Irrigation Of Agricultural Land Research Articles

Reconstruction of the Subsurface of Al-Hassa Oasis Using Gravity Geophysical Data

Al-Hassa city, located in Eastern Saudi Arabia, boasts the world’s largest oasis and the most expansive naturally irrigated lands. Historically, a total of 280 natural springs facilitated significant groundwater discharge and irrigation of agricultural land. Furthermore, the water in certain springs formerly had a high temperature. The spatial variability of the water quality was evident. At the same time, Al-Hassa Oasis is situated on the northeastern side of the Ghawar field, which is the largest conventional onshore oil field in the world in terms of both reserves and daily output (approximately 3.8 mmb/d). The aforementioned traits suggest an intricate subsurface that has not yet been publicly and thoroughly characterized. Due to the presence of significant cultural noise caused by agricultural and nearby industrial activities, a robust, easy-to-use, and accurate geophysical method (gravity) was used to cover an area of 350 km2, producing the 3D subsurface model of the study area. A total of 571 gravity stations were collected, covering the whole Al-Hassa Oasis and parts of the nearby semi-urban areas. The gravity data were corrected and processed, and a 3D inversion was applied. The resulting 3D geophysical subsurface modeling unveiled an intricate subterranean configuration and revealed lateral variations in density, indicating the presence of a potential salt dome structure, as well as fracture zones that serve as conduits or obstacles to the flow of the subsurface fluids. This comprehensive modeling approach offers valuable insights into the subsurface dynamics of the broader study area, enhancing our understanding of its qualitative tectonic and hydraulic features and their impacts on the area’s natural resources, such as groundwater and hydrocarbons.

The Threat of Saltwater Intrusion on Rice Farming in Katingan I Lowland Irrigation Area, Central Kalimantan

The Katingan I Lowlands Irrigation Area (LIA) is one of tidal lowlands irrigation area in Central Kalimantan, Indonesia. Because the Katingan I LIA utilizes water from the estuary, the occurence of saltwater intrusion is likely to occur. Assessing water salinity due to saltwater intrusion provides essential information for farmers to manage water appropriately. In addition, this information can also be used by the government to develop policies and management strategies for Katingan I LIA. Saltwater intrusion that occurs when sea water flows into irrigation canals and agricultural land can lead to increased salinity. High salinity levels can affect agricultural productivity, especially in rice crops. Therefore, a thorough salinity study is needed to support the development of rice farming. This study aims to evaluate salinity levels due to saltwater intrusion and understand the factors affecting them. The study measured tidal (water level elevation), electrical conductivity (EC), and salinity data of the Katingan River and several locations in the primary and secondary channels. Data collection methods included continuous and instantaneous measurements using portable data logger installations and handheld devices. The existing water salinity conditions at Katingan I LIA obtained the maximum water salinity value from the three locations of 14,536 ppm and the lowest water salinity value of 3.02 ppm. The maximum water salinity value that enters the primary canal is 5,547 ppm, higher than the thershold salinity value for rice farming (5,120 ppm). Therefore, anticipatory measuers must be conducted to reduce salinity intrusion, such as optitmizing water channels, making water gates, and managing the water use efficiently. It is also recommended that measurements be carried out during the dry season to see the comparison of results and the magnitude of the maximum water salinity value that occurs because salinity problems occur more during the dry season

Mapping land-use and land-cover changes through the integration of satellite and airborne remote sensing data.

An integrated, remotely sensed approach to assess land-use and land-cover change (LULCC) dynamics plays an important role in environmental monitoring, management, and policy development. In this study, we utilized the advantage of land-cover seasonality, canopy height, and spectral characteristics to develop a phenology-based classification model (PCM) for mapping the annual LULCC in our study areas. Monthly analysis of normalized difference vegetation index (NDVI) and near-infrared (NIR) values derived from SPOT images enabled the detection of temporal characteristics of each land type, serving as crucial indices for land type classification. The integration of normalized difference built-up index (NDBI) derived from Landsat images and airborne LiDAR canopy height into the PCM resulted in an overall performance of 0.85, slightly surpassing that of random forest analysis or principal component analysis. The development of PCM can reduce the time and effort required for manual classification and capture annual LULCC changes among five major land types: forests, built-up land, inland water, agriculture land, and grassland/shrubs. The gross change LULCC analysis for the Taoyuan Tableland demonstrated fluctuations in land types over the study period (2013 to 2022). A negative correlation (r = - 0.79) in area changes between grassland/shrubs and agricultural land and a positive correlation (r = 0.47) between irrigation ponds and agricultural land were found. Event-based LULCC analysis for Taipei City demonstrated a balance between urbanization and urban greening, with the number of urbanization events becoming comparable to urban greening events when the spatial extent of LULCC events exceeds 1000 m2. Besides, small-scale urban greening events are frequently discovered and distributed throughout the metropolitan area of Taipei City, emphasizing the localized nature of urban greening events.

Random Forest Analysis of Exogenous Variables Impacting Rice Production in the Philippines

This research examines the relationship of rice production as the endogenous variable in a production function theory that considers key exogenous factors such as fertilizer consumption, irrigation water use, agricultural machinery, poverty rate, and agricultural land area. The study reveals the interdependencies shaping rice production in the Philippines. Applying the Cobb- Douglas function enhanced through the random forest regression algorithm establishes fertilizer consumption's focal role, focusing its essential impact on rice yields. Proper allocation of irrigation, access to agriculture machinery, poverty alleviation, and effective land use appear as significant contributors to overall production, defining 98% of the variability in rice production in random forests in both the in-sample and out-of-sample results. The findings emphasize the necessity for holistic strategies in agricultural planning, aiming for targeted interventions in fertilizer management, irrigation infrastructure, mechanized farming, poverty alleviation, and land-use.

STUDY ON THE USE OF AGRICULTURAL LAND IN THE NORTH-WEST DEVELOPMENT REGION OF ROMANIA BASED ON THE SOCIOLOGICAL SURVEY

The paper aims to present the situation of agricultural lands and the effects of their management on the sustainable development of agriculture in the North-West Development Region of Romania, at the level of 2023. The study is based on data taken through the sociological survey method based on a questionnaire, of a number of 276 respondents. The collected data were interpreted for the following indicators: the type of agriculture practiced, agricultural techniques applied, the involvement of agricultural farms in associative forms, the surface of agricultural land, irrigation of agricultural land, fragmentation of agricultural land, types of crops and the use of modern technologies for a digital agriculture. After analysing the data, it is observed that a predominantly conventional and mixed agriculture is practiced, using an average of 150 hectares per farm. Due to the large presence of arable land, the main crops are field crops, represented by cereals and fodder plants. Permanent crops represented in particular by permanent meadows are owned by the majority of farmers (87.3%), and horticultural crops are present in only 27.17% of farms. Modern technologies have a high potential in the development of the region and must be exploited more in the future.

Priority areas for the development of field fodder production in view of the climate crisis

This article covers the topical issue of the general impact of climate change on Ukrainian agriculture and on the field fodder production industry specifically, as well as the problems of adapting agriculture to modern environmental conditions. The authors set out to substantiate promising ways of developing modern field fodder production considering climate change. For this, the study employed the abstract-logical method, system analysis, methods of systematisation and classification, and a range of economic and statistical research methods (comparison, series of dynamics, method of structural groupings). Both negative and positive manifestations of the climate crisis in crop production were highlighted, and possible measures to counteract risks and ways to use potential opportunities to develop field fodder production given the impact of climate change were systematised. Particular attention was paid to the global practices of agriculture in the face of climate change, namely, the components of a climate-smart crop production system. The study also described the main promising measures of adaptation of field fodder production to climate change: irrigation of agricultural land, arrangement of snow retention systems in the fields, rainwater harvesting, selection and introduction of new varieties of fodder crops, effective crop rotation, increase in sowing of drought-resistant fodder crops, optimisation of agricultural technologies to reduce losses of fodder crops at the stages of harvesting and storage, application of organic farming, the latest soil fertilisation technologies and the use of nanotechnology in soil cultivation. The findings of this study can be used by managers of specific agricultural enterprises, as well as by advisory services and government agencies in the field of agricultural policy implementation.

Wastewater quality index (WWQI) as an indicator for the assessment of sanitary effluents from the oil and gas industries for reliable and sustainable water reuse

With the development of numerous industries, the increasing use of water resources and the discharge of pollutants into the environment, particularly industrial wastewater, has become extremely important. The purpose of this study was the assessment of sanitary wastewater treatment plants attributed to the oil and gas industries as reliable and sustainable water resources based on the wastewater quality index (WWQI). The findings revealed that the facilities under investigation effectively process and discharge their effluents following the Environmental Protection Organization's standards. Springtime has the maximum removal in wastewater treatment plants (WWTPs), with typical removal values of COD and BOD5 of 96.1% and 97.1%, while pH in the effluent of these WWTPs was 7.22, and DO in the range of 1–6.3 mg/L throughout this period. In addition, fecal coli removal efficiencies were 98.6%, respectively. Finally, the wastewater treatment system in the four refineries investigated has resulted in a considerable decrease in microbiological and organic pollutants in conformity with environmental regulations permitting wastewater reuse for irrigation and agriculture, as well as discharge into adsorption wells. However these treatment plants perform poorly in terms of cumulative and WWQI models (13.86–16.05), it is clear from the results and discussion of this research that the results of the treated wastewater from the under-investigation plants comply with the Environmental Protection Organization of Iran's standards required for discharge to surface water or reuse in agricultural land irrigation. Still, the treatment system should be constantly audited and improved to reach a higher rank according to the WWQI.

Bulanık Mantık Yaklaşımı Kullanılarak Kızılırmak Nehri Aylık Ortalama Akımlarının Tahmini

River flow values are used in the design and operation of hydraulic structures. Determining the correct flow value is important in terms of controlling water movements in the operation of hydraulic structures, irrigation of agricultural lands, hydroelectric production, environmental protection and flood control. In the literature, different methods are used to predict possible river flows using the available data. The fuzzy logic approach is a kind of intelligent system method used in solving problems involving uncertainty. The method has been widely used in the modeling of hydrological data for 2000’s. In this study, the fuzzy logic method was applied to estimate the flow data of Yamula Station on the Kızılırmak River in the Kızılırmak basin, one of the largest basins in Turkey. In addition to these flow station data, the monthly average temperature and monthly total precipitation data of the Kayseri meteorology station, which affects the station flows, were also used for modeling. Three different models were created for the flow estimates. In these models, temperature and precipitation data were selected as input values and river flow data were chosen as output values. In the models, 1982-2012 data of the stations were used. Model output data were tested with data set of 2013, 2014 and 2015. As a result, it has been seen that the fuzzy logic approach gave healthy results when both temperature and precipitation data were used as inputs.

First evidence of widespread, severe soil erosion underneath centre-pivot irrigation systems

Centre-pivot systems are widely used for irrigation in agriculture. However, excessive water application rates under low pressure centre-pivot systems can lead to soil erosion, which degrades soil structure and increases crop vulnerability to droughts. Although efforts have been deployed to measure soil erosion underneath individual centre pivots, a large-scale systematic assessment of extent and severity of soil erosion in centre-pivot irrigated fields is currently lacking. Here we used Google Earth™ satellite images to provide first evidence of widespread, severe soil erosion in centre-pivot irrigated agricultural land. We focused on the municipality of Cristalina (6154 km2), in the Brazilian Central Highlands, where centre pivots irrigate approximately 60,000 ha of cropland. The study area is in the Cerrado biome, which is one of the most important grain-producing regions in the world and Brazil's main centre-pivot irrigation area. By mapping erosion features under centre pivots, we found that 29 % of centre-pivot fields displayed signs of rill erosion, with individual rills up to a length of 1200 m. Most erosion features were identified during the dry season of the Brazilian Cerrado, which coincided with the period of greater satellite-image availability. Moreover, we found that compacted centre-pivot-wheel tracks often triggered rill incision and that eroding centre-pivot fields displayed higher slope gradients and were better connected to surface waters than the non-eroding fields. Ultimately, the frequent identification of severe erosion features in the centre-pivot fields during the dry season indicates that irrigation causes and/or aggravates soil erosion in Cristalina and likely in other parts of the Brazilian Cerrado. This first systematic evidence of widespread soil erosion underneath centre-pivot systems highlights that irrigation erosion is an important but neglected driver of land degradation, and that urgent action is required to protect affected soils for future generations.

Himalayan watersheds in Nepal record high soil erosion rates estimated using the RUSLE model and experimental erosion plots

The rising unpredictability in the food supply chain in many parts of the world is related to soil loss and poor agricultural output. The Revised Universal Soil Loss Equation (RUSLE), widely used for estimating soil loss, was applied in the western mid-hills in Nepal, with steep slopes and fragile geology. This region is at high risk for rapid soil erosion and mass wasting. To estimate soil loss, this study utilized the RUSLE model with experimental erosion plots in the Aadhikhola and Tinahukhola watersheds, capturing real-time erosion in the field. The annual soil loss for the Aadhikhola watershed is estimated at ∼41.4 tons ha−1 yr−1. In contrast, in the Tinahukhola watershed, soil loss is low (∼24.1 tons ha−1 yr−1). Although annual rainfall showed an increasing trend in both watersheds, the change in soil loss was statistically insignificant. The high erosion rates from the experimental plots in both watersheds support the model outputs. Results from the experimental plots recorded the rate of soil erosion for different land use as: irrigated agricultural land > rainfed agricultural land > forests. The trends highlight the role of human activities in enhancing soil erosion in these mountainous terrains in terms of medium to long-term perspectives. Therefore, sustainable agriculture practices in these terrains must investigate alternate ways to decrease soil erosion to support people's livelihoods.

Analysis of Cadmium (Cd) Heavy Metal Content in Mosambique Tilapia Fish (Oreochromis mossambicus) Derived from Rawa Taliwang Lake to Enrich Ecotoxicology Lecture Material in 2022

Rawa Taliwang Lake is used as a tourist spot, recreation, irrigation of agricultural land and fishing grounds by local fishermen. Increased community activity around the lake causes heavy metal pollution to enter the waters. The purpose of this study was to determine the levels of cadmium (Cd) in mosambique tilapia fish from Rawa Taliwang Lake thus enrich ecotoxicology lecture material and find out whether mosambique tilapia fish from Rawa Taliwang Lake is still safe for consumption based on the Food and Drug Control Agency (BPOM) Regulation No. 9 of 2022 concerning requirements for heavy metal contamination in food processing. Sampling used a purposive sampling method and analysis of cadmium using Atomic Absorption Spectrophotometer. The results showed that the concentration of cadmium heavy metal in mosambique tilapia fish 0,1977 mg/kg and it is still safe for consumption by the public because it still below 0,30 mg/kg. Suggested further research regarding analysis of metals in various types of fish and fish body tissues such as kidneys, liver and gills as a comparison.

Land Subsidence Susceptibility Mapping Using Interferometric Synthetic Aperture Radar (InSAR) and Machine Learning Models in a Semiarid Region of Iran

Most published studies identify groundwater extraction as the leading cause of land subsidence (LS). However, the causes of LS are not only attributable to groundwater extraction. Other land-use practices can also affect the occurrence of LS. In this study, radar interferometric techniques and machine learning (ML) models were used for the prediction, susceptibility zoning, and prioritization of influential variables in the occurrence of LS in the Bakhtegan basin. The LS rate was characterized by applying an interferometric synthetic aperture radar (InSAR). The recursive feature elimination (RFE) method was used to detect and select the dominant combination of indicators to prepare an LS susceptibility map. Three ML models, including random forest (RF), k-nearest neighbors (KNN), and classification and regression trees (CART), were used to develop predictive models. All three models had acceptable performance. Among the ML models, the RF model performed the best (i.e., Nash–Sutcliffe efficiency, Kling–Gupta efficiency, correlation coefficient, and percent bias metrics of 0.76, 0.78, 0.88, and 0.70 for validating phase, respectively). The analysis conducted on all three ML model outputs showed that high and very high LS susceptibility classes were located on or near irrigated agricultural land. The results indicate that the leading cause of land LS in the study region is not due to groundwater withdrawals. Instead, the distance from dams and the proximity to anticlines, faults, and mines are the most important identifiers of LS susceptibility. Additionally, the highest probability of LS susceptibility was found at distances less than 18 km from synclines, 6 to 13 km from anticlines, 23 km from dams, and distances less than 20 to more than 144 km from mines. The validated methods presented in this study are reproducible, transferrable, and recommended for mapping LS susceptibility in semiarid and arid climate zones with similar environmental conditions.

Evaluation of regression models' accuracy for estimating soil heavy metals content from topographic rectified satellite imagery (Case study: Irankouh from Iran)

Although the traditional approach is vital in environmental studies, satellite images have recently become one of the main tools for estimating soil pollution due to their advantages. Among sources of soil pollution, heavy metals (HMs) play a crucial role; in this regard, evaluating the soil contamination anomaly is indispensable due to an enormous number of HMs mines and agricultural land irrigation by industrial sewage in developing countries. Therefore, the main goals of this study are: to evaluate Landsat-8 image capability for estimating HMs content (Cr, Cd, Co, and AS) of the soil, performance evaluation of linear and nonlinear regression models, and topographic influence on the estimation accuracy of heavy metals. To do so, we applied multivariate-linear, partial least square, exponential regression, and neural network models to achieve a relation between the HMs content and soil spectral reflectance. Regarding the R2 value of models, the neural network demonstrated a more acceptable performance than other models. The results show that topographic correction improves the accuracy of HMs estimation; for example, the Minnaert model obtained the highest score (equal to 30.02), which is sufficient to support the preceding sentence. Furthermore, the neural network and Minnaert (with a score of 17.56) would produce the best results for estimating HMs content.

Growing Corn and Sugar Beets with Feedlot Effluent, Air Injection, and Subsurface Drip Irrigation System in Western Nebraska

As a state with the most irrigated agricultural land in the United States, Nebraska relies on freshwater resources for its irrigation. In addition to these conventional water sources, using nonconventional alternatives for crop production can be important during water shortage times. In this research, effluent from a feedlot lagoon was used as an irrigation water source at a subsurface drip irrigation (SDI) system for corn (C) and sugar beet (SB) production in western Nebraska during the 2019 and 2021 growing seasons. The objective of this study was to evaluate the effect of air injection on C and SB yield when using feedlot runoff as an irrigation source in a SDI system. Results indicated that air injection treatment (O), compared to noninjection treatment (NO), increased corn yield by 5.50% in the 2019 growing season, yet differences were not significant. During the 2021 growing season, O significantly increased corn yield by 9.17% (p = 0.04). Differences in irrigation water productivity (IWP) of NO (14.19±1.90 kg ha−1 mm−1) and O (14.86±1.79 kg ha−1 mm−1) were not significant during the 2019 growing season while significant differences in IWP of NO (22.61±5.88 kg ha−1 mm−1) and O (24.68±4.55 kg ha−1 mm−1) were observed during the 2021 growing season (p = 0.004). In sugar beets, no significant difference was observed in crop yield or sucrose yield between O and NO during both growing seasons. Differences in IWP were not significant during the 2019 growing season (NO: 0.10±0.02 kg ha−1 mm−1, O: 0.10±0.03 kg ha−1 mm−1) and 2021 growing season (NO: 0.10±0.04 kg ha−1 mm−1, O: 0.09 ±0.02 kg ha−1 mm−1).

From fallow ground to common ground: Perspectives on future land uses in the San Joaquin valley under sustainable groundwater management

Agriculture dominates California's San Joaquin Valley with over five million acres of farmland produces 400 different commodities ranging from nuts, tree fruits, vines, and row crops. During dry years agricultural production in the San Joaquin Valley uses about 53% of total applied water in the state. Implementation of California's Sustainable Groundwater Management Act (SGMA) will restrict groundwater pumping, likely reducing irrigated agricultural land use resulting in conversion to alternative land uses. To promote collaborative and inclusive efforts to repurpose agricultural land, California's legislature established a funding program administered by the Department of Conservation, the Multibenefit Land Repurposing Program (MLRP), in 2021. To ensure that land repurposing plans under the MLRP and SGMA represent San Joaquin Valley community needs this paper examines public perceptions of future land uses under SGMA through a phone survey. Respondents (n = 197) were recruited through a stratified random sample of mobile numbers registered within communities in the San Joaquin Valley classified as disadvantaged communities (DACs) (n = 32). Our results show that most respondents were somewhat (33%) or not at all (54%) familiar with SGMA, highlighting the need for outreach efforts to overcome barriers to representation, translation, and education about future water and land use decisions. Survey respondents identified secure water supplies (e.g., groundwater recharge) (35%) and less-water intensive agriculture (27%) as their top land use priorities to address groundwater overdraft under SGMA, indicating that the status quo for land use is preferred to alternative land uses. Preference for maintaining agriculture as primary land use (27%), we correlated with agricultural identity and lack of interest in community or global benefits such as schools and climate change mitigation. The findings from this study underscore the local variability in land use values and the importance to engaging local communities in land use decision-making, especially as they relate to changing current practices toward a more climate-resilient but agriculturally productive future with less land and less water.

Аналіз напрямів вивчення наслідків катастрофи на Каховській ГЕС та можливих сценаріїв їх вирішення

Another crime of the occupiers against the Ukrainian people was the blowing up of the dam of the Kakhovka hydroelectric power station, which took place on June 6, 2023, which was carried out in order to stop the advance of Ukrainian troops. The consequences of this man-made disaster were the shallowing of the Kakhovsky Reservoir, the water supply systems for the cooling ponds of the Zaporizhzhya NPP were destroyed, water shortages were caused in the Kherson, Zaporizhzhya, and Dnipropetrovsk regions, and the Black Sea was polluted by petroleum products. Along with the environmental and humanitarian catastrophe, the explosion of the Kakhovskaya HPP also led to an energy crisis, because Ukraine lost part of its water and energy capacity, as well as the ability to regulate the frequency and voltage in the power grid, and the water supply and irrigation of agricultural lands in the south of the country were disrupted. Today, the question of the expediency of reproducing the Kakhovskaya HPP remains relevant.

Arsenic and its management in soil

Arsenic (As) is a toxic metalloid and carcinogenic element that occurs widely in environment around the world. Arsenic is introduced into soil and water through geological (weathering of rocks and minerals) and anthropogenic pathways (mining, pesticides, fertilizers, timber treatment etc). Irrigation of agricultural land with As-contaminated groundwater or wastewater, particularly in India, Bangladesh and South-East Asia resulted in the accumulation of arsenic in both soils and plants posing risks to soil ecosystems and human health. Arsenic in soil and water exists in a different valence state, but predominantly as toxic As(III) and less toxic As(V) form. Arsenic toxicity is one of the most challenging problems in drinking water, as well as food crops (Samal et al., 2021). With greater public awareness of arsenic poisoning in animals and human nutrition, there has been growing interest in remediation technologies for mitigating As-contaminated ecosystems. Remediation of As-contaminated soil improves physical, chemical and biological approaches that may achieve either partial/complete removal of arsenic from soil and water. Many technologies like bioremediation, phytoremediation, soil mixing, soil washing, soil capping, filtration, adsorption and immobilization are used for arsenic removal from soil and water. Phytoremediation is a bioremediation process that uses various types of plants to remove, transfer, stabilize, and/or destroy contaminants in the soil and groundwater. But most of the arsenic still remains in the environment and there is always a risk of leaching caused by changes in the environmental conditions. Integrated approach involving a combination of physical, chemical and biological technologies is needed for the successful and effective management of As-contaminated environment.

An Algorithm to Detect Endangered Cultural Heritage by Agricultural Expansion in Drylands at a Global Scale

This article presents AgriExp, a remote-based workflow for the rapid mapping and monitoring of archaeological and cultural heritage locations endangered by new agricultural expansion and encroachment. Our approach is powered by the cloud-computing data cataloguing and processing capabilities of Google Earth Engine and it uses all the available scenes from the Sentinel-2 image collection to map index-based multi-aggregate yearly vegetation changes. A user-defined index threshold maps the first per-pixel occurrence of an abrupt vegetation change and returns an updated and classified multi-temporal image aggregate in almost-real-time. The algorithm requires an input vector table such as data gazetteers or heritage inventories, and it performs buffer zonal statistics for each site to return a series of spatial indicators of potential site disturbance. It also returns time series charts for the evaluation and validation of the local to regional vegetation trends and the seasonal phenology. Additionally, we used multi-temporal MODIS, Sentinel-2 and high-resolution Planet imagery for further photo-interpretation of critically endangered sites. AgriExp was first tested in the arid region of the Cholistan Desert in eastern Pakistan. Here, hundreds of archaeological mound surfaces are threatened by the accelerated transformation of barren lands into new irrigated agricultural lands. We have provided the algorithm code with the article to ensure that AgriExp can be exported and implemented with little computational cost by academics and heritage practitioners alike to monitor critically endangered archaeological and cultural landscapes elsewhere.

Irrigation water use driving desiccation of Earth’s endorheic lakes and seas

ABSTRACT Through 2019, the Caspian Sea excluded, the majority (54–60%) of Earth’s irrigation-impacted endorheic lake and sea (ELS) areal extent has been lost in basins that contain as much as 20% of global irrigated agricultural land. Estimates of irrigated agriculture contribution to ELS desiccation based on a steady-state water balance equation for endorheic basins generally agree that this contribution is on the order of 70–90% at the global scale. However, large uncertainties or errors in attribution – as large as 100% – are observed with respect to particular ELS, suggesting that attributions based on a single irrigated agriculture dataset, should be treated cautiously. The observed areal contraction in ELS attributed to irrigated agriculture corresponds to an estimated one-third decrease in ELS volume, excluding the Caspian Sea. Such volumetric decrease is expected to at least double solute concentration in 40–47% of Earth’s ELS.

Results of the study of the hydraulic ram technology of water lifting from watercourses

This paper is aimed at studying the hydraulic ram (hydram) technology of water lifting from watercourses for water supply of pastures and irrigation of agricultural land with improving the technological parameters of a hydram pump – increasing energy indicators: hydraulic shock pressure, supply, head, and efficiency, and increasing the reliability of its operation, creating convenience and ease of maintenance. The improved design and technological scheme of a hydram pump unit is substantiated, which has originality and is protected by the patent for the invention KZ No. 34,027, the patent holder is the non-profit joint-stock company “Kazakh National Agrarian University” (NJSC KazNAU). Formulas for substantiating the technological and technical parameters of a hydram pump are proposed, the reliability of which is confirmed experimentally. The purpose of the study is to develop an alternative technology for lifting water from watercourses using a hydraulic ram pump, to substantiate the main technological and technical parameters with improved indicators compared to analogues – increasing hydraulic shock pressure, supply, head, efficiency and improving the reliability of operation, creating convenience and ease of maintenance. The following research methods were used in the study: patent with an operability review, theoretical and experimental approaches. As a result, the obtained theoretical formulas were experimentally confirmed. Based on the results of patent research, operability review, and own research at NJSC KazNAU, an improved design and technological scheme of a hydram pump has been developed. The design and technological scheme of an improved hydram pump unit is given. Based on a comparative analysis of the characteristics of the new hydram pump and its analogue, a clear advantage of the new pumping unit has been established.