 2. Working Report II: The inventory of subnational irrigation statistics for the Asian part of the Digital Global Map of Irrigated Areas 3. Working Report III: Geospatial information used to locate irrigated areas within the subnational units in the Asian part of the Digital Global Map of Irrigated Areas 4. Working Report IV: Update of the Digital Global Map of Irrigated Areas in Asia, Results Map

A plot of one's own: gender relations and irrigated land allocation policies in Burkina Faso

Women in development / Gender / Land use / Land management / Policy / Female labor / Households / Irrigated farming / Social impact / West Africa / Burkina Faso / Dakiri

The Role of Irrigation in Determining the Global Land Use Impacts of Biofuels

In recent years there has been a flurry of activity aimed at evaluating the land use consequences of biofuels programs and the associated carbon releases. In this paper we argue that these studies have tended to underestimate the ensuing land use change, because they have ignored the role of irrigation, and associated constraints on cropland expansion. In this paper, we develop a new general equilibrium model which distinguishes irrigated and rainfed cropping industries at a global scale. Using the new model we evaluate the implications of land use change due to US ethanol programs, in the context of short run constraints on the expansion of irrigated cropland. Since irrigated area tends to offer a higher yield than its rainfed counterpart, this provides an upper bound on the change in cropland following biofuel expansion. We find that the biofuel-induced expansion in global cropland cover is about 16 percent larger when the irrigation constraint is imposed. This translates into a 21 percent increase in land use emissions due to US ethanol production. This estimate represents an upper bound, since irrigated area can be expanded over the medium run in many places around the world.Land Economics/Use, Resource /Energy Economics and Policy,

Can the Federal Reserve Bank’s Survey of Agricultural Credit Conditions Forecast Land Values?

The value of land dominates the financial structure of most American agricultural production firms, and land values are an important factor in long-term agricultural planning and risk management. As the primary source of collateral for farm loans, farmland values have significant implications for both producers as well as bankers financing agricultural loans. The Federal Reserve Bank of Kansas City’s Survey of Agricultural Credit Conditions is an expert opinion survey in which agricultural bankers provide land value forecasts. As the survey has drawn increased attention, the survey has drawn criticism regarding its use qualitative data to forecast land values. Our research examines the value of the survey data with respect to its ability to forecast movement in land values. Three techniques are used in the analysis. Interpreting the aggregate forecasts as probability estimates, Brier’s probability scores are used to evaluate aggregate bankers’ predictions. Next, turning points are evaluated using contingency tables. Finally, Granger causality tests are used to determine the dynamic relationship between land value predictions and actual land value changes reported by bankers. Bankers’ forecasts predict land values for irrigated and ranchland well, but non-irrigated forecasts were only marginally helpful in prediction non-irrigated farmland values. Forecasts provided in the survey may be beneficial, especially considering the scarcity of other publicly available data.farmland, forecasting, land values, Federal Reserve Bank, Agribusiness, Financial Economics,

Applications of digital image analysis capability in Idaho

The use of digital image analysis of LANDSAT imagery in water resource assessment is discussed. The data processing systems employed are described. The determination of urban land use conversion of agricultural land in two southwestern Idaho counties involving estimation and mapping of crop types and of irrigated land is described. The system was also applied to an inventory of irrigated cropland in the Snake River basin and establishment of a digital irrigation water source/service area data base for the basin. Application of the system to a determination of irrigation development in the Big Lost River basin as part of a hydrologic survey of the basin is also described

Diagnosis of Local Land-Atmosphere Feedbacks in India

Following the convective triggering potential (CTP)–humidity index (HIlow) framework by Findell and Eltahir, the sensitivity of atmospheric convection to soil moisture conditions is studied for India. Using the same slab model as Findell and Eltahir, atmospheric conditions in which the land surface state affects convective precipitation are determined. For India, CTP–HIlow thresholds for land surface–atmosphere feedbacks are shown to be slightly different than for the United States. Using atmospheric sounding data from 1975 to 2009, the seasonal and spatial variations in feedback strength have been assessed. The patterns of feedback strengths thus obtained have been analyzed in relation to the monsoon timing. During the monsoon season, atmospheric conditions where soil moisture positively influences precipitation are present about 25% of the time. During onset and retreat of the monsoon, the south and east of India show more potential for feedbacks than the north. These feedbacks suggest that large-scale irrigation in the south and east may increase local precipitation. To test this, precipitation data (from 1960 to 2004) for the period about three weeks just before the monsoon onset date have been studied. A positive trend in the precipitation just before the monsoon onset is found for irrigated stations. It is shown that for irrigated stations, the trend in the precipitation just before the monsoon onset is positive for the period 1960–2004. For nonirrigated stations, there is no such upward trend in this period. The precipitation trend for irrigated areas might be due to a positive trend in the extent of irrigated areas, with land–atmosphere feedbacks inducing increased precipitation

UTILIZATION OF VARIOUS METHODS AND A LANDSAT NDVI/GOOGLE EARTH ENGINE PRODUCT FOR CLASSIFYING IRRIGATED LAND COVER

Methods for classifying irrigated land cover are often complex and not quickly reproducible. Further, moderate resolution time-series datasets have been consistently utilized to produce irrigated land cover products over the past decade, and the body of irrigation classification literature contains no examples of subclassification of irrigated land cover by irrigation method. Creation of geospatial irrigated land cover products with higher resolution datasets could improve reliability, and subclassification of irrigation by method could provide better information for hydrologists and climatologists attempting to model the role of irrigation in the surface-ground water cycle and the water-energy balance. This study summarizes a simple, reproducible methodology using 30-meter resolution Landsat NDVI data for classifying irrigated land cover in semi-arid western Montana by leveraging the rising availability of machine learning algorithms in geographic information systems (GIS) software programs to compare results from models constructed using Decision Trees, Random Forest, and principal components analysis. Finally, this study was an attempt to subclassify irrigated land cover into a geospatial layer that distinguishes center pivot irrigation systems from other methods. The Random Forest model was the best model for classifying irrigated land cover, validating its recent use for classifying irrigated land cover in other studies. Further, the NDVI dataset that interpolates cloud and cloud shadow pixels with a user-specified climatology provided a time-series dataset with sufficient spatial and temporal resolution for time-series irrigated land cover classification at the basin and growing season scales. This dataset provides a viable alternative to coarse resolution products often used for creation of geospatial irrigated area datasets at larger scales and an opportunity to create small-scale irrigated area datasets that provide more detailed information. Finally, subclassification of irrigation by method was unsuccessful, but availability of small-scale evapotranspiration datasets and a time-series green index dataset without cloud contamination could improve models

How to manage salinity in irrigated lands: a selective review with particular reference to irrigation in developing countries

Irrigation management / Irrigable land / Soil salinity / Water use efficiency / Soil degradation / Irrigated farming / Policy making / Developing countries

The Global Crop Water Model (GCWM) : documentation and first results for irrigated crops

A new global crop water model was developed to compute blue (irrigation) water requirements and crop evapotranspiration from green (precipitation) water at a spatial resolution of 5 arc minutes by 5 arc minutes for 26 different crop classes. The model is based on soil water balances performed for each crop and each grid cell. For the first time a new global data set was applied consisting of monthly growing areas of irrigated crops and related cropping calendars. Crop water use was computed for irrigated land and the period 1998 – 2002. In this documentation report the data sets used as model input and methods used in the model calculations are described, followed by a presentation of the first results for blue and green water use at the global scale, for countries and specific crops. Additionally the simulated seasonal distribution of water use on irrigated land is presented. The computed model results are compared to census based statistical information on irrigation water use and to results of another crop water model developed at FAO