English

Water Accounting Plus for Water Resources Reporting and River Basin Planning

The financial and economic mechanism of balanced use of natural resources includes a wide specification of environmental, organizational, economic and financial instruments. The author's vision of the multi-vector nature of the ecological and economic assessment of water resources is outlined, which is a comprehensive approach to the analysis of the use and management of water resources for making informed decisions with the determination of priorities for Ukraine. It is substantiated that formation of fundamental scientific bases for the evaluation of water resources of Ukraine should be based on the use of ecological and economic approaches, in particular: ecological dimension, economic analysis, social dimension, technical analysis, legal and regulatory context, risk analysis, climate change analysis, water infrastructure projects, water conflict management, environmental impact monitoring and assessment, alternative scenarios. A study of publicly available data on the assessment of the use of water resources of Ukraine was conducted. Based on the results of the study, we proposed the structure of a multi-vector model of the tools of the ecological and economic mechanism of water resources assessment, which is systematized according to interrelated instrumental blocks: ecological dimension — assessment of the impact of any water projects or activities on natural ecosystems, aquatic biological resources, and water quality; economic analysis — consideration of economic indicators; social dimension — assessment of the impact of projects on society; technical analysis — analysis of technical solutions, engineering aspects and technological parameters of water projects; legal and regulatory context — consideration of relevant legislative and regulatory requirements; analysis — risk assessment of possible risks and development of strategies for their management. The ecological and economic approach helps ensure balanced use of water resources, taking into account the needs of humanity and the requirements of the environment. On the basis of the multi-vector nature of the ecological and economic assessment of water resources, recommendations on environmental protection, optimal use of resources, social impact of projects, risk management strategies and other important aspects can be provided. The author's approach to theoretical-methodological approaches and methodological provisions regarding the formation of a model of tools for the ecological-economic mechanism of water resources assessment, the effective influence of which is aimed at balancing the ecological, economic and social components of the use of water resources of Ukraine, is proposed. It is substantiated that the functioning of multi-directional tools of the ecological and economic mechanism will ensure both greening and increasing the economic and social effectiveness of the use of water resources, the consolidation of management aspects around strategic tasks and priorities determined by the Basic principles of the state environmental policy of Ukraine for the period up to 2030.

Efficient and sustainable utilization of resources, particularly land and water resources for agriculture have occupied the centre stage in the economic agenda of a nation. The regional resource availability and the biotic, abiotic and socio-economic constraints are largely varied in the any crop production system of that region. The integration of sustainable resource use with the production programs and income as objectives of farming thus, leads to a multiple objective-planning framework. Attaining sustainable increase in agriculture production by considering the biophysical variability of the region without affecting the natural resources base is therefore very important to achieve food security for the growing population in a developing country situation. The current study is to develop appropriate land use pattern in crop agriculture for sustainable land and water use to the agricultural development in the Bavani Basin of western zone of Tamil Nadu state in southern India, using a multiple goal linear programming approach. Bhavani basin in the western zone of Tamil Nadu - one of the most diversified in bio physical features, was evaluated in this study. The land use model employed in the study following the bio-economic model by Shiferaw and Holden, (2003) who incorporated the important variations in the biophysical system (land and soils) and market characteristics. This study traced the alternative cropping pattern which would maximizes the farm net income at a relatively lower water requirement, lower land requirement (hectare days to ensure relatively more fallow period to lower land exhaustion rate) and that would lower the environment damage in-terms of lower Environmental Impact Quotient (EIQ) with the given land and ground water availability of each identified ten homogeneous land units beside the length of growing period determined on the basis of quantum and distribution of rainfall and temperature. The major biophysical factors considered beside the land availability, ground and surface water availability were; crop suitability for the particular soil type, crop sequence and climatic variations and these factors were specified as constraints in the land use model. The input data for the model were collected from the sample respondents in the delineated homogeneous land units. The actual water availability for each standard week (t) was estimated after adjusting the effective rainfall received during the period of crop stand from the total water requirement of each crop activity. The land use model estimates revealed the possibility of increasing the crop income from the current level of INR 6.14 billion to INR 8.25 billion annually. This alternative crop plan also helped to reduce the area under high water consuming crops in water deficit areas.

Prospective changes in irrigation water requirements caused by agricultural expansion and climate changes in the eastern arc mountains of Kenya

Urgency of the research. Full and effective use of the potential of land resources as one of the competitive advantages of agricultural production. Target setting. Effective and rational use of land resources is of great importance for the national economy of Ukraine. Actual scientific researches and issues analysis. Specifics of the effective use of agricultural lands were studied by such scholars as Balayev A. D., Balyuk S. A., Hrekov V. A., Krymska L. O., Koval M. V., Medvedev V. V., Melnychuk L. S., Tarariko O. H. and others. Uninvestigated parts of general matters defining. Scientists do not adequately cover the issue of structuring the problems of increasing the efficiency of agricultural land use. The research objective. The article is intended to identify and structure the main issues, the effectiveness of the use of agricultural land and determine the ways of their solution. The statement of basic materials. The article considers and structures the issues of efficient use of agricultural land in Ukraine. The influence of ecological and economic factors on the efficiency of land resources use negatively affecting the quality and fertility of the land is analysed. Conclusions. Effective use of land resources provides for the creation of a material base for ensuring the conservation, reproduction and further increase of the level of economic return of land.

Ethiopia is a growing country which is in need of scientific ground for land use planning and agricultural-based economy. Evaluation of land use/land cover (LULC) changes helps for proper scheduling and use of natural resources with safe administration in accordance with time and dynamic population growth of the country, specifically in the study area. One of the detailed and useful ways to develop land use evaluation and classification maps is the use of geospatial techniques such as remote sensing and geographic information systems (GIS). The main focus of this study is to evaluate the dynamics of land use and land cover (LULC) changes in the Abelti Watershed, Omo-Gibe River basin, Ethiopia. Maximum likelihood algorithm approach supervised classification method was used for identifying the LULC changes using satellite data to know LULC changes in the watershed. Quantifications of spatial and temporal dynamics of land use/cover changes were accomplished by using three satellite images of 2000, 2010, and 2017 and classifying them via a supervised classification algorithm by using Earth Resources and Development System (ERDAS) software and finally applying the postclassification change detection technique was performed by using ArcGIS 10.3. From the LULC analysis, the increase was observed in the agricultural area and settlement area from 2000 to 2017. On the other hand, shrub land followed a declining trend during the study period. However, forest and bare land followed variable trends during the study period in which forest declined from 2000 to 2010 but increased from 2010 to 2017 and bare land increased from 2000 to 2010 and declined from 2010 to 2017. Generally, the driving force behind this change was population growth, rapid urbanization, and deforestation which resulted in a wide range of environmental impacts, including degraded habitat quality in the watershed.

As one of the last agricultural frontiers of the humid tropics, Amazonia is the largest area of the world currently undergoing frontier settlement. Although the earliest intrusions of foreign populations into Amazonia date from pre-Hispanic times, the large-scale entrance of peasant colonists into the vast region is a recent phenomenon. Much of this movement represents the spontaneous migration of peoples, but governments in the region have also become increasingly interested in opening up and integrating Amazonia to national and international economies. These actions are frequently seen as potential solutions to a number of national problems, including the need to increase agricultural production, correct spatial imbalances in the distribution of population, exploit frontier lands for reasons of national security, and defuse potentially serious political problems resulting from the existing agrarian structure, landlessness, and unemployment. The upper basin of the Amazon in Ecuador, bordering on the eastern slopes of the Andes, is one such area of frontier settlement. Recent decades have witnessed the rapid conversion of these Amazonian forests to agricultural uses through a series of schemes bearing such labels as land development and colonization. Most forest intervention in the region has come at the hands of colonist farmers attempting to establish land claims along transport routes originally constructed to aid in petroleum exploration and exploitation. These are farmers who formerly have made a living in long-established farmlands and who, for various reasons (population pressures, pervasive poverty, maldistribution of farmland, lack of inputs for intensive cultivation, lack of nonagrarian livelihood opportunities, and generally inadequate rural development) have been increasingly squeezed out of their homelands. A marginal person by virtue of his low socioeconomic and political status, the farmer often perceives

The Cerrado is the most biodiverse savanna in the world, with a high rate of endemism and the provision of essential ecosystem services. Currently, the Cerrado presents a wide range of land uses and is constantly affected by land-use conversion due to its high agricultural productive potential. Among these uses, silvopastoral systems (SPS) with native trees stand out as an alternative model that integrates local biodiversity with economic practices of natural resource use. This research aims to clarify the current status of these systems and assess their economic, productive, and social potential in the Cerrado of northern Minas Gerais. In Chapter 1, we assessed the economic performance and sensitivity of the three main land uses in the region: agriculture, silvopastoral systems with native trees, and Eucalyptus plantations, with different sample sizes. For each system, we calculated gross margin and profitability indicators, considering income and both fixed and variable costs. Sensitivity analysis was conducted using a Monte Carlo simulation and a Random Forest model. The results revealed statistically significant differences in cost structure, income composition, and profitability across systems. Eucalyptus plantations showed the highest average profitability and the lowest economic risk, although they are highly dependent on external inputs (hired labor, market access, and infrastructure). SPS presented intermediate performance, with lower variable costs and potential ecological co-benefits, although their productive and commercial remains underutilized. Agriculture, primarily family-based and subsistence-oriented, showed the lowest profitability due to high fixed costs and limited market integration. Family labor was the main fixed cost component in both agriculture and SPS, strongly influencing the economic results. Despite the differences, low-risk farms were identified across all land uses, suggesting that profitability is achievable under supportive conditions. These findings underscore the importance of specific public policies that promote financial planning, technical assistance, and diversification of income sources in each land use. In Chapter 2, we investigated which productive, environmental, socioeconomic, technical, and farm-related factors influence the adoption and intensification of SPS with native trees. Based on interviews conducted with over 100 farmers, we used the Seemingly Unrelated Regressions (SUR) model, estimated through the Full Information Maximum Likelihood (FIML) method. Three equations were developed to assess the adoption of SPS, the intensification of its use through the generation of products, and the commercialization of these products. We found that 12 variables, distributed across the five groups of factors, influence the adoption and intensification of SPS differently. Water availability for production and the presence of family labor are key factors for intensification, although they do not directly affect adoption. In contrast, the age of farmers and their environmental awareness impact adoption but not intensification, often associated with older and more environmentally conscious farmers. Variables such as the total number of land uses and currently productive land uses positively affect all equations, while the distance between the farmer’s residence and the productive area has a negative effect. Based on these findings, we propose public policies targeting two groups, adopters and non-adopters, so that efforts to promote SPS with native trees focus not only on increasing adoption but also on intensifying its use. In Chapter 3, we investigated the NTFP market through interviews with traders located in the study region and major urban centers of the Cerrado in Minas Gerais. Using K-means clustering, we identified three market segments: small-scaled, medium-scaled, and large-scaled. The small-scaled market is characterized by low product diversity, predominantly unprocessed goods, and is found in municipalities with smaller populations, resulting in a more limited market. The medium-scaled market has the highest proportion of processed products and is present in the main municipalities of the study region but still has limited product diversity and volume. The large-scaled market includes traders located in large urban centers and the most populous municipality of the region, with higher commercialization levels, diverse suppliers, and a broad variety of products and species. Despite these differences, certain products such as pequi (Caryocar brasiliense) are found across all market segments, highlighting their commercial relevance. At the same time, each segment includes exclusive products, indicating a specialization in supply. The NTFP market context reveals a high economic and productive potential, particularly relevant for farmers who adopt SPS with native trees, given the variety of market scales and products identified. Keywords: land use; rural sustainability; non-timber forest products; economic analysis; farmers’ decision-making ; family farming; value chains; agroforestry systems; climate adaptation; productive diversification

This paper provides an overview of planning requirements, including regulatory, and implementation approaches for achieving ecologically sound reclamation and restoration of mines upon closure in the USA. Mine closure includes mined-out areas, decommissioning of plants and structures, and appropriate monitoring of post-mining land, water, and air resources. Although the discussion provides general guidelines, each mine closure site presents unique challenges. The overall chemical composition of coal and associated strata with mineable coal seams, structural characteristics of the deposit, weather patterns, environmental conditions, processing and scale of mining of the deposit, and public and private infrastructure must be considered. Future land use and water resource requirements are also important considerations. The planning and closure activities must ensure that the resultant site has the appropriate post-mining land and water resources use, and the site does not pose any future environmental and health and safety risks. These requirements suggest that closure activities should be integrated with the mining activity planning process from the start. This paper discusses mine closure issues and describes several practices for a surface coal mine in the Western USA.

The impact of land use- and climate change on the managed eco-geomorphic balance in the Alps

CLUE: a conceptual model to study the Conversion of Land Use and its Effects

CA-ANN models which integrate Cellular Automata (CA) and Artificial Neural Networks (ANNs) for simulating land use change, usually urban and non-urban, predict the final land use type of a cell by the greatest similarity or probability after model parameters were defined in the training stage. In this study, the Monte Carlo approach was introduced into a CA-ANN model to simulate multiple land use changes with a case study in Shenzhen, China. The final land use type of a cell was jointly determined by the Monte Carlo approach and artificial neural network. The model performance were evaluated based on cell-to-cell comparison between simulated maps and actual ones by overall accuracy and kappa coefficient. The input maps of 1996, 2000 and 2004 were combined into three scenarios, the overall accuracies and kappa coefficients were all greater than 81.91% and 0.71 respectively. The land use maps of from 2004 to 2020 with 4 years interval were simulated and the results showed that build up will increase steadily while woodland will decrease. The impacts of spatial variables, neighborhood size and cell size on model performance were obtained by sensitive analysis. The simulation performance were all acceptable compared with the existing studies. The model performance would increase slightly as either neighborhood size or cell size increased, and that proximities to railways and city center were the main factors driving the dynamics of land use change in the study area.

Reliable crop mapping is essential in land and water management studies to understand the spatial distribution and dynamics of agricultural practices, to model resource use and production, and to propose sustainable scenarios for agricultural and water management. This work presents high-resolution crop mapping for the Mediterranean area, which is particularly interesting due to the limited data availability and the high level of land use heterogeneity. The main European land use dataset, Corine Land Cover (CLC), lacks the specificity required for accurate agricultural classification, especially for crop differentiation, and does not provide frequent or timely updates, which are crucial for many applications. Other more recent EU-wide crop mapping efforts (d’Andrimont et al, 2021) still lack regional accuracy due to widely scattered training data. To overcome these limitations, a large-scale crop mapping initiative was implemented in Sardinia to test and validate an artificial intelligence–based approach for Mediterranean environments. In this context, irrigated agriculture is a key sector for the sustainable management of limited water resources. The method uses Sentinel‑2 time series and survey data from the LPIS (Land Parcel Identification System). The study relies on IOTA2, a land‑use map production chain first developed and tested at the French level, producing maps with 24 land‑use classes. The originality of the approach lies in the use of open‑source satellite images and an automated processing workflow based on supervised classifiers, making crop mapping faster and easily reproducible across years.Learning samples are derived from 2018 LPIS data, supplemented by CLC and CLCplus Backbone datasets for natural areas and the Urban Atlas for urban areas. Two nomenclatures are tested: a detailed versus a simplified one, with 32 and 26 thematic classes, respectively, both focusing on Mediterranean-relevant crop typologies. The two nomenclatures are evaluated with sampling rates of 10%, 50%, and 100% of training pixels. Results show that the simplified nomenclature achieves higher accuracy, with an Overall Accuracy (OA) of 0.77 compared to 0.61 for the detailed nomenclature, using 100% training pixels. Increasing the training sample rate improves classification quality in both nomenclatures: in the short nomenclature, OA values are 0.596, 0.613, and 0.774 for 10%, 50%, and 100% sampling rates. In the detailed nomenclature, the improvement is weaker, with OA values of 0.596, 0.601, and 0.610, indicating that increasing sample size does not resolve class confusion. Among agricultural classes, rice, citrus, vegetables, and grapevine achieve the highest classification scores, which are among the crops with the largest irrigation requirements. Nuts, cereals, and fruit trees perform poorly, mainly due to insufficient training samples. Overall, the proposed nomenclature significantly improves the crop classes available in the CLC by increasing crop specificity and differentiation. This study presents a framework for fully automatic crop‑map production in Mediterranean environments, ensuring fast reproducibility over the years thanks to the use of openly accessible satellite imagery and an automated processing chain. This can improve the accuracy and reliability of water accounting for the agricultural sector and help promote sustainable use of limited water resources in the Mediterranean areas.

Most of the territory of the Republic of Tajikistan (93%) is occupied by mountain ranges and only 7% of the territory is lands suitable for agriculture. In this regard, the population density is very high and amounts to 60 people per 1 square kilometer of the area. The population at the beginning of 2019 was 5.3 million people, and in 2021, it was 9,537,645 people, an increase of about 80%. The demographic situation, the lack of suitable land for agriculture leads to the violation of the ecological balance that has developed in the last 30 years in Tajikistan, including on irrigated lands, which led to a decrease in crop yields by 1.5–2.0 times. One of the reasons for the decrease in productivity is the irrational use of land resources and anthropogenic impacts on reclamation lands. The intensification of the use of agricultural lands leads to their degradation, the development of desertification; a special place is occupied by irrigated lands, the problems of their conservation and improvement of their condition. The solution of these problems is based on objective and up-to-date information about the state and use of irrigated lands, as well as timely and reliable information received. In this regard, there is a need to identify and assess the existing environmental and socio-economic problems in the use of reclamation lands, the timely reconstruction of reclamation systems, the development of ways to solve the identified problems, as well as the development of methodological recommendations to justify the effectiveness of the implementation of state agricultural land management programs, taking into account regional characteristics. The existing information on the state and use of agricultural lands is contained in various organizations, is fragmented, of different scales and of different information. To use such information, it is necessary to transform it, which can lead to a significant loss of information, a decrease in its accuracy, and, consequently, its reliability. Modern geoformation technologies using remote sensing methods of the Earth at the present time can significantly improve the quality of research conducted when monitoring irrigated lands. In this regard, monitoring, analysis, assessment and forecasting of the ameliorative state of irrigated lands of the Republic of Tajikistan, and their conservation based on the development of criteria for environmental and socio-economic assessment of the use of reclaimed lands and the development of recommendations for the reconstruction of melioration systems based on the use modern geoinformation technologies and the use of aerospace images is relevant.

The Constraint Cellular Automata (CCA) land use model has found many applications in research and planning practices. A CCA model (the RUHUNUPURA model) was set up for the Ruhunupura area of Sri Lanka using the METRONAMICA® software. Preliminary model simulations revealed that the model is not capable of capturing the proper dynamics of the ‘chena’ land use class, which is a particular practice of shifting cultivation. Essentially, the ‘short memory’ of the model can neither account for the gradual decrease in soil fertility after an area of forest has been cleared for cultivation, nor can it capture the process of regen eration once the plot is fallowed. Chena is a common land use class (15% of the model area in 2001) and by its nature highly dynamic. Therefore, we extended the CCA model with a component that modifies land suitability as a function of the time since the last land use transition. The RUHUNUPURA model was set up with eleven land use classes out of which seven are dynamic (chena, build-up area, homestead, forest, paddy, other crops, and shrub and other uncultivated area), and four are static (inland fresh water, brackish water, un-modelled land, and sea) over the simulation period. In this model, the transition potential of a cell from one state to another is determined by five factors; neighbourhood interaction, zoning, accessibility, suitability and age, the latter being the newly introduced component. The direct effect of age is set to apply only for the land use classes chena and shrub and other uncultivated area. On one hand ‘age’ acts to linearly decrease the potential of chena lands to remain chena over time and keeps the effect constant once a chena is 6 years old. On the other hand ‘age’ linearly increases the potential of shrub and other uncultivated areas to change into chena over time, and becomes constant when the shrub and other uncultivated area reaches 5 years. The extended RUHUNUPURA model was calibrated for the period 1985 to 2001 and the results were assessed in terms of location-to-location overlap as well as structural similarity at multiple scales. These results give confidence in the representation of land use dynamics for all the main land use classes (shrub and other uncultivated area, homesteads, chena, forest, and paddy) except for the class other crops. The class build-up area, which is expected to become more important in future developments, did not expand much over the calibration period and therefore remains untested. A scenario was formulated to examine the model’s ability to capture chena dynamics, and transformed in to a model simulation from 2001 to 2030. The simulation results show that the model adapts to produce shortening fallow periods and long cultivation periods of chena, as a result of increasing pressure on land. We conclude that the model extension is crucial for a model area which includes shifting cultivation. The extension affects not only the land use class chena, but through spatio-temporal interactions that are already present in the original CCA model the whole land use system is better represented. Category/Keywords: Natural Resource Management / Land use model, Cellular Automata, Shifting cultivation, Sri Lanka .