Dynamics of the Condition of Reclaimed Agricultural Lands in the Russian Federation

Abstract

Water reclamation contributes to a guaranteed increase in the yield of agricultural lands and can also negatively affect the quality of the land. Technical malfunction of reclamation systems, outdated reclamation technologies, poor water quality, and untimely drainage may result in such negative processes as resalting and bogging. In Russia, state monitoring of reclaimed lands is carried out annually and obtained data are used to identify soil degradation and pollution to fix the problems at the appropriate times. The Russian economic crisis at the end of the last century affected the state of the reclaimed lands. The authors have analyzed the reclamation state of agricultural lands in all constituent entities of the Russian Federation for the period between 2010 and 2020. The entities have been classified according to the reclamation state of lands located within their territories. The authors have evaluated the structural changes over the past decade and analyzed their causes. The research results can help solve the problems of federal and regional management of reclaimed lands. They are also applicable to solving the problems of choosing priority areas of investment policy to preserve soil fertility.

1. Introduction

According to the official data of the State Report on the State and Use of Lands in the Russian Federation, as of 1 January 2020, the total area of agricultural lands is 381,673 thousand hectares; 58% of them are agricultural lands. The most significant part belongs to arable land (59%), 29% are pasture fields, 9% are hayfields, 2% and 1% are occupied by grasslands and plantations. Land reclamation can provide a guaranteed increase in crop yields and prevent crop loss through irrigation or drainage of excess water by drainage systems.

State monitoring of reclaimed lands is a part of the state monitoring system of Russia. Based on this monitoring, any changes in reclaimed lands are identified and evaluated. Federal state budgetary institutions for land reclamation and agricultural water supply annually submit cadastral forms of rates for assessing the land reclamation condition and the technical condition of reclamation systems to the Ministry of Agriculture of the Russian Federation. Manufacturers of agricultural products provide information on the areas of land to be reclaimed through reclamation activities. The Land Reclamation Cadastre of Russia is annually updated according to the collected data. In the future, the collected data serve to identify soil degradation and pollution to rectify them in a time [1].

The following factors are monitored on the irrigated lands: groundwater level, groundwater and irrigation water salinity, the degree of soil salinity in the 0–100 cm layer, the degree of soil alkalinity, the number of flooded settlements. The following factors are monitored on the drained lands: groundwater level, the timing of the excessive groundwater and surface water removal in single-acting systems, the required drainage rate, and humidity of the root zone during dry-weather vegetation period in double-acting systems. A comprehensive assessment of above-mentioned factors distinguishes the land reclamation state as good, satisfactory, or unsatisfactory.

The economic crisis of the late 20th century in Russia and changing ownership forms affected the state of the reclaimed land and the efficiency of its use. An analysis of the current state of reclaimed land shows that the degradation in the engineering state of irrigation and drainage systems is related to the wastage of a large portion of the fixed assets [2]. In agricultural production, only 7068.327 thousand hectares of reclaimed land, which corresponds to 75% of their area, are used for growing crops. Considerable underfunding led to a decrease in the technical state of irrigation and drainage systems in Russia. It negatively affected the land reclamation state. The degradation of agricultural lands in the non-chernozem belt of the Russian Federation is largely connected to the unsatisfactory state of reclamation systems [3].

Today, 3820.561 thousand hectares are irrigated in Russia, corresponding to 82% of the total irrigated area. Heavy equipment deterioration, rising prices for energy resources, and reclamation equipment resulted in transferring a significant part of irrigated land to rainfed lands [4]. Part of the irrigated land is inoperative due to bogging. The unsatisfactory technical condition of irrigation systems on the territory of arid regions led to the resalting of lands due to excessive irrigation, water application without proper drainage, poor quality of irrigation water state, and the exploitation of rice systems on naturally saline lands. The problem of degradation of irrigated lands is a long-term problem of the Aral basin where the irrigation of cotton fields with water of poor quality and ineffective drainage cannot provide soil desalinization in oases [5]. In the Republic of Kalmykia, out of 6264 thousand hectares of agricultural lands, 94 thousand hectares are bogged up and 2505 thousand hectares are salinized [6]. Natrium salinization of soils associated with insufficient quality of irrigation water occurs in Western Siberia [7].

Intensive resalting and bogging during irrigation reclamation are problems in many countries that produce agricultural products in arid regions. According to analysts, yield losses in arid regions due to soil salinity can range from 18–26% to 43% [8]. Processes of carbonate soil salinization on large reclamation systems have been recorded for a long time in Romania [9]; bogging arose during the new lands reclamation in the Nile Delta in Egypt [10]. Currently, Iraq is taking key measures to control salinization and bogging of irrigated lands [11]. The issues of reconstruction and restoration of reclamation systems are relevant for Ukraine [12]. In India, due to a decrease in the productivity of irrigated agriculture, measures to increase agricultural production on rainfed lands are being taken at the country level [13].

Due to a malfunction of the drainage network and a poor agroecological condition of soils (close groundwater level, poor water-physical and agrochemical quality of soils), at the beginning of 2020, 3,247,766 thousand hectares of agricultural lands amounting to 68% of the drained land area were drained in Russia. Drainage systems of the Leningrad region require renewal and monitoring [14]. To solve the problems of federal and regional management of the fund of reclaimed lands, choosing priority areas of investment policy, and the preservation of soil fertility, there should be a generalized classification of the constituent entities of the Russian Federation according to the reclamation state of agricultural lands.

2. Methods

The study material is an array of official statistical data on the land reclamation state of the Russian Federation for the period from 2010 to 2020 taken from Appendix 6 to the National Report “On the State and Use of Lands in the Russian Federation”.

Depending on the regions’ natural and climatic conditions and specialization, reclamation activities are carried out on the territory of 79 regions of the country to ensure the sustainability of agricultural production. According to the official data, at the beginning of 2020, there were 9446.032 thousand hectares of reclaimed farmlands in Russia, 4664.595 thousand hectares of them irrigated, and 4781.437 thousand hectares drained. Six constituent entities of the Russian Federation only provide drainage of agricultural lands, while fifteen entities carry out irrigation reclamation. On the territory of other regions, both drainage and irrigation reclamation are carried out to ensure a guaranteed harvest.

The share of ameliorated land in the total area of agricultural lands differs significantly across federal districts. The ratios of irrigation and drainage reclamation are also different (Figure 1).

For example, today, in the Northwestern Federal District, 26.7% of agricultural lands is drained, and only 0.2% is irrigated. In the North Caucasus Federal District, 8.1% of agricultural lands is irrigated, and 0.2% is drained. In the Urals Federal District, 0.7% of agricultural lands is irrigated, and 0.9% is drained. In Russia nationwide, the share of ameliorated agricultural lands is 4.3%, of which 2.1% is irrigated, and 2.2% is drained.

Research methods are structural data analysis and multidimensional data analysis methods, particularly cluster analysis. Cluster analysis is widely used in land administration tasks as it is one of the key methods of the decision support system for solving land management problems in Hungary [15]. Using Ward’s method and the k-means method, the authors have analyzed the development of land relations in Ukraine’s regions [16]. Various types of agricultural landscapes and their spatial distribution in Brandenburg, Germany, were determined using a two-stage cluster analysis [17]. The fuzzy and k-means methods were used to solve the problems of structuring agricultural lands by product types in Indonesian regions [18].

Scientists widely use multidimensional statistical methods to estimate temporal and spatial changes in complex water quality datasets. They also use the dominant component analysis and cluster analysis to solve water management problems in urban, rural, and industrial areas in the municipality of Campo Grande in Brazil [19]. Cluster analysis is applied to classify water catchments by land use classes in the upper transborder catchment of the Nisa River [20]. As part of other multidimensional analysis methods, cluster analysis is used to assess temporal and spatial variations in water quality in the Fuji and Kuban river basins [21,22]. Effectiveness comparison of the cluster, factor, and discriminant analysis in relation to water quality monitoring data of the Gomti River (the main tributary of the Ganges River, India) substantiated the possibility of creating a monitoring network [23].

The authors present a method for classifying Russian Federation entities. The method is based on the general estimation of agricultural lands condition located all over their territory. The total surface of the entity reclaimed lands is presented by irrigated and drained agricultural lands.

The authors used a k-means method for clusterization. The method relates to the iterative classification methods. Initially, three clusters were set, and their elements correspond to the general estimation of agricultural lands condition. In the first cluster, the reclaimable condition of agricultural land is estimated as “good”, the second cluster as “satisfactory”, third—“unsatisfactory”. During the classification, the entities were grouped according to the “maximum similarity inside the cluster (minimal in-group dispersion) and maximum differences among clusters (maximum intergroup dispersion)” rule.

Each entity was described with the set of quantitative variables type X1, X2, X3. To evade the standardization of the variables, the original array of the reclaimed lands surface in each entity was detailed according to the reclaimable land condition (good, satisfactory, unsatisfactory), and each element of the array was converted into fractional relations depending on:

$$x_{ij}=\frac{S_{ij}}{S_{j\mathsf{\Sigma }}}$$

(1)

where j—is a number of the entity (j = 1.79); i—index according to the reclaimed land condition (i = 1 if “good”, i = 2 if “satisfactory”, and i = 3 if “unsatisfactory”); S_ij—the total surface of j—reclaimable lands entity, according to the estimation of the reclaimable condition i; S_j∑—the total surface of j-entity reclaimed lands.

The authors have also classified the entities according to the reclaimable land condition in general and the reclaimable condition of irrigated and drained lands. To estimate the dynamics of lands condition, the entities were clustered based on data from 1 January 2010 to 1 January 2020.

3. Results and Discussion

The dynamics of reclaimed agricultural lands condition from 2010 to 2020 in Russia is presented in

Table 1. Condition dynamics of reclaimable agricultural lands in Russian Federation.

	1 January 2010 (thous·ha)	1 January 2020 (thous·ha)	2020 to 2010 (%)
total surface of reclaimable agricultural lands	9032.80	9045.38	0.1%
Total surface of irrigated agricultural lands	4237.10	4263.943	0.6%
Reclamative condition of irrigated agricultural lands
good	2008.20	2252.50	12.2%
satisfactory	1141.20	1139.728	−0.1%
unsatisfactory	1087.70	871.714	−19.9%
Total surface of drained agricultural lands	4795.70	4781.437	−0.3%
reclamative condition of drained agricultural lands
good	878	924.338	5.3%
satisfactory	2380.20	2204.45	−7.4%
unsatisfactory	1537.50	1652.649	7.5%

. For the last eleven years, the surface of reclaimed agricultural lands didn’t change: the surface of irrigated lands increased by 0.6%, the surface of drained lands decreased by 0.3%. The reclaimed land condition has significantly changed. In the system of irrigated lands, the part of lands with good reclaimable condition increased by 12.2%, the part of satisfactory and unsatisfactory condition lands decreased by 0.1% and 19.9%. In the system of drained lands, the part of agricultural lands with good reclaimable condition increased by 5.3% when satisfactory and unsatisfactory condition lands part decreased by 7.4% and 7.5%.

The authors have carried out the cluster analysis of the reclaimable condition of agricultural lands in separate entities of the Russian Federation using the STATISTICA software pack. They have used the primary sorting of the distances between the objects and have chosen the observed constant intervals. Euclidian distance between the clusters is a geometric distance in the multi-dimensional space and characterized the grade of interaction between the objects in cluster analysis. The quality of each group is checked with the inequality dispersion hypothesis between the clusters and inside the clusters using the F-criterion (Fisher’s criterion). The level of importance for each cluster was way less than 0.05. Each of the suggested classifications is to be correct. Mean values for each cluster are presented in Figure 2 (the part of agricultural lands surface of a particular reclaimable condition to the total surface of reclaimed lands).

Mainly “good” reclaimed land condition corresponds to Cluster 1, “satisfactory”—Cluster 2, “unsatisfactory”—Cluster 3. The reclaimed land condition in Russian Federation entities is classified as of January 2010 and January 2020. Figure 3 presents the numbers of entities in clusters.

For eleven years, the number of entities where the “good” reclaimable condition in lands dominated has increased. Simultaneously, the number of entities in clusters with “satisfactory” and “unsatisfactory” reclaimed lands condition has decreased. The changes in the number of entities among cluster distribution happened. While in 2010, 45% of the entities with reclaimable lands entered the “satisfactory” cluster by their reclaimable condition, in 2020 43% of the entities recorded the “good” condition of their reclaimed lands.

During the analysis of irrigated lands condition, these values changed from 38% to 52%, for drained lands from 25% to 35%. The presented positive changes occurred due to the implementation of the Federal target program “Development of land reclamation of agricultural lands in Russia for 2014–2020”.

The number of included entities in clusters in 2010 according to the irrigated and drained lands was different. The territory of 38% of the reclaimed lands was estimated as “good”, 32% as “satisfactory”, and 30% as “unsatisfactory”. For drained lands—25%, 40% and 35%. The differences in the total amount of clusters for irrigated and drained lands remained the same in 2020. According to the condition of drained lands, 52% of the entities got into the “good” cluster, 28%—“satisfactory”, 20%—“unsatisfactory”. For drained lands in 2020, the number of the entities in clusters is less optimistic: 35% of the entities relate to the “good” reclaimed land condition cluster, 37%—“satisfactory”, 29%—“unsatisfactory”.

Table 2. Russian Federation’s entity classification of farmland reclamative condition.

Cluster 1 “Mostly Good Condition”	Cluster 2 “Mostly Satisfactory Condition”	Cluster 3 “Mostly Unsatisfactory Condition”
Irrigated cultural lands
Belgorod Region Bryansk Region Voronezh Region Kaluga Region Kursk Region Lipetsk Region Yaroslavl Region Republic of Adygea Krasnodar Region Volgograd Region Rostov Region Republic of Ingushetia Karachay-Cherkess Republic Republic of North Ossetia-Alania Stavropol Region Republic of Bashkortostan Republic of Mordovia Chuvash Republic Perm Krai Nizhny Novgorod Region Orenburg Region Penza Region Samara Region Saratov Region Chelyabinsk Region Altai Republic Tyva Republic The Republic of Khakassia Altai Region Irkutsk Region Kemerovo Region Novosibirsk Region Omsk Region Tomsk Region Kamchatka Krai Primorye Krai Amur Region	Vladimir Region Ivanovo Region Oryol Region Ryazan Region Tambov Region Tver Region Tula Region Leningrad Region Novgorod Region Kabardino-Balkar Republic Mari El Republic Republic of Tatarstan UdmurtiaKirov Region Ulyanovsk Region Kurgan Region Sverdlovsk Region Krasnoyarsk Region Republic of Buryatia Jewish Autonomous Region	Moscow Region Smolensk Region Vologda Region Kaliningrad Region Pskov Region Republic of Kalmykia Krasnodar Region The Republic of Dagestan Chechen Republic Tyumen Region Republic of Sakha (Yakutia) Trans-Baikal Krai Khabarovsk Region Magadan Region
Drained agricultural lands
Belgorod Region Bryansk Region Voronezh Region Kostroma Region Lipetsk Region Smolensk Region Murmansk Region Pskov Region Republic of Adygea Krasnodar Region Rostov Region Republic of North Ossetia-Alania Republic of Bashkortostan Republic of Mordovia Perm Krai Nizhny Novgorod Region Penza Region Altai Region Irkutsk Region Omsk Region Primorye Krai Amur Region	Ivanovo Region Kaluga Region Kursk Region Oryol Region Yaroslavl Region Arkhangelsk Region Vologda Region Kaliningrad Region Novgorod Region Republic of Tatarstan Udmurt Republic Kirov Region Ulyanovsk Region Kurgan Region Sverdlovsk Region Tyumen Region Kemerovo Region Novosibirsk Region Tomsk Region Republic of Buryatia Kamchatka Krai Sakhalin Region Jewish Autonomous Region	Vladimir Region Moscow Region Ryazan Region Tambov Region Tver Region Tula Region Republic of Karelia Komi Republic Leningrad Region Mari El Republic Chuvash Republic Chelyabinsk Region The Republic of Khakassia Krasnoyarsk Region The Republic of Sakha (Yakutia) Trans-Baikal Krai Khabarovsk Region Magadan Region

presents the details of distributing the entities to clusters as of 1 January 2020.

The analysis of the changes inside the cluster system has shown the efficiency of repairing and technical reconstruction of reclaimable systems in regions. Compared to the year 2010, 16 entities of the Russian Federation show an increase in reclaimed lands condition, while four entities demonstrated the deteriorated condition. For eleven years, 26 entities remained in the “good” condition, 14 entities—“satisfactory”, 11 entities—“unsatisfactory”. During the analyzing period, the reclaimable condition of drained lands in 12 entities significantly improved, in 6 entities—decayed. “Good” and “satisfactory” drained lands condition remained the same in 15 and 13 entities. In 13 entities, the reclaimable condition of drained agricultural lands still can be categorized as “unsatisfactory”.

Efficient use of agricultural lands requires improving productivity and soil quality in Russia [24]. In April 2021, the government of the Russian Federation adopted the “State Program for the effective involvement of agricultural lands in the turnover and the development of the reclamation complex”. The program claims to provide a moisture regime of irrigation systems on 1353.5 thousand hectares surface and prevent the withdrawal and preservation of reclaimed lands on the surface of at least 3686.6 thousand hectares.

The program provides the implementation of applied scientific research and large investment projects. To combat soil salinization, it is necessary to use the accumulated world experience: to apply progressive technologies of irrigation and drainage on reclamation systems, resource-saving methods of agricultural production, to use phytoremediation and bioremediation methods for soil and wastewater treatment in regions with favorable natural and climatic conditions [25,26].

4. Conclusions

To generally estimate the state of reclaimed lands within each constituent entity of the Russian Federation, the authors have proposed to use the aggregate of the proportional ratio of land surface types that are in an “unsatisfactory”, “satisfactory”, and “good” reclaimable condition.

As a result of the application of cluster analysis, all entities of the Russian Federation, on whose territory the reclamation systems are located, are divided into three clusters with a generalized assessment of “good”, “satisfactory”, and “unsatisfactory” land condition.

The RF constituent entities have been classified by the amount of irrigated lands, drained lands, and reclaimed lands in general, according to official statistics data for 2010 and 2020. The statistical quality of each group was checked at the 5% significance level, and the classification is accepted to be correct.

The results obtained can be used in solving the problems of managing the fund of reclaimed lands at the federal and regional levels.